Towards living sustainably: A study of Australian ... · A study of Australian consumers’...
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“Towards living sustainably: A study of Australian consumers’ sustainable behaviours and intentions” Judith Rex Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Faculty of Business and Enterprise Swinburne University of Technology 2012
Transcript of Towards living sustainably: A study of Australian ... · A study of Australian consumers’...
“Towards living sustainably:
A study of Australian consumers’ sustainable
behaviours and intentions”
Judith Rex
Thesis submitted in fulfilment of the
requirements for the degree of
Doctor of Philosophy
Faculty of Business and Enterprise
Swinburne University of Technology
2012
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Abstract
Recognising the need to increase society’s concern for the environment and natural
resources, governments and organisations have moved towards developing and adopting
policies to promote the uptake of sustainable behaviours, such as recycling and reducing
the reliance on non-renewable energy sources. Driven by the author’s interest in the
environment and conservation, the principal motive for this research study is to
understand the success of initiatives to encourage Australian consumers to adopt
sustainable practices in their daily lives.
Using an extended version of the Theory of Planned Behaviour (TPB), it explores the
effects of Australians’ attitudes, perceived behavioural control (PBC), subjective norm,
personal normative motives (PNM), internal ethics and moral intensity in predicting
their sustainable behaviour and intentions. To achieve the aims of this study, four
research questions and 17 hypotheses are examined in detail using exploratory factor
analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling
(SEM). The survey questionnaire is based on the extant literature, adapted to the
sustainable context and pre-tested using depth interviews. The quantitative data is
collected using an online survey with a final representative sample of 511 Australians.
The study demonstrates that sustainable behaviour and intention is most reliably
measured by “likely behavioural intention” (LBI) and “lifestyle behaviour”. The sample
was most likely to adopt sustainable practices which involved little effort or cost, and
least likely to adopt more expensive products such as double-glazed windows. The key
driver of sustainable behaviour and intention was consumers’ “internal ethics” which
reflects their beliefs that they have an obligation to live sustainably. The other
exogenous constructs had a lesser effect on their behaviour and intention, suggesting
that the TPB was only moderately useful in predicting behaviour and intention.
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While many Australians have started their journey towards adopting sustainable
practices, this study suggests that the theory does not provide a complete account of the
reasons for sustainable intention and behaviour. Engaging in sustainable practices is a
highly complex topic, and further research is required to understand the additional
measures and constructs that need to be included in order to better explain the variance
in Australians’ behaviour. This particularly applies to understanding the issues that
drive behavioural change as well as the limiting factors that prevent their adoption,
particularly the cost. Understanding the factors that would make consumers pay more
for sustainable products and services, as well as the factors that would increase their
sense of ethical obligation, could also be a topic for future research.
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Acknowledgements
This thesis is the culmination of a most enjoyable time spent researching and learning
about the academic approach to presenting a research study. I have many people to
thank for their guidance and support along my PhD journey. First, I would like to thank
Bill Callaghan for getting me started on my thesis journey. Bill’s practical knowledge of
marketing and business gave me the inspiration to attack this project with great
enthusiasm. I would also like to thank Alex Maritz and Heath McDonald for their
invaluable insights and advice in the latter stages of preparing the thesis. Another big
thank you goes to Denny Meyer who has very been very patient and generous with her
time as I learned to apply structural equation modelling for my data analysis. Denny’s
passion for statistics and helping PhD candidates is amazing. Foremost, I want to thank
Tony Lobo who has been my principal supervisor. Tony, thank you for your invaluable
advice during the preparation of this thesis and for your energy and guidance in working
with me to complete my PhD.
To all my friends and family, thank you for your understanding, friendship and support.
I particularly want to thank John, Sophie and David Rex who have so enthusiastically
encouraged me to complete my PhD.
Finally, I dedicate this thesis to my parents. Foremost, I dedicate this thesis to my
father, John Barrett, who supported and encouraged me to pursue my dream of
becoming a Doctor of Philosophy. Sadly, he died before achieving his great dream to
see me graduating and wearing the “floppy hat”. Thank you also to my mother, Sue
Barrett, who has the most amazing strength and who has always been there for me and
for our family.
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Certificate of authorship/originality
I certify that the work in this thesis has not previously been submitted for a degree nor
has it been submitted as part of requirements for a degree except as fully acknowledged
within the text.
I also certify that the thesis has been written by me. Any help that I have received in my
research work and the preparation of the thesis itself has been acknowledged. David
Hudson (Institute for Social Research, Swinburne University of Technology) edited this
thesis. The editing addressed only style and grammar and not its substantive content.
In addition, I certify that all information sources and literature used are indicated in the
thesis.
Signature of Candidate
_________________________________________________
Judith Rex
January 15, 2012
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Table of Contents
Abstract ....................................................................................................................... 2 Acknowledgements ........................................................................................................... 4 Certificate of authorship/originality .................................................................................. 5 List of Appendices .......................................................................................................... 11 List of Tables .................................................................................................................. 12 List of Figures ................................................................................................................. 14 Abbreviations used in this thesis ..................................................................................... 15 Chapter 1: Introduction to the research study ............................................................... 16
1.1 Introduction ........................................................................................................ 16 1.2 Environmental conferences and social marketing ............................................. 19 1.3 Studies in ethical decision making and sustainability ....................................... 20 1.4 Aims of this study .............................................................................................. 22 1.5 Justification for the research .............................................................................. 25 1.6 Developing the study ......................................................................................... 28 1.7 Structure of the thesis ........................................................................................ 30 1.8 Definition of key terms ...................................................................................... 33
Chapter 2: Literature review – the context to the study ................................................ 35 2.1 Introduction ........................................................................................................ 35 2.2 Social marketing ................................................................................................ 37
2.2.1 Examples of social marketing campaigns ................................................ 39 2.3 Sustainability ..................................................................................................... 41 2.4 Sustainable consumption ................................................................................... 42 2.5 Ethics and ethical consumption ......................................................................... 43 2.6 Green and environmental consumption ............................................................. 46 2.7 Linking ethical, sustainable and environmental consumption ........................... 49 2.8 Sustainable behaviours ...................................................................................... 50 2.9 The Social practices model ................................................................................ 53
2.9.1 Lifestyle and capital sustainable behaviours ........................................... 54 2.10 Changing sustainable behaviours ...................................................................... 57 2.11 Chapter summary ............................................................................................... 59
Chapter 3: Theoretical frameworks – investigating the determinants of sustainable and ethical decision making ................................................................................................... 61
3.1 Introduction ........................................................................................................ 61 3.2 Background ........................................................................................................ 63 3.3 Behavioural intention models ............................................................................ 64 3.4 Early models of the ethical decision-making process ........................................ 66
3.4.1 Rest’s and Trevino’s models of ethical decision making ........................ 66 3.4.2 The nature of the issue and situational characteristics ............................. 68
3.5 Protection Motivation Theory (PMT) ................................................................ 69 3.6 Theory of Reasoned Action (TRA) ................................................................... 70 3.7 Theory of Planned Behaviour (TPB) ................................................................. 72
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3.7.1 Applications of the TRA and TPB ........................................................... 74 3.7.2 Shaw’s models of behavioural intention .................................................. 76
3.8 Latent constructs ................................................................................................ 78 3.9 Behavioural intention and actual behaviours ..................................................... 78 3.10 Actual behaviours .............................................................................................. 80 3.11 Attitudes ............................................................................................................. 82 3.12 Behavioural beliefs ............................................................................................ 85 3.13 Perceived behavioural control and control beliefs ............................................. 86 3.14 Subjective norm and normative beliefs ............................................................. 88 3.15 Personal normative motives ............................................................................... 90 3.16 Internal ethics – ethical obligation and self-identity .......................................... 91
3.16.1 Ethical obligation ..................................................................................... 91 3.16.2 128BSelf-identity ............................................................................................. 92
3.17 41BMoral intensity ................................................................................................... 94 3.17.1 129BMeasuring moral intensity ....................................................................... 95 3.17.2 130BComparing the moral intensity dimensions ............................................. 98
3.18 42BOverview of relevant models and studies ........................................................ 100 3.19 43BDemographic variables .................................................................................... 103 3.20 44BValues and behavioural variables .................................................................... 106
3.20.1 131BEnvironmental concern .......................................................................... 107 3.21 45BChapter summary ............................................................................................. 109
Chapter 4: 3BTheoretical frameworks, research questions and hypotheses ................... 112 4.1 46BIntroduction ...................................................................................................... 112 4.2 47BBackground ...................................................................................................... 114 4.3 48BDeveloping the theoretical frameworks ........................................................... 115
4.3.1 132BThe theoretical frameworks ................................................................... 116 4.4 49BResearch questions ........................................................................................... 119 4.5 50BResearch objectives ......................................................................................... 121 4.6 51BLatent constructs and hypotheses .................................................................... 123
4.6.1 133BAttitudes ................................................................................................. 123 4.6.2 134BControl beliefs and perceived behavioural control (PBC) ..................... 124 4.6.3 135BSubjective norm, PNM and normative beliefs ....................................... 125 4.6.4 136BInternal ethics ......................................................................................... 127 4.6.5 137BMoral intensity ....................................................................................... 128
4.7 52BMeasuring sustainable behaviour and intention............................................... 129 4.7.1 138BCapital and lifestyle behaviour and intention ........................................ 130 4.7.2 139BLikely behavioural intention (LBI) ........................................................ 131
4.8 53BSummary of research objectives and hypotheses ............................................ 132 4.9 54BDemographic segmentation ............................................................................. 133 4.10 55BChapter summary ............................................................................................. 134
Chapter 5: 4BResearch methodology and design ............................................................ 136 5.1 56BIntroduction ...................................................................................................... 136 5.2 57BResearch methodology decisions ..................................................................... 138 5.3 58BThe unit of analysis and the sample ................................................................. 139 5.4 59BEthical considerations ...................................................................................... 140 5.5 60BThe behaviour and intention constructs ........................................................... 141
5.5.1 140BMeasuring capital and lifestyle behaviours and intention ..................... 142 5.5.2 141BCapital intention ..................................................................................... 143
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5.5.3 142BLifestyle intention .................................................................................. 143 5.5.4 143BLikely behavioural intention (LBI) ........................................................ 144
5.6 61BLatent exogenous constructs ............................................................................ 145 5.6.1 144BAttitudes ................................................................................................. 146 5.6.2 145BBehavioural beliefs ................................................................................ 147 5.6.3 146BPerceived behavioural control (PBC) .................................................... 148 5.6.4 147BControl beliefs ....................................................................................... 149 5.6.5 148BSubjective norm ..................................................................................... 149 5.6.6 149BNormative beliefs ................................................................................... 150 5.6.7 150BPersonal-normative motives (PNM) ...................................................... 150 5.6.8 151BInternal ethics ......................................................................................... 150 5.6.9 152BMoral intensity ....................................................................................... 151
5.7 Demographic questions ................................................................................... 152 5.7.1 153BAge ......................................................................................................... 153 5.7.2 154BGender .................................................................................................... 153 5.7.3 155BMarital status ......................................................................................... 153 5.7.4 156BNumber of children in household .......................................................... 154 5.7.5 157BEducation and income ............................................................................ 154 5.7.6 158BOccupation ............................................................................................. 155 5.7.7 159BResidence ............................................................................................... 155 5.7.8 160BOther classification questions ................................................................ 156
5.8 62BDeveloping the questionnaire .......................................................................... 156 5.8.1 Order of the questions ............................................................................ 158 5.8.2 161BAdapting the questions .......................................................................... 159 5.8.3 162BLikert scales ........................................................................................... 159
5.9 63BPre-testing the questionnaire ............................................................................ 160 5.9.1 163BThe depth interviews .............................................................................. 161 5.9.2 164BDeveloping the moral intensity scenario ............................................... 164
5.10 64BPrimary data collection .................................................................................... 166 5.10.1 165BAdvantages and disadvantages of using online surveys ........................ 167 5.10.2 166BThe sampling frame ............................................................................... 168 5.10.3 167BThe process for collecting the data ........................................................ 169
5.11 65BThe data analysis process ................................................................................. 169 5.12 66BSummary of the research methodology and design ......................................... 170 5.13 67BReliability and validity .................................................................................... 170
5.13.1 168BReliability .............................................................................................. 171 5.13.2 169BValidity .................................................................................................. 172
5.14 68BChapter summary ............................................................................................. 173 Chapter 6: 5BAnalysis and results .................................................................................. 175
6.1 69BIntroduction ...................................................................................................... 175 6.2 70BResponse to the questionnaire ......................................................................... 177 6.3 71BDemographic profile of respondents ............................................................... 178 6.4 72BImportant issues facing Australia today .......................................................... 180 6.5 73BConcern for the environment and sustainability .............................................. 180 6.6 74BSummary of the statements included in the constructs .................................... 181 6.7 75BSummary of the capital and lifestyle behaviour constructs ............................. 183 6.8 76BSplitting the sample ......................................................................................... 186 6.9 77BExploratory factor analysis (EFA) ................................................................... 186
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6.10 78BEFA for Attitudes ............................................................................................ 188 6.11 79BEFA for behavioural beliefs ............................................................................. 190 6.12 80BEFA for Perceived behavioural control (PBC) ................................................ 190 6.13 81BEFA for Control beliefs ................................................................................... 191 6.14 82BEFA for normative beliefs, subjective norm and PNM ................................... 192 6.15 83BEFA for Internal ethics .................................................................................... 193 6.16 84BEFA for Moral intensity ................................................................................... 193 6.17 85BEFA for capital and lifestyle behaviour and intention ..................................... 194 6.18 86BEFA for likely behavioural intention (LBI) ..................................................... 195 6.19 87BSummary of the latent constructs based on the EFA ....................................... 196 6.20 88BConfirmatory factor analysis (CFA) ................................................................ 197
6.20.1 170BDescriptive fit indices ............................................................................ 198 6.21 89BFindings from the CFA and measurement models .......................................... 199 6.22 90BCFA for attitudes ............................................................................................. 200 6.23 91BCFA for behavioural beliefs and attitudes ....................................................... 202 6.24 92BCFA for Control Beliefs and Perceived Behavioural Control (PBC) .............. 204 6.25 93BCFA for normative beliefs, subjective norm and PNM ................................... 206 6.26 94BCFA for internal ethics .................................................................................... 207 6.27 95BCFA for Moral intensity .................................................................................. 208 6.28 96BCFA for lifestyle intention and behaviour ....................................................... 209 6.29 97BLikely behavioural intention (LBI) .................................................................. 210 6.30 98BSummary of latent constructs based on the CFA ............................................. 211 6.31 99BStructural Equation Modelling (SEM) ............................................................. 212
6.31.1 171BTesting for normality and multicollinearity ........................................... 213 6.32 100BDeveloping the SEM for likely behavioural intention (LBI) ........................... 214 6.33 101BDeveloping the final SEM for lifestyle behaviour and intention ..................... 219 6.34 102BDiscussion of hypothesis tests – constructs not in final SEM ......................... 223
6.34.1 173BCapital behaviour and intention ............................................................. 223 6.34.2 172BPersonal normative motives ................................................................... 224 6.34.3 174BControl beliefs and perceived behavioural control ................................ 224
6.35 103BDiscussion of hypothesis tests – constructs included in the final SEM ........... 225 6.35.1 175BBehavioural beliefs and attitudes ........................................................... 225 6.35.2 176BNormative beliefs and subjective norm ................................................. 227 6.35.3 177BInternal ethics – Self-identity and ethical obligation ............................. 228 6.35.4 178BMoral intensity ....................................................................................... 228
6.36 104BSummarising the findings of the hypothesis testing ........................................ 229 6.37 Summary of the outcomes of the EFA, CFA and SEM ................................... 230 6.38 105BInvariance testing ............................................................................................. 233 6.39 106BInvariance testing for the LBI model ............................................................... 234
6.39.1 179BInvariance testing – gender .................................................................... 234 6.39.2 180BInvariance testing – child under 18 and no child under 18 .................... 235 6.39.3 181BInvariance testing – own /don’t own their dwelling .............................. 236 6.39.4 182BInvariance testing – city and x-city ........................................................ 237 6.39.5 183BInvariance testing – lead a sustainable lifestyle ..................................... 238 6.39.6 184BOverview of the invariance testing for the LBI model .......................... 240
6.40 107BInvariance testing for lifestyle behaviour and intention model ....................... 241 6.40.1 185BInvariance testing – gender .................................................................... 241 6.40.2 186BInvariance testing – child under 18 and no child under 18 .................... 242
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6.40.3 187BInvariance testing – own /don’t own their dwelling .............................. 243 6.40.4 188BInvariance testing – city and x-city ........................................................ 244 6.40.5 189BInvariance testing – lead a sustainable lifestyle ..................................... 245 6.40.6 190BOverview of the invariance testing for lifestyle model .......................... 247
6.41 108BChapter summary ............................................................................................. 248 Chapter 7: 6BDiscussion, recommendations and conclusions ........................................ 250
7.1 109BIntroduction ...................................................................................................... 250 7.2 110BRevisiting the theoretical models ..................................................................... 252 7.3 111BExogenous constructs ...................................................................................... 255
7.3.1 191BBehavioural beliefs ................................................................................ 255 7.3.2 192BAttitudes ................................................................................................. 256 7.3.3 193BPersonal normative motives ................................................................... 258 7.3.4 194BSubjective norm and normative beliefs ................................................. 259 7.3.5 195BPerceived behavioural control and control beliefs ................................. 261 7.3.6 196BInternal ethics ......................................................................................... 262 7.3.7 197BMoral intensity ....................................................................................... 263
7.4 112BInterrelationships between the exogenous constructs ...................................... 265 7.5 113BBehaviour and intention constructs ................................................................. 265
7.5.1 198BClassifying capital and lifestyle behaviours .......................................... 266 7.5.2 199BPromoting the identified sustainable behaviours ................................... 269 7.5.3 200BCapital and lifestyle behaviours as predictors of intention .................... 269 7.5.4 201BLikely behavioural intention (LBI) ........................................................ 270 7.5.5 202BSummarising the behaviour and intention constructs ............................ 272
7.6 Summarising the invariance testing ................................................................. 273 7.7 115BRevisiting the research questions and hypotheses ........................................... 274 7.8 116BContributions to theory .................................................................................... 276 7.9 117BConclusions ...................................................................................................... 280 7.10 118BLimitations of the study ................................................................................... 281 7.11 119BFurther research directions .............................................................................. 282
References ................................................................................................................... 284 Conference papers presented by the candidate based on this research study ............... 322
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List of Appendices Appendix 1: Conceptual Model of Buyer Behaviour, Howard and Sheth (1969) 300 Appendix 2: Theory of Ethics, Hunt and Vitell (1986). 300 Appendix 3: Issue contingent model of ethical decision making in organisations,
Jones (1991) 301 Appendix 4: Issue-risk-judgement model of ethical decision making, Tan (2002) 301 Appendix 5: Willingness to pay more for environmentally friendly products,
Laroche et al. (2001, p. 504) 301 Appendix 6: Ethics approval letter 302 Appendix 7: Summary of constructs in questionnaire 303 Appendix 8: Moral intensity scenarios tested in depth interviews 307 Appendix 9: Final questionnaire 308 Appendix 10: Final SEM for LBI 317 Appendix 11: Regression weights 318 Appendix 12: Squared multiple correlations 318 Appendix 13: Fit indices 318 Appendix 14: Final model lifestyle behaviour and intention 319 Appendix 15: Regression weights 320 Appendix 16: Squared multiple correlations 320 Appendix 17: Fit indices 321
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List of Tables Table 2.1 Proposed classification for sustainable behaviours 56 Table 3.1 Relevant studies that measure behavioural intention 79 Table 3.2 Relevant studies that measure actual behaviour 82 Table 3.3 Relevant studies that measure attitudes 84 Table 3.4 Relevant studies that measure behavioural beliefs 86 Table 3.5 Relevant studies that measure PBC 87 Table 3.6 Relevant studies that measure control beliefs 88 Table 3.7 Relevant studies that measure subjective norm 89 Table 3.8 Relevant studies that measure normative beliefs 90 Table 3.9 Summary of the study that measures personal normative motives 91 Table 3.10 Relevant studies that measure ethical obligation 92 Table 3.11 Relevant studies that measure self-identity 94 Table 3.12 The six characteristics of moral intensity 96 Table 3.13 Source of the constructs for this study 101 Table 3.14 Main findings and further research from some relevant models 102 Table 4.1 Research hypotheses for the exogenous and endogenous constructs 116 Table 4.2 Summary of research objectives and hypotheses 132 Table 5.1 Summary of the paradigmatic issues and the research approach 139 Table 5.2 Demographics included in the questionnaire 152 Table 5.3 Descriptors used for Likert scales 160 Table 5.4 Decisions made about the quantitative research approach 170 Table 6.1 Comparison of sample’s demographics and ABS population statistics 179 Table 6.2 Summary of lifestyle attitudes 181 Table 6.3 Summary of mean, SD and mode for the statements in the study 182 Table 6.4 Summary of capital behaviours and intention 184 Table 6.5 Summary of lifestyle behaviours and intention 185 Table 6.6 Summary of items used for the EFA analyses 188 Table 6.7 Factor solution for the EFA for Attitudes 189 Table 6.8 Factor solution for the EFA for behavioural beliefs 190 Table 6.9 Factor solution for the EFA for PBC 190 Table 6.10 Factor solution for EFA for control beliefs 191 Table 6.11 EFA for normative beliefs, subjective norm and PNM 192 Table 6.12 Factor solution for the EFA for internal ethics 193 Table 6.13 Factor solution for the EFA for moral intensity 194 Table 6.14 Factor solution for the EFA for lifestyle 195 Table 6.15 EFA for likely sustainable behavioural intention (LBI) 196 Table 6.16 Summary of the EFA analyses 197 Table 6.17 Descriptive fit statistics used to test the hypotheses 199 Table 6.18 Summary of the CFA and EFA analyses 200 Table 6.19 Regression weights for attitudes 202 Table 6.20 Regression weights for behavioural beliefs and attitudes 204 Table 6.21 Regression weights for control beliefs and PBC 205 Table 6.22 Regression weights for PNM normative beliefs and subjective norms 207
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Table 6.23 Regression weights for internal ethics 208 Table 6.24 Regression weights for moral intensity 209 Table 6.25 Regression weights for LBI 211 Table 6.26 Summary of statistics from the CFA measurement models 211 Table 6.27 Summary of statements based on the EFA and the CFA 212 Table 6.28 Regression weights for the final LBI model 216 Table 6.29 Estimates of squared multiple correlations (R2) for LBI 218 Table 6.30 Regression weights for final lifestyle behaviour and intention model 222 Table 6.31 Estimates of squared multiple correlations (R2) for lifestyle behaviour 222 Table 6.32 Summary of the findings from the hypothesis testing 230 Table 6.33 Statements retained/deleted after the EFA, CFA and SEM analyses 231 Table 6.34 Invariance tests for males and females 234 Table 6.35 Standardised structural weights for males and females 234 Table 6.36 Updated invariance tests for people with child/no child under 18 235 Table 6.37 Standardised regression weights for households with child under 18 236 Table 6.38 Invariance tests for people who own/don’t own their dwelling 237 Table 6.39 Standardised structural weights for people who own and don’t own their
dwelling 237 Table 6.40 Invariance tests for people living in capital cities and x-city 238 Table 6.41 Standardised structural weights for people living in capital cities/x-city 238 Table 6.42 Invariance tests for people who agree/disagree that they lead a
sustainable lifestyle 238 Table 6.43 Standardised measurement weights for agree or disagree lead
sustainable lifestyle 239 Table 6.44 Summary of invariance testing for LBI model 240 Table 6.45 Invariance tests for males and females 241 Table 6.46 Standardised regression weights for males and females 241 Table 6.47 Invariance tests for people with child/no child under 18 in household 242 Table 6.48 Standardised regression weights for households with child under 18 242 Table 6.49 Invariance tests for people who own/don’t own their dwelling 243 Table 6.50 Standardised structural weights for people who own their dwelling 244 Table 6.51 Invariance tests for people living in capital cities (city) and outside
capital cities (x-city) 244 Table 6.52 Standardised structural weights for people living in capital cities/x-city 245 Table 6.53 Invariance tests for lead a sustainable lifestyle 245 Table 6.54 Standardised measurement weights for lead a sustainable lifestyle 246 Table 6.55 Summary of invariance testing for lifestyle behaviour and intention 247 Table 7.1 Comparing attitudes in this study and Laroche et al. (2001) 257 Table 7.2 Adoption categories for capital and lifestyle behaviours 267 Table 7.3 The sustainable behaviours classification 268 Table 7.4 Comparing behaviour constructs in this study and Laroche et al. (2001) 271 Table 7.5 Summary of findings from accepted hypotheses 274 Table 7.6 Summary of contributions made by the current study 277
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List of Figures Figure 1.1 Roadmap of chapter 1 18 Figure 1.2 The process of the research study 29 Figure 1.3 Structure of the thesis (adapted from Perry (1995)) 32 Figure 2.1 Topics to be examined in the literature review 36 Figure 2.2 Roadmap of chapter 2 37 Figure 2.3 Linking green, sustainable and ethical consumption 50 Figure 2.4 The Social Practices Model 54 Figure 3.1 Roadmap of chapter 3 62 Figure 3.2 Theory of Reasoned Action (TRA) 70 Figure 3.3 Theory of Planned Behaviour (TPB) 73 Figure 3.4 Shaw’s ‘Model 2’ 77 Figure 3.5 Past behaviour, behavioural intention and future behaviours 81 Figure 4.1 Roadmap of chapter 4 113 Figure 4.2 Theoretical framework for likely behavioural intention 117 Figure 4.3 Theoretical framework for lifestyle behaviour and intention 118 Figure 4.4 Theoretical framework for capital behaviour and intention 119 Figure 5.1 Roadmap of chapter 5 137 Figure 6.1 Roadmap of chapter 6 176 Figure 6.2 CFA for attitudes 201 Figure 6.3 CFA for behavioural beliefs and attitudes 203 Figure 6.4 CFA for control beliefs and PBC 205 Figure 6.5 CFA for PNM, norm beliefs and subjective norms 206 Figure 6.6 CFA for internal ethics 208 Figure 6.7 CFA for moral intensity 209 Figure 6.8 CFA for lifestyle intention and behaviour 210 Figure 6.9 CFA for likely behavioural intention 210 Figure 6.10 Final SEM for LBI 216 Figure 6.11 Final SEM for lifestyle behaviour and intention 221 Figure 7.1 Roadmap of chapter 7 251 Figure 7.2 Overall conclusions for LBI 253 Figure 7.3 Overall conclusions for lifestyle behaviour and intention 254
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Abbreviations used in this thesis
Abbreviation Meaning AMOS Analysis of Moment Structures, version 18 CFA Confirmatory factor analysis EFA Exploratory factor analysis LBI Likely behavioural intention PBC Perceived behavioural control PNM Personal normative motives SEM Structural equation model(ling) SPSS Statistical Package for the Social Sciences, version 18 TPB Theory of Planned Behaviour TRA Theory of Reasoned Action
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Chapter 1: Introduction to the research study
This research study was motivated by the author’s interest in conservation and
protecting the environment. It was further enhanced by a research grant that the author
completed in 2005. In seeking to understand the success of the social marketing
campaign called ‘Target 155’ that encouraged Melbourne residents to restrict their
water consumption at home to 155 litres per person per day, this study examined the
practices and attitudes towards conserving water during a long drought in Melbourne,
Australia. The findings demonstrated that while many consumers were concerned about
the low levels in the state’s water storages, they needed incentives and motivations to
increase their adoption of water-saving practices. What this study did not model was an
understanding of the factors that would motivate and encourage consumers to save
water.
The ‘Target 155’ was just one of many campaigns at the time that was designed to
encourage the uptake of sustainable behaviours. Another was the ‘Reuse, Reduce and
Recycle’ campaign that encouraged reduction of waste, energy and water usage in
Australian homes and businesses. Such campaigns targeted sustainable behaviours such
as recycling waste materials, installing solar panels and rain water tanks, and reducing
the reliance on non-renewable energy sources.
Many of the initiatives related to conservation and sustainability throughout the world
have originated from the 1983 United Nations’ World Commission on the Environment
and Development. As a result of this commission, many governments and organisations
have adopted the sustainability concept in their business and marketing plans for the
first time. More recently, initiatives such as the 1997 Kyoto Protocol and the
Copenhagen climate conference in 2009 have confirmed the need for the population to
adopt sustainable behaviours in their daily lives. These actions have shaped the social
1.1 Introduction
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and economic policies of many levels of government, in Australia and throughout the
world.
This awareness of the need to preserve the environment has resulted in a proliferation of
studies that seek to understand sustainable consumption behaviour (Cherrier 2005;
Dunlap & Jones 2002; Giddens 2002; Shaw & Shiu 2003; Williams 2005) and by
organisations and businesses (Longenecker, Moore, Petty, Palich, & McKinney 2006;
Malhotra & Miller 1998; O'Riordan 2006; Paolillo & Vitell 2002; Trafimow & Borrie
1999). Based on this, it was decided that a worthy topic for this PhD study would be to
examine the factors that influence the sustainable behaviour and intentions of
Australians in their daily lives. As it was expected that the drought would eventually
end (and it has!), it was decided that this study should measure behaviour and intentions
across a range of sustainable behaviours.
This research study was designed to examine the issue of intention to engage in
sustainable behaviours and of actual adoption of such behaviours. It does this by
examining the literature and then translating this into a study that examines these issues
from the perspective of Australian consumers in their daily lives. This study is based on
issues debated in the business, psychological and social marketing literature in topics
such as social marketing, consumption, sustainability, behavioural intention and ethical
decision making.
The topic of sustainability is important as today’s governments and organisations are
not only focused on making a profit, but also seek environmental and social benefits
(Chabowski, Mena & Gonzalez-Padron 2010). This study aims to answer questions
such as: Which consumers are adopting sustainable practices in their daily lives? What
motivates consumers to intend to adopt sustainable behaviours? Are existing models of
ethical behaviour and intention applicable to sustainable consumption behaviours?
This chapter introduces the research study. After providing the background to the
research, its aims are elicited and the research is justified. The development of the
research methodology and design is described, followed by the structure of the thesis,
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and some key terms are described at the end of the chapter. The structure of this thesis is
based on that suggested by Perry (1995).
Figure 1.1 provides a roadmap of this chapter.
Figure 1.1 Roadmap of chapter 1
Source: Adapted from Perry (1995)
Chapter 1: Introduction to the
research study
Developing the study
Studies in ethical decision making
and sustainability
Environmental conferences and
social marketing
Descriptions of key terms
The structure of the thesis
Justification for the research
Aims of this study
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In Australia, it has been argued that the increased awareness of the need to protect the
environment largely originated from the public protests against the construction of dams
in the Tasmanian wilderness in the 1970s and early 1980s (Riedy 2005). These
coincided with the 1972 United Nations Conference on the Human Environment, held
in Stockholm, which examined links between the environment and development on a
global scale.
In 1983, the United Nations established the World Commission on Environment and
Development (WCED) chaired by Harlem Brundtland. This was also convened to
propose strategies to address issues associated with the environment and development.
The Brundtland Report that was called “Our Common Future” was released in 1987.
Following this, the Earth Summit was convened in Rio de Janeiro in 1992 to create
agreements and conventions on critical issues such as climate change, desertification
and deforestation. This resulted in many businesses, governments and international
organisations, including the World Bank, adopting the sustainability concept and
incorporating it into their business and marketing plans < http://www.iisd.org/sd/>.
In 1997, the Kyoto conference on climate change produced an international framework
by which developed countries agreed to specific targets for cutting their emissions of
greenhouse gases. These amounted to an average of 5% reductions against 1990 levels
over the period from 2008 to 2012 (http://unfccc.int/kyoto_protocol/items/2830.php).
This framework became known as the Kyoto Protocol
(http://www.globalissues.org/article/183/cop3-kyoto-protocol-climate-conference). In
2009, the Copenhagen climate conference included developing countries such as China
and India for the first time. The resulting Copenhagen Accord provides a revised
framework to cut global greenhouse gas emissions. Subsequent climate change
conferences were held in Cancun, Mexico in 2010 and in Bangkok, Thailand in April
2011. The adoption of a worldwide sustainable development paradigm has continued to
be an important part of the work done by the United Nations.
1.2 Environmental conferences and social marketing
20
While there is some debate about whether or not climate change is occurring naturally
or whether it is human-induced, such conferences have raised the social awareness of
the need to protect the environment. Hence, environmental issues are often categorised
as social issues (Banerjee, Iyer & Kashyap 2003; Geller 1989), and social marketing
strategies have been utilised to raise awareness of such issues, both at home and in the
workplace (Donovan & Henley 2003; Glenane-Antoniadis, Whitwell, Bell, & Menguc
2003). The success of social marketing campaigns in changing behaviour can be
measured by the amount of social pressure that exists to undertake sustainable
behaviours (Fielding, McDonald & Louis 2008) such as recycling and using low energy
light globes.
Based on this, one obvious question that needs to be answered is: How successful have
initiatives that encourage sustainable behaviours been in Australia? This question forms
the basis of this thesis.
In the last 50 years, there have been many changes in attitudes towards the environment
and protecting our natural resources (Ellen, Wiener & Cobb-Walgren 1991). Early
studies examined issues such as donating, recycling and conservation behaviours
(Granzin & Olsen 1991), recycling (Webster 1975) and using phosphate-free detergents
(Brooker 1976). More recently, the frequency of studies that relate to the environment
and sustainable issues has increased. Examples include studies of environmental action
in and around the home (Gilg, Barr & Ford 2005), purchasing fair trade products (Shaw
& Shiu 2003), and ethical and sustainable issues related to building a new dam (Routhe,
Jones & Feldman 2005).
Many of these studies were based on early theoretical and conceptual frameworks of
consumer decision making published in textbooks by authors such as Nicosia (1966),
Howard and Sheth (1969), Hansen (1972) and Bettman (1979). While these early
models focused on explaining the behaviour of consumers both at home and in the
1.3 Studies in ethical decision making and sustainability
21
workplace, these models were subsequently adapted to explain consumers’ behaviour in
the ethical and sustainable context. The early conceptual frameworks of ethical decision
making were reported by authors such as Rogers (1975), Fishbein and Ajzen (1975),
Ajzen and Fishbein (1980), Hunt and Vitell (1986) and Rest (1986). Such models
demonstrate the alternatives or actions that an individual might take to resolve this
ethical issue, and distinguished between volitional and non-volitional behaviours.
Volitional ethical behaviours are those that the consumer has control over, including
buying fair trade products and taking a shorter shower. Non-volitional behaviours are
those that the consumer has no control over, such as the building of a new dam.
At about the same time, the “Theory of Ethics” was published by Hunt and Vitell
(1986) which illustrates the alternatives or actions that an individual might take to
resolve an ethical issue. Prior to this, models such as the Protection Motivation Theory
(PMT) (Rogers 1975), Theory of Reasoned Action (TRA) (Fishbein & Ajzen 1975) and
Theory of Planned Behaviour (TPB) (Ajzen 1985) had been developed to understand
the link between behavioural intention and actual behaviour, with attitudes, subjective
norm and perceived behavioural control.
The importance and utility of theories and models such as the TRA and TPB have been
demonstrated by the proliferation of studies that have used them in their discussion of
environmental and sustainable issues in the ethical context. These include studies by
Wall, Devine-Wright and Mill (2007) and Fielding, McDonald and Louis (2008) who
applied modified versions of the TPB to environmentally sensitive behaviours, Sparks
and Shepherd (1992) who applied it to buying organic food, Kalafatis, Pollard, East and
Tsogas (1999) who used the TPB to study the factors that influence consumers’
intention to buy environmentally friendly green products in the UK and Greece, and
Shaw and associates (Shaw & Shiu 2003; Shaw, Shiu & Clarke 2000) who applied a
modified version to understand the purchasing of fair trade grocery products.
Such studies have extended the TPB by including different constructs to improve the
predictive ability of their models. These include moral intensity (Bennett, Anderson &
Blaney 2002; Jones 1991; McMahon & Harvey 2006; Singhapakdi, Vitell & Kraft
1996), the nature of the issue (Jones 1991), personal normative motives (Wall, Devine-
22
Wright & Mill 2007), internal ethics (Chedzoy & Burden 2007; Shaw & Shiu 2003) and
demographics (Carrigan, Szmigin & Wright 2004; Laroche, Bergeron & Barbaro-Forleo
2001; Petts, Herd & O'Heocha 1998).
While there are many models that explain ethical decision making, further research is
needed to improve their predictive ability. For example, Shaw and associates (2000,
2003, 2005, 2006) demonstrated that while a modified version of the TPB is useful in
explaining the purchasing of fair trade grocery products, more research is needed to
increase the amount of variance explained by the model.
Other research discusses the need to better understand the effects of demographics when
predicting decision making. For example, Petts, Herd and O’Heocha (1998) recommend
that research is needed to explore the link between age and attitudes and concern for the
environment, Dubinsky and Loken (1989) called for research to investigate the
relationship between intentions and behaviour, and Laroche, Bergeron and Barbaro-
Forleo (2001) suggested the need for research to explain which consumers are likely to
pay more for environmentally friendly products. Wells (2011) discussed the need to
include socio demographic variables in studies that target consumers, as well as
confirming the link that exists between behavioural intentions and environment-related
consumer behaviour. These and other issues that justify this research study are
discussed later in this chapter.
Fielding, Terry, Masser and Hogg (2008) argue that academic studies should use
existing models of behaviour with the inclusion of additional constructs, and for these
models to be explored in other contexts. Bearing this in mind, the overall aim of this
study is to determine the effectiveness of an extended version of the TPB in predicting
sustainable behaviour and intention among a representative sample of Australians. More
broadly, the three aims are summarised below.
1.4 Aims of this study
23
1. To determine which latent exogenous constructs are the best predictors
of sustainable behaviour and intention.
The extant literature has demonstrated the utility of the TPB when predicting a wide
range of behaviours, from intention to purchase fair trade products, to its ability to
predict the behavioural intentions of non-specialist primary school teachers to teach
dancing to students. Due to the prominence of sustainability issues today, this study
builds on existing research and uses an extended version of the TPB to predict what
drives Australian consumers to intend to engage in a range of sustainable behaviours.
The theoretical frameworks for this study include three constructs that are identified in
the original version of the TPB, as well as three additional constructs that have been
identified in subsequent studies. The three exogenous constructs from the TPB are
attitudes, perceived behavioural control and subjective norm, and the three additional
constructs are personal normative motives (Wall, Devine-Wright and Mill, 2007),
internal ethics (Shaw, 2003) and moral intensity (Jones, 1991, Singhapakdi et al. 1999;
Singhapakdi, Vitell & Kraft 1996). Wall, Devine-Wright and Mill (2007) suggested the
inclusion of personal-normative motives to explain the fact that behaviours that reduce
personal utility, such as by decreasing convenience, may be perceived as difficult and
therefore not achievable. This construct has been combined with the other two
normative constructs (subjective norm and normative beliefs) as justified in a later
section of this thesis. In this study, the antecedents to attitudes are behavioural beliefs,
the antecedents to perceived behavioural control are control beliefs, and the antecedents
to subjective norm are normative beliefs.
The second aim of this study is to test the reliability and validity of the latent exogenous
constructs in predicting sustainable behavioural intention.
2. To determine how to measure sustainable behaviour and intention.
This study measures both the adoption of sustainable behaviours, as well as behavioural
intention. The literature has demonstrated that behavioural intention and past behaviour
(which is called “behaviour” in this thesis) can be measured in two ways. Firstly,
24
behavioural intention can be measured by asking respondents to indicate how likely
they are to engage in sustainable behaviours. A 7-point Likert scale is used to measure
the strength of their responses to a series of statements, such as the likelihood of
engaging in behaviours in the home and away from home.
Secondly, behavioural intention and past behaviours can be measured by using a list of
actual behaviours and asking respondents to indicate which they have already done,
which is also called “past behaviour”, and which they intend to do in the future. These
behaviour constructs are measured using a dichotomous scale (yes/no). These constructs
are called behaviour and behavioural intention, respectively. For the analysis, these are
computed to measure the actual number of behaviours that have been done in the past or
that are intended to be done in the future.
For this study, it was decided to use both measures of behaviour and intention. This
would allow the researcher to determine which best explains sustainable behaviours or,
indeed, if both are worthy of inclusion. In addition, the dichotomous intention and
behaviour constructs are included to measure the ability of past behaviour to predict
behavioural intention in the sustainable context and to examine the effect of the
exogenous constructs on past behaviour. For this study, past behaviour is the mediating
construct between the exogenous constructs and the endogenous behavioural intention
construct.
Hence, the second aim of this study is to determine which of the endogenous
behavioural constructs improve the predictive ability of the TPB in explaining the
sustainable behavioural intention of Australian consumers.
3. To understand the effect of control variables on the ability of the
theoretical model to predict sustainable behaviour and intention.
Control variables including demographics and geographics are also measured to
determine the extent to which they influence intention to engage in sustainable
behaviours. Research has demonstrated the effect that variables such as gender, the
presence of children aged under 18 years, home ownership and where the person lives
25
can have on behaviour and intention. Hence, the third aim of this research study is to
determine which control variables account for significant differences in explaining
sustainable behaviour and intention, using invariance testing for this analysis.
These research aims will enable marketers and policy makers to understand the success
of campaigns that target the adoption of sustainable behaviours, using an extended
version of the TPB, among Australian consumers.
This research study is based on the need to better understand the antecedents to
sustainable behaviour and intention from the perspective of the Australian consumer. A
study of the relevant literature revealed some gaps which are elaborated below.
1. Research is needed to understand sustainability from the consumer’s
perspective.
Much research in the domain of ethical decision making and sustainability has
examined the issues from the perspective of the student (for example, Street & Street
(2006) or students who are managers (Weber & Gillespie 1998). Many of the studies
have been conceptual and designed to predict ethical and unethical behaviour in
organisations such as those reported by Tsalikis, Seaton and Shepherd (2007),
Longenecker et al. (2006), Zabel (2005), Banerjee, Iyer and Kashyap (2003) and
Solymossy and Masters (2002). Others have assessed the actions that have been
recommended, intended or preferred to resolve a hypothetical ethical situation, for
example, Tan (2002).
While there has been much research into sustainability issues from the perspective of
businesses and students, there is a need for more research from the perspective of the
consumer (Voronoff 2005). In addition, Gilg et al. (2005, p. 503) noted the need for
policy makers to focus on “changing the language of consumption, away from ‘green’
1.5 Justification for the research
26
and towards ‘sustainable’, so as to incorporate activities that do not necessarily have
green credentials, but also a greater focus on who does what”.
Voronoff (2005) noted the need for research that focuses on the individual, as
community sustainability happens at a “human scale” and within social networks. Such
research is also needed due to the “paucity of research on the topic in premier marketing
journals” (Chabowski, Mena & Gonzalez-Padron 2010, p. 1). This suggests a general
lack of high quality research in this domain.
In summary, this study is designed to examine the intention and uptake of sustainable
behaviours among consumers. Further, there is the need for research to include a
representative sample of all the population of the country, as the opinions and
behaviours of students are not representative of the population.
2. Research is needed to confirm the adaptability of an extended version of
the TPB in predicting sustainable behaviour and intention.
Authors such as Shaw and associates (2000, 2003, 2005, 2006), Bennett et al. (2002)
and Wall et al. (2007) have called for more constructs to be included in the TPB to
better explain behavioural intention. Different iterations of the TPB have included
constructs such as personal normative motives and internal ethics, while moral intensity
has been included in studies that use the ethical decision-making process to understand
behavioural intention (Bennett, Anderson & Blaney 2002; Jones 1991; McMahon &
Harvey 2006; Singhapakdi, Vitell & Kraft 1996). This study proposes that these three
constructs – personal normative motives, internal ethics and moral intensity – be added
to the TPB, as previous studies have shown that individually they are good predictors of
sustainable and/or environmental behaviours.
3. There is the need to examine behaviour and intention for a range of
sustainable behaviours, and using different measures of behavioural
intention.
27
Another justification, addressed by the second aim of this study, is to measure
behavioural intention in two ways. As well as measuring behavioural intention using a
Likert scale, this study differs from others as it aims to measure a range of actual
sustainable behaviours that consumers intend to do (intention) and those that they have
done (past behaviours) in their daily lives. These behaviours range from those that are
easy to adopt to those that are more difficult to adopt.
Gilg, Barr and Ford (2005) measured “past behaviours” that were concerned with
environmental action in and around the home in the UK. They classified their green and
sustainable behaviours into three categories: purchase decisions, habits and recycling.
However, their study was restricted to daily behaviours such as keeping heating down to
save energy, using the shower rather than the bath, avoiding toxic detergents and
recycling glass. It did not include longer-term behaviours such as using solar energy and
installing double-glazed windows. Most of the other research studies have used models
such as the TPB to examine only one behaviour. For example, Trafimow and Borrie
(1999) used the TPB to examine the likelihood of stealing fossilised wood from
Petrified Forest National Park; Routhe et al. (2005) used it to predict the likelihood of
supporting the construction of a new dam; Hagger and Chatzisarantis (2006) studied the
likelihood of buying a magazine; and Shaw and Shiu (2003) used the TPB to predict
behavioural intention for buying fair trade products.
In conclusion, this study addresses some gaps in the literature. It is based on a
representative sample of Australian consumers and uses an extended version of the TPB
to measure sustainable behaviour and intention in two ways: by asking about the
likelihood of behaving in a sustainable manner, and by using lists of sustainable
behaviours that are relevant to consumers.
The outcome of this study will be to improve the ability of models such as the TPB to
explain sustainable behaviour and intention. It will also have many applications to
marketing practice as governments and other organisations will be able to use the
findings to better devise social marketing campaigns that target ways of achieving
greater commitment to and engagement in sustainable behaviours.
28
Using the literature, this thesis examines relevant concepts, constructs and theoretical
frameworks that relate to ethical and sustainable consumption. The three theoretical
frameworks developed for this study are based on extended versions of the TPB.
Specifically, these frameworks include attitudes, perceived behavioural control and
subjective norm, which were included in the original TPB as antecedents to behaviour
and intention. Extended versions of the TPB have also included personal normative
motives and internal ethics as antecedents to behaviour and intention. For this study, the
moral intensity construct is also included, as it has been demonstrated that moral
intensity influences the different stages of the ethical decision-making process.
The terms “capital” and “lifestyle” behaviour are defined in this study (see section
2.9.1), and these are used to label two of the exogenous constructs. There are three
dependent variables for this study, which are labelled likely behavioural intention,
capital intention and lifestyle intention. The capital and lifestyle “past” behaviour
constructs have been included as mediating variables to the two “capital” and “lifestyle”
intention constructs, respectively. Demographic variables are included to determine
their effect on the independent and the dependent variables.
Consequently, the three theoretical frameworks are developed as outlined in chapter 4,
and the research questions and hypotheses are elicited, based on these three frameworks.
The individual has been chosen as the unit of study, following Voronoff’s (2005)
recommendation of the need to understand issues such as sustainability from the
individual’s perspective. This is because individuals are responsible for their own
behaviour and ultimately have the ability to influence the behaviour and decision
making of others at home, in the workplace and away from home. The data for this
research was collected using an online survey with the final sample size of 511
Australians aged 18 years and older. The quantitative research methodology was
selected as the research questions required that the constructs were quantified, and
because all constructs that needed to be measured have been operationalised in existing
1.6 Developing the study
29
research. Depth interviews were used to pre-test the questionnaire and to develop the
scenario for the moral intensity construct.
The final stage of the research design involves a statistical evaluation of the findings
using SPSS and AMOS to produce a structural equation model (SEM) to test and refine
the theoretical frameworks and to provide a best-fit model. SPSS and AMOS allow for
testing the multiple interrelationships between the independent and the dependent
constructs, thus providing a higher level of complexity in the data analysis than more
traditional means (Cunningham 2008). As a result of the data analysis, a new body of
knowledge was developed and the theoretical framework was adjusted accordingly. The
process of this research study is shown in Figure 1.2.
Figure 1.2 The process of the research study
Source: Adapted from Zikmund (1997)
Identifying
relevant
constructs
Existing
theory and
gaps in the
research
Discussion of
the research
findings
Developing
theoretical
frameworks
Developing
research
questions and
hypotheses
Methodological
development
and data
collection
Analysis of the
data using
SPSS and
AMOS
Relate to theory
and contribute to
the body of
knowledge
30
The structure of this thesis is based on Perry’s (1995) approach to presenting a PhD
thesis. There are seven chapters:
Chapter 1 provides an introduction and background to this thesis.
Chapter 2 is the first of the two literature review chapters. It provides an
introduction to the research study, defining the context and background,
focusing on sustainability, ethical consumption and social marketing. This
chapter is written in the context of the increasing interest in understanding
environmental and social issues from the business and marketing perspective in
the literature. Included is a discussion on the impact that ethical and sustainable
practices have on our lifestyles and the systems in place in society, as well as the
kinds of sustainable behaviours that have been measured in relevant studies.
Chapter 3 is the second part of the literature review. It includes a review of the
literature related to studies of the ethical and sustainable decision processes used
by consumers, households, organisations and businesses. This chapter
demonstrates the diverse range of studies and theoretical models that have been
published with respect to behavioural intention, ethical behaviour, sustainability
and decision making. In doing so, it focuses on the exogenous constructs that are
included in the theoretical frameworks: behavioural beliefs, attitudes, control
beliefs, perceived behavioural control (PBC), normative beliefs, subjective
norm, personal normative motives (PNM), internal ethics and moral intensity. It
also includes a discussion about variables such as demographics, behaviours and
values that can affect decision making. In considering the appropriate theoretical
frameworks to investigate the research question, authors from various marketing
disciplines including marketing, psychology and sociology are considered.
1.7 Structure of the thesis
31
Chapter 4 formalises the theoretical frameworks and defines the related research
questions and hypotheses. The theoretical models include the exogenous latent
constructs that may lead a consumer to intend to adopt sustainable behaviours.
The rationale explaining the linkage between the exogenous constructs, the
demographic variables and the behaviour and intention constructs is articulated.
Chapter 5 discusses the methodology used to develop and collect the data for
this study. Included is an outline of the paradigmatic issues and ethical
considerations, as well as details of the exploratory and quantitative research
methodology and the sampling method used to collect the primary data. The
discussion focuses on the development of the questionnaire and a description of
how each of the constructs and control variables is measured, along with key
reliability and validity issues that have been considered in the research design.
Chapter 6 includes a presentation of the findings from the survey questionnaire
based on the research questions and hypotheses that are outlined in chapter 4.
This chapter describes the process of analysing the findings based on the
quantitative research using SPSS and AMOS. This analysis includes
correlations, means, standard deviations, exploratory factor analysis (EFA),
confirmatory factor analysis (CFA) and SEM. A profile of the respondents in the
final sample is also included.
Chapter 7 discusses the implications and conclusions of this study and links the
primary research findings to the theoretical framework. Based on the study’s
findings, it includes the development of modified theoretical frameworks, and
recommendations are made about areas for further research. This chapter raises
issues that need to be considered when marketing sustainability to consumers
and outlines the limitations of this study.
The structure of the thesis is presented diagrammatically in Figure 1.3
.
32
Figure 1.3 Structure of the thesis (adapted from Perry (1995))
Chapter 1: Introduction
to the research study
Chapters 2 and 3:
Literature review
Chapter 2: The context of the study: social
marketing, sustainable and ethical issues
and behaviours
Chapter 3: Models of ethical behaviour,
latent constructs and segmentation variables
Chapter 4: Theoretical
framework, research
questions and hypotheses
Theoretical frameworks, research
questions and hypotheses, description of
the constructs
Chapter 5: Research
methodology and design Research methodology, data collection
and data analysis techniques, reliability
and validity
Chapter 6: Analysis and
results
Description of the sample, data analysis
and hypothesis testing using EFA, CFA
and SEM
Chapter 7: Discussion,
conclusions and
recommendations
Research discussion, contribution to
theory and practice, recommendations for
further research
33
The five key terms which are critical to this thesis are described below.
Ethics is a “characteristic which constitutes good and bad human conduct and
that which decides what is good and evil, right and wrong and thus what we
ought and ought not to do. The ethical sense of right and wrong is derived by a
set of social values through which our actions can be tested. In a social group,
the ethical standards are set keeping the social values as the base” (Maheshwari
& Ganesh 2006, p. 76).
An ethical consumer is one “who consider[s] environmental issues, animal
issues and ethical issues, including oppressive regimes and armaments, when
shopping” (Shaw et al. 2005a, p. 185).
A moral or ethical decision is “One that is both legal and morally acceptable to
the larger community” (Jones 1991, p. 367). According to Jones (1991), the
terms “moral” and “ethical” are considered to be equivalent terms and are used
interchangeably in this study.
A moral or ethical issue is one that has a moral or ethical component which has
“consequences for others and involves choice, or volition, on the part of the
decision maker”. Such an issue is one that “is present where a person’s actions,
when freely performed, may harm or benefit others” (based on the work of
Velasquez and Rostankowski 1985, cited in Jones (1991, p. 367)).
The OECD describes sustainable consumption as “The consumption of goods
and services that meet basic needs and quality of life without jeopardising the
needs of future generations” (2002, p. 16).
1.8 Definition of key terms
34
Chapter 2 gives a detailed description of the first part of the literature review by
discussing the context of this research study.
35
Chapter 2: Literature review – the context to the study
Since the end of the eighteenth century, mankind has been aware of the need to adopt
behaviours to protect the environment. It was at this time that the effects of
industrialisation and economic development coupled with population growth greatly
increased the demand for environmental resources. Over time, the increasingly rapid use
of natural resources and the resultant increase in waste materials has had an impact on
ecological systems and quality of life throughout the world (Riedy 2005).
The prominence of these issues intensified in the 1990s which was labelled as the
“decade of the environment”. Social and environmental concerns assumed more
importance in the decision-making process of consumers and organisations (Menon &
Menon 1999), and it was claimed that at least 50% of Australians had made
considerable behavioural adjustments for environmental reasons and there was growing
interest in the wider availability of “greener” products (Said 1996).
Coupled with the growing awareness of the need to protect the environment, the 1990s
saw the emergence of consumer ethics research. This was the result of the need to study
the effects of environmental, sustainable and green issues which were classified as
ethical issues. While there had been some research into ethics in the marketing domain
prior to the 1990s, only 5% of these studies examined ethics in consumer situations
(Vitell 2003). In such a climate, it seems that understanding ethical consumption from
the consumer’s perspective is central to our understanding of consumer behaviour.
This research study posits that in order to enable a more effective response to marketing
campaigns that target sustainability and ethical decision making, these concepts need to
be investigated in more detail. This chapter describes the literature related to the context
2.1 Introduction
36
and background of this study, focusing on social marketing, sustainability and ethical
consumption. The next chapter (chapter 3) explores models and theoretical frameworks
that describe the determinants of consumers’ sustainable attitudes and motivations
related to their ethical behavioural intention and actual behaviours.
Figure 2.1 summarises the topics that are examined in the two literature review
chapters.
Figure 2.1 Topics to be examined in the literature review
In pursuing the literature review, environmental and sustainable consumption have been
examined where possible from the individual consumer’s perspective. Due to the scant
literature relating to the individual consumer’s perspective on sustainable marketing and
ethical decision making, the author has also examined literature that discusses the issues
from the perspective of the community as a whole and the business or organisational
perspective. Conceptual papers have also been included.
This research study focuses on the literature that relates to the marketing context, where
possible. In some instances, concepts and theory that relate to disciplines such as
sociology or consumer psychology have also been included where they give useful
information relating to the aims of the study.
Figure 2.2 provides a roadmap of this chapter.
Chapter 2: Context of the
research study
Social marketing Sustainability and sustainable consumption Ethical and green consumption Environmental consumption The Social Practices Model – capital and lifestyle behaviours Changing behaviours
Chapter 3: Theoretical frameworks
Behavioural intention models Models of ethical decision making Theory of Reasoned Action and Theory of Planned Behaviour The latent exogenous constructs Demographic variables, knowledge, values and behavioural variables
37
Figure 2.2 Roadmap of chapter 2
Source: Adapted from Perry (1995)
Before issues such as “sustainability” and “ethical” are discussed, the next section
describes social marketing, which forms important background information for this
thesis.
Social marketing is focussed on achieving behavioural change at all levels of society:
micro, group, macro-national and macro-global (Domegan, Davison & McCauley
2.2 Social marketing
Chapter 2: Literature review – the
context of the research study Sustainability, sustainable,
ethical, green and
environmental consumption
The Social Practices Model –
capital and lifestyle
behaviours
Sustainable behaviours
Social marketing
Changing behaviours
38
2010). It largely originated from rising customer and employee expectations,
government legislation and pressure, investor interest in social criteria, and changing
business procurement practices (Kotler 2002).
As social marketing has its roots in psychology, anthropology and economics, there was
debate over its definition and boundaries. One of the first instances can be attributed to
Kotler and Levy (1969) who proposed a broadened concept of marketing by questioning
whether the marketing principles of the time were “transferable to the marketing of
organisations, persons and ideas”. They argued that there was a need to rethink the
“product” construct, suggesting that the definition should include not only physical
goods, but also services, persons, organisations and ideas. This was important because
social marketing is often viewed as the promotion of “ideas” only. Secondly, they
asserted that an organisation’s perspective of their customers also needs to include other
stakeholders such as suppliers, trustees or directors and the general public.
Kotler and Levy’s (1969) recognition of the need for a broadened concept of marketing
initially met with some criticism. Authors such as Luck (1969) believed that they had
gone “too far” conceptually, and that they had not given enough consideration to the
complexity of such a broadened concept. Needless to say, the debate continued with
Kotler and Zaltman (1971) arguing that “specific social causes could benefit from
marketing thinking and planning” (p. 11), citing issues such as pollution control, mass
transit and drug abuse. They saw social marketing as a “bridging mechanism” between
the behavioural scientist’s knowledge of human behaviour and the “socially useful
implementation of what that knowledge offers” (Kotler & Zaltman 1971, p. 12).
Andreasen (2002, p. 7) argued that social marketing should be described as a “process
for developing social change programs” with the ultimate objective of effecting
behavioural change, beyond the original idea of simply gaining acceptance of the idea
of social change. His definition has been used widely: “the application of commercial
marketing technologies to the analysis, planning, execution, and evaluation of programs
to influence the voluntary behaviour of target audiences in order to improve their
personal welfare and that of their society” (p. 7).
39
Donovan and Henley (2003) argued that this definition was too restrictive as it only
related to voluntary behaviours, was too complex and was not widely generalisable.
Donovan and Henley (2003, p. 16) described social marketing as “seek[ing] to inform
and persuade and, where deemed necessary, to legislate to achieve its goals.” Another
definition described it as a tool that can be used to influence a target market to change
their behaviour for the sake of “improving health, preventing injuries, protecting the
environment, or contributing to the community” (Kotler, Roberto & Lee 2002, p. 5).
The link between social marketing and understanding consumer behaviour in the
sustainable context was recognised by their shared objective of influencing behaviour
(Glenane-Antoniadis et al. 2003). One of the main distinctions was that social
marketing aims to achieve behavioural change “and engender goodwill for the benefit of
society” (Glenane-Antoniadis et al. 2003, p. 335), whereas consumer behaviour aims to
affect change in consumption patterns, not necessarily for the benefit of society.
The next section discusses examples of social marketing campaigns.
The multiple exchange processes require managers of social marketing campaigns to
satisfy and involve the extensive network of stakeholders (Domegan, Davison &
McCauley 2010). There is a greater scrutiny of marketing practices that are seen to be
harmful to society, including issues that are related to environmental degradation such
as the increasing amounts of waste materials (Bekin, Carrigan & Szmigin 2006). Such
social perspectives on sustainable development emphasise the individual and cultural
factors that drive humans to damage (or protect) the environment. They draw attention
to the human impacts of economic and environmental issues and focus on ways of
bringing about personal and organisational change through policy and individual action
(Riedy 2005).
2.2.1 Examples of social marketing campaigns
40
The objective of many social marketing programs was to change people’s behaviour in
order to improve their health and well-being (i.e. the benefit). They have also been used
to encourage the “de-marketing” of products or behaviours such as littering and
smoking. Other examples include campaigns to reduce drink driving and tobacco use,
and to promote the adoption of sustainable products or behaviours.
There have been a number of environmental programs that have adopted a social
marketing approach, such as campaigns to reduce water consumption and to increase
recycling in Australia. The Body Shop’s social marketing campaign emphasises the
environmental and social attributes of its products (http://www.thebodyshop.com).
The Big Clean Up (BCU) in Auckland, New Zealand is an example of a community
based social marketing campaign that resulted in increasing sustainable behaviours in
households and businesses. This project, which started in 2001, was mainly targeted at
consumers who are not already committed to a “green” lifestyle. The BCU aimed at
reducing pollution, restricting the burning of rubbish or garden waste and reducing
consumption of water and electricity. While described as a successful campaign, it has
been recognised that changing behaviour is a long-term process that requires co-
operation between “individuals, groups and society” (Frame 2004).
Although providing information can be an effective means of generating awareness and
changing attitudes, it was believed that behavioural change will not necessarily occur
with such a stimulus. Community based social marketing was developed as an
alternative to information based campaigns by focusing on marketing initiatives that are
directed at the community level. The process includes selecting and identifying barriers
to behaviours, developing programs to target the behaviours and to overcome the
barriers, implementing the program and evaluating its effectiveness (McKenzie-Mohr &
Smith 1999). Community based social marketing is important to this research as it could
be used to implement social marketing campaigns that aim to increase the uptake of
sustainable behaviours.
41
Over 20 years ago, the Brundtland Commission (1987) defined sustainable development
as the “adoption of sustainable behaviours that would meet the needs of current
generations without compromising the ability of future generations to meet their needs”
(p. 43). While this description of sustainable development continues to be widely
quoted, Riedy (2005, p. 14) commented on its “vagueness”, in particular, the definition
of “needs”, whose needs take precedence in cases of conflict, and whether any genuine
sacrifices in terms of lifestyle are required (Chabowski, Mena & Gonzalez-Padron
2010, p. 77).
Convincing consumers to behave in a sustainable way or to adopt a sustainable lifestyle
is a gradual process that is part of a holistic move towards a new lifestyle (Gilg, Barr &
Ford 2005). While Schaefer and Crane (2010) commented that sustainable
consumption is probably rare for affluent consumers and restricted to a small number of
highly committed environmentalists, this could be changing as more consumers adopt
sustainable practices. Such a changed orientation in the way that consumers live their
lives has led marketers to adopt a “new marketing orientation” (Karna, Hansen & Juslin
2003). Both Strong (2000) and Karna, Hansen and Juslin (2003) have argued that this
“new marketing orientation” accounts for the fact that today’s marketers need to
consider sustainability as part of their overall strategy. This is particularly true as
consumers pursue their affluent lifestyles and as developed countries put their
competitive needs ahead of concern for the environment.
Another perspective on sustainability defines it in terms of “balancing economic,
ecological, and social goals and consequences” (Chabowski, Mena & Gonzalez-Padron
2010, p. 77). For the purposes of this study, sustainability is defined in terms of its
impact on the environment and the systems in place in society, based on what is done in
consumers’ daily lives. In this way, their actions in adopting a sustainable lifestyle can
help to protect the long-term viability of the planet.
2.3 Sustainability
42
The next section discusses various definitions of sustainable consumption.
The process of adopting sustainable consumption behaviours has been often discussed
in the literature and consequently there are many terms used to describe “sustainable
consumption”. One of the simplest definitions is:
“consumption that entails reduced adverse environmental impacts” (Paavola
2001, p. 228).
The OECD defines it as:
“consumption of goods and services that meet basic needs and quality of life
without jeopardising the needs of future generations” (2002, p. 16).
Sustainable consumption refers to practices that include “community sustainability” as
described by Voronoff (2005), as well as “sustainable behaviour” (McKenzie-Mohr &
Smith 1999) and “pro-environmental behaviours” (Jackson 2005, Wells, 2011). None
of these authors offered definitions of the terms; they only gave examples to illustrate
what they understood them to mean. For example, Voronoff (2005) used “community
sustainability” to refer to the processes that can be used to achieve a sustainable society:
Community sustainability “involves fostering a sense of responsibility for and the
adoption of pro-environmental actions, practices, choices, lifestyles, behaviours or
habits that have the effect of reducing resource consumption and waste”
(Voronoff 2005, p. 7).
Voronoff (2005, p. 6) used this term deliberately to find a “neutral ground” between the
term “sustainable behaviour” used by social psychologists such as McKenzie-Mohr and
Smith (1999) and the term “sustainable consumption” used by authors such as Jackson
(2005) and Spaargaren (2003). Such sustainable behaviours can be applied to short-term
2.4 Sustainable consumption
43
solutions such as recycling or buying organic foods and to long-term solutions such as
building new dams (Routhe, Jones & Feldman 2005) and installation of solar panels and
reducing greenhouse emissions (Jackson 2005). These examples will be discussed later
in this chapter.
In terms of industry specific studies on sustainability, Carson, Gilmore, Ascenção and
Fawcett (2004) used tourism as an example of an industry that can utilise both the
sustainability and the marketing concepts. They noted that when promoting a location,
the industry needs to find the right balance between concern for the environment along
with the infrastructure, facilities and communications aspects of the sites. Their
recommendations included more emphasis on promoting the sustainability of tourism
sites, as this recognises the importance of social and environmental needs, while
protecting these locations for future generations. In other words, there is the need to find
the right balance between the social impacts of tourism such as improving lifestyles and
well-being, meeting consumers’ needs and wants, and physical impacts such as
preserving natural resources and the environment.
What is evident from the literature is that the terms ethical, sustainable and green
consumption have been used interchangeably. The next sections investigate the
literature, starting with ethics and ethical consumption.
Social theorists and psychologists are responsible for much of the early academic work
on ethical behaviour. They developed their theories based on the social impacts of
materialism and on Maslow’s hierarchy of needs (Cherrier & Murray 2004).
Maheshwari and Ganesh (2006, p. 76) defined ethics as a characteristic “which
constitutes good and bad human conduct and that which decides what is good and evil,
right and wrong, and thus what we ought and ought not to do”. As such, it refers to
choices that an individual makes which are derived by a set of “social values through
which our actions can be tested” (Maheshwari & Ganesh 2006, p. 76).
2.5 Ethics and ethical consumption
44
Ethical consumers are “those consumers who consider environmental issues, animal
issues and ethical issues, including oppressive regimes and armaments, when shopping”
(Shaw et al. 2005b, p. 185). Cherrier’s (2005) phenomenological study of nine
American respondents who “consume ethically” established that individuals internalise
their own ethical consumption behaviour, and that social norms need to be internalised
in order to influence behaviour.
The term “ethical consumption” is widely used and is responsible for the emergence of
marketing practices that target these ethical consumers (Shaw et al. 2005). The growth
of ethical consumerism largely resulted from seven occurrences: “the ‘caring’ customer
of the 1990s; peer group pressure; media interest; increasing corporate responsibility;
supplier power; the wider availability of fair trade products; and the high quality and
performance of alternatives” (Tallontire, Rentsendorj & Blowfield 2000, p. 7).
Ethical consumption is defined as “the conscious and deliberate choice to make certain
consumption choices due to personal and moral beliefs” (Carrigan, Szmigin & Wright
2004, p. 401). Ethical consumption behaviours or “ethical consumerism” are “decision
making, purchases, or other consumption experiences that are affected by the
consumer’s ethical concerns” (Cooper-Martin & Holbrook 1993, p. 113).
“Ethical consumerism” refers to behaviours that incorporate all the principles of
environmental consumerism (Tallontire, Rentsendorj & Blowfield 2000), and while
“marketing is a tool used to increase consumption to the benefit of capitalist
exploitation” (Cherrier & Murray, 2004, p. 520), this is not always to the benefit of the
environment. In other words, not all of what we consume may be necessary for our
daily lives. It is the commercial interests in modern society that have created the
multitude of goods and services that are now regarded as “needs” that in reality could
pose a threat to the environment (Cherrier & Murray 2004). For example, consider
household electrical appliances: how many are used and how many are actually needed?
Tallontire, Rentsendorj and Blowfield (2000) described three types of ethical
consumerism: positive ethical purchase behaviour, negative ethical purchase behaviour,
and consumer action or lobbying. Positive ethical purchase behaviour is associated with
45
buying goods with ethical characteristics; negative ethical purchase behaviour is
associated with boycotts, avoiding goods with unethical characteristics (such as clothing
made in ‘sweatshops’ in China); and consumer action or lobbying is associated with
activities such as lobbying and taking direct action about an issue (Ouellette & Wood
1998).
There is growing evidence that ethical concerns for many issues including the
environment are increasing and are evident when consumers adopt or change their
lifestyle to a more “sustainable” or “green” orientation (Paavola 2001). Ethical concerns
are responsible for the increasing popularity of organic and fair trade food, as well as
raised concerns about the environmental damage of some farming practices (Gilg, Barr
& Ford 2005; Shaw & Shiu 2003). They have resulted in ethical consumption which
includes the market for ethical investment products, organic produce (Shaw et al. 2005,
p. 186), the emergence of the market for fair trade products and media interest in fair
trade issues, and increasing corporate responsibility and supplier power (Carrigan,
Szmigin & Wright 2004; Tallontire, Rentsendorj & Blowfield 2000).
Karna et al. (2003) used the term “environmental” or “green” marketing to describe the
move towards sustainable development which aims to satisfy stakeholders in a
profitable and sustainable way. Thus, ethical and green consumerism can be used as a
source of competitive advantage for “socially and ethically aware organizations”
(Tallontire, Rentsendorj & Blowfield 2000, p. 11), hence the development of recycled
products and pro-environmental reusable shopping bags.
It is important to understand that, while consumers who adopt ethical behaviours can be
considered to be ethical consumers, the reverse does not always apply. For example, “on
one level, I am an ‘unethical’ consumer since I do not concern myself with issues of
animal cruelty or sweatshop labour when making purchases, but I am also ‘ethical’
since I buy ‘fair trade’ coffee and recycled paper products” (Carrigan, Szmigin &
Wright 2004, p. 416). In other words, a person or business that does not use a fair trade
product is not necessarily considered to be unethical. However, there is evidence that
although consumers may act in an ethical manner, this does not necessarily mean that
they prefer sustainable products (Kim 2010).
46
Bekin, Carrigan and Szmigin (2006) demonstrated that, until recently, many consumers
had not understood how they could significantly improve their own behaviour with
respect to ethical issues. They suggested that the literature avoided addressing waste and
disposal behaviour as an example of an action that is potentially empowering to
consumers. Changing consumers’ behaviours so that they could achieve their
environmental goals means that they need affordable and skilled resources to assist with
their recycling and encouragement to take a less disposable view of their possessions
(Bekin, Carrigan & Szmigin 2006).
In this thesis, the words “ethical” and “moral” are used interchangeably according to
their use in the extant literature. Notably, Jones (1991) noted that the terms “moral” and
“ethical” are considered to be equivalent terms. He defined a moral or ethical decision
as “One that is both legal and morally acceptable to the larger community” (Jones 1991,
p. 367). Another example was given when May and Pauli (2002) when they were
discussing the Theory of Planned Behaviour and moral intensity (see chapter 3). They
noted that the process of moral decision making was also referred to as “ethical decision
making”.
The previous discussion has highlighted that moves towards sustainable and ethical
consumption have lead to the development of products that are environmentally
friendly. Environmentally ethical views are “the moral relationship between the human
race and the natural environment” (Tsai & Tsai 2008, p. 288). In this way,
“environmental ethics” address questions such as whether the ethical relationship
between the human race and the natural environment is appropriate (Tsai & Tsai 2008).
From this, we can assume that environmental ethics is an extension of ethical
consumption, as it occurs when natural resources are treated not just as commodities but
as segments of the whole ecology (Shaw et al. 2005). Social marketing campaigns to
reduce energy and water consumption are examples of campaigns that encourage
2.6 Green and environmental consumption
47
“environmental ethics” as they lead to a reduction in the impact of environmental
consumption.
An awareness of environmental ethics can lead to environmental consumerism, also
referred to in the literature as “environmentally responsible consumption” and “green
consumption” (Arnould, Price & Zinkhan 2004). These refer to behaviours “undertaken
with the specific aim to reduce negative impacts on the environment” (Chabowski,
Mena & Gonzalez-Padron 2010, p. 90). They include activities related to the
purchasing, use and disposal of goods such as buying organic produce, fair trade goods,
looking for products with less packaging, using recycled paper products and using
products such as detergents that have a reduced environmental impact (Gilg, Barr &
Ford 2005). Green activities also refer to non-purchase decisions such as recycling and
using one’s own bag, rather than a plastic carry bag provided by a shop.
Green consumption can be extended to include the consumption behaviours of
consumers who avoid certain types of products. These include actions that cause
damage to the environment and products linked with cruelty to animals (Chabowski,
Mena & Gonzalez-Padron 2010), as well as purchasing environmentally friendly
products or adopting behaviours such as recycling (Carrigan, Szmigin & Wright 2004).
In other words, the behaviour of green consumers is “affected by pro-environmental
attitudes and behaviours” (Arnould, Price & Zinkhan 2004, p. 827). A “green
orientation” can vary according to the situation as in some instances green consumers
may behave in a sustainable manner, whilst in others they may show little concern for
the environment. For example, choosing to buy organic products may mean that the
products have to travel a long way, which is not necessarily good for the environment,
and using one’s own shopping bag may not take into account the environmental impacts
of its production.
While ethical concerns are often ongoing and cannot be addressed by social marketing
campaigns, green consumption can be managed on a social level because the ethical
consumer tends to stick to their principles (Seyfang 2006). For example, being
concerned about the “people” aspects of issues such as manufacturing, they may avoid
products made in the Third World where workers are paid low wages and live in poor
48
conditions (Tallontire, Rentsendorj & Blowfield 2000). Such concerns about
“environmental” and “green” issues have been attributed in part to the increasing
popularity of products such as organic food, which can alert other consumers to ethical
concerns about issues such as modern farming practices and their consequent damage to
the environment (Shaw & Shiu 2003). This has led to the development of models of
consumer decision making which consider a societal-centred viewpoint of consumption.
What is common to this discussion is that it does not matter whether or not a consumer
is “ethical” or “sustainable” or “green”, but there is a need to consider their total
purchases and behaviours rather than focusing on what they do not do. In fact,
consumers have a choice about their behaviour and many practise “consumption as
voting” or “voluntary simplicity” or “individuation” as they use their purchase or non-
purchase in the market place as a form of demonstrating their empowerment (Shaw,
Newholm & Dickinson 2006).
“Voluntary simplicity” means choosing to limit material consumption in order to free an
individual’s resources, primarily money and time. This then allows them to seek
satisfaction through non-material aspects of life (Shaw & Newholm 2002). It means that
as consumers we are creating societies according to what we purchase or use (or don’t
purchase or use) and the consumption behaviours that we adopt. In a similar way,
“individuation” describes the personal actions that people take when they decide to
consume or not to consume, indicating that the motivation to act can be very much one
of an “individual duty” (Shaw, Newholm & Dickinson 2006). Such individuals are
trying to maximise control over their lives and to minimise their dependence on
institutions (Iwata 2006) by declaring that the motivation to act is their own individual
decision or one of “individual duty” (Chabowski, Mena & Gonzalez-Padron 2010).
Consumers who have the time to consider the information available to them can then
make a judgement that may or may not result in a decision to buy or use an ethical
product or service, and in this respect they appear to be behaving responsibly and
ethically (Carrigan, Szmigin & Wright 2004). It seems therefore that “individuation”
applies to situations where the consumption behaviour falls under the banner of being
“ethical” or when there exists a more ethical alternative.
49
The previous discussions have demonstrated that sustainable consumption is different to
ethical consumption as it relates to a wide range of behaviours, some of which are not
necessarily ethical. For example, boycotting a brand because the manufacturer uses
cheap labour is an ethical choice rather than a sustainable choice. Ultimately, such
behaviours represent an individual choice that is contingent upon living in the world
today (Beck 1992). What is evident is that all green products and behaviours are
sustainable and ethical, but that the reverse does not necessarily apply.
Ethical consumption behaviour has been described as a “selfless and active practice”
(Cooper-Martin & Holbrook 1993) conducted within the constraints imposed by a
situation and one that has ethical consequences. While the consequences of not adopting
ethical consumption behaviours can have serious ramifications, the consequences of not
adopting sustainable behaviours are not necessarily so serious. What is important is that
consumers’ awareness of ethical (and moral) concerns is raised so that they recognise
that there is an ethical element attached to the issue, that their decision to act will affect
others and that some choice must be involved, in other words, that the person has
“volition” or a choice (Jones 1991). Therefore, sustainable consumption is considered to
be one of the possible outcomes of an ethical decision, but it does not necessarily lead to
ethical consumption. It has also been said that the word sustainable refers to products
with positive ethical attributes (Luchs et al. 2010). In this way, it can be regarded as a
precursor to ethical consumption, which explains the link between the two.
In a similar way, the term “green consumption” refers to the consumption behaviours of
consumers who adopt or avoid certain types of products. A green orientation can vary
according to the situation as in some instances green consumers may behave in a
sustainable manner, whilst in others they may show little concern for the environment.
It may lead to the consumer being considered to be ethical and sustainable, but it is not
necessarily linked to being environmental. Examples include behaviours such as using
dual flush toilets and buying organic and fair trade products.
2.7 Linking ethical, sustainable and environmental consumption
50
Figure 2.3 has been adapted by the author to summarise the link between green,
sustainable, environmental and ethical consumption behaviours. It illustrates that green
consumption behaviours are important in order to achieve sustainable and ethical
consumption behaviours, but that not all green behaviours are environmental. It also
shows that not all sustainable behaviours are ethical.
Figure 2.3 Linking green, sustainable and ethical consumption
Source: Adapted from Rex (2008)
This research study will focus on sustainable consumption behaviours.
Both in Australia, and throughout the world today, consumers are faced with water
shortages, climate change, greenhouse emissions and pollution, loss of species, waste
and rubbish disposal and recycling (www.sustainability.vic.gov.au). According to a
Roy Morgan Poll conducted in 2008, 55% of Australians believe Global Warming is
one of the most important environmental issues facing the world today, with 23%
believing pollution and 21% water management issues (including drought) are also
prominent issues. Water conservation is a more important issue in Australia where 46%
of respondents believe water conservation, water management or drought is the most
2.8 Sustainable behaviours
Green consumption
Ethical consumption Sustainable consumption
Environmental consumption
51
important environmental issue facing Australia; while Global Warming (28%) is less
important in Australia http://www.roymorgan.com/resources/pdf/papers/20080505.pdf.
Such environmental issues have prompted the need for consumers to change their
consumption behaviour. This has lead to the need “to conceptualise sustainable
consumption behaviour, lifestyles and daily routines” (Spaargaren 2003, p. 687).
Social marketing campaigns are designed to address such issues by raising the
awareness and adoption of sustainable and environmental behaviours. Examples include
campaigns to encourage consumers to use reusable shopping bags and the campaign in
Melbourne, Australia to encourage consumers to restrict their water usage to 155 litres/
day/ person.
Adopting sustainable behaviours is a personal choice that is largely based on social
norms and can have little or no benefit for the individual. For example, recycling is
more inconvenient than just disposing of a container (due to rinsing and sorting) as well
as having no monetary or utilitarian reward. Much social pressure exists to undertake
(or not) sustainable behaviours (Fielding et al. 2008). It is hoped that, due to high
visibility and social pressures, consumers will readily undertake such activities or they
will claim to do so, in order to be seen to be acting as they want others to accept
(Fielding et al. 2008). In this way, sustainable consumption behaviours will manifest
themselves in order to achieve a sustainable society.
When seeking examples of sustainable consumption behaviours, the search revealed
many ‘hits’ in both refereed and non-refereed sources. Sustainable websites such as
http://www.sustainable.com.au/ listed specific products such as front loader washing
machines, rain water tanks and solar systems for energy and hot water. Other examples
of sustainable behaviours included those that involved a more substantial capital outlay
and provided a longer-term solution such as construction of sustainable buildings,
renewable energy and harvesting rain water (http://www.sustainable.com.au/).
Routhe et al. (2005) examined the cognitive, evaluative, conative and behavioural
influences that determined public support for building a dam, and Petts et al. (1998)
examined concern for the environment. Petts et al. (1998) examined issues such as toxic
52
waste, radioactive waste, household waste disposal, sewage and oil spills, loss of
wildlife, ozone layer depletion, the need for energy conservation, air quality, extinction
of wildlife, water quality, traffic, global warming, noise, loss of open spaces and
pollution (1998, p. 712, 717). They showed that individuals are concerned about the
environment and that they have a “broad understanding of environmental issues and
concern that businesses should behave in an environmentally responsible manner”,
which they commented mirrors the findings reported in general public surveys (p. 728).
In their studies, Granzin and Olsen (1991), Laroche et al. (2001) and Spaargaren (2003)
included sustainable activities such as using non-phosphate detergents, avoiding throw-
away plastic bags and packaging while shopping, recycling and using bicycles, public
transport or walking for short-distance travel. Voronoff (2005) included behaviours
such as taking a shorter shower and restricting the watering of gardens. Peattie and
Peattie (2009) discussed behaviours such as recycling, (not) lawn-watering, and
installing tanks and solar systems.
Jackson (2005, p. 3) gave the following examples of pro-environmental behaviours:
“recycling of household wastes, purchase of ‘sustainable’ products, using energy
efficient appliances, choosing green electricity tariffs, composting garden and kitchen
waste, investing in ‘ethical’ funds, conserving water or energy, buying organic food,
returning electrical goods for reuse or recycling, switching transport mode, changing
travel behaviour, buying remanufactured or reused goods, reducing material
consumption and pursuing ‘voluntary’ simplicity (a lifestyle choice)”.
Pickett-Baker and Ozaki (1999) found that recycling bottles, cans, glass and
newspapers, as well as composting garden waste, were the most likely environmental
behaviours that had been done by their sample of females in London, and attributed
their adoption to recent social marketing campaigns. They also argued that the success
of such campaigns can be attributed to strong normative influences from family and
friends, especially from younger household members.
53
Despite the many examples of sustainable behaviours, there were few models that
provided a classification of these behaviours. One that is relevant to the consumption of
sustainable products and behaviours is Spaargaren’s (2003) ‘Social practices’ model.
Spaargaren’s (2003) Social practices model relates sustainable consumption behaviours
to social (behavioural) practices by relating social practices with the “actor” (lifestyle)
and the “structure” (the system of provision). It is a sociological model as it focuses on
actual behavioural practices “that an individual shares with other human agents”
(Spaargaren 2003, p. 687). In this way it differs from attitude-behaviour models such as
the TPB (which is described in chapter 3) as these behavioural practices are at the centre
of the model rather than constructs such as attitudes or norms.
The social practices model has been used in this study as it “looks into the possibilities
for designated groups of actors to reduce the overall environmental impacts of their
normal daily routines involving clothing, food, shelter, travel, sport, and leisure” (p.
687). Second, it analyses the process of reducing the environmental impacts of
consumption in terms of the “deliberate achievements of knowledgeable and capable
agents who make use of the possibilities offered to them in the context of specific
systems of provision” (p. 687). In other words, Spaargaren’s (2003) model focuses on
actual behavioural practices “situated in time and space that an individual shares with
other human agents” (p. 688). This model is shown in Figure 2.4.
2.9 The Social practices model
54
Figure 2.4 The Social Practices Model
Source: Spaargaren (2003, p. 688)
Before strategies for behavioural change can be implemented, examples of sustainable
behaviours need to be summarised and categorised to ultimately understand which
behaviours can be changed and which have already been changed. While Spaargaren’s
(2003) Social practices model is a useful foundation, it lacks actual examples of
sustainable behaviours. For this study, these examples need to have direct implications
for resource consumption for individuals in their daily lives. The next section examines
ways to categorise examples of sustainable behaviours.
In seeking a direction to classify examples of sustainable behaviours, it is apparent that
they can be classified into two categories. For the purposes of this research study, these
are labelled “lifestyle behaviours” and “capital behaviours”. For the purposes of this
study, lifestyle behaviours are defined as:
“Lifestyle behaviours are those behaviours that relate to the lifestyle of the consumer
and require little or no capital outlay. Examples include using public transport
2.9.1 Lifestyle and capital sustainable behaviours
55
rather than driving, and turning off lights and electrical goods that are not
necessary. Lifestyle behaviours are also classified as behaviours that relate to usage,
hence using energy efficient appliances and non-phosphate detergents are classified
as lifestyle behaviours rather than capital behaviours.”
For the purposes of this study, capital behaviours are defined as:
“Capital behaviours are those behaviours that require a capital outlay, such as
buying a front loader washing machine and having windows double-glazed.”
These are further classified into behaviours that are intended to be done in the future,
which are labelled “lifestyle intention” and “capital intention”, respectively. Lifestyle
behaviours that relate to individual consumers in their daily lives have been defined
according to the study by Ouellette and Wood (1998), Kraft et al. (2005) and Hagger
and Chatzisarantis (2006) as behaviours that were done in the last two weeks. Lifestyle
intention refers to behaviours that the consumer intends to do in the next two weeks.
Capital behaviour is defined as behaviours that have already been done or installed, and
capital intention refers to behaviours that the consumer intends to do or install in the
next two years.
Fritzsche and Becker (1983) found that when moral dilemmas are faced, ethical
behaviour is more likely to be prompted by issues or behaviours that have serious
consequences, than by those that have modest consequences. It seems therefore that any
classification of behaviours should include a range of sustainable behaviours from those
that have little consequence, to those that have more severe consequences.
In adapting Spaargaren’s (2003) Social practices model, the author has developed a new
classification for sustainable behaviours. This is based on the work of authors such as
Petts et al. (1998) who examined behaviours related to concern for the environment;
Granzin and Olsen (1991), Laroche et al. (2001), Spaargaren (2003) and Jackson (2005)
who included sustainable activities such as using non-phosphate detergents, avoiding
throw-away plastic bags and packaging while shopping, recycling and using bicycles,
public transport or walking for short-distance travel; Voronoff (2005) who included
56
behaviours such as taking a shorter shower or restricting the watering of gardens; and
Peattie and Peattie (2009) who discussed behaviours such as recycling, (not) lawn-
watering, and installing tanks and solar systems.
The new classification proposes that changes need to be made to the labels used in the
Social practices model for it to apply to today’s environment. The “shelter/housing”
category has been relabelled “housing/sustainability at home”, “food” has been
relabelled “food/shopping”, travel has been relabelled “transport” and there is a new
category called “actions” that a person can take to reduce consumption or to influence
other people’s sustainable behaviours. Leisure, clothing and sport are not included in
this study as such behaviours are not deemed to be relevant.
It can be seen that all capital behaviours sourced from the literature are included in the
category labelled “housing and sustainability at home”. The examples of lifestyle
behaviours have been included in the four categories of “housing/sustainability at
home”, “food/shopping”, “transport” and “actions”. This is summarised in Table 2.1.
Table 2.1 Proposed classification for sustainable behaviours Spaargaren (2003)
New classification
Capital behaviours Lifestyle behaviours
Shelter/ housing
Housing/ sustainability at home
Dual flush toilets, energy efficient lighting, front loader washing machine, water efficient shower heads, dripper system in garden, rain water tank(s), recycling/grey water system, solar hot water/ electricity panels/heating, double-glazed windows and doors
Tried to save water, used energy efficient appliances, turned off lights/electrical goods that are not necessary, had a shower for more than four minutes (scale to be reversed), recycled household wastes, e.g. compost, newspapers, bottles, used non-phosphate detergents
Food Food/ shopping
Bought free range or organic products or fair trade products, restricted my use of plastic bags when shopping
Travel Transport Used public transport rather than driving
None Actions Lobbied or took direct action about an issue or brand or product, thought about reducing my greenhouse emissions, bought or did something positive to encourage sustainable behaviour, tried to reduce what I buy and use
57
As marketers strive to motivate sustainable consumption, they are challenged by the fact
that many people find themselves locked into consumption patterns that may be
unsustainable, often because of habit, routines, social norms and expectations, cultural
values, institutional barriers, inequalities in access and restricted choice (Van Vliet &
Stein 2004). In society today, “consumption is increasingly considered to be a private
affair” (Van Vliet & Stein 2004, p. 354). For this reason it can be difficult to change due
to the “network” bound systems to which modern households are connected, such as the
water supply and waste disposal systems.
Recognising the need to increase concern for the environment, governments have
moved towards developing and adopting policies to promote the uptake of sustainable
behaviours such as recycling and energy reduction programs. This has led to the concept
of “sustainable development” which has become embedded in many professions,
including architecture and town planning, and consequently has shaped the political and
economic policies of many levels of government (Staley 2006). The advent of “green
marketing” and triple bottom line accounting which includes a consideration of
corporate profits, as well as the community and the environment, are examples of
processes that focus on concern for the environment (Arnould, Price & Zinkhan 2004).
Sustainable development policies tend to rely on consumers making substantial changes
to their present (unsustainable) behaviour (Zabel 2005). Being restricted by the systems
that are currently in place means that any impediments will need to be substantially
reduced or fully removed before consumers can contemplate the uptake of a changed or
new behaviour, no matter how willing or how desirable it may be (Byrne & Polonsky
2001; Chabowski, Mena & Gonzalez-Padron 2010). Changing such fixed systems can
be more difficult than changing the behaviour of consumers, as ethical consumption
behaviour is directed and controlled by systems and structures of production and
competition (Cherrier 2005).
2.10 Changing sustainable behaviours
58
In general terms, behavioural change is less likely to occur when the behaviour has a
long-term rather than a short-term reward (Ouellette & Wood 1998). For example,
people may decide that they should adopt a healthier lifestyle. However, because the
short-term rewards are not immediately evident as they affect the person’s enjoyment of
life, the new behaviours are often quickly discarded. This can happen because of the
lack of immediate evidence that the new behaviour will yield positive outcomes, and it
is not until it becomes an automatic reaction that the long-term benefits are understood.
Consumers need to be given the opportunity to learn and adopt new behaviours by
understanding the long-term benefits, and the most effective change strategies are those
that impede performance of established behaviours while aiding in the formation of new
ones which become regular habits (Ouellette & Wood 1998).
Arkesteijn and Oerlemans (2005) demonstrated that effective behavioural change can be
achieved by encouraging consumers to manually switch between renewable and non-
renewable supplies at different times of the day. Other studies have shown that
consumer demand patterns respond closely to structural principles whereby the
consumer conforms to normative and prescribed practices of ethical consumption (Van
Dam & Stallaert 1978). Marketers need to encourage consumers to buy brands and use
services that are less damaging to the environment (Kalafatis et al. 1999).
Important too is the visibility of the behaviour. Diffusion theory postulates that early
adoption is closely linked to social visibility and is motivated by social benefits,
particularly when peer pressure is evident (Arkesteijn & Oerlemans 2005). To maintain
consumers’ interest in changing behaviours, such strategies should ensure that there are
immediate, positive consequences as a result of adopting the new behaviour, while
providing the opportunity for its repetition in an environment that supports this change
(Ouellette & Wood 1998). Adoption of different behaviours by peers or reference
groups can be seen to be an endorsement of its desirability (Arkesteijn & Oerlemans
2005).
59
Chapter 2 describes the context and background of this research study, focusing on
social marketing, sustainable behaviours, sustainability and ethical consumption. It is
argued that sustainable and ethical consumption patterns of behaviour are becoming
increasingly important due the increased awareness and concern about issues such as
global warming, pollution and a scarcity of natural resources for future generations. As
it has been recognised that behavioural change can be hard to achieve in society, the
development of the social marketing concept was examined.
Sustainable practices have been described as those that aim to reduce the impact of our
lifestyles on the environment and the systems in place to ensure our society’s long-term
viability. Ethical consumption behaviours refer to “decision making, purchases or other
consumption experiences that are affected by the consumer’s ethical concerns” (Cooper-
Martin & Holbrook 1993, p. 113). Raising consumers’ awareness of ethical concerns
and sustainable practices is needed to achieve a degree of concern for the environment,
and consumers need to adopt them as part of their daily lifestyle.
While much has been written about ethical, sustainable and environmental
consumption, there was confusion in the literature about the exact meaning of these
three terms which are often used interchangeably. First, it is apparent that sustainable
consumption is different to ethical consumption and that the consequences of not
adopting sustainable behaviours are not necessarily as bad as not adopting ethical
behaviours. Therefore, sustainable consumption is considered to be one of the possible
outcomes of an ethical decision, but it does not necessarily lead to ethical consumption.
It has been demonstrated that ethical concerns are determinants of achieving
environmental, sustainable and ethical consumption, and that not all ethical
consumption behaviours are sustainable.
There are many examples of sustainable behaviours in the literature and these have been
classified into categories of “lifestyle” and “capital” sustainable behaviours and
2.11 Chapter summary
60
classified according to Spaargaren’s (2003) Social practices model. All behaviours
included in the proposed model have direct or indirect implications for resource
consumption and therefore for sustainable consumption. Lifestyle behaviours are
defined as behaviours that require little or no capital outlay and relate to the consumer’s
lifestyle or usage; while capital behaviours are defined as behaviours that require a more
substantial capital outlay.
While this chapter has provided the context and background of this study, chapter 3
explores models and theoretical frameworks that describe the determinants of
consumers’ sustainable attitudes and motivations related to their ethical behavioural
intention and actual behaviours.
61
Chapter 3: Theoretical frameworks – investigating the
determinants of sustainable and ethical decision making
In 1987, the Brundtland Commission defined and examined sustainable development,
heralding the start of increased awareness of and commitment to adoption of sustainable
lifestyles. As discussed in chapter 2, this corresponded with studies of consumer
decision making being adapted to account for studies that examined ethical issues.
Chapter 3 provides an overview of the theoretical frameworks that have been considered
in the process of preparing this research study to address the aims outlined in chapter 1.
Sustainable issues have been classified as ethical issues in the literature and therefore it
seems logical to use models of ethical decision making to examine the antecedents to
sustainable behaviours and intention. The studies discussed in this chapter demonstrate
that developing an understanding of consumer and ethical behaviour was fundamental
for understanding how to motivate and encourage sustainable consumption and pro-
environmental consumer behaviour (Jackson 2005).
More specifically, this chapter focuses on theories and models of consumer behaviour
and ethical decision making, as well as diversity in the population, including
demographics, behaviours and values. This body of knowledge links the context of the
study as presented in chapter 2 to the theories of consumer behaviour and ethics.
Figure 3.1 provides a roadmap of this chapter.
3.1 Introduction
62
Figure 3.1 Roadmap of chapter 3
Source: Adapted from Perry (1995)
Chapter 3: Theoretical
frameworks –
investigating the
processes and
antecedents of
sustainable and ethical
decision making
Chapter summary
Latent
constructs that
influence the
likelihood to
engage in
sustainable
behaviours
Behavioural intention models
and models of the ethical
decision-making process
Demographic variables,
knowledge, values and
behavioural variables
Attitudes,
PBC,
subjective
norm, PNM,
internal ethics,
moral intensity
Theory of Reasoned Action
(TRA) and Theory of Planned
Behaviour (TPB)
63
Many models of ethical decision making are based on early models of the consumer
decision-making process developed and published over 40 years ago in textbooks by
authors such as Bettman (1979), Hansen (1972), Howard and Sheth (1969) and Nicosia
(1966). These models describe the five customer choice stages involved in the selection,
consumption and disposal of goods and services: problem recognition, information
search, evaluation of alternatives, purchase decision and post-purchase behaviour
(Kotler et al. 2006, p. 262). The models examined in this chapter include conceptual
models that form the basis for subsequent research that examine the influences on
environmental consumer behaviour, as well as cognitive models which emphasise
beliefs rather than emotions as the key determinants of attitudes and behaviours.
Research into ethical behaviour has extended the consumer behaviour literature and has
demonstrated that ethical consumption behaviour was not necessarily determined by
either individual characteristics or by normative obligations, but rather was a result of
the interplay between individual choice (agency) and societal power (structure). This
means that ethical consumption behaviour can be viewed in two ways: as a rational and
voluntary choice reflecting individual characteristics, taste and preferences, or as an
enforced choice imposed by a complex system of social, cultural and material
(re)production (Cherrier 2005). For these reasons, it is a complex task to understand
what makes a consumer behave ethically and what initiates an ethical decision, no
matter what the context.
One approach to theoretical modelling examines behaviour as a function of processes
and characteristics which are external to the individual, such as incentives, institutional
constraints and social norms. The external approach exemplifies that a change in
external conditions can have a vital influence on individual behaviours, meaning that
consumers are “locked in” to consumption choices by external conditions including
economic necessity and social expectations (Jackson 2005).
3.2 Background
64
In order to develop campaigns and policies to elicit behavioural change, a clear
understanding of which individuals or consumers are willing to participate in
environmental protection activities is also needed (Granzin & Olsen 1991). This is
important given the diverse range of attitudes and behaviours related to the environment
and sustainability issues. As behaviour can be a function of processes and
characteristics which are internal to the individual, demographics, attitudes and values
are also considered. Relating this to sustainable behaviours, the basis of the internal
approach is that changes in sustainable consumption and behaviour are related to
changes in individual’s beliefs and attitudes. This means that consumers are more likely
to choose sustainable behaviours if they hold the appropriate beliefs or attitudes and/or
if they are of the relevant demographic or values segment.
Before examining models of ethical decision making, Howard and Sheth’s (1969)
Theory of Buyer Behaviour is introduced. This widely recognised and complex model
laid the foundation for much of the research discussed in this chapter.
Modelling consumer behaviour to predict behavioural change has been a primary
concern of researchers for many years and has resulted in the class of models called
behavioural intention (BI) models. While most originated from the health literature,
they have been adapted to the marketing domain to help marketers and policy makers
understand the directions needed when setting communications objectives and for
generating strategies to achieve these objectives.
Importantly, BI models have been based on the understanding that past behaviour was
not always a good predictor of future behaviour (see, for example, Bamberg, Ajzen &
Schmidt (2003, p. 186)). This was not always the case, as it was only when conditions
are relatively stable that past behaviour can be a significant predictor of future
behaviour. New information can change behaviour and beliefs, as well as affecting
3.3 Behavioural intention models
65
intentions and perceptions of behavioural control, and this can in turn influence future
behaviour (Bamberg, Ajzen & Schmidt 2003).
Howard and Sheth’s (1969) Conceptual Model of Buyer Behaviour, being one of the
first such models, has been the basis of subsequent models that have been used to
inform marketing strategies related to the relationships that exist between external
stimuli and brands in consumer choice. This model illustrates the diverse range of
inputs (including perceptual and learning constructs) that lead to purchasing behaviours
(outputs). These include many internal and external variables that influence buyer
behaviour, such as quality, price, distinctiveness, service, availability, family, reference
groups, social class, intention, attitude, purchase, brand, comprehension, brand
attention, attention, confidence, perceptual satisfaction, bias, motives, choice criteria,
stimulus ambiguity and overt search. The model is shown in appendix 1.
The complexities of this and other early models of consumer behaviour have been
criticised because they included “virtually every known social-psychological construct
and process” (Ajzen and Fishbein 1980, p. 15). While describing the extent to which
social and cultural factors shape, influence or constrain motives and behaviour in the
“social medium” (Jackson 2005, p. 80), their complexity and the lack of definition of
the variables means that they are hard to test empirically. Nevertheless, the importance
of Howard and Sheth’s model lies in the fact that it illustrates the diverse range of
influences that are considered to be important constructs in understanding consumer
behaviour.
Models that describe the ethical decision-making process and other models of consumer
behaviour are discussed in following sections. One common link in the early research
into ethical decision making was that much of it originated from the work of Hunt and
Vitell (1986) and Rest (1986, in Jones (1991)).
66
One of the first theoretical models developed to explain marketing ethics was the
Theory of Ethics developed by Hunt and Vitell (1986). This was subsequently revised
by Hunt and Vasquez-Parraga (1993) and more recently by Hunt (2006). It assumes that
the activity or situation was perceived as an ethical issue and models the alternatives or
actions that the individual might take to resolve this. It builds on deontological and
teleological moral philosophies to explain why people have “different views on the
ethicality of marketing activities, as well as to explain ethical and/or unethical
behaviour” (Hunt & Vasquez-Parraga 1993, p. 79).
Deontology refers to the intrinsic “rightness” or “wrongness” of the issue and the
behaviour that occurs, irrespective of the consequences. This was based on the
perception of the individual’s duties, obligations and responsibilities with respect to the
action or issue, and the outcome that they will behave honestly or fairly (or not) (Hunt
& Vasquez-Parraga 1993). Teleology refers to the philosophy that an act was right only
if it produces a greater outcome of “good” rather than “bad”. This requires forecasting
an individual’s behavioural consequences based on the event happening, and
determining the desirability (or not) of the actions or behaviours based on the
importance of the stakeholders involved (Hunt & Vasquez-Parraga 1993).
The model illustrates that deontological evaluation affects ethical judgements directly,
but not intentions directly, whereas teleological evaluation affects both ethical
judgements and intentions directly. The Hunt Vitell Theory of Ethics is included in
appendix 2.
At about the same time as the Hunt and Vitell model was published, Rest (1986, in
Jones (1991)) proposed a four-part model for individual ethical decision making and
3.4 Early models of the ethical decision-making process
3.4.1 Rest’s and Trevino’s models of ethical decision making
67
behaviour which examines the development of individual moral thought processes and
behaviour by individuals in organisations. In this model, ethical behaviour and ethical
decision making are used to link an individual’s interest in an action with their concern
for the environment. This was based on the definition that an ethical decision was “a
decision that was both legally and morally acceptable to the larger community” (Jones
1991, p. 367). According to Jones (1991), a moral issue when freely performed may
harm or benefit others and must involve choice.
Rest (1986, in Jones (1991)) depicted the consumer ethical decision-making process and
suggested that an individual goes through four steps when making a decision: recognise
the moral issue, or the “awareness” step; make a moral judgement; establish moral
intent or intention; and implement moral actions during the ethical decision making and
behaviour process, or the “behaviour” step. In other words, once an individual has
recognised a moral issue, they make a moral judgement which is a “prescriptive
assessment of what is right or wrong” (Trevino 1986, p. 604). They then establish moral
intent (or intention to behave) and the final step is to implement moral actions or
behaviours during the ethical decision-making process. It is interesting to note that
while there has been much research into the ethical and moral judgement stage, less
research has been undertaken on the other three stages (Chan & Leung 2006).
Ferrell and Gresham (1985) argued that moral intention subsequently leads to actual
moral behaviour because intentions are shown to be good predictors of individuals’
behaviours in the Theory of Reasoned Action (TRA) which is discussed in a following
section. Studies into moral and ethical decision making in the environmental context
have demonstrated that intentions significantly predict behaviours, for example, in a
household composting recycling study (Trafimow & Borrie 1999).
Trevino’s (1986) Person-Situation Interactionist Model provides an alternative to Rest’s
model. Trevino (1986) identified individual and situational factors that influence the
ethical decision-making process and pioneered research into their mutual interaction. It
is these individual and situational factors that interact with the cognitive component of
the decision process that determines “how an individual is likely to behave in response
to an ethical dilemma” (Trevino 1986, p. 602). Beginning with the existence of an
68
ethical dilemma, this model also includes a cognitions stage whereby a moral judgement
is made that leads to the final behaviour stage.
Such ethical models have led to the development of “various socio psychological
theories (that) postulate how beliefs, attitudes, intentions, and actions are related”
(Routhe, Jones & Feldman 2005, p. 879). It has been recognised that the development
of models that measure ethics in the marketing context was inevitable due to the fact
that “marketing, in general, and the buyer/seller dyad, in particular, is a place where
many ethical problems in business arise” (Vitell & Ho 1997, p. 699).
The influence of individual and situational characteristics on ethical decision making
was originally justified because “behaviour in practical situations is not simply a
product of fixed individual characteristics, but results from an interaction between the
individual and the situation” (Trevino 1986, p. 610). Referring to Trevino’s (1986)
Person-Situation Interactionist Model, Jones (1991) commented that “the details of
moral decision-making and behaviour processes become irrelevant if the person does
not recognise that he or she is dealing with a moral issue” (Jones 1991, p. 391).
Consequently, Jones (1991) proposed an Issue Contingent Model of ethical decision
making in organisations based on the work of Rest (1986, in Jones (1991)), Trevino
(1986), Dubinsky and Loken (1989), Ferrell and Gresham (1985) and Hunt and Vitell
(1986). This is shown in appendix 3. Jones notes that “the relative importance of
personal and situational factors might vary considerably, from issue to issue” (1991, p.
391). In other words, it is the varying intensity of moral issues that determines moral
recognition, judgement and action within the ethical decision-making process and the
extent to which these later stages are consistent. This model is shown in appendix 3.
Fritzsche and Becker (1983) and Chia and Mee (2000) also argue that ethical behaviour
is dependent on the nature of the problem or issue being encountered. This means that
3.4.2 The nature of the issue and situational characteristics
69
the characteristics of the issue largely determine ethical decision making and behaviour.
Fritzsche and Becker (1983) argue that when moral dilemmas are faced, ethical
behaviour is more likely to be prompted by serious consequences than by modest
consequences.
Among the category of behavioural intention models, there exist models that deal with
the conceptualisation of the influences on behaviour. These are often referred to as
knowledge-attitude-behaviour models or attitude-behaviour models as they link beliefs,
attitudes and intentions and the resulting actions or behaviour in different ways. They
include the Protection Motivation Theory (PMT), the Theory of Reasoned Action
(TRA) and the Theory of Planned Behaviour (TPB). These models have all been
applied to many marketing and ethical contexts and have consistently demonstrated
strong correlational relationships between attitudes and behaviour and/or behavioural
intentions (Sparks, Shepherd & Frewer 1995). These models are examined in the
following sections.
Rogers’ (1975) Protection Motivation Theory (PMT) is a conceptual model that was
first published in the Journal of Psychology. It describes how consumers assess threats
before adopting behaviours or taking some kind of action. One of the underlying
assumptions of the PMT is that an event was “noxious” and likely to occur (Rogers
1975). As the model looks at “protection” behaviour, it also specifies certain cognitive
and informational factors that derive from a message or communication which
determine a response to an event. Hence, this model then describes that people can deal
with such a noxious event by using the information or knowledge that they have gained
to prevent the occurrence of that event.
In 1983, Rogers updated the PMT by adding in a fourth component, self-efficacy. Beck
(1984, p. 121) defined this as “the individual’s belief or expectation that he/she can
successfully perform or master a given response”.
3.5 Protection Motivation Theory (PMT)
70
The Theory of Reasoned Action (TRA) was developed by Fishbein and Ajzen (1975).
It is an extension of the PMT and represents a general theory of social behaviour. The
TRA illustrates that behavioural beliefs, normative beliefs, control beliefs, attitudes,
subjective norm and perceived behavioural control all influence behavioural intention,
which then affects actual behaviour.
The TRA has been widely used in psychology and the social sciences, including
marketing and business. It has been used to explain a disparate range of behaviours in
contexts such as family planning, smoking marijuana, condom use, exercise, dental
hygiene and sugar consumption. The TRA has also been used to predict environmental
behaviour, including household activities such as conserving water, recycling,
composting, energy and consumer purchases (Routhe, Jones & Feldman 2005). The
TRA is shown in Figure 3.2.
Figure 3.2 Theory of Reasoned Action (TRA)
Source: Adapted from Ajzen and Fishbein (1980)
3.6 Theory of Reasoned Action (TRA)
Behavioural
beliefs
Attitude
towards the
behaviour Behavioural
intention
Subjective
norm
Normative
beliefs
Actual
behaviour
71
Routhe et al. (2005) applied the TRA to examine planned behaviour with respect to the
environmental issue of building a new dam in the USA. In doing so, they developed a
conceptual framework that described public opposition (or support) for a collective
action that impacts on environmental quality, in this case, building a dam to meet local
water supply needs. Consistent with the TRA, this framework describes the antecedents
to actual behaviour as being behavioural intention, attitudes, subjective norm,
behavioural beliefs and normative beliefs.
When examining the TRA, Dubinsky and Loken (1989) focused on the behavioural
outcomes, attitudes and performance of sales personnel. This target market was chosen
because it was believed that sales personnel received much criticism about their ethical
behaviour. They proposed that “evaluating the outcomes of a particular behaviour
directly affects one’s attitude toward the behaviour but only indirectly influences actual
performance” (p. 83). Their findings suggest that seven variables influence ethical
decision making: behavioural intentions, attitude towards the behaviour, subjective
norms, behavioural beliefs, outcome evaluations, normative beliefs and motivations to
comply.
There have been other examples of studies on community sustainability supporting the
TRA, including one by Voronoff (2005). This exploratory study was designed to gain a
better understanding of the “practicalities, difficulties and achievements” experienced
by key stakeholders in selected community sustainability programs in Victoria,
Australia (Voronoff 2005, p. 4). It concludes that the TRA was a good model for
understanding this behaviour, though being exploratory in nature the findings need to be
treated as such. The recommendations included practical suggestions such as the need
for community based social marketing campaigns to adopt a holistic approach towards
sustainable programs. This study was important as it included operational definitions for
some constructs and variables used in this study. The Theory of Planned Behaviour
(TPB) is an extension of the TRA and it is examined in the next section.
72
The Theory of Planned Behaviour (TPB) (Ajzen 1985) was developed in response to
criticisms that the TRA was not applicable to non-volitional or less-volitional
behaviours. Non-volitional behaviours are those that consumers have no choice about
or that they are not necessarily willing to do.
Thus, the TPB was an extended version of the TRA which also included a measure of
the extent to which one’s intentions to perform such non-volitional behaviours can be
carried out. This additional construct was called perceived behavioural control (PBC)
and was added as a third independent predictor of behavioural intention. The PBC
construct measures the amount of control one has over the behaviour. The underlying
determinants of PBC were termed “control beliefs”, which refer to a person’s subjective
assessment of whether they possess the necessary skills, resources and opportunity to
successfully perform a given action (Routhe, Jones & Feldman 2005).
In other words, the TPB describes behavioural intention as determined by a person’s
overall evaluation of a behaviour (or their attitude towards it), the perceived social
pressure surrounding the behaviour (subjective norm) and perceived control over factors
that may facilitate or inhibit performance (perceived behavioural control). The TPB is
shown in Figure 3.3.
3.7 Theory of Planned Behaviour (TPB)
73
Figure 3.3 Theory of Planned Behaviour (TPB)
Source: Adapted from Chang (1998), Chedzoy and Burden (2007, p. 57) and Hughes, Ham and Brown (2009b, p. 40).
The TRA and TPB have been applied by many authors in many contexts, and through
such applications there have been many adaptations of the models. For example, the
original TRA and TPB only tested the relationships hypothesised by the theory between
attitudes, PBC and subjective norm with behavioural intention. They did not consider
interrelationships between attitudes and PBC and subjective norm, which have been
shown to not be necessarily independent (Chang 1998; Vallerand et al. 1992).
Of relevance to this research are the studies that use these models to better understand
consumer and organisational decision making in the environmental and sustainable
context. Some of the relevant applications of the TRA and the TPB are discussed in the
next section.
Perceived
behavioural control
Control beliefs
Subjective norm Normative
beliefs
Attitude towards
the behaviour
Behavioural
beliefs
Behavioural
intention
Actual
behaviour
74
Some of the many examples of applications of the TPB includes studies by Wall et al.
(2007) and Fielding et al. (2008) who applied it to environmentally sensitive
behaviours. Wall et al. (2007) examined students’ travel modes in the UK and
concluded that personal normative motives and perceived behavioural control are the
only statistically significant predictors of travel intentions in the TPB. This was a
similar finding to Fielding et al.’s (2008) study of farmers. They demonstrate that strong
intentions to engage in sustainable practices are determined by normative support and
the perception (PBC) that that they can easily do so. This was particularly true of
respondents who hold positive attitudes towards environmental activism. In doing so,
these two studies demonstrate the utility of the TPB in understanding environmental
behaviours by concluding that it was an effective model for identifying the predictors of
these types of behaviours (Fielding, McDonald & Louis 2008).
When comparing their findings to the TPB, Routhe et al. (2005) demonstrated that
Perceived Behavioural Control (PBC) was not an antecedent to the behaviour of
building a new dam. They contended that a person’s attitudes towards building a dam to
meet local water supply needs should be predictive of their willingness to support its
construction, rather than their attitudes towards the environment, and their belief that the
benefits would outweigh the costs. They found little interest in the “collective action” of
building a dam as most of the sample demonstrated that they would not support this
project. This highlights the need for policy makers to educate the population about the
importance of new concepts and ideas, rather than just assuming that, even though there
was a need for this project because of low water storages, there would be public support
for it.
Another application of the TPB was described by Sparks and Shepherd (1992) who
studied buying organic vegetables and by Kalafatis, Pollard, East, and Tsogas (1999)
who examined the determinants that influence consumers’ intention to buy
environmentally friendly “green” products in the UK and Greece. Both studies concur
3.7.1 Applications of the TRA and TPB
75
with the original TPB that demonstrated that attitudes, subjective norm and perceived
behavioural control are significant determinants of behavioural intentions. In the study
by Kalafatis et al. (1999), the behavioural patterns for the more established market in
the UK are more consistent with the original TPB model than in Greece.
When examining moral and ethical behaviour in organisations, two studies by
Maheshwari and Ganesh (2006) and Solymossy and Masters (2002) are important with
respect to sustainability. Maheshwari and Ganesh (2006) examine ethical decision
making among a sample of regulators, social groups and managers. They attribute the
increasing awareness of ethical decision making to the strong social condemnation of
the business practices of organisations such as the Gap clothing company and Nike. In
doing so, they developed a framework of ethical decision making and behaviour that
applied to individuals in organisations, to understand the implementation of a code of
ethical conduct at Tata Steel.
This framework illustrated that ethical decision making and the behaviour of individuals
in an organisation were influenced by moral intensity (to be discussed later in this
chapter) as well as intrinsic and extrinsic variables. The intrinsic variables include moral
awareness, individual values, demographic variables and personality traits. The extrinsic
variables include the organisational ethical climate and the level of accountability.
Together these variables affect the overall organisational behaviours and outcomes.
Solymossy and Masters (2002) conducted an exploratory study and proposed a model of
ethical decision making for small business entrepreneurs which demonstrates the
complexity of ethical decisions in their businesses. They concluded that a moral
behaviour was less likely to occur without the moral judgement occurring, and moral
judgement was more likely to occur when the moral dimension of an issue was
recognised. Zabel’s (2005) conceptual study used a modified version of the TPB to
produce “A model of human behaviour for sustainability”. This complex conceptual
model largely originated from psychology and examined the natural, cultural and
situational factors that affect human behaviour with regards to sustainability.
76
Important for this research is the work reported by Deirdre Shaw and colleagues, and
this is discussed in the next section.
Deirdre Shaw and colleagues conducted a study of “ethical” consumers in the UK by
including a questionnaire in the December/January 1997-98 issue of Ethical Consumer
magazine on consumers’ purchasing of fair trade grocery products, defined as low
involvement products and totally under volitional control. This research sought to
understand more about the decision-making processes of ethical consumers for purchase
intention. Their sample of subscribers to Ethical Consumer was deemed to be an
“extreme” group of ethical consumers that were sampled because it was stated that past
research had “tended to neglect the ethical consumer” (Shaw & Shiu 2003, p. 1485).
The findings from this one study were published in seven journal articles between 2000
and 2006.
Shaw and Shiu (2003) subsequently developed a modified version of the TPB which
demonstrates the multidimensional nature of many of the constructs such as the
subjective norm. They conclude that internal ethics was a latent construct that comprises
ethical obligation and self-identity (Shaw & Shiu 2003). Internal ethics and subjective
norm then form the latent “internal reflection” construct which was a determinant of
behavioural intention. This concurs with Cherrier’s (2005) finding that social norms
must be internalised in order to impact ethical behaviour.
The resultant model was simply called “Model 2”. This adopts a “layered” model
structure which “allows constructs and factors to be placed within empirically and
conceptually defensible groupings, which are arguably better able to reflect underlying
connotative processing” (Shaw & Shiu 2003, p. 1494).
Despite general support in the literature for the TRA and the TPB up to this time, this
study rejects these models because of their poor ability to explain behavioural intention
3.7.2 Shaw’s models of behavioural intention
77
and the assumption that the model measures are uni-dimensional. According to Shaw
and Shiu (2003), this reflects the complex nature of cognitive processing. This model
accounts for 52% of the variance in behavioural intention and is shown in Figure 3.4.
Figure 3.4 Shaw’s “Model 2”
Source: Shaw and Shiu (2003, p. 1494)
Interestingly, a closer examination of Model 2 highlights some confusing conclusions.
For example, the correlation between “pbc_traditional” and external control was 0.99
which could suggest that multicollinearity exists in the model. All correlations whether
significant or not have been shown, which was unusual in the presentation of such a
model. None of the articles viewed by the author could validate the findings of the
Structural Equation Modelling (SEM).
78
Based on the previously mentioned studies, the next sections discuss the relevant latent
constructs that are included in the theoretical framework for this research study:
behavioural intention and actual behaviours, behavioural beliefs, attitudes, control
beliefs, PBC, normative beliefs and subjective norm, personal normative motives,
internal ethics and moral intensity. The discussion begins with behavioural intention
and actual behaviours.
Behavioural intention in the ethical context refers to the stage when a person intends to
behave in an ethical or unethical manner and is the cognitive representation of their
readiness to perform a given behaviour (Routhe, Jones & Feldman 2005). Models such
as the TRA and the TPB demonstrated that behavioural intention was influenced by
attitudes and behavioural beliefs regarding positive outcomes and social approval. They
also verified that attitudes were antecedents to actual behaviour. Actual behaviour
represents the stage in which a person engages in or adopts an ethical or unethical action
(McMahon & Harvey 2006; Routhe, Jones & Feldman 2005).
There are many studies that have measured behavioural intention in different contexts.
For example, Trafimow and Borrie (1999) examined the likelihood of stealing fossilised
wood from Petrified Forest National Park, Routhe et al. (2005) examined the likelihood
of supporting the construction of a new dam and Hagger and Chatzisarantis (2006)
studied the likelihood of buying a magazine. In these studies, both behavioural intention
and likely to perform actual behaviours were measured using a Likert scale and one or
more statements. Where there was more than one statement, the construct was derived
by computing a score based on their answers to all statements.
3.8 Latent constructs
3.9 Behavioural intention and actual behaviours
79
The study conducted by Shaw et al. (2003) was an example of a study that used one
scale to measure behavioural intention. When measuring the likelihood to purchase fair
trade products, they used a 7-point Likert scale from likely to unlikely to ask
respondents to rate the following statement “The next time you go grocery shopping
how likely are you to purchase a fair trade product?” Kraft et al. (2005) used a 7-point
agree to disagree Likert scale to measure behavioural intention for two behaviours,
regular exercise and recycling drinking cartons. Laroche et al. (2001) measured
likelihood of paying a higher price for green products and environmentally friendly
groceries using a 9-point Likert scale from very likely to not at all likely. They also
measured consumers’ willingness to pay a higher price for green products and
environmentally friendly groceries.
Table 3.1 summarises the ways that behavioural intention has been measured in the
sustainable context.
Table 3.1 Relevant studies that measure behavioural intention Statement(s) Scale used Author(s) The next time you go grocery shopping, how likely are you to purchase a fair trade product?
7-point likely unlikely scale, scored from +3 likely to -3 unlikely.
Shaw et al. (2000), (2003)
Likelihood of paying a higher price for green products and environmentally friendly products
9-point Likert scale from very likely to not at all likely
Laroche et al. (2001)
For each behaviour, four items assessed intention: “I expect to perform behaviour over the next two weeks”; “How likely is it that you will perform behaviour over the next two weeks”; “I intend to perform behaviour over the next two weeks”; “I plan to perform behaviour over the next two weeks.”
All items are responded to on 7-point scales ranging from very unlikely to very likely
Kraft et al. (2005, p. 484)
Behavioural intentions are measured by two items: “I plan to buy a magazine in the next two weeks” and “I intend to buy a magazine in the next two weeks.”
6-point Likert-type scales anchored by 1 (unlikely) and 6 (likely).
Hagger and Chatzisar-antis (2006, p. 736)
Support – vote for a public official who supports building a dam than any other activity; plan to talk to neighbours, relatives and friends; contact a public official about their support Opposition – willing to attend a meeting to express opposition; willing to donate time and money to express opposition
7-point Likert scale, 3= very likely to -3 = very unlikely, unsure as midpoint, with five measures/scales measuring support and opposition. Scales are summed to form behavioural intention scale
Routhe et al. (2005, p. 887)
I intend to walk on a treadmill for at least 30 minutes each day in the forthcoming month; I will try to walk on a treadmill for at least 30 minutes each day in the forthcoming month; I plan to walk on a treadmill for at least 30 minutes each day in
7-point Likert scale from extremely unlikely to extremely likely; 7-point Likert scale from definitely true to definitely false; 7-point Likert scale from strongly disagree to strongly
Ajzen (2002, p. 4)
80
the forthcoming month agree My purchasing a fair trade product will (a) result in a fair price for fair trade producers (b) support fair trade producers (c) result in the non-exploitation of fair trade producers (d) result in my peace of mind (e) encourage retailers to stock fair trade products (f) withdraw support from non-ethical companies (g) entail purchasing a product which is not readily available (h) entail purchasing a product which is more expensive (i) entail purchasing a quality product
7-point likely unlikely scale, scored from +3 on the positive side to -3 on the negative side
Shaw et al. (2000) Shaw and Shiu (2003)
“I feel under social pressure to perform .. behaviour over the next two weeks”; “Most people who are important to me would wish that I performed .. behaviour”; “Most people who are important to me think that I should perform .. behaviour”; and “Most people who are important to me would like that I performed .. behaviour.
Four questions (for each behaviour), measured by 7-point scales – disagree completely/agree completely, very unlikely/ very likely, should absolutely not/ should absolutely, very much dislike/ very much like. Behaviour measured over the “next two weeks’.
Kraft et al. (2005, p. 484)
“I am happy to pay xx because it is only a small part of my food expenditure”, and objections to pay: “I don’t think people should have to pay more to support the legislation”
Used a scale of 0 to 10 where 10 indicated that this was “very much like my way of thinking”
Bennett et al. (2002)
How likely do you think (you) would be to take the sample?
7-point scale from extremely unlikely (-3) to extremely likely (+3). Four semantic differential scales are used to measure attitudes towards the taking a sample. 7-point scales are used with the following anchors: Good- bad, Harmful- beneficial, Rewarding- punishing, Pleasant- unpleasant
Trafimow and Borrie (1999, p. 36)
Chapter 2 described examples of actual behaviours that can be measured in order to
understand behavioural intention, and behaviours that have already been done which are
also called “past behaviours”. Authors such as Kraft et al. (2005) and Sparks and
Shepherd (1992) measured behavioural intention and actual behaviours using
dichotomous (yes/no) questions in their studies on recycling and exercise and on the
purchasing of organic vegetables, respectively. In other words, they used examples of
actual behaviours in their studies, rather than statements and Likert scales. This is based
on the premise that actual behaviours can be an antecedent to future behavioural
intention (Ouellette & Wood 1998; Trafimow & Borrie 1999). In addition, this can
3.10 Actual behaviours
81
depend on the type of behaviour being measured, the context or the population being
examined (Trafimow & Borrie 1999).
Ouellette and Wood (1998) noted that past behaviour was indirectly related to
behavioural intention through its effects on predictors such as attitudes and norms, and
that both past behaviour and behavioural intention can be predictors of future behaviour.
Their study measured this by asking about behaviours performed annually or
biannually, as well as those performed daily or weekly. Figure 3.5 summarises their
findings.
Figure 3.5 Past behaviour, behavioural intention and future behaviours
Source: Ouellette and Wood (1998, p. 64)
Note that the numbers appended to the single-headed arrows are standardised regression
coefficients (beta values) and the numbers appended to the double-headed arrows are
bivariate correlation coefficients (r) ***p< .001.
Five ways that examples of actual behaviours and future behavioural intention have
been measured in the literature are summarised in Table 3.2.
Behaviours performed daily or
weekly
Behaviours performed annually
or biannually
82
Table 3.2 Relevant studies that measure actual behaviour Statement(s) Scale used Author(s) Organically grown vegetables are defined as vegetables “that are grown without the use of artificial fertiliser and pesticides”. The mean consumption frequency of the organically produced vegetables served as the index of consumption (“past behaviour”).
Subjects are requested to indicate the number of times per month, on average, that they consumed each of 14 common vegetables, and how many of these occasions involved the consumption of “organically-grown” vegetables
Sparks & Shepherd (1992, p. 393)
Have you performed (behaviour) during the past two weeks?
For both recycling and exercise, behaviour was measured by means of a dichotomous variable (yes/no)
Kraft et al. (2005, p. 485)
How often have you performed (the target behaviour) in the past (time frame)?
The scale anchors typically specified frequency of performance; for example, for the time frame of two weeks, anchors ranged from never to every day.
Ouellette & Wood (1998)
Using 7-point Likert-type scales with scale points almost every day, most days, on about half the days, a few times, but less than half the days, a few times, once or twice and never.
After two weeks, participants self-reported their behaviour for each of the 30 behaviours on a single item (e.g. “In the past two weeks, how often have you bought a magazine?”)
Hagger & Chatzisarantis (2006, p. 736)
Recycling – using the blue or green box (bag) for recycling; When buying something wrapped, check that it is wrapped in paper or cardboard made of recycled material; Refusing to buy products from companies accused of being polluters; Buying plastic knives, forks or spoons; Buying styrofoam cups
9-point Likert scale from never to always considering environmental issues when making a purchase (two statements) and buying environmentally harming products (two statements)
Laroche et al. (2001)
Attitudes reflect “an individual’s personal beliefs, positive or negative, about enacting a
target behaviour” (Hagger & Chatzisarantis 2006, p. 731). They are defined as “an
enduring disposition to consistently respond in a given manner to various aspects of the
world; composed of affective, cognitive and behavioural components” (Zikmund et al.
2011, p. 247).
The attitude construct is complex as it requires the use of many statements to capture its
essence, and there are many ways that attitudes have been measured and in different
contexts. For example, Shaw and colleagues measure attitudes towards buying fair trade
products, and Kraft et al. (2005) examine undertaking regular exercise and recycling
drinking cartons. While the many examples of attitudinal statements can be
3.11 Attitudes
83
distinguished at the conceptual and empirical level, they are generally combined
together to form the one attitude construct (Hagger & Chatzisarantis 2006).
According to Laroche et al. (2001) the most frequently studied attitudes in ecological
literature with respect to environmentally friendly behaviour are “importance and
inconvenience” (p. 506). They also argued that, as green consumers believe that
environmental conditions are deteriorating and represent serious problems facing the
world, that an individual’s perception about the “severity of ecological problems might
influence his/her willingness to pay more for ecologically compatible products” (p.
507). Hence, they included these three constructs in their study, which were measured
by the “importance” of recycling, the “inconvenience” of being environmentally
friendly and the “severity” of environmental problems. The importance of recycling was
measured by three statements, the inconvenience of being environmentally friendly by
two, and the severity of environmental problems by five. They concluded that the three
composite attitudinal constructs had a reliable influence on attitudes, and in turn, that
the attitude construct was a significant determinant of behavioural intention.
In measuring the severity of environmental problems, the statements range from
wasting water and electricity to issues associated with pollution, all of which are
expressed as negative statements. In measuring the relative “importance” of recycling,
importance was described as “whether consumers view environmentally compatible
behaviours as important to themselves or society as a whole” (Laroche, Bergeron &
Barbaro-Forleo 2001, p. 506). Laroche et al.’s (2001) third attitudinal construct
describes the “inconvenience” of being environmentally friendly. In sum, the statements
describe that, despite knowing that the products they use will harm the environment,
consumers do so purely for convenience. Further, the more that the consumer perceives
the task or behaviour as inconvenient, the less likely they are to perform it. Hence, the
“severity”, “inconvenience” and the “importance” of the task are important constructs to
measure when considering attitudes related to the environment (Laroche, Bergeron &
Barbaro-Forleo 2001, p. 507).
The constructs that measure attitudinal constructs including “severity”, “importance”
and “inconvenience” along with other attitude measures are summarised in Table 3.3.
84
Table 3.3 Relevant studies that measure attitudes Statement(s) Scale used Author(s) In our country, we have so much electricity that we do not have to worry about conservation Since we live in such a large country, any pollution that we create is easily spread out and therefore of no concern to me With so much water in this country, I don’t see why people are worried about leaking faucets and flushing toilets; Our country has so many trees that there is no need to recycle paper; The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state; Recycling will reduce pollution; Recycling is important to save natural resources; Recycling will save land that would be used as dumpsites; Keeping separate piles of trash for recycling is too much trouble; Trying to control pollution is much more trouble than it is worth
9-point Likert scale from strongly agree to strongly disagree Severity of environmental problems (five statements) Importance of recycling (three statements) Inconvenience of being environmentally friendly (four statements)
Laroche et al. (2001, p. 509)
6-point semantic differential scales, which tapped the affective (pleasant–unpleasant) and instrumental (useful–useless) aspects of attitudes.
Attitudes are measured using two items with a common stem: “Buying a magazine in the next two weeks would be…”
Hagger & Chatzisar-antis (2006, p. 736)
“In general, my attitude towards purchasing a fair trade product is…” (Favourable to unfavourable).
7-point likely unlikely scale, scored from +3 to -3
Shaw at al. (2000), Shaw and Shiu (2003)
To measure overall evaluation of attitudes towards building a dam. The scales are summed to form the construct and based on the following: important/unimportant, positive/ negative, good/ bad, wise/ foolish, beneficial/ harmful
7-point Likert scale, 3 = good/beneficial and -3 = bad/harmful and 0 = unsure with five measures/ scales
Routhe et al. (2005, p. 888)
“My performing behaviour during the next two weeks would be…” related to undertaking regular exercise and recycling drinking cartons.
Eight items measured with 7-point bipolar adjective scales: unwise–wise, harmful–beneficial, useful–useless, wrong–right, good–bad, relaxing–stressful, pleasant–unpleasant and boring–interesting
Kraft et al. (2005, p. 484)
First, the subjects are asked to respond to the statement Eating organic vegetables is… Second, they are asked to respond to the statement: In general, my attitude towards eating organic vegetables is… on a scale with endpoints marked extremely unfavourable and extremely favourable. Third, they are asked to rate the statement: In general, my attitude towards eating organic vegetables is… on a scale with endpoints marked extremely negative and extremely positive.
Semantic differential (extremely foolish extremely wise / extremely bad-extremely good / extremely harmful-extremely beneficial / extremely unenjoyable-extremely enjoyable / extremely unpleasant-extremely pleasant
Sparks & Shepherd (1992, p. 392)
85
The TRA and the TPB postulate that people’s attitudes towards different behaviours are
determined by their behavioural beliefs. These in turn affect their thoughts (cognitive)
and feelings (affective) and thus influence behaviour (Kalafatis et al. 1999).
“Behavioural beliefs” link the behaviour of a person or an organisation to its perceived
attributes and these can influence a person’s attitudes or feelings about the outcome. In
other words, it was the combination of a person’s behavioural beliefs that a particular
behaviour will lead to certain outcomes and their evaluations of those outcomes that
leads to the development of attitudes (Sparks, Shepherd & Frewer 1995).
Routhe et al. (2005) describe the two components that comprise behavioural beliefs,
which are called outcome beliefs and outcome evaluations. Outcome beliefs refer to a
“person’s beliefs about the probability of specific consequences occurring as a result of
a given behaviour”, whereas outcome evaluations represent “a person’s subjective
evaluation of each outcome”. Pickett-Baker and Ozaki (1999) argue that the link
between behavioural beliefs and attitudes demonstrates the need for marketers to change
consumers’ attitudes in order to influence decision making and behaviour. Refuting this,
Shaw and Shiu (2002) argue that behavioural beliefs may not be a direct measure of
attitudes, rather that beliefs “aggregate to form a latent factor that is a different
perspective of attitudes from the direct measure” (Shaw & Shiu 2002, p. 115).
Behavioural beliefs are measured by Routhe et al. (2005) in their study of attitudes
towards building a new dam and by Shaw et al. (2003; 2000) in their study of
purchasing fair trade products, as summarised in Table 3.4.
3.12 Behavioural beliefs
86
Table 3.4 Relevant studies that measure behavioural beliefs Statement(s) Scale used Author(s) Building a new dam will… Degrade wildlife and fish habitats, degrade the environment for future generations, lower the cost of water, help the economy grow, help water utilities better serve their customers, provide new recreation and tourism opportunities and provide enough water to meet current and future needs in the county.
7-point Likert scale, 3 = likely and -3 = unlikely, 0 = unsure.
Routhe et al. (2005, p. 885)
My purchasing a fair trade product will (a) result in a fair price for fair trade producers (b) support fair trade producers (c) result in the non-exploitation of fair trade producers (d) result in my peace of mind (e) encourage retailers to stock fair trade products (f) withdraw support from non-ethical companies (g) entail purchasing a product which is not readily available (h) entail purchasing a product which is more expensive (i) entail purchasing a quality product
7-point likely unlikely scale, scored from +3 on the positive side to -3 on the negative side
Shaw et al. (2000, p. 893)
Actual behavioural intention can also be influenced by perceived behavioural control
(PBC) and control beliefs, which are discussed in the next section.
Perceived behavioural control (PBC) reflects the ease of performing an action (Routhe,
Jones & Feldman 2005, p. 886) and refers to how easy or difficult a person believes that
this was likely to be (Shaw, Shiu & Clarke 2000). Linking this to pro-environmental
actions, Jones (1991) discussed that PBC reveals public perceptions of institutional
barriers to action. This was based on the theory that consumers who lack the necessary
confidence or opportunities to perform a particular behaviour are unlikely to form
strong behavioural intentions despite the fact that their attitude and subjective norm may
be favourable (Kalafatis et al. 1999). PBC has been described as a construct that
comprised two interrelated components called “self-efficacy” or “perceived difficulty”
and “controllability” or “perceived control” (Kraft et al. 2005).
There are conflicting findings about the effect of PBC in the TPB. Chang (1998)
demonstrated that it was the most important construct in predicting unauthorised
software copying, while Routhe et al. (2005) found that the “perceived control” variable
(or PBC) was not a significant predictor of public support for building a new dam:
3.13 Perceived behavioural control and control beliefs
87
“theoretically speaking this is not an expression of environmental concern since it
reflects perceptions of the ease of performing an action” (p. 886). This demonstrated
that the effect of PBC can depend on the type of ethical behaviour being measured.
As with the other constructs, PBC has been measured in different studies and different
contexts, as summarised in Table 3.5.
Table 3.5 Relevant studies that measure PBC Statement(s) Scale used Author(s) The PBC scale was measured using two items: “How much control do you have over buying a magazine in the next two weeks” and “For me to buy a magazine in the next two weeks would be…”
Responses are given on 6-point Likert-type scales with end points 1 (very low control) and 6 (very high control) and 1 (very difficult) and 6 (very easy), respectively.
Hagger & Chatzis-arantis (2006, p. 736)
“For me to perform behaviour over the next two weeks would be difficult”; and “How easy or difficult would it be for you to perform behaviour over the next two weeks?” “If I wanted to, I would not have problems in succeeding to perform behaviour over the next two weeks”; “How confident are you that you could perform behaviour over the next two weeks”; and “If you actually tried, how likely is it that you would succeed to perform behaviour over the next two weeks” “I have full control over performing behaviour over the next two weeks” (disagree completely/agree completely); and “How much control do you feel over performing behaviour over the next two weeks” “It is completely up to me whether or not I perform behaviour over the next two weeks” and “It is first and foremost up to myself whether or not I perform behaviour over the next two weeks”
For each behaviour, PBC was assessed by nine indicators, all measured by 7-point Likert scales – disagree completely/ agree completely, very difficult/ very easy, completely unconfident/ completely confident, very unlikely/ very likely, no control at all/complete control. Two items made reference to how easy or difficult (PD) performance of the behaviour was perceived to be. Three questions measured how confident (CON) the respondent was that he/she would be able to successfully perform the behaviour: Two items are phrased to reflect perceived control (PC). Finally, two items measured the locus of control (LOC).
Kraft et al. (2005, p. 484)
For me the purchase of fair trade grocery products is…” (easy to difficult)
7-point easy difficult scale, scored from +3 on the positive side to -3 on the negative side.
Shaw et al. (2000) (2003)
PBC depends on specific beliefs, known as control beliefs, which can be measured as
the product of two measures: the power of a factor to assist the desired action and the
perceived access to the factor (Kalafatis et al. 1999). In other words, PBC measures how
easy or difficult it is to perform the behaviour.
88
The PBC construct has been used in contexts such as being an important predictor of
adults’ exercise intention and exercise behaviour (Conn, Tripp-Reimer & Maas 2003).
Some ways that control beliefs have been measured are shown in Table 3.6.
Table 3.6 Relevant studies that measure control beliefs Statement(s) Scale used Author(s) Perceived control was measured with three items: (i) How much control do you have over whether you do or do not eat organic vegetables?, (ii) For me to eat organic vegetables is…; (iii) If I wanted to, I could easily eat “organic” vegetables whenever I eat vegetables
7-point Likert scale with the response scale endpoints marked very little control and complete control; extremely difficult and extremely easy; and extremely unlikely and extremely likely.
Sparks and Shepherd (1992)
Please indicate below whether or not you consider that the following are problems which affect the amount of fair trade grocery products which you purchase: (a) availability (b) limited range (c) location of retail outlets (d) price (e) obtaining information regarding what products are fairly traded (f) availability in supermarkets
7-point likely unlikely scale, scored from +3 on the positive side to -3 on the negative side. From, never a problem to always a problem
Shaw et al. (2000) Shaw and Shiu (2003)
10 statements such as – Exercise is difficult because I am not committed to exercise, Exercise is good for my health, Exercise is difficult because I am too tired, Exercise is difficult because I don’t have time, Exercise is difficult because it is inconvenient
7-point Likert scale from strongly agree to strongly disagree
Conn et al. (2003)
As well as the attitude towards the behaviour and PBC, behavioural intention can be
determined by the subjective norm and its antecedent called normative beliefs.
Normative measures are included in this study because social marketing campaigns and
policies involve all levels of society. This is attributable to the fact that individuals
influence and are influenced by others in their daily lives including other consumers,
marketers and policy makers. Therefore, the needs and wants of other consumers,
marketers and policy makers at the macro and micro levels need to come into
congruence in order to meet their similar goals (Domegan, Davison & McCauley 2010).
One important normative construct was subjective norm. This has been described as “a
function of the individual’s normative beliefs about whether salient referents think he or
she should engage in the behaviour and motivations to comply with these referents
(Dubinsky & Loken 1989, p. 85). It refers to consumers’ perceptions of the level of
3.14 Subjective norm and normative beliefs
89
social pressure to perform a behaviour; it was not their own personal belief. In other
words, the subjective norm was a combination of people’s perceptions that other people
who are important to them think they should or should not perform the behaviour in
question and their motivation to comply with what others expect them to do (Hagger &
Chatzisarantis 2006). If the attitude and the subjective norm are favourable, and the
greater the perceived control of the situation, then there was a greater likelihood that the
person will intend to perform the behaviour (Hagger & Chatzisarantis 2006).
Subjective norm has been measured in various studies as summarised in Table 3.7.
Table 3.7 Relevant studies that measure subjective norm Statement(s) Scale used Author(s) Most people who are important to me think I should purchase fair trade grocery products (likely to unlikely).
7-point likely unlikely scale, scored from +3 on the positive side to -3 on the negative side.
Shaw et al. (2000) Shaw and Shiu (2003)
Most people who are important to me think I should support building a new dam in the county
7 category scale, never-always, which indicates general support/ opposition to build dam
Routhe et al. (2005, p. 885, 888)
“I feel under social pressure to perform behaviour over the next two weeks” (disagree completely/agree completely); “Most people who are important to me would wish that I performed behaviour (very unlikely/very likely); “Most people who are important to me think that I (should absolutely not/should absolutely) perform behaviour”; and “Most people who are important to me would (very much dislike/very much like) that I performed behaviour.
Four questions (for each behaviour), measured by 7-point scales, assessed subjective norm Behaviour measured over the “next two weeks”.
Kraft et al. (2005, p. 484)
Comprised two items: “Other people important to me would want me to buy a magazine in the next two weeks” and “Most people who are important to me would approve of me reading a magazine in the next two weeks.”
6-point Likert-type scales anchored by 1 (disagree) and 6 (agree).
Hagger & Chatzis-arantis (2006, p. 736)
Respondents are asked whether they felt that most people who are important to them thought that they should or should not perform the behaviour of interest
A 7-point scale was used with responses ranging from “definitely should” perform the behaviour (+ 3) to “definitely should not” perform the behaviour (-3).
Dubinsky & Loken (1989)
The antecedents of subjective norms are normative beliefs, which are personal beliefs
about “whether specific individuals or groups important to a person think the person
should or should not perform a given action” (Routhe, Jones & Feldman 2005, p. 879).
They measure whether particular referents (such as family and friends) think the
respondent should or should not do the action in question (Kalafatis et al. 1999).
90
Alternatively, intention to behave in a particular way can be influenced by a person’s
belief about what “important others” think that they should or should not do (Ajzen &
Fishbein 1980). Normative beliefs refer to specific social pressure to support an action
(Routhe, Jones & Feldman 2005).
Zabel (2005, p. 722) asserts that “sustainability is basically a normative concept”, and
normative beliefs have been measured in various studies as summarised in Table 3.8.
Table 3.8 Relevant studies that measure normative beliefs Statement(s) Scale used Author(s) Please indicate below how likely it is that the following groups think you should purchase fair trade grocery products: (a) friends (b) family (c) fair trade producers (d) church (e) ethical organisations (e.g. charities, environmental groups) (f) multinationals (g) retailers who stock fair trade products”
7-point likely unlikely scale, scored from +3 on the positive side to -3 on the negative side.
Shaw et al. (2000) Shaw and Shiu (2003)
For each behaviour respondents are asked whether they believed 13 “important referents” thought they should perform the behaviour of interest.
A 7-point scale was used, from “extremely likely” (+3) to “extremely unlikely” (- 3).
Dubinsky & Loken (1989)
People think that most of the following support/oppose building the new dam – family members, close personal friends, neighbours
7 category scale, never-always, which indicates general support /opposition to build dam
Routhe et al. (2005, p. 887)
Wall et al. (2007) explored UK drivers’ motivations for switching (or not switching)
travel modes. Their sample included university students and academics who reported
commuting by car at least four days per week and who intended to maintain or reduce
their car use for commuting in the year after the survey. They reported that the effects of
attitudes, PBC and subjective norm on behavioural intention are based on underlying
beliefs. For example, subjective norm depends on beliefs about the wishes of other
people and the individual’s motivation to comply with them. While PBC influences
behavioural intention, they argue that it can also directly affect behaviour, while at the
same time moderating the behavioural intention-behaviour relationship.
Wall et al. (2007) suggest the inclusion of personal-normative motives to the TPB to
explain the fact that behaviours that reduce personal utility, such as by decreasing
3.15 Personal normative motives
91
convenience, may be perceived as difficult and therefore not achievable. Personal norms
are activated by an awareness of the consequences of behaviours and beliefs about
personal responsibility for the consequence and thus refer to feelings of obligation and
responsibility. Table 3.9 summarises how Wall et al. (2007) measured PNM.
Table 3.9 Summary of the study that measures personal normative motives Statement(s) Scale used Author PNM for travel-mode choice: 1. I feel personal responsibility for helping to solve my town/city’s transport problems. 2. I don’t feel any personal responsibility for causing my town/city’s transport problems. 3. I feel morally obliged to avoid using the car to get to university.
5-point Likert scale, Disagree strongly, disagree, neither agree nor disagree, agree, agree strongly
Wall et al. (2007)
Sparks et al. (1995), Shaw and Shiu (2003) and Chedzoy and Burden (2007)
demonstrated the importance of including ethical obligation and self-identity in models
of behavioural intention, saying that consumers perceive that they have an ethical
obligation to perform these behaviours, and that ethical and sustainable behaviours are a
part of a consumer’s self-identity.
Ethical obligation represents an individual’s internalised ethical rules, which reflects
their beliefs about what is right or wrong (Shaw & Shiu 2002). Sparks et al. (1995)
investigated the role of perceived ethical obligation within the structure of the TPB to
understand attitudes towards the use of gene technology in food production. Consistent
with the TPB, Sparks et al. (1995) demonstrated the strong predictive link between
behavioural beliefs and outcome evaluations, attitudes and expectations with respect to
gene technology. They also found that while the perceived ethical obligation construct
produced only a marginally significant independent contribution to the prediction of
expectations, it did provide a significant contribution to the prediction of attitudes. This
finding was consistent with a later study which demonstrated that a feeling of moral
3.16 Internal ethics – ethical obligation and self-identity
3.16.1 Ethical obligation
92
obligation was a powerful motivator of environmental behaviour and that people with
high environmental motivation tend to be less sensitive to price (Tanner & Kast 2003).
A summary of some relevant studies that measure ethical obligation is shown in Table
3.10.
Table 3.10 Relevant studies that measure ethical obligation Statement(s) Scale used Author(s) I feel that I have an ethical obligation to avoid eating food produced by gene technology and I feel that I have an ethical obligation to support the use of gene technology in food production.
Subjects responded on a 7-point scale ranging from disagree very strongly (1) to agree very strongly (7).
Sparks et al. (1995, p. 274)
I feel that I have an ethical obligation to purchase fair trade grocery products
7-point agree disagree scale, scored from +3 on the positive side to -3 on the negative side.
Shaw et al. (2003)
Originating from the sociological and the psychological literature, a person’s self-
identity (or self-concept) has an important influence on behaviour (Sparks & Shepherd
1992). Self-identity is a construct which accounts for the fact that ethical issues are not
considered in isolation (Shaw & Shiu 2002).
Authors such as Sparks and Shepherd (1992), Shaw and Shiu (2002) and Hagger and
Chatzisarantis (2006) added the “self-identity” construct to the TPB. The rationale was
that “as an issue becomes central to an individual’s self-identity, then behavioural
intention is accordingly adjusted” (Shaw & Shiu 2003, p. 1488). Further, in the context
of ethical decision making, it was believed that ethical consumers may make ethical
consumption choices because ethical issues have become an important part of their self-
identity (Shaw, Shiu & Clarke 2000).
Sparks and Shepherd (1992), Shaw and Shiu (2003), Hagger and Chatzisarantis (2006)
and Chedzoy and Burden (2007) argue that self-identity influences intention to behave.
Sparks and Shepherd (1992) examined self-identity and found that this construct affects
both attitudes and intentions to eat organically produced vegetables in the following
3.16.2 128BSelf-identity
93
week, while Chedzoy and Burden (2007) found that a person’s self-identity influenced
their interest in dancing. Similarly, Shaw and Shiu (2003) demonstrated its influence in
the behaviour of “ethical consumers” with respect to fair trade products, and Hagger and
Chatzisarantis (2006) demonstrated its influence in the behavioural intention to buy a
magazine in the next two weeks.
A summary of some relevant studies that measure self-identity is shown in Table 3.11.
Table 3.11 Relevant studies that measure self-identity Statement(s) Scale used Author(s) Two items measured the construct: “buying a magazine in the next two weeks is an important part of who I am” and “I think of myself as the type of person who would buy a magazine in the next two weeks.”
Responses are given on 6-point Likert-type scales with end points 1 (strongly disagree) and 6 (strongly agree).
Hagger & Chatzisar-antis (2006, p. 736)
“How important, in general, are the following ethical considerations to you when you go grocery shopping?” (Important to unimportant). This question contained 13 items, e.g. “fair trade”, “human rights”, “animal welfare”.
I think of myself as someone who is concerned about ethical issues” (agree to disagree).
Shaw et al. (2005b; 2002; 2006; 2002; 2003; 2000)
To assess self-identity, trainees are presented with four sentences, for example, “I think of myself as a person who teaches dance”, “a person who generally recognises the educational benefits of dance.”
These items are scored on a 7-point Likert-like scale from 1 “disagree strongly” to 7 “agree strongly”.
Chedzoy & Burden (2007)
Two measures of identification with green consumerism were used. The first statement was I think of myself as a “green consumer”; the second was I think of myself as someone who is very concerned with “green issues”.
Response scales are marked disagree very strongly and agree very strongly.
Sparks & Shepherd (1992, p. 392)
Shaw and Shiu (2003) combined ethical obligation and self-identity and labelled the
combined effect of this construct “internal ethics”, based on the strong correlation that
exists between ethical obligation and self-identity (0.56) in their study. They conclude
that although these two constructs are distinct from each other, there was a degree of
commonality between them, given their importance with respect to the ethical focus of
their studies (Shaw & Shiu 2003).
Another important construct that needs to be considered is moral intensity, which is
discussed in the next section.
94
In 1991, Jones made a significant contribution to the ethical decision-making literature
by discussing how the characteristics of the moral issue could have an influence on
ethical decision making in organisations. He described moral intensity as “the extent of
issue-related moral imperative in a situation” (p. 372). Jones’ (1991) moral intensity
construct, also called the Perceived Moral Intensity Scale (PMIS), was used to explain
the four stages of Rest’s (1986) model of the ethical decision-making process, with
respect to how an organisation engages in moral behaviour.
Jones’ (1991) original issue contingent model describes the relationship between moral
intensity and the moral/ethical decision-making process. It illustrates that moral and
ethical issues determine not only the recognition step but also the judgement and action
sequence of the process. The moral intensity construct and its impact on intentions in
situations involving ethical dilemmas has been much researched, for example,
Singhapakdi et al. (1996), May and Pauli (2002) and Henik (2005). As well as studies in
the marketing context, moral intensity has also been examined in disciplines as diverse
as accounting and agriculture (Bennett, Anderson & Blaney 2002; Leitsch 2006).
Solymossy and Masters (2002) discuss that the steps towards moral behaviour are
affected by the moral intensity of the issue, relationships with other people in the
organisation, individual and situational characteristics, and level of cognitive moral
development (CMD). May and Pauli (2002) relate moral intensity to the TPB in the
context of the treatment of waste water and examined this in the context of moral
recognition, evaluation and intention. This model was also important for this thesis as
the process of moral decision making was referred to as “ethical decision making” (see,
for example, Maheshwari and Ganesh’s (2006) framework), thus supporting a premise
of this research study that the words can be used interchangeably.
While research has demonstrated that perceived moral intensity influences ethical
perceptions, intentions (Singhapakdi et al. 1999; Singhapakdi, Vitell & Kraft 1996) and
3.17 41BMoral intensity
95
ethical decision making (Paolillo & Vitell 2002), it seems that the moral intensity
construct influences ethical decision making in different ways, depending on the ethical
and moral issue being addressed. For example, when measuring the influence that the
moral intensity dimensions have on moral evaluations in ethical decision making, May
and Pauli (2002) commented that the antecedent factors in Ajzen’s (1985) TPB are
more strongly related to managers’ ethical intentions regarding the treatment of waste
water when the magnitude of consequences was low (i.e. low perceived harm) than
when it was high (i.e. high perceived harm).
Many authors, including Singhapakdi et al. (1996), May and Pauli (2002) and
McMahon and Harvey (2006), describe how to measure the latent moral intensity
construct quantitatively using the six moral intensity characteristics (described below).
In the studies reported in the literature, respondents were given a scenario to read or
listen to which involved a moral dilemma. The number and types scenarios used were
quite varied. For example, Frey (2000) included two scenarios, Vitell and Patwardhan
(2008, p. 208) used four and McMahon and Harvey (2006, p. 386) used 18.
Respondents were then asked a series of questions to gauge the level of their moral
intensity about the scenario, to measure six characteristics: magnitude of consequences
(MC), social consensus (SC), probability of effect (PE), temporal immediacy (TI),
proximity (PX) and concentration of effect (CE). The components of the moral issue are
expected to have interactive effects, and moral intensity was expected to increase if
there was an increase in any one (or more) component(s).
Table 3.12 summarises the descriptions of the six characteristics of the moral intensity
construct, based on a variety of sources that encompass the different interpretations of
the construct.
3.17.1 129BMeasuring moral intensity
96
Table 3.12 The six characteristics of moral intensity Characteristic Description Magnitude of the consequences (MC)
Jones (1991) defined MC as “the sum of the harms (or benefits) done to victims (or beneficiaries) of the moral act in question” (p. 374). Weber (1996) found that business managers’ reactions to a moral issue are significantly influenced by the magnitude of the consequences of the moral issue. Fritzsche and Becker (1983, p. 279) found that respondents “would act more ethically in dilemmas posing serious consequences than they would in less risky situations”. More recently, magnitude of consequences was found to have a positive effect on both recognition and behavioural intention to act in a study that focused on environmental issues (Chia & Mee 2000).
Social consensus (SC)
Jones (1991, p. 375) defined this as “the degree of social agreement that a proposed act is good or evil”. Socialisation theories suggest that morality is derived from the external social system (Trevino 1986) and hence social consensus was included as a component of moral intensity expected to largely influence the likelihood of moral judgement. A high degree of social consensus reduced the ambiguity while making a choice and therefore can lead to ethical decision making. More recently, social consensus has been empirically tested and found to positively affect issue recognition (Chia & Mee 2000).
Probability of effect (PE)
PE is “a joint function of the probability that the act in question will actually take place and the act in question will actually cause the harm (benefit) predicted” (Jones 1991, p. 375). For example, “a 2% probability that an act will occur is less morally intense than a 98% probability, and a 2% probability that harm (benefit) will be caused by the act is less morally intense than a 98% probability” (McMahon & Harvey 2006, p. 382).
Temporal immediacy (TI)
This is “the length of time between the present and the onset of consequences of the moral act in question, a shorter time implying a greater immediacy” (Jones 1991, p. 376). Jones (1991) observed that “individuals also seem to react more strongly to injustices that have immediate effects as opposed to those that have effects in the distant future” (p. 371). Temporal immediacy affects recognition of a moral issue (Chia & Mee 2000) and a shorter length of time implies a greater temporal immediacy.
Proximity (PX)
Jones described this as “the feeling of nearness (social, cultural, psychological or physical) that the moral agent has for victims (beneficiaries) of the evil (beneficial) act in question” (1991, p. 376). “Intuitively, people tend to become much more concerned about moral issues that affect those who are close to them rather than those with whom they have little or no contact” (Jones 1991, p. 371). Increased proximity can increase an individual’s concern in the decision-making process.
Concentration of effect (CE)
“The concentration effect of the moral act is an inverse function of the number of people affected by an act of given magnitude” (Jones 1991, p. 377). In other words, it is considered worse to hurt one person seriously than to cause a slight injury to many people. In the business context, managers may ignore immediate returns in favour of ethics in their decision making when the concentration of effects is high.
Source: Based on Jones (1991), Weber (1996), Fritzsche and Becker (1983), Chia and Mee (2000) and McMahon and Harvey (2006)
The literature demonstrates that the authors have used different numbers of statements
to measure the individual characteristics of moral intensity. Singhapakdi, Vitell et al.’s
(1996) original list was based on the work of Jones (1991) and included 16 statements
to measure each of the six moral intensity dimensions. Magnitude of consequences was
measured with a four item scale, probability of effect was measured using three items,
proximity was measured using two items, temporal immediacy was measured using two
97
items, concentration of effect was measured using three items and social consensus was
measured using two items.
Frey (2000), May and Pauli (2002) and McMahon and Harvey (2006) argue that some
of the statements that measure the six dimensions of the moral intensity construct are
highly intercorrelated, and supplementary factor analyses revealed that some of the
dimensions loaded together. Consequently, it was recommended that the number of
statements used to calculate the moral intensity construct be reduced from 16 to either
12 or six. In Vitell and Patwardhan’s (2008, p. 208) study, the six statements used are:
The overall harm (if any) as a result of the action would be very small
(magnitude of consequences = MC)
Most people would agree that the action is wrong (social consensus = SC)
There is a very small likelihood that the action will actually cause harm
(probability of effect = PE)
The action will not cause any harm in the immediate future (temporal
immediacy = TI)
If one were a personal friend of the person(s) harmed, the action would be
wrong (proximity = PX)
The action will harm few people, if any (concentration of effect = CE).
Authors such as May and Pauli (2002), McMahon and Harvey (2006) and Vitell and
Patwardhan (2008) use a 7-point Likert scale to calculate their moral intensity
summated score, where 1 represents disagree strongly and 7 represents agree strongly.
The next section discusses some findings from studies that have incorporated the moral
intensity construct.
98
Many scholars have tested the validity and complexity of the six dimensions of the
moral intensity construct and the effect of moral intensity on ethical decision-making
models. Authors such as May and Pauli (2002), Henik (2005) and McMahon and
Harvey (2006) have recommended that moral intensity be simplified from six
dimensions to fewer (often two or three) dimensions, depending on the context of the
ethical and moral issue. Some examples are given in subsequent paragraphs.
Singhapakdi et al. (1996) conducted a study using the American Marketing
Association’s membership mailing list as the sampling frame. With a sample size of 453
(response rate = 23%) they found that five of the six moral intensity dimensions are
significantly related to ethical intentions. They grouped these into two factors: “harm”
which was measured by MC, PE, TI and CE, and “social pressure” which was measured
by SC and PX. Their conclusions are summarised below:
May and Pauli (2002, p. 92) demonstrated that the magnitude of consequences and
social consensus dimensions play “the most important role in individuals’ judgments”.
They conclude that the moral intensity construct comprises three factors: probable
magnitude of harm (which includes MC, PE, PX and TI), concentration of effect and
social consensus.
3.17.2 130BComparing the moral intensity dimensions
MORAL INTENSITY – Singhapakdi et al. (1996)
Harm: MC, PE TI, CE Social Pressure: SC, PX
MORAL INTENSITY – May and Pauli (1999)
Probable magnitude of harm: MC, PE, PX, TI CE SC
99
Henik (2005) argues that MC and SC seem to be the strongest indicators of moral
intensity. They concluded that MC was the most “consistent determinant” of both the
judgement and intention stages when Moral Intensity was objectively manipulated and
that SC was a “consistent predictor of intentions only” (p. 20). Henik (2005) also
suggested two factor loadings for the moral intensity scale, as shown below. Note that
unlike Singhapakdi et al.’s (1996) study, they did not label the two factors.
Also reflecting on the nature of the moral intensity construct, McMahon and Harvey
(2006) suggested a different, three factor structure. The first factor includes magnitude
of consequences (MC), probability of effect (PE) and temporal immediacy (TI) and was
labelled “Probable Magnitude of Consequences”, the second was labelled “Proximity”
and the third was labelled “Social Consensus”. They omitted concentration of effect
(CE) because the “items that were used did not appear to be assessing the specific
characteristic that was posited by Jones” (p. 402). This was similar to the finding of
Chia and Mee (2000) who also found that concentration of effect has no influence on
moral issue recognition, raising the question of its validity within the moral intensity
theory.
McMahon and Harvey’s (2006) findings are summarised below.
MORAL INTENSITY – McMahon and Harvey (2006)
Probable Magnitude of
Consequences: MC, PE, TI
Social Consensus
SC
Proximity
PX
MORAL INTENSITY – Henik (2005)
MC, PX, CE SC, TI, PE
100
Chia and Mee (2000) argued that the effects of magnitude of consequences and social
consensus, as well as proximity and temporal immediacy, have a consistently strong
influence on the recognition of moral issues. They found only weak evidence for the
influence of probability of effect, and no evidence for concentration of effect on the
recognition of moral issues.
The considerable variation in the moral intensity construct means that more work was
needed to reach a universal agreement of what exactly comprises the construct.
Inevitably, it could be found that this variation depends on the context in which the
construct was measured (Chia & Mee 2000). It has also been argued by McMahon and
Harvey (2006) that the term “moral intensity” may be a “misnomer” as it does not “refer
to a moral notion (guided by normative ethical theory), but rather to the moral relevance
of characteristics of the issue being considered in the decision making process” (p. 402).
While they called for further research to decide on a better name, it was apparent that
the moral intensity construct seems to be important in understanding ethical decision
making, hence its inclusion in this study.
The next section gives an overview of relevant models and studies discussed in this
chapter.
This chapter has introduced the constructs and variables that measure the issues
associated with the intention to engage in behaviours, mainly from the ethical and
sustainable context. Table 3.13 summarises the important models for this study and the
main constructs included in each.
3.18 42BOverview of relevant models and studies
101
Table 3.13 Source of the constructs for this study Model and author(s) Main constructs Buyer behaviour Hunt and Vitell (1986)
Inputs and outputs Perceptual constructs Learning constructs
Theory of Reasoned Action (TRA) Ajzen and Fishbein (1980) For volitional behaviours only
Behavioural beliefs Normative beliefs Control beliefs Attitudes towards the behaviour Subjective norm Perceived behavioural control Intention and behaviour
Theory of Planned Behaviour (TPB) Ajzen (1985) For volitional and non-volitional behaviours
Behavioural beliefs/beliefs about outcomes Evaluation of outcomes Normative beliefs Control beliefs/relative importance of attitude and norm Attitudes towards the behaviour Subjective norm Perceived behavioural control Intention and behaviour
Issue contingent model Model Jones (1991) McMahon and Harvey (2006)
Moral intensity Recognise moral issue Make moral judgement Establish moral intent Engage in moral behaviour
“Model 2” Shaw and Shiu (2003)
Perceived behavioural control (PBC) External control Behavioural control Subjective norm Attitudes towards the behaviour Ethical obligation Self-identity Internal ethics and internal reflection Behavioural intention
Conceptual framework for understanding public opposition (or support) for a collective action that impacts environmental quality: building a dam to meet local water supply needs. Routhe et al. (2005)
Universe of action* Actual behaviour Behavioural intention and attitudes Subjective norm Behavioural beliefs Normative beliefs
* Note that “universe of action” is “all collective actions that could significantly impact the environment” (Routhe, Jones & Feldman 2005, p. 883).
The studies reported in this chapter also contain recommendations for further research.
Table 3.14 summarises the main findings and recommendations. It demonstrates the
need for studies to examine the constructs that determine behavioural intention in more
detail and for the need to operationalise these constructs.
102
Table 3.14 Main findings and further research from some relevant models Authors
Name of model/ Sample details
Main findings/ conclusions
Further research
Ajzen (1985)
Theory of Planned Behaviour Conceptual model
The TPB was developed to include non-volitional behaviours and perceived behavioural control. It did this by linking PBC with behavioural intentions with attitudes, subjective norm.
There is the need to apply the TPB to issues ranging from environmental behaviours to explaining moral behaviour in organisations.
Hunt & Vitell (1986). Revised in 1993
Theory of marketing ethics Conceptual model
Assumed that the activity or situation was perceived as an ethical issue and it models the alternatives or actions that the individual might take to resolve it.
Work is needed to operationalise the concepts in the model and to test the model empirically.
Dubinsky & Loken (1989, p. 103)
Model for analysing ethical decision making in marketing Sales people, sales related behaviours
Factors that influence ethical decision making, behavioural intention, attitude, perceived social influence to perform the behaviour, behavioural beliefs about the outcomes associated with performing the behaviour, evaluations of those outcomes, normative beliefs, motivations to comply with the referents.
Investigate relationship between intentions and behaviour, test in other contexts; understand effects of other external factors such as economic conditions.
Granzin & Olsen (1991)
348 adult residents of a major western metropolitan area in USA
Demographics, media usage patterns, information sources and knowledge provided an understanding of participants who had been involved in three environmental protection activities: donating items for reuse, recycling newspapers and walking when possible for reasons of conservation and environmental concern.
Jones (1991)
Issue contingent model (conceptual) demonstrated the importance of the characteristics of the moral issue and moral intensity on decision making
Based on Rest’s (1986) model, the issue contingent model described ethical decision making in organisations. The moral component of a problem (moral issue) can be characterised in terms of its moral intensity.
The model needs to be tested empirically. Many authors including Vitell and Patwardhan (2008) tested the moral intensity construct.
Petts et al. (1998)
389 employees in SMEs in the EU
Younger people are more concerned about the environment; attitudes do not predetermine behaviour.
To explore the link between age and attitudes/concern for the environment in the workplace.
Laroche et al. (2001)
907 Individuals in a large USA city Exploratory study
Attitudes, values, demographics and behaviours, affect willingness to pay more for green products. High factor loadings on factor analysis, Cronbach alphas between 0.65 and 0.87.
More factors need to be examined to explain which consumers are likely to pay more for environmentally friendly products (p. 515).
103
Paolillo & Vitell (2002)
235 business managers in USA
Personal, organisational and moral intensity factors and ethical decision making. Regression showed that MI is the only significant factor affecting EDM. The nature of the issue was important. R2 = 0.531
Investigate other ethical issue related factors that might affect EDM, e.g. cultural and legal factors.
Shaw & Shiu (2003)
Model “2” 1,472 ethical consumers
Based on the TPB, included factors influencing behavioural control and internal reflections affecting behavioural intention.
Need to explore possible links between ethical obligation and self-identity and the underlying values that are important to consumers who hold ethical concerns. Need to research this model in other countries.
Henik (2005)
176 part-time MBA students in USA
Moral intensity can be described as a 2 factor solution -MC, LC, CE and SC, TI, PV. Findings are close to Singhapakdi et al. (1996). MI was a significant determinant of judgements and intentions.
Gilg et al. (2005) noted the need for policy makers to target specific demographic and
values segments to facilitate the move to sustainable lifestyles. The next section
discusses the internal factors that can influence sustainable and ethical decision making.
These include both demographics and values segments, which are important given the
diverse range of behaviours that are related to the environment and sustainability issues.
According to the literature, internal factors such as age, gender, marital status and the
presence of children can affect issues that relate to the environment and sustainability.
Some studies, particularly those regarding the “age” variable, are conflicting. Petts et al.
(1998) and Carrigan et al. (2004) have suggested that age can be an important
moderating variable in environmental ethics and behaviour. Carrigan et al. (2004)
argued that there was some disagreement about the age at which consumers become
more “ethical” in their behaviour, citing previous research which indicates that an
ethical consumer can be either aged 35 and older or 55 and older. They also found that
3.19 43BDemographic variables
104
people aged over 65 are more likely than younger people to “do what they can” with
respect to ethical consumption (p. 403). They attribute this to the fact that younger
consumers can be more likely to voice their opinions through public actions such as
signing a petition, whereas older consumers can be more inclined to exercise their
freedom of choice more quietly, such as choosing what to buy and what not to buy.
Petts et al. (1998) interviewed 389 employees in SME’s in the EU and concluded that
fewer younger people, particularly those aged under 25 years, were concerned about the
environment compared to those aged 55+. They demonstrated that the 18-54 year old
cohort display the greatest levels of support for environmental issues, while older
people are more likely to engage in recycling (Petts, Herd & O'Heocha 1998). It seems
that the older cohort was more likely to adopt ethical behaviours as they have had more
time to absorb and act on ethical purchase information (Carrigan, Szmigin & Wright
2004, p. 404). Petts et al. (1998) recommended further research to explore the link
between age and attitudes and concern for the environment.
Granzin and Olsen (1991) demonstrated that females were more likely to donate their
time to volunteer programs and were more concerned about nuclear energy, while men
were more knowledgeable and concerned about acid rain. Laroche et al. (2001)
suggested that the kinds of consumers who were willing to pay more for
environmentally products were most likely to be female and married with at least one
child living at home.
With respect to marital status and the presence of children in the household, married
persons are more committed to conservation (Granzin & Olsen 1991). While the
number of children was positively related to the purchase of ecology-oriented products,
it was negatively related to willingness to pay more for matters related to environmental
clean-up (Granzin & Olsen 1991). Brooker (1976) concluded that the number of
children was a significant determinant of behaviour with respect to the environment. He
suggested that this could be related to the fact that individuals with larger families are
more likely to have children in school where environmental issues are discussed. This
could then make parents more likely to succumb to pressure regarding conformance
with socially acceptable behaviour concerning the environment.
105
Another study relating to demographics was presented by Tan (2002) who has
developed an “Issue-risk-judgement” model of ethical decision making which included
moderating variables such as age, gender, education and income. These variables are
demonstrated to affect the moral intensity, perceived risks and moral judgements for
ethical choices, which in turn affect the outcome of the ethical decision-making process.
Tan’s (2002) study examined a person’s intention to purchase pirated software. This
model is shown in appendix 4.
Higher levels of education and higher income levels have been linked to greater concern
for the environment and greater likelihood of participation in environmental protection
activities (Schaper 2002) including energy conservation and willingness to pay for
cleaning the environment (Granzin & Olsen 1991). On the contrary, Smith and Oakley
(1994) found that formal education and ethical values are negatively correlated,
suggesting that as education increases, the likelihood of ethical decision making
decreases. Higher social class has been related to greater participation in environmental
causes, greater likelihood of joining or supporting environmental groups, stronger
attitudes towards environmental protection and greater support for energy conservation
(Granzin & Olsen 1991).
Individuals living in areas with higher property values (suggesting home ownership) are
found to be more likely to participate in recycling activities, and those living in single-
family dwellings displayed a greater commitment to conservation (Granzin & Olsen
1991). The rural versus urban context was also shown to be an important determinant in
ethical decision making. For example, McEachern (2008) demonstrated that people
living in rural areas had a higher involvement in the purchase process for fresh meat
than urban consumers.
While demographics are found to be important variables in explaining environmentally
friendly behaviours, it seems that “knowledge, values and/or attitudes” (Laroche,
Bergeron & Barbaro-Forleo 2001, p. 505) can be just as important. Values and
behavioural segmentation are discussed in the next section.
106
Values, which describe the lifestyle of individuals (Spaargaren 2003), are an abstract
construct that serve as a guiding principle for selecting or evaluating behaviour, people
and events (Collins, Steg & Koning 2007). They are a function of knowledge, attitudes
and intentions (Ferrell & Gresham 1985) and can be used to explain attitudes and
intentions towards protecting the environment.
Many studies have used behavioural variables and values to segment the market for
sustainability and the environment. Schwartz (1992) developed one of the most widely
used typologies that comprised 57 values which are grouped into 10 value clusters that
are used to describe individual differences in values. These are: conformity, tradition,
universalism, benevolence, power, achievement, hedonism, stimulation, self-direction
and security. Due to the complex nature of Schwartz’s (1992) study, this values
construct was not included in this research study.
It has been argued that while pro-environmental values do not guarantee that pro-
environmental behaviour will occur, they are likely to do so (Kalafatis et al. 1999). The
Big Clean Up (BCU) social marketing initiative in Auckland, New Zealand, was
designed to encourage individuals and households to engage in sustainable living
(Frame 2004). There are many behavioural segmentation variables used in this study.
For example, customers are segmented into three groups: those who lead a totally
“environmentally considerate” lifestyle where the environment was considered “in
almost every action”, those who lead a pragmatic lifestyle where the environment was
only considered when “it was reasonable and practical to do so”, and an unconcerned
lifestyle where the environment was “not considered at all” (p. 520). This was similar to
Spaargaren’s (2003) description of an “environmentally friendly attitude” and a “green
or sustainable lifestyle” (p. 689).
The market in the BCU was also segmented into three behavioural groups (each
representing approximately one-third of the population) based on lifestyle motivations:
3.20 44BValues and behavioural variables
107
“will not shift (change)”, “will shift (change) through increased awareness, knowledge,
skills and participation” and “already with us in values and actions” (Frame 2004, p.
518). Another segmentation that arose from this study classified the market into seven
values’ groups reflecting behavioural intention. These ranged from the “browns” who
are “unhappy in lifestyle or already committed to lifestyle” and resistant to change;
through to the “dark greens” who are “strongly committed to lifestyle” and also resistant
to change. The main target market of the BCU was the “ambivalent to green” group
who are attracted to a changing lifestyle and are willing to change their behaviours
(Frame 2004, p. 519). However, Frame (2004) notes that “while these may be
appropriate lifestyle classifications for consumer product marketing research, it was
unclear to what extent they are applicable to complex issues such as sustainable
development where deeper reflection and a deeper shift in consumer behaviour are
needed” (p. 520).
Routhe et al. (2005) also discuss behavioural intention and posit that it was “the most
proximate predictor of behavioural support for environmental values” when it comes to
building a new dam (p. 881). They segmented the market into consumers who are
“opponents”, “proponents” or “undecided (Routhe et al. 2005, p. 890).
Another important behavioural segmentation variables affecting ethical and sustainable
behaviour was “environmental concern” and this is discussed in the next section.
Environmental concern has long been recognised as an important segmentation variable,
with Jones and Dunlap (2004) demonstrating the link (albeit weak) between age and
environmental concern. Dunlap and Jones (2002) used attitude theory and the TPB to
conceptualise environmental concern by identifying affective and cognitive ways that
people can express support for environmental issues. They commented that affective
expressions are people’s “attitudes towards very specific problems or issues” ranging
from disposal of toxic wastes and recycling “to broader issues such as environmental
3.20.1 131BEnvironmental concern
108
problems or protection”, and cognitive expressions are “people’s knowledge and beliefs
about environmental issues” (Dunlap & Jones 2002, p. 490). Environmental concern is a
multidimensional construct which “reflects the degree to which people are aware of
environmental problems, believe they are serious and need attention, are willing to
support efforts to solve them, and actually do things that contribute to their solution”
(Dunlap & Jones 2002, p. 485). Environmental concern is conceptualised as a general
attitude that reflects the extent to which the consumer is worried about the threats to the
environment (Datta 2011, p. 127). Further, environmentally conscious behaviours are
influenced by perceived consumer effectiveness, environmental concern and perceived
knowledge of environmental issues.
Due to the general feeling of uncertainty about the environment, there was a growing
individual need to feel secure and to spend more time with family and friends, which
could in turn encourage more people to adopt sustainable lifestyles (Malhotra & Miller
1998). Brooker (1976) found that individuals who are higher on Maslow’s self-
actualisation dimension are more likely to be socially conscious consumers and to show
environmental concern. While “environmental concern” was described as
“conceptualised and measured in [a] myriad [of] ways and usually without a coherent
theoretical framework” (Routhe, Jones & Feldman 2005, p. 875), research has
demonstrated that the more environmentally concerned that citizens are, the more
knowledgeable they are about possible solutions to environmental problems (Granzin &
Olsen 1991). It was also argued that people who are more knowledgeable about
environmental issues were more willing to pay a premium for green products (Laroche,
Bergeron & Barbaro-Forleo 2001).
Knowledge has been recognised as a variable that influences all stages of the decision-
making process (Laroche, Bergeron & Barbaro-Forleo 2001). It can do so in three ways:
how consumers gather and organise information, how much information is used in
decision making, and how consumers evaluate products and services (Laroche,
Bergeron & Barbaro-Forleo 2001). There have been varying research findings about
how knowledge affects “ecologically compatible” behaviour, ranging from being a
significant predictor to the reverse (Granzin & Olsen 1991).
109
A good summary of the above discussion was presented in the conceptual framework
provided by Laroche et al. (2001, p. 504) which showed that demographics, knowledge,
values, attitudes and behaviours affect consumers’ willingness to pay more for
environmentally friendly products. This figure is shown in appendix 5.
The 1980s saw the emergence of research into ethical decision making, notably the
“Theory of Ethics” developed by Hunt and Vitell (1986) which illustrated the
alternatives or actions that the individual might take to resolve an ethical issue. Prior to
this, models such as the Protection Motivation Theory (PMT) (Rogers 1975), Theory of
Reasoned Action (TRA) (Fishbein & Ajzen 1975) and Theory of Planned Behaviour
(TPB) (Ajzen 1985) were developed to understand intention to perform a particular
behaviour. These demonstrated that the antecedents to behavioural intentions were
attitudes, subjective norm and perceived behavioural control.
Subsequently, authors such as Shaw and Shiu (2003), Wall, Devine-Wright and Mill
(2007) and Fielding, McDonald and Louis (2008) applied the TPB to different contexts
and argued that in order to improve its predictive power, additional constructs needed to
be considered for inclusion. Shaw and Shiu (2003) applied the TPB to ethical
consumers’ behaviours with respect to free trade products, and Wall, Devine-Wright
and Mill (2007) and Fielding, McDonald and Louis (2008) applied it to environmentally
sensitive behaviours. Such studies supported the robustness of modified versions of the
TPB in explaining intention to behave. For example, Wall, Devine-Wright and Mill’s
(2007) study suggested the need to include personal normative motives to explain the
fact that behaviours that reduce personal utility may be perceived as difficult and
therefore unattainable. Sparks et al. (1995), Shaw and Shiu (2002) and Chedzoy and
Burden (2007) demonstrated the need to include ethical obligation and self-identity in
models of behavioural intention. Shaw and Shiu (2003) went a step further, combining
these two constructs and labelling their combined affect as “internal ethics”.
3.21 45BChapter summary
110
Prior to this, Jones (1991) had made a significant contribution to the ethical decision-
making literature by discussing how the characteristics of the moral issue could have an
influence on ethical decision making in organisations. Jones’ (1991) moral intensity
(MI) construct was used to explain the four stages that describe how an organisation
proceeds to engage in moral behaviour, including behavioural intention and actual
behaviour. This construct was used in many studies by authors such as May and Pauli
(2002), Henik (2005) and McMahon and Harvey (2006).
As well as the constructs included in the models of behavioural intention, there has been
discussion about the need to measure the effects of internal factors such as age, gender,
marital status, presence of children and education in order to understand their effects on
environmental issues and sustainability. For example, Petts et al. (1998) and Carrigan et
al. (2004) suggest that age can be an important moderating variable in environmental
ethics and behaviour, and Laroche et al. (2001) suggest that females and married people
with at least one child living at home are willing to pay more for environmentally
friendly products. Higher levels of education and higher income levels have been linked
to greater concern for the environment and a greater likelihood of participation in
environmental protection activities (Schaper 2002) including energy conservation and
willingness to pay for cleaning the environment (Granzin & Olsen 1991). Tan (2002)
extended models of ethical decision making by developing an issue-risk-judgement
model which links variables including age, gender, education and income with moral
intensity for ethical choices. Individual or personal values such as environmental
concern can also be used to explain attitudes and activities towards the environment and
its protection (Frame 2004).
While conceptual models play an important role in understanding what motivates
consumer behaviour and what drives behavioural change, there are few examples of
studies examining the constructs from the perspective of the consumer and using a
cross-section of the population. Many of the studies quoted in this chapter are
conceptual only and not based on empirical evidence. Those that are based on empirical
evidence are often based on studies of students (Street & Street 2006; Wall, Devine-
Wright & Mill 2007) or students who are managers (Weber & Gillespie 1998). Other
111
models are either too complex to be tested empirically (such as the Theory of Ethics) or
are focused on only a few constructs, such as the role of moral intensity in ethical
decision making (Sparks & Shepherd 1992).
In summary, the literature demonstrates that behavioural intention can be explained by
using an extended version of the Theory of Planned Behaviour (TPB). Of particular
interest for this research study are the six independent exogenous constructs and their
related antecedents. These are attitudes and their antecedents called behavioural beliefs,
perceived behavioural control (PBC) and their antecedents called control beliefs,
subjective norm and their antecedents called normative beliefs, personal normative
motives, internal ethics and moral intensity.
In addition, the literature demonstrates that there are two ways that behavioural
intention could be measured: Firstly, behavioural intention can be measured by asking
respondents about their likelihood to engage in certain kinds of behaviours. Secondly,
behavioural intention and past behaviour can be measured by asking respondents about
which specific behaviours they have engaged in or adopted and which they intend to
engage in or adopt in the future. For this study, the exogenous constructs are labelled
likely behavioural intention (LBI), lifestyle behaviour, lifestyle intention, capital
behaviour and capital intention. In this study, measures of actual behaviour are
measures of “past behaviour”.
The next chapter uses the information from the literature to design the theoretical
frameworks to address the research questions that are to be examined. Subsequently,
the constructs are operationalised and the research hypotheses are developed based on
the theoretical frameworks.
112
Chapter 4: 3BTheoretical frameworks, research questions
and hypotheses
This research study’s aims are predicated on the knowledge that sustainable and ethical
behavioural patterns can be understood and even changed by examining the combined
effects of the latent exogenous constructs described in the different theories of
behavioural intention, notably the Theory of Planned Behaviour (TPB). This is
especially relevant today as governments and organisations work together to encourage
consumers to adopt sustainable behaviours. This means that there is the need to target
specific groups who are likely to engage in sustainable lifestyles with greater efficacy in
order to achieve these objectives (Cunningham 2008).
Therefore, this study aims to determine which latent exogenous constructs are the best
predictors of behavioural intention in the sustainable context. It also aims to determine
how to measure sustainable behaviour and intention, as well as understanding the effect
of control variables including demographics on the ability of the theoretical models to
predict sustainable behavioural intention.
This chapter describes the processes involved in developing the theoretical frameworks
based on the literature review in chapters 2 and 3. It also discusses the development of
the research questions and hypotheses for the latent exogenous and endogenous
constructs. Figure 4.1 provides a roadmap of this chapter
.
4.1 46BIntroduction
113
Figure 4.1 Roadmap of chapter 4
Source: Adapted from Perry (1995)
Chapter 4: Developing the
theoretical framework, research
questions and hypotheses
Measuring sustainable
behavioural intention
Latent constructs and
hypotheses
Demographic segmentation
Developing the theoretical
frameworks
Research questions and
research objectives
Summary of research objectives
and hypotheses
Chapter summary
114
The primary objective of this research study is to investigate the applicability of an
extended version of Ajzen’s (1985) Theory of Planned Behaviour (TPB) and its ability
to measure sustainable behavioural intention. The other objective is to understand which
of the three behavioural intention constructs best explain sustainable behavioural
intention.
The original version of the TPB describes behavioural intention as determined by the
combination of three latent constructs: the attitudes towards the behaviour, the
perception of behavioural control and subjective norm. In other words, if the attitude
and the subjective norm are favourable and there is the perception of control over the
situation, then there is a greater likelihood that the person or organisation will intend to
perform the behaviour in question.
Shaw et al. (2000, p. 880) quoted Ajzen (1991, p. 199) when they noted that the TPB is
“open to the inclusion of additional predictors if it can be shown that they capture a
significant proportion of the variance in intention or behaviour after the theory’s current
constructs have been taken into account”. As a result, there have been many
modifications of the TPB, described by authors such as Chang (1998), Kalafatis et al.
(1999), Chedzoy and Burden (2007), Hughes, Ham and Brown (2009b) and Fielding,
McDonald and Louis (2008).
This study proposes that the three constructs in the original TPB be examined with the
inclusion of three additional constructs, to predict their ability to determine behavioural
intention. The three additional constructs are internal ethics (Hagger & Chatzisarantis
2006; Shaw & Newholm 2002; Shaw, Shiu & Clarke 2000; Sparks, Shepherd & Frewer
1995), personal normative motives (Wall, Devine-Wright & Mill 2007) and moral
intensity (Jones 1991; McMahon & Harvey 2006).
4.2 47BBackground
115
A theoretical framework is a collection of theories and models from the literature which
underpins a positivistic research study which explains the research questions and
hypotheses (Zikmund 1997).
For this study, three theoretical frameworks are presented, all of which include five
exogenous constructs and five endogenous constructs. The number of exogenous
constructs has been decided upon in accordance with Bentler and Chou (2002) who
suggest that theoretical models should contain about five to six exogenous constructs.
The five latent exogenous constructs included in this study are attitudes, perceived
behavioural control (PBC), subjective norm/personal normative motives/normative
beliefs, internal ethics and moral intensity. The three constructs called subjective norm,
personal normative motives (PNM) and normative beliefs are combined to form the one
“normative” construct called “subjective norm/PNM/normative beliefs”. This was done
because Bentler and Chou (2002) suggested that each construct in a theoretical model
should be measured by three to four indicators, and the resultant normative construct
has a total of five measures: two for normative beliefs, one for subjective norm and two
for PNM.
The theoretical frameworks also include five latent endogenous constructs. These have
been labelled “likely behavioural intention” (LBI), “lifestyle intention” and “capital
intention”. Past behaviour is measured by two constructs that have been labelled
“lifestyle behaviour” and “capital behaviour” and these are included as mediating
constructs in this study. Additionally, the theoretical frameworks assume that the five
latent exogenous constructs influence the latent endogenous constructs in an equal way.
Table 4.1 summarises the research hypotheses for this study. There are a total of 17
hypotheses, of which 15 relate to the lifestyle and capital intention constructs.
4.3 48BDeveloping the theoretical frameworks
116
Table 4.1 Research hypotheses for the exogenous and endogenous constructs
Likely behavioural intention (LBI)
Lifestyle intention
Capital intention
Latent exogenous constructs Behavioural beliefs and attitudes H1 H6 H11 Control beliefs and PBC H2 H7 H12 Subjective norm, PNM, normative beliefs H3 H8 H13 Internal ethics H4 H9 H14 Moral intensity H5 H10 H15 Latent endogenous behaviour constructs Lifestyle behaviour H16 Capital behaviour H17
The details of the research hypotheses are elaborated later in this chapter. The next
section describes the theoretical frameworks for this study.
The three theoretical frameworks, with the corresponding hypotheses included, are
shown in Figures 4.2, 4.3 and 4.4. The first illustrates the antecedents to likely
behavioural intention (LBI).
4.3.1 132BThe theoretical frameworks
117
Figure 4.2 Theoretical framework for likely behavioural intention
Source: Adapted from Ajzen (1985), Chang (1998), Kalafatis et al. (1999), Shaw et al. (2000), McMahon and Harvey (2006), Chedzoy and Burden (2007), Wall, Devine-Wright and Mill (2007), Vitell and Patwardhan (2008), Fielding, McDonald and Louis (2008), Hughes, Ham and Brown (2009b), Bennett et al. (2002), Laroche et al. (2001)
The second theoretical framework illustrates the antecedents to lifestyle behaviour and
intention.
118
Figure 4.3 Theoretical framework for lifestyle behaviour and intention
Source: Adapted from Ajzen (1985), Chang (1998), Kalafatis et al. (1999), Shaw et al. (2000), McMahon and Harvey (2006), Chedzoy and Burden (2007), Wall, Devine-Wright and Mill (2007), Vitell and Patwardhan (2008), Fielding, McDonald and Louis (2008), Hughes, Ham and Brown (2009b)
The third theoretical framework illustrates the antecedents to capital behaviour and
intention.
119
Figure 4.4 Theoretical framework for capital behaviour and intention
Source: Adapted from Ajzen (1985), Chang (1998), Kalafatis et al. (1999), Shaw et al. (2000), McMahon and Harvey (2006), Chedzoy and Burden (2007), Wall, Devine-Wright and Mill (2007), Vitell and Patwardhan (2008), Fielding, McDonald and Louis (2008), Hughes, Ham and Brown (2009b)
The first research aim discussed in chapter 1 was to understand which latent exogenous
constructs were the best predictors of sustainable behaviour and intention. The four
research questions for this study have been postulated to understand the effects of the
latent exogenous constructs on each of the three behavioural intention constructs.
4.4 49BResearch questions
120
The first research question was developed to understand the antecedents to likely
behavioural intention (LBI):
How do consumers’ attitudes, perceived behavioural control (PBC), subjective
norm/PNM/normative beliefs, internal ethics, and moral intensity affect their likely
behavioural intention (LBI) with respect to sustainable behaviours?
The second research question was developed to understand the antecedents to lifestyle
behaviour:
How do consumers’ attitudes, perceived behavioural control (PBC), subjective
norm/PNM/normative beliefs, internal ethics, and moral intensity affect their lifestyle
behaviour with respect to sustainable behaviours?
The third research question was developed to understand the antecedents to capital
behaviour:
How do consumers’ attitudes, perceived behavioural control (PBC), subjective
norm/PNM/normative beliefs, internal ethics, and moral intensity affect their capital
behaviour with respect to sustainable behaviours?
The fourth research question was developed to understand the effect of lifestyle (past)
behaviour and capital (past) behaviour on lifestyle and capital behavioural intention,
respectively.
What is the effect of lifestyle and capital behaviour on lifestyle and capital
behavioural intention?
121
Based on the research questions that were elicited above, the research objectives for this
study are described below.
The research objectives (RO 1-5) for the first research question are:
1. To what extent do consumers’ attitudes affect their likely behavioural
intention (LBI)?
2. To what extent does consumers’ perceived behavioural control (PBC)
affect their likely behavioural intention (LBI)?
3. To what extent do consumers’ subjective norm/PNM/normative beliefs
affect their likely behavioural intention (LBI)?
4. To what extent do consumers’ internal ethics affect their likely
behavioural intention (LBI)?
5. To what extent does consumers’ moral intensity affect their likely
behavioural intention (LBI)?
The research objectives (RO 6-10) for the second research question relating to lifestyle
behaviour are:
6. To what extent do consumers’ attitudes affect their lifestyle behaviour?
7. To what extent does consumers’ perceived behavioural control (PBC)
affect their lifestyle behaviour?
4.5 50BResearch objectives
122
8. To what extent do consumers’ subjective norm/PNM/normative beliefs
affect their lifestyle behaviour?
9. To what extent do consumers’ internal ethics affect their lifestyle
behaviour?
10. To what extent does consumers’ moral intensity affect their lifestyle
behaviour?
The research objectives (RO 11-15) for the third research question relating to capital
behaviour are:
11. To what extent do consumers’ attitudes affect their capital behaviour?
12. To what extent does consumers’ perceived behavioural control (PBC)
affect their capital behaviour?
13. To what extent do consumers’ subjective norm/PNM/normative beliefs
affect their capital behaviour?
14. To what extent do consumers’ internal ethics affect their capital
behaviour?
15. To what extent does consumers’ moral intensity affect their capital
behaviour?
The research objectives (RO 16-17) for the fourth research question are:
16. What is the effect of lifestyle behaviour on lifestyle behavioural
intention?
17. What is the effect of capital behaviour on capital behavioural intention?
123
The latent exogenous constructs and the related hypotheses for this research study are
described in this section, beginning with attitudes.
Attitudes are measured in order to examine the following research objectives (RO):
RO1: To what extent do consumers’ attitudes affect their likely behavioural intention
(LBI)?
RO6: To what extent do consumers’ attitudes affect their lifestyle intention?
RO11: To what extent do consumers’ attitudes affect their capital intention?
Behavioural beliefs are the antecedents to attitudes and both these constructs are
included in the original Theory of Planned Behaviour (TPB). It is believed that a
person’s beliefs and their evaluations of the outcomes of their actions can dictate their
attitudes towards a behaviour (Ajzen & Fishbein 1980; Sparks, Shepherd & Frewer
1995). Therefore, behavioural beliefs measure the perceived likelihood and desirability
of a behaviour or outcome occurring (Routhe, Jones & Feldman 2005).
An attitude is “a summed product of the individuals’ beliefs and their evaluation of
those beliefs” (Shaw & Shiu 2003, p. 1487). Using the TPB, many studies by authors
such as Hagger and Chatzisarantis (2006), Kraft et al. (2005), Routhe et al. (2005),
Shaw and associates (Shaw & Shiu 2003; Shaw, Shiu & Clarke 2000), Laroche et al.
(2001) and Sparks and Shepherd (1992) have concluded that attitudes are predictive of
behavioural intention. These effects have been studied in different contexts, for
example, Sparks, Shepherd and Frewer (1995) concluded that the summed products of
4.6 51BLatent constructs and hypotheses
4.6.1 133BAttitudes
124
behavioural beliefs and outcome evaluations correlated significantly with attitudes
towards eating food produced by using gene technology.
In measuring attitudes, of particular interest for this research study is the work of
Laroche et al. (2001) who demonstrated that fun and enjoyment (through tasks such as
recycling and reducing pollution) are positively related to attitudes about behaving in an
environmentally friendly or sustainable manner. They argue that understanding the
severity of the situation and the importance of recycling as well as the inconvenience of
being environmentally friendly are important attitudinal constructs that influence the
intention to behave in an environmentally friendly manner (Laroche, Bergeron &
Barbaro-Forleo 2001). “Importance” is described as “whether consumers view
environmentally compatible behaviours as important to themselves or society as a
whole” (Laroche, Bergeron & Barbaro-Forleo 2001, p. 506) and is measured by three
statements. “Inconvenience” refers to how inconvenient it is for the consumer to
perform the behaviour and is measured by two statements. “Severity of environmental
problems” is measured by five statements.
Based on the studies of the combined effects of behavioural beliefs and attitudes, the
following hypotheses are developed – one for each behavioural construct:
H1: Attitudes have a positive influence on likely behavioural intention (LBI).
H6: Attitudes have a positive influence on lifestyle behaviour.
H11: Attitudes have a positive influence on capital behaviour.
Control beliefs are determined by two measures: the power of a factor to assist the
desired action (in this case, a sustainable behaviour) and the perceived access to the
factor (or behaviour) (Kalafatis et al. 1999). PBC refers to how easy or difficult a person
believes that performing a behaviour is likely to be (Routhe, Jones & Feldman 2005;
4.6.2 134BControl beliefs and perceived behavioural control (PBC)
125
Shaw, Shiu & Clarke 2000) and reveals public perceptions of institutional barriers to
pro-environmental action (Jones 1991). Using a regression analysis, Sparks et al. (1995)
found that perceived behavioural control and self-reported concern about environmental
issues provided independent contributions to the prediction of expectations about eating
food produced by gene technology in the future. However, while most authors have
demonstrated the importance of PBC, Routhe et al. (2005) reported that “perceived
control” is not a significant predictor of public support for building a new dam. Control
beliefs and perceived behavioural control (PBC) were included in the original TPB and
are measured in order to examine the following research objectives:
RO2: To what extent does consumers’ perceived behavioural control (PBC) affect their
likely behavioural intention (LBI)?
RO7: To what extent does consumers’ perceived behavioural control (PBC) affect their
lifestyle behaviour?
RO12: To what extent does consumers’ perceived behavioural control (PBC) affect
their capital behaviour?
Therefore, the following hypotheses are proposed – one for each behavioural construct:
H2: PBC has a positive influence on likely behavioural intention (LBI).
H7: PBC has a positive influence on lifestyle behaviour.
H12: PBC has a positive influence on capital behaviour.
The subjective norm refers to the perception that intention to behave in a particular way
is influenced by a person’s belief about what important others think that they should or
should not do with respect to the behaviour in question (Ajzen & Fishbein 1980). It
4.6.3 135BSubjective norm, PNM and normative beliefs
126
refers to generalised social pressure to support an action, by indicating perceived
normative pressure to support the action, such as building a new dam (Routhe, Jones &
Feldman 2005, p. 885). Normative beliefs are beliefs about what “significant others”
including family, close friends and neighbours think and the extent to which they are
significant referents for the individual. In other words, they refer to specific social
pressure to support an action (Routhe, Jones & Feldman 2005).
In a similar way, personal normative motives (PNM) refer to feelings of obligation and
responsibility and are activated by an awareness of the consequences of a behaviour and
beliefs about personal responsibility for the consequences (Wall, Devine-Wright & Mill
2007). They are used to explain the fact that behaviours that reduce personal utility
(such as by decreasing convenience) may be perceived as difficult and therefore not
achievable. Jones (1991) argued that “norms”, which included subjective norm and
normative beliefs, affect behavioural intention.
The latent subjective norm, PNM and normative beliefs are included to examine the
following research objectives:
RO3: To what extent do consumers’ subjective norm/PNM/normative beliefs affect their
likely behavioural (LBI)?
RO8: To what extent do consumers’ subjective norm/PNM/normative beliefs affect their
lifestyle behaviour?
RO13: To what extent do consumers’ subjective norm/PNM/normative beliefs affect
their capital behaviour?
To understand the influence that subjective norm, PNM and normative beliefs have on
the behavioural constructs, the following hypotheses are proposed – one for each
behavioural construct:
H3: Subjective norm/PNM/normative beliefs have a positive influence on likely
behavioural intention (LBI).
127
H8: Subjective norm/PNM/normative beliefs have a positive influence on lifestyle
behaviour.
H13: Subjective norm/PNM/normative beliefs have a positive influence on capital
behaviour.
Over 10 years ago, Shaw et al. (2000) noted that ethical concerns had often been
neglected in previous studies and concluded that the “internal ethics” construct is a
predictor of behavioural intention. Their modified version of the TPB illustrates that
internal ethics is a latent construct that comprises ethical obligation and self-identity.
Self-identity is a construct which accounts for the fact that ethical issues are not
considered in isolation. Shaw and Shiu noted that ethical consumers “may make ethical
consumption choices because ethical issues have become an important part of their self-
identity” (2002, p. 1488). Originating from the sociological and the psychological
literature, a person’s self-identity (or self-concept) has been demonstrated to have an
important influence on behaviour (Hagger & Chatzisarantis 2006; Sparks & Shepherd
1992). The rationale for the addition of self-identity to the TPB is that “as an issue
becomes central to an individual’s self-identity, then behavioural intention is
accordingly adjusted” (Shaw & Shiu 2003, p. 1488). Ethical obligation represents an
individual’s internalised ethical rules which reflect their beliefs about what is right or
wrong (Shaw & Shiu 2002).
In this research study, internal ethics is measured in order to examine the following
research objectives:
RO4: To what extent do consumers’ internal ethics (measured by ethical obligation and
self-identity) affect their likely behavioural intention (LBI)?
4.6.4 136BInternal ethics
128
RO9: To what extent do consumers’ internal ethics (measured by ethical obligation and
self-identity) affect their lifestyle behaviour?
RO14: To what extent do consumers’ internal ethics (measured by ethical obligation
and self-identity) affect their capital behaviour?
In order to examine the influence that internal ethics has on the behavioural constructs,
the following hypotheses are proposed – one for each behavioural construct:
H4: Internal ethics has a positive influence on likely behavioural intention (LBI).
H9: Internal ethics has a positive influence on lifestyle behaviour.
H14: Internal ethics has a positive influence on capital behaviour.
Jones (1991) described moral intensity (MI) as “the extent of issue-related moral
imperative in a situation” (p. 372). He proposed the MI construct to explain the four
stages that describes how an organisation engages in moral behaviour, from recognition
of the issue, through to making a judgement about the issue and establishing moral
intent, to engaging in moral behaviour. MI is measured by six characteristics:
magnitude of consequences (MC), social consensus (SC), probability of effect (PE),
temporal immediacy (TI), proximity (PX) and concentration of effect (CE).
Tanner and Kast (2003) demonstrated that a feeling of moral obligation is a powerful
motivator of environmental behaviour, and Singhapakdi et al. (1996) and Paolillo
(2002) concluded that the ethical decision-making process is influenced by the moral
intensity of the situation. Moral intensity has been included in the theoretical
frameworks for this study as it has been suggested that there is the need for the
inclusion of “moral considerations” in studies of ethical behaviour and for the
“inclusion of appropriate measures of this factor in empirical studies” (Sparks &
4.6.5 137BMoral intensity
129
Shepherd 1992, p. 397). As such, it is expected that the inclusion of moral intensity in
this study will act as a “conceptual bridge” (Routhe, Jones & Feldman 2005) by linking
this construct with existing attitude-behaviour theory
Moral intensity is measured in order to examine the following research objectives:
RO5: To what extent does consumers’ moral intensity affect their likely behavioural
intention (LBI)?
RO10: To what extent does consumers’ moral intensity affect their lifestyle behaviour?
RO15: To what extent does consumers’ moral intensity affect their capital behaviour?
To understand the influence that moral intensity has on the behavioural constructs, the
following hypotheses are developed – one for each behavioural construct:
H5: Moral intensity has a positive influence on likely behavioural intention (LBI).
H10: Moral intensity has a positive influence on lifestyle behaviour.
H15: Moral intensity has a positive influence on capital behaviour.
Behavioural intention is the cognitive representation of readiness to perform a given
behaviour (Routhe, Jones & Feldman 2005). Models such as the TRA and TPB
illustrate that behavioural intention is influenced by beliefs regarding positive outcomes
and social approval. Behavioural intention is a latent construct that has been measured
in many ways depending on the context of the study. For example, Routhe et al. (2005)
examined the likelihood to support building a new dam, and Hagger and Chatzisarantis
(2006) studied the likelihood of buying a magazine.
4.7 52BMeasuring sustainable behaviour and intention
130
Previous studies have measured behavioural intention in two ways: by asking about the
likelihood to do behaviours in the future using a dichotomous (yes/no) measurement
(Hagger & Chatzisarantis 2006; Kraft et al. 2005) and by measuring likelihood to
perform behaviours using a Likert scale from “very likely” to “not at all likely” (Kraft et
al. 2005; Shaw, Shiu & Clarke 2000). They have also discussed the importance of
measuring examples of past behaviours in order to understand their relationship with
future behavioural intention (Ouellette & Wood 1998).
For this research study, there are three constructs that measure behavioural intention and
two that measure past behaviours, which are called “behaviours”. The three intention
constructs have been labelled “likely behavioural intention” (LBI), “lifestyle intention”
and “capital intention”. The two behaviour constructs have been labelled “lifestyle
behaviour” and “capital behaviour”. While LBI is measured using a Likert scale, the
capital and lifestyle constructs are measured by asking respondents to say which
behaviours they have done or intend to do, using dichotomous questions. The lifestyle
and capital constructs are then derived as a “computed” construct that is calculated by
adding the number of behaviours that a person has done or intends to do. Details of
these constructs are discussed in the next section.
In chapter 2, it was proposed that actual examples of sustainable behaviours can be
classified into “capital” and “lifestyle” behaviours. Authors such as Ouellette and Wood
(1998) demonstrated that past behaviour can be a predictor of future behaviour; hence
measures of both behavioural intention (in the future) and past behaviours
(“behaviours”) are included in this study.
For this research study, capital and lifestyle “behaviours” are measured by asking which
behaviours respondents have done in the past. Capital behaviours are measured by
asking about which behaviours or products have been already done or adopted, and
4.7.1 138BCapital and lifestyle behaviour and intention
131
lifestyle behaviours by asking about which behaviours have been done in the last two
weeks.
Capital intention is measured by asking respondents which behaviours they intend to do
in the next two years, and lifestyle intention by asking which behaviours respondents
intend to do in the next two weeks. These time periods are based on the work of Kraft et
al. (2005) and Hagger and Chatzisarantis (2006) and these measures are discussed in
more detail in chapter 5.
To understand the influence that past behaviours have on behavioural intention, the
following hypotheses are developed:
H16: Lifestyle behaviour is a predictor of lifestyle behavioural intention.
H17: Capital behaviour is a predictor of capital behavioural intention.
Authors such as (Shaw & Shiu 2003; Shaw, Shiu & Clarke 2000), Laroche et al. (2001),
Ajzen (2002), Kraft et al. (2005), Hagger and Chatzisarantis (2006), Wall et al. (2007)
and Chedzoy and Burden (2007) measured likelihood to perform the behaviours, using a
Likert scale from “very likely” to “not at all likely”. For example, Shaw and associates
measured the likelihood to purchase fair trade products.
Different studies have used different measures of behavioural intention. For example,
Kraft et al. (2005) measured likelihood to engage in behaviours in the home and away
from home, and Bennett et al. (2002) and Laroche et al. (2001) measured likelihood of
buying products even if they cost more and likelihood of paying a higher price for
products. It is the combination of these four statements that has led to the development
of a latent construct which has been labelled “Likely behavioural intention” (LBI) for
this research study.
4.7.2 139BLikely behavioural intention (LBI)
132
Overall, in this study there are four research questions, 17 research objectives and 17
research hypotheses. Table 4.2 summarises the research objectives (ROs) and
hypotheses.
Table 4.2 Summary of research objectives and hypotheses Research objectives
Research hypotheses
RO1: To what extent do consumers’ attitudes affect their likely behavioural intention (LBI)?
H1: Attitudes have a positive influence on likely behavioural intention (LBI).
RO6: To what extent do consumers’ attitudes affect their lifestyle behaviour?
H6: Attitudes have a positive influence on lifestyle behaviour.
RO11: To what extent do consumers’ attitudes affect their capital behaviour?
H11: Attitudes have a positive influence on capital behaviour.
RO2: To what extent does consumers’ perceived behavioural control (PBC) affect their likely behavioural intention (LBI)?
H2: PBC has a positive influence on likely behavioural intention (LBI).
RO7: To what extent does consumers’ perceived behavioural control (PBC) affect their lifestyle behaviour?
H7: PBC has a positive influence on lifestyle behaviour.
RO12: To what extent does consumers’ perceived behavioural control (PBC) affect their capital behaviour?
H12: PBC has a positive influence on capital behaviour.
RO3: To what extent do consumers’ subjective norm/PNM/normative beliefs affect their likely behavioural intention (LBI)?
H3: Subjective norm/PNM/normative beliefs have a positive influence on likely behavioural intention (LBI).
RO8: To what extent do consumers’ subjective norm/PNM/normative beliefs affect their lifestyle behaviour?
H8: Subjective norm/PNM/normative beliefs have a positive influence on lifestyle behaviour.
RO13: To what extent do consumers’ subjective norm/PNM/normative beliefs affect their capital behaviour?
H13: Subjective norm/PNM/normative beliefs have a positive influence on capital behaviour.
RO4: To what extent do consumers’ internal ethics (measured by ethical obligation and self-identity) affect their likely behavioural intention (LBI)?
H4: Internal ethics has a positive influence on likely behavioural intention (LBI).
RO9: To what extent do consumers’ internal ethics (measured by ethical obligation and self-identity) affect their lifestyle behaviour?
H9: Internal ethics has a positive influence on lifestyle behaviour.
RO14: To what extent do consumers’ internal ethics (measured by ethical obligation and self-identity) affect their capital behaviour?
H14: Internal ethics has a positive influence on capital behaviour.
RO5: To what extent does consumers’ moral intensity affect their likely behavioural intention (LBI)?
H5: Moral intensity has a positive influence on likely behavioural intention (LBI).
RO10: To what extent does consumers’ moral intensity affect their lifestyle behaviour?
H10: Moral intensity has a positive influence on lifestyle behaviour.
RO15: To what extent does consumers’ moral intensity affect their capital behaviour?
H15: Moral intensity has a positive influence on capital behaviour.
RO16 What is the effect of lifestyle behaviour on H16: Lifestyle behaviour is a predictor of lifestyle
4.8 53BSummary of research objectives and hypotheses
133
lifestyle behavioural intention? behavioural intention. RO17 What is the effect of capital behaviour on capital behavioural intention?
H17: Capital behaviour is a predictor of capital behavioural intention.
Demographics were also included as control variables in order to understand the third
aim of this study: to understand the effect of control variables on the ability of the
theoretical model to predict sustainable behavioural intention.
A review of the literature has demonstrated that internal factors such as gender, marital
status, the presence of children aged under 18 years, home ownership and where the
person lives can affect issues that relate to the environment and sustainability. Some of
the main findings related to demographic segmentation are summarised below:
Granzin and Olsen (1991) and Laroche et al. (2001) found that there can be
differences in attitudes and environmental behaviours between males and
females.
Granzin and Olsen (1991) found that married persons are more committed to
conservation. Both Brooker (1976) and Granzin and Olsen (1991) demonstrated
that presence of children in a household is a significant determinant of behaviour
with respect to the environment.
Tan (2002) developed an issue-risk judgement (IRJ) model of ethical decision
making that included age, gender, education and income and their relationship to
the Moral Intensity, perceived risks and moral judgements for ethical choices.
Schaper (2002), Granzin and Olsen (1991) and Smith and Oakley (1994) related
education and income (which combine with occupation to form the socio-
4.9 54BDemographic segmentation
134
economic construct) to concern for the environment and the likelihood of
participation in environmental protection activities.
Granzin and Olsen (1991) related home ownership to participation in recycling
activities and commitment to conservation.
McEachern (2008) demonstrated that people living in rural areas had a higher
involvement in the purchase process for fresh meat than urban consumers.
This chapter has discussed the development of the three theoretical frameworks and the
related research questions and hypotheses for this research study.
The overall aim is to examine what drives consumers to engage in sustainable behaviour
and to determine if behaviour is an antecedent to behavioural intention. Based on the
TPB and other studies, the theoretical frameworks describe sustainable behaviour and
intention as determined by five constructs: attitudes, perceived behavioural control
(PBC), subjective norm and PNM and normative beliefs, internal ethics and moral
intensity. The theoretical frameworks also illustrate that there are three latent
behavioural intention constructs and two latent behavioural constructs. These have been
labelled likely behavioural intention (LBI), lifestyle intention and capital intention,
which have been labelled capital behaviour and lifestyle behaviour.
Based on the theoretical frameworks, four research questions have been postulated. The
first is developed to understand the antecedents to likely behavioural intention (LBI),
the second to understand the antecedents to lifestyle behaviour, the third to understand
the antecedents to capital behaviour, and the fourth to understand the effect of past
behaviour on future behaviour.
Based on these questions, 17 research objectives and 17 hypotheses have been outlined
to be examined in detail. As well as examining the constructs in the theoretical
4.10 55BChapter summary
135
frameworks, the literature demonstrates that demographics such as age, gender, marital
status, presence of children, home ownership and where the person lives can affect
behavioural intention and actual behaviour. These variables are also included in this
study to determine their effect on the theoretical frameworks.
The next step is to translate these constructs into quantifiable measures and to develop
the research methodology, which is described in chapter 5.
136
Chapter 5: 4BResearch methodology and design
Having defined the research questions and the hypotheses in chapter 4, the research
design can be planned (Newholm 2007). This chapter describes and justifies the
processes involved in developing and adopting the research methodology and design to
collect the primary data for this study.
The research design for this study is guided by the researcher’s understanding and
beliefs about the nature of reality (ontology) and how knowledge about reality is gained
from within the paradigm (epistemology) (Newholm 2007). The resultant theoretical
frameworks define the paradigm and the “shared framework of assumptions” (Veal
2005, p. 24) within which the research functions. In considering the optimal research
methodology and design for this study, the benefits and limitations of the ontology,
epistemology and the available research methods have been assessed. This includes
consideration about which research methods were most appropriate to enable the
collection of the quantitative data required for the statistical and analytical techniques
that were needed to address the research questions and hypotheses. Included in these
considerations is the need for the research to examine how the existing constructs affect
each other as dependent and independent constructs.
This chapter includes a discussion about the data collection methodologies that were
employed, as well as the ethical considerations. Operationalising the constructs, the
development and testing of the questionnaire and the data analysis processes were
discussed. This chapter concludes with a discussion about issues relating to reliability
and validity. Figure 5.1 provides a roadmap of this chapter.
5.1 56BIntroduction
137
Figure 5.1 Roadmap of chapter 5
Source: Adapted from Perry (1995)
Chapter 5:
Research
methodology
and design
Reliability and validity
The unit of analysis and the sample
Exogenous and endogenous constructs
and demographics
Research methodology decisions
Ethical considerations
Primary data collection and analysis
Demographic questions
Developing the questionnaire and pre-
testing the questionnaire
138
A positivist, deductive approach is the primary focus of the data collection for this
study. This approach has been chosen as the overall aim is to examine what drives
consumers to intend to engage in sustainable behaviours by testing and expanding on
existing models of behaviour. In addition, as the questionnaire for the quantitative data
collection needed to be pre-tested and modified to the sustainable context and for the
Australian sample, depth interviews were also required.
The epistemology for this research study’s quantitative data collection adopts a
positivist approach incorporating a pragmatic ontology. The positivist paradigm focuses
on objective description and explanation and is used to explain the behaviour of
individuals, groups or organisations on the basis of facts and observations that were
usually quantitative (Veal 2005). This paradigm has been adopted as the overall
objective of the research study is to understand the predictive nature of the constructs in
explaining consumers’ behaviours and intention. This is consistent with other research
into ethical and social marketing issues that has often adopted a positivist approach.
A pragmatic post-constructivist ontology is used as it views the truth as a construct of
belief systems in each particular context. This means that multiple realities are distinct
and intangible for individuals founded socially and experientially (Perry et al. 1999).
This ontology is used to understand situations in real world contexts, rather than seeking
an understanding of the antecedents in an artificial or experimental setting or seeking to
identify a universal truth (Schaefer 2005). A hypothetical-deductive quantitative
approach based on “prior logical reasoning” (Veal 2005, p. 26) is appropriate as the
constructs have all been defined in previous research, which means that the research
objectives and hypotheses have been developed prior to starting the data collection.
The paradigmatic issues and the research approach are summarised in Table 5.1.
5.2 57BResearch methodology decisions
139
Table 5.1 Summary of the paradigmatic issues and the research approach
Paradigmatic issues Approach adopted
Ontological perspective Post-constructivist Epistemology Positivist using quantitative research Approach Non-experimental Hypothetical – Deductive Mathematical using quantitative (numerical) surveys, multivariate
analysis and SEM
The next section describes the unit of analysis and the sample size for the research
study.
The unit of analysis is an integral consideration for this study as it is a defining factor
for the development of the research process. Nardi (2007) concurs that decisions about
data collection, sample size and methodology are all influenced by the unit of analysis
which constitutes the primary empirical object, individual or group under investigation.
As a means of advancing academic knowledge about attitudes, influences and
behaviours with respect to sustainable behavioural intention, obtaining responses from a
sample of the Australian population is important. The unit of analysis for this study is
consumers aged 18 years and over in metropolitan, regional and rural areas.
Deciding on the sample size was largely determined by understanding the number of
cases required for effective statistical analysis of the data. As the population for the
survey is all Australians aged 18 and older, a large sample size is possible. For this
study and due to the sample size requirements for running a SEM, a total sample of
about 500 is required. This size was decided upon as the total sample needed to be
randomly split into two independent samples for the purposes of the analysis and both
needed to include 200 or more respondents (Cunningham 2008).
The “calibration sample” is required for the Exploratory Factor Analysis (EFA) and
“validation sample” is required for the Confirmatory Factor Analysis (CFA) and the
5.3 58BThe unit of analysis and the sample
140
SEM. For this study, the calibration sample is 200 respondents and the validation
sample is 311 respondents.
The larger sample size for the CFA (N=300) allows for greater confidence and accuracy
in the reporting of the research findings by reducing the margin of error and increasing
the confidence limits. Reviewing tables that determine the optimal sample size, where
the proportion of the parameter in the population is assumed to be over 85% or under
15% (Zikmund 1997) reveals that a sample of 311 respondents would allow for a
reliability of ± 5% points. Cunningham (2008) also recommends that the ratio of the
number of participants to the number of “parameters” under investigation be in the
order of 20:1 (while also suggesting that 10:1 can be sufficient). In this case, there were
nine parameters or constructs that need to be measured, and a sample of 300 is more
than adequate.
The research study has been framed according to Swinburne University of
Technology’s code of ethics, as discussed in the next section.
The importance of adhering to Swinburne University’s ethical code has been noted, and
details of the study and the data collection procedures have been provided to Swinburne
University’s ethics committee. This includes details of how the research study addresses
the required ethical procedures before and during the data collection, as well as in the
subsequent reporting of the research findings and the data storage.
Ethical considerations require respect for the individual’s right to privacy in all aspects
of the research, including sampling, measuring and analysing the data (Newholm 2007).
This has been achieved as respondents could not be identified due to the anonymity of
the survey questionnaire and the consequent anonymity of the final data file.
It was made clear to respondents that agreeing to complete the questionnaire implies
that they have given their informed consent to participate in the survey. They were
5.4 59BEthical considerations
141
informed that the research was for academic purposes, with the findings being used to
develop policies in the future. The following explanation was given in the introduction
to the questionnaire:
“The findings of this research can then be used to understand current issues facing the
community today and to develop policies and procedures that could assist in changing
current practices.”
A copy of the ethics approval letter has been included in appendix 6. Further details of
the guidelines and procedures for human research conducted at Swinburne University of
Technology can be found at: http://www.research.swinburne.edu.au/researchers/ethics/.
The next sections describe how the constructs in the theoretical frameworks have been
operationalised, beginning with the behavioural intention constructs.
The theoretical frameworks reveal that there were three behavioural intention constructs
that were labelled “likely behavioural intention” (LBI), “capital intention” and “lifestyle
intention”. Lifestyle behaviours were defined in this thesis as those that require little or
no capital outlay and relate to the consumer’s lifestyle or usage, while capital
behaviours were defined as those that require a more substantial capital outlay.
The three behavioural intention constructs were measured in two ways. Capital and
lifestyle intention were measured by asking respondents to indicate which behaviours
they have done and intend to do, using a dichotomous question which asked them to say
“yes” or “no” to a list of sustainable behaviours. Their answers were then summed using
the “compute” function in SPSS to calculate the total number of behaviours done. The
LBI construct was measured by asking respondents to indicate how likely they were to
behave in different situations, with their answers being measured using a Likert scale
and summed to form the construct.
5.5 60BThe behaviour and intention constructs
142
The next section describes the measurement of capital and lifestyle behaviours and
intention in more detail.
Studies by authors such as Laroche et al. (2001), Tan (2002), Shaw and Shiu (2003),
Spaargaren (2003), (Gilg, Barr & Ford 2005) and Jackson (2005) have included many
examples of sustainable behaviours, ranging from those that require a capital outlay
such as installing double-glazing and water efficient shower heads to those that require
a change of lifestyle such as recycling waste products and using public transport rather
than driving. These behaviours were defined and labelled as “capital behaviours and
intention” and “lifestyle behaviours and intention” in chapter 2.
Measuring actual examples of behaviours is important for this research study because
there has been little research into the areas of determining, measuring and/or predicting
intention to behave and actual behaviour in “real world” ethical and sustainable decision
situations. Much research in this context measured behaviours that could be used to
address a hypothetical ethical situation (for example, Tan (2002)) and others were based
on the conceptual theories of sustainable behaviours (Solymossy & Masters 2002; Zabel
2005). Others have described that it is the varying intensity of issues or behaviours that
can affect the stages of the ethical decision-making process (Chia & Mee 2000;
Fritzsche & Becker 1983; Jones 1991). In consideration of this, the behaviours that were
included in the questionnaire include a range of sustainable behaviours from those that
have little consequence, to those that have more severe consequences in terms of their
adoption, either because of the effort required or because of their cost.
To measure lifestyle behaviours, this study focuses on past behaviours that relate to
individual consumers in their daily lives, which have been defined by Hagger and
Chatzisarantis (2006) as behaviours that were done in the last two weeks. They also
described behavioural intention as behaviours that the consumer intended to do in the
next two weeks (lifestyle intention) and intended to do or install in the next two years
5.5.1 140BMeasuring capital and lifestyle behaviours and intention
143
(capital intention). Capital behaviour was defined as behaviours that have already been
done or installed.
The discussion begins with a description of how the capital and lifestyle behaviours
were measured in this study; a “Q” denotes the question number used in the final
questionnaire, for example, Q2 refers to question 2.
Authors such as Jackson (2005), Routhe et al. (2005), Voronoff (2005), Laroche et al.
(2001) and Spaargaren (2003) have included many examples of the kinds of behaviours
that can be measured in studies about sustainable behaviours. Using the classification
for sustainable behaviours that is proposed in chapter 2 and based on Spaargaren’s
(2003) Social practices model, the capital behaviours measured in this study were those
related to “housing and sustainability at home”. Those included in the questionnaire
were:
“Double-glazing, dripper system in the garden, dual flush toilets, energy efficient
lighting, front loader washing machine, rain water tank(s), recycling/grey water system,
solar hot water or solar electricity panels or solar heating and water efficient shower
heads.”
Actual examples of capital behaviours were measured in Q2 and capital intention was
measured in Q3. These were defined as behaviours that have already been done (capital
behaviours) and that they intend to do or install in the next two years (capital intention).
Based on the same research as for Q2 and Q3, authors such as Jackson (2005), Routhe
et al. (2005), Voronoff (2005) and Laroche et al. (2001) discussed examples of lifestyle
5.5.2 141BCapital intention
5.5.3 142BLifestyle intention
144
behaviours that can be measured in research studies. The lifestyle behaviours that were
measured in this study were those related to “housing and sustainability at home”, “food
and shopping”, “transport” and “actions”. Those included in the questionnaire were:
“Try to save water; use energy efficient appliances; lobby or take direct action about
an issue or brand or product; recycle household wastes, e.g. compost, newspapers,
bottles; think about reducing my greenhouse emissions; turn off lights/electrical goods
that are not necessary; use public transport rather than driving; have a shower for
more than 4 minutes; buy free range or organic products or fair trade products; buy or
do something positive to encourage sustainable behaviour; use non-phosphate
detergents; restrict my use of plastic bags when shopping; try to reduce what I buy and
use.”
Actual examples of lifestyle behaviours were measured in Q4 by asking about
behaviours done in the last two weeks and lifestyle intention was measured in Q5 by
asking respondents what they intend to do in the next two weeks.
Shaw et al. (2000), Shaw and Shiu (2003), Ajzen (2002), Kraft et al. (2005), Bennett et
al. (2002), Kraft et al. (2005), Hagger and Chatzisarantis (2006), Wall et al. (2007) and
Chedzoy and Burden (2007) discuss that behavioural intention can be measured by
asking respondents how likely they were to engage in behaviours in different situations,
using a Likert scale to record their answers.
As this research study is designed to measure sustainable behavioural intention, the
statements from the literature were modified to be applicable to the sustainable context.
For example, Kraft et al. (2005) measured likelihood to engage in recycling drink
containers and exercising and Bennett et al. (2002) measured likelihood of paying a
premium for locally killed meat.
5.5.4 143BLikely behavioural intention (LBI)
145
In this study, LBI was measured using four statements. To match its context,
respondents were asked about their likelihood to perform sustainable behaviours in the
home and away from home, Hence, the following two questions were included:
“How likely are you to engage in sustainable behaviours in the home?”
“How likely are you to engage in sustainable behaviours away from home?”
Likelihood of paying a higher price for sustainable products and likelihood of buying
sustainable products even if they cost more (Bennett, Anderson & Blaney 2002;
Laroche, Bergeron & Barbaro-Forleo 2001) have also been modified. They were
measured by asking the following two questions:
“How likely are you to pay a higher price for sustainable products?”
“When choosing between alternatives, how likely are you to choose the product or
alternative that is sustainable, even if it costs more?”
It is the combination of the four previously mentioned statements that have been
measured on a 7-point Likert scale from agree strongly to disagree strongly that has led
to the development of the LBI latent construct.
This section describes the six latent exogenous constructs that were measured in this
study. These were attitudes, PBC, subjective norm, PNM, internal ethics and moral
intensity. Behavioural beliefs and normative beliefs are also discussed, as they were the
antecedents to attitudes and subjective norm, respectively.
In the theoretical frameworks, PNM and subjective norm (and its antecedent normative
beliefs) have been combined to form the one construct. However, as this section gives
5.6 61BLatent exogenous constructs
146
the background to the development of the statements to measure the constructs, PNM,
subjective norm and normative beliefs were treated separately in this discussion.
While there were many authors who measured attitudes, Laroche et al. (2001)
demonstrated that attitudes with respect to the environment and recycling can be
measured by grouping the statements into three categories:
Severity of environmental problems (five statements)
Importance of recycling (three statements)
Inconvenience of being environmentally friendly (two statements).
Adapting the statements used in Laroche et al.’s. (2001) study to the sustainable context
resulted in the following statements used in this study. All were measured using a 7-
point Likert scale from strongly agree to strongly disagree and were asked in Q6.
Severity of environmental problems
“In our country, we have so much electricity and water that we do not have to worry
about conservation”
“Since we live in such a large country, any pollution that we create is easily spread out
and therefore of no concern to me”
“With so much water in this country, I don’t see why people are worried about leaking
taps and flushing toilets”
“Our country has so many trees that there is no need to recycle paper”
5.6.1 144BAttitudes
147
“The earth is a closed system where everything eventually returns to normal, so I see no
need to worry about its present state”
Importance of recycling
“Recycling will reduce pollution”
“Recycling is important to save natural resources’
“Recycling will save land that would be used for landfill”
Inconvenience of being environmentally friendly
“Keeping separate piles of rubbish for recycling is too much trouble”
“Trying to control pollution is much more trouble than it is worth”
Routhe et al. (2005), Ajzen (1988), Ajzen and Fishbein (1980), Sparks et al. (1995) and
Shaw et al. (2000, 2003) measured behavioural beliefs (also called “beliefs about
outcomes”), using a Likert scale from strongly agree to strongly disagree. Based on
their studies, the following statements have been adapted to the sustainable context and
were used to measure behavioural beliefs in this study:
The question asked was: “If we do not adopt a sustainable lifestyle this will…
“Damage the environment for future generations”
“Increase the cost of water and electricity”
“Have no effect on the way we live” (this has been reversed in the analysis)
5.6.2 145BBehavioural beliefs
148
Due to recent discussion in the media about climate change, the following statement has
been added to the behavioural beliefs construct:
“Result in climate change”
Ajzen (1985), Sparks and Shepherd (1992), Malhotra and Miller (1998), Shaw et al.
(2000, 2003), Carson et al. (2004), Kraft et al. (2005), Hagger and Chatzisarantis (2006)
and Wall et al. (2007) all included a description of how to measure perceived
behavioural control (PBC).
A more recent approach by Wall, Devine-Wright & Mill (2007) proposes that PBC can
be measured using four statements which have been appropriately adapted to the
sustainable context:
“It would be difficult for me to adopt a sustainable lifestyle”
“If I wanted to, I would not have problems in adopting a sustainable lifestyle”
“I have full control over adopting a sustainable lifestyle”
“It is completely up to me whether or not I adopt a sustainable lifestyle”
5.6.3 146BPerceived behavioural control (PBC)
149
Based on the studies by Shaw et al. (2000, 2003) and Sparks and Shepherd (1992), the
following statements have been modified to the sustainable context to measure control
beliefs. This construct is measured using a dichotomous question (yes/no).
“Which, if any, of the following affect whether or not you adopt a sustainable lifestyle?”
“The availability of sustainable products”
“The cost of sustainable products”
“The amount of information available about sustainable products”
“The quality of sustainable products”
Shaw et al. (2000, 2003), Routhe et al. (2005), Kraft et al. (2005), Hagger and
Chatzisarantis (2006) and Wall et al. (2007) used a “strongly agree” to “strongly
disagree” Likert scale to measure subjective norm. For this study, the following single
statement is used:
“Most people who are important to me think I should adopt a sustainable lifestyle”.
5.6.4 147BControl beliefs
5.6.5 148BSubjective norm
150
Ajzen (1988), Shaw et al. (2000, 2003) and Routhe et al. (2005) measured normative
beliefs using a Likert scale from strongly agree to strongly disagree. The following
statements were used in this research study.
“My close friends think that I should live sustainably”
“My close family members think that I should live sustainably”
The statements measuring personal normative motives have been adapted from the
study by Wall et al. (2007). The following statements were included:
“I feel personally responsible for helping to protect the environment”
“I feel morally obliged to take measures to help to protect the environment”
Internal ethics is a latent variable that has been described by Shaw et al. (2000, 2003). It
comprised two constructs, which were labelled “ethical obligation” (EO) and “self-
identity” (SI). Again, statements were measured using a 7-point agree-disagree Likert
scale.
The statement that measures ethical obligation is:
“I feel that I have an ethical obligation to live sustainably”
5.6.6 149BNormative beliefs
5.6.7 150BPersonal-normative motives (PNM)
5.6.8 151BInternal ethics
151
Self-identity was measured by Sparks and Shepherd (1992), Shaw et al. (2000), Shaw
and Shiu (2003) and Hagger and Chatzisarantis (2006). To accommodate green, ethical
and sustainable issues, the statements have been modified, as shown below:
“I think of myself as someone who is very concerned about sustainable issues”
“I think of myself as someone who is very concerned about ethical issues”
“I think of myself as someone who is very concerned about green issues”
Many authors including Singhapakdi et al. (1996), May and Pauli (2002), McMahon
and Harvey (2006) and Vitell and Patwardhan (2008) described how to measure the
latent moral intensity construct, using a range of scenarios. While the process of
developing the moral intensity scenario for this study is described later in this chapter,
the final scenario is shown below.
“The Watson family has no intention of changing their habits to become more
sustainable in their daily living. For example, they refuse to recycle anything or to
reduce their water or energy use or to take reusable bags when shopping. They drive a
large inefficient car, and they continue to water their garden most days. This is despite
water restrictions and the recent introduction of initiatives intended to make people
become more aware of sustainability and protecting the environment.”
Using this scenario and based on the work of authors including Singhapakdi et al.
(1996), May and Pauli (2002) and McMahon and Harvey (2006), the moral intensity
latent construct was measured by asking respondents to rate six statements on a 7-point
Likert scale:
Probability of Effect (PE) “There is a very small likelihood that their behaviour
will actually cause harm to the environment.”
5.6.9 152BMoral intensity
152
Social Consensus (SC) “Most people would agree that their behaviour is
wrong.”
Magnitude of Consequences (MC) “The overall harm (if any) as a result of their
behaviour would be very small.”
Temporal Immediacy (TI) “Their behaviour will not cause harm to the
environment in the immediate future.”
Proximity of Effect (PX) “The harmful effects (if any) of the decision will affect
people that are close to the Watson’s.”
Concentration of Effect (CE) “Their behaviour will harm few, if any, people.”
Table 5.2 summarises the demographic questions included in the questionnaire. As not
all of these demographics have been used in the analysis, the nine that were included
have been marked with an asterisk (*) in the first column. These are described in more
detail in the following sections.
Table 5.2 Demographics included in the questionnaire Included in the analysis
Demographics included in the questionnaire
* Number of people now living in the household in different age groups Type of dwelling they live in Whether own their dwelling, have a mortgage or rent their dwelling Number of bedrooms in their dwelling * Age * Gender * Marital status Whether they are the main income earner in their household Current work status * Occupation * Highest level of education * Personal annual income from all sources before tax Household’s approximate total annual income from all sources before tax * Whether they live in capital city or another area * State or territory they live in
5.7 Demographic questions
153
Carrigan et al. (2004) and Petts et al. (1998) concluded that ethical consumers can
include people in several age ranges, including 35+, to 55+, and the over 65s. They
demonstrated that these age groups were more likely than younger people to “do what
they can” with respect to ethical consumption. The 18-54 year old cohort showed the
greatest levels of support for environmental issues. The age groups used were 18-24,
25-34, 35-44, 45-54, 55-64, 65-74, 75-84 and 85+.
Granzin and Olsen (1991) argued that females are more concerned about the effects of
nuclear energy, while men are more knowledgeable and concerned about acid rain.
Laroche et al. (2001) suggested that females and married people with at least one child
living at home are more likely to be willing to pay more for environmentally products.
Hence, gender is included in the questionnaire.
As well as the study by Laroche et al. (2001) who suggested married people with at
least one child living at home were more likely to be willing to pay more for
environmentally products, Granzin and Olsen (1991) demonstrated that married people
were more committed to conservation.
Using classifications provided by the Australian Bureau of Statistics (ABS), the
following answer places were used to measure marital status: married/de facto,
divorced, widowed and single.
5.7.1 153BAge
5.7.2 154BGender
5.7.3 155BMarital status
154
Granzin and Olsen (1991) and Brooker (1976) demonstrated that the number of children
in a household was positively related to the purchase of ecology-oriented products and
negatively related to willingness to pay more for matters related to an environmental
clean-up. It appears that the number of children can be a significant determinant of
behaviour with respect to the environment.
To measure the number of children in a household, the following question is asked:
“Including yourself, how many people currently live in your household in the following
age groups? Aged 0-17 years; Aged 18-25 years; and Aged 26 or over?”
According to Schaper (2002), higher levels of education and income have been linked to
greater concern for the environment and greater likelihood of participation in
environmental protection activities. The following questions and answer places were
included in this study, based on the ABS classifications.
“What is the highest level of education you have reached?”
The answer places were: primary, some secondary, completed secondary, some TAFE,
some university, completed TAFE/uni degree.
“What is your approximate annual income from all sources before tax?”
The answer places ranged from less than $30,000 to $150,000 or more and were listed
on the questionnaire.
5.7.4 156BNumber of children in household
5.7.5 157BEducation and income
155
The construct that measures socio-economic status combines respondents’ education,
income and occupation. Their occupation was also asked, to allow for calculation of the
socio-economic scale. In order to measure occupation, respondents were asked:
“What is your current occupation?”
The answer places which were based on ABS classifications were: professional, e.g.
doctor, teacher, nurse or manager of a business; other white-collar, e.g. clerical; blue-
collar, e.g. tradesperson; unskilled worker; student; home duties; and not currently
employed.
In order to determine if there were any differences in the answers by where respondents
lived, they were asked two questions:
“Do you live in a capital city, a large regional centre, a small regional centre or a rural
or country area?”
“What state or territory do you live in? NSW, Victoria, Queensland, SA, WA, Tasmania,
ACT, Northern Territory.”
5.7.6 158BOccupation
5.7.7 159BResidence
156
As well as asking questions to measure the demographics of the sample, it was logical
to include questions to understand respondents’ propensity to lead a sustainable lifestyle
and to be environmentally friendly.
In question Q6a, respondents were asked to rate whether they agree or disagree with the
following statement, using a 7-point Likert scale:
“I lead a sustainable lifestyle.”
Spaargaren (2003, p. 689) measured “agreement” about having an environmentally
friendly attitude using a 7-point Likert scale, and the following statement is included:
“I have an environmentally friendly attitude.”
The next section describes the development of the questionnaire.
The questionnaire for the quantitative data collection uses a structured direct-question
method, with the inclusion of one open ended question at the end of the questionnaire to
enable respondents to express their opinions about the issues that were included in the
questionnaire. Structured questions limit the “number of allowable responses”
(Zikmund et al. 2011, p. 134). They were used in this study based on the structured
questions have been defined in previous research studies.
The introduction to the questionnaire defines the context of the study as well as
including instructions for completing the questionnaire. It was important to define
5.7.8 160BOther classification questions
5.8 62BDeveloping the questionnaire
157
“sustainability” and “ethics” in the introduction to the questionnaire. The literature
review revealed that there were many definitions of sustainable consumption by authors
such as McKenzie-Mohr and Smith (1999), Paavola (2001), the OECD (2002),
Voronoff (2005) and Jackson (2005). Consolidating these produced the following
definition which has been included in the introduction to the questionnaire.
“Sustainability refers to protecting the environment for the long-term benefit of the
planet. Sustainability aims to encourage people to recycle items such as organic
materials, paper and bottles; to save water and electricity; to change people’s shopping
and consumption habits, so that economic growth and environmental protection work
together, rather than in competition with each other.”
Sustainability was considered to be both a moral and an ethical issue in this research
study, and in order to clarify the distinction between sustainable and ethical issues,
“ethical issues” were also defined in the introduction to the questionnaire. Based on the
literature review, the following definition was used:
“Ethical issues are broader than sustainable issues. They include concerns for the third
world, the environment and animal issues, and they have led to the development of
products and services such as fair trade products. Fair trade products are those that
are purchased under equitable trading agreements, ensuring a fair price and fair
working conditions for the producers and suppliers of those products. Fair trade coffee
is a good example of this.”
The introduction also included the following introduction to ensure that the survey was
completed by the appropriate person:
“This survey is designed to understand current issues facing Australian consumers in
their daily lives, in particular relating to sustainability and ethical issues. It should be
completed by people aged 18+ who are Australian citizens, and by the person to whom
the email was addressed.”
Where the informant was not available, the following instruction was included:
158
“If this person is not available, then the questionnaire should be completed by a person
of a similar age in the household.”
As all constructs have been defined in previous studies, the first task was to arrange the
questions in a logical order. The opening questions need to be “interesting, simple to
comprehend and easy to answer” (Zikmund et al. 2011, p. 290). Therefore, question 1
asks respondents to nominate the first, second and third most important environmental
and sustainable issues facing Australia today. The answers were based on the literature
and included climate change, lack of water/water shortage, waste/rubbish disposal,
recycling, loss of species and greenhouse emissions/pollution.
These were followed by questions that measure the constructs in the theoretical
frameworks, with the demographic questions being included at the end, as summarised
below.
Question 1 measures important environmental issues facing Australia today;
Questions 2 to 5 measure the capital and lifestyle behaviours and intention;
Question 6 measures the following latent constructs: attitudes, subjective norm,
internal ethics, PNM and PBC;
Question 7 measures likely behavioural intention (LBI);
Question 8 measures control beliefs;
Question 9 measures moral intensity;
The remaining questions measure the demographics.
5.8.1 Order of the questions
159
Adapting the questions to the context of this study involved using “Australian” words
and words that were relevant to the “sustainable” context. For example, in the “attitude”
construct, “Keeping separate piles of trash for recycling is too much trouble” (Laroche,
Bergeron & Barbaro-Forleo 2001) was changed to “Keeping separate piles of rubbish
for recycling is too much trouble”, as the word “trash” is not commonly used in
Australia.
An example of adapting the questions for the sustainable context is demonstrated by
adapting the statements that measure subjective norm. Shaw and associates (2000,
2003) used the following wording: “Most people who are important to me think I should
purchase fair trade grocery products”. For this study, the words “I should purchase fair
trade grocery products” have been changed to “I should live sustainably”.
A summary of the constructs that have been included in the questionnaire and their
sources is included in appendix 7.
Many of the questions used a Likert scale which is described in the next section.
The Likert scale, developed by Rensis Likert, is a widely accepted way of measuring
constructs such as attitudes and intention that is simple and easy to use (Peattie &
Peattie 2009). It was originally developed to allow respondents to indicate whether they
agree or disagree with statements that measure attitudes. More recent adaptations
include Likert scales to measure importance, likelihood to engage in a behaviour and
confidence in behaving in particular ways (Veal 2005). They can include from four to
11 categories, depending on the study (Peattie & Peattie 2009).
5.8.2 161BAdapting the questions
5.8.3 162BLikert scales
160
The literature search revealed differences in the ways that the Likert scales have been
used, most often ranging from 5-point to 9-point scales. For example, Laroche et al.
(2001) used 9-point scales from strongly agree to strongly disagree and Wall et al.
(2007) used 5-point scales from disagree strongly to agree strongly.
Most authors cited in this thesis used a 7-point Likert scale to measure the constructs.
For example, Shaw et al. (2000) and Shaw and Shiu (2003) used a 7-point “likely” to
“unlikely” scale, scored from +3 to -3, Routhe et al. (2005) used a 7-point scale but the
individual scale descriptors were not defined, and McMahon and Harvey (2006) used a
7-point scale from “1” representing “strongly agree”, to “7” representing “strongly
disagree”. Therefore, it has been decided to use a 7-point Likert scale in this study.
Table 5.3 describes the descriptors and numeric codes that were used for the Likert
scales. In this study, they measured both “likelihood” and “agreement”.
Table 5.3 Descriptors used for Likert scales
Numeric code Scale descriptor Likelihood Agreement 7 Very likely Strongly agree 6 Likely Agree 5 Fairly likely Agree slightly 4 Neither likely or unlikely Neither agree nor disagree 3 Not very likely Disagree slightly 2 Not likely Disagree 1 Not at all likely Disagree strongly
Depth interviews have been used to pre-test the questionnaire and to develop the
scenario for the moral intensity construct, as described in the next section.
The pre-test (or pilot test) is a vital component of the research process as it helps to
identify and eliminate potential problems (Newholm 2007). For this study, depth
interviews have been used to pre-test the questionnaire and to develop the moral
intensity scenario. These are “relatively unstructured, extensive interviews” that involve
an interviewer asking questions and probing the participant on their reaction and
5.9 63BPre-testing the questionnaire
161
response to different issues (Zikmund et al. 2011, p. 79). Being qualitative in nature,
depth interviews provided a quick and effective methodology to pre-test and modify the
questionnaire for this research.
In this study, depth interviews were used to ensure that the modifications made to the
wording to adapt the questionnaire to the ethical and sustainable context were in fact the
meanings that have been interpreted by respondents. They also allowed respondents to
provide feedback on layout, grammar, structure and content. The first drafts of the
questionnaire were tested in hard copy, allowing the researcher to identify items that
have been consistently regarded as ambiguous, repetitive or otherwise difficult and to
revise them accordingly (Wall, Devine-Wright & Mill 2007).
Pre-testing was followed by an adaptation of protocol analysis in the debriefing stage to
understand the issues associated with completing the questionnaire and to refine the
moral intensity scenario (see the next section). Protocol analysis is a form of verbal
report that requires respondents to give an account of their thought processes as they
complete the draft of the questionnaire (Rex 2008). This provides the researcher with an
understanding of the ways in which people attend to information stored in short-term
memory when solving problems (Smagorinsky 1998) or, in this case, when completing
a questionnaire. As such, this provides evidence to either change a question that might
be unclear to respondents or to accept the questionnaire if there have been no concerns
with its completion.
Using the method described by Wall et al. (2007), the pre-testing process involved
giving each participant a copy of the questionnaire. The depth interviews were
conducted by the author who had previous expertise in acting as facilitator through her
experience in the marketing research industry. Each participant completed the survey in
the researcher’s presence and was then encouraged to verbalise their reactions and
responses.
5.9.1 163BThe depth interviews
162
By obtaining an immediate reaction to the questionnaire, this allowed for modifications
to be made to improve the wording and sequence of the questions before it was tested
again with the sample. As well as being encouraged to think aloud, respondents were
asked to write down their thoughts with respect to the questionnaire in general and to
identify any problems they encountered in answering the questions. They were also
asked questions to check their understanding of the individual questions as well as their
comprehension of particular areas of the questionnaire that might have needed attention.
These include issues such as:
Question and item structure: was the structure of the questions clear and were
the questions relevant to the structure of the questionnaire?
Were the questions appropriate and relevant to the study?
Were the questions worded appropriately? Were they easily understood?
Did the questionnaire flow in a logical manner?
Final thoughts on the content, form and layout of the questionnaire.
Selection of the sample was based on convenience and availability, with all participants
for the depth interviews being known to the researcher. It was not necessary to be
precise with the selection procedure as the exercise focuses on testing the drafts of the
questionnaire and in developing, modifying and testing the moral intensity scenario.
Participants were invited to take part in the depth interviews and were informed one
week in advance to confirm that they were available. To ensure that proper procedures
were undertaken, permission to conduct the depth interviews was obtained from the
university’s ethics committee, and participants were given a letter of informed consent
that explained the purpose of the exercise.
The participants were fairly representative of the population with a mixture of males
and females, ethnicities, ages and professions. They included people aged between 18
163
and 82 years who were students, business managers, retired, unemployed, lawyers and
blue-collar workers. Two depth interviews were conducted with people who lived
outside Melbourne and the other six with people who live in Melbourne suburbs. This
was done to ensure that the potential diversity of opinions was considered in the
development of the final questionnaire.
The respondents who participated in the depth interviews were:
Male, aged 82, retired, married, lives in large country town in Victoria
Female, aged 23, student, single, lives in Melbourne
Male, aged 18, apprentice, single, lives in Melbourne
Female, aged 35, lawyer, married, lives in Melbourne
Male, aged 48, mechanic, married, lives in Melbourne
Female, aged 42, nurse, married, lives in country Victoria
Male, aged 60, retired, divorced, lives in Melbourne
Female, aged 45, home duties, married, lives in Melbourne.
At the conclusion of the depth interviews, some minor modifications were made to the
content and layout of the questionnaire. For example, the word “faucet” was changed to
“tap” and the order of questions was changed to make the questionnaire flow more
logically. For example, Q6b was separated from Q6a as respondents became weary of
completing questions with the Likert scale. The ease of use of the Likert scales was
demonstrated in the pre-testing as they had no problems understanding the scales and
commented that the categories described were good representations of their opinions
and attitudes.
164
Finally, the author checked to ensure that the items and questions included in the final
questionnaire actually measured the constructs included in the theoretical frameworks.
The depth interviews were used to develop the scenario for the moral intensity
construct, as described in the next section.
In order to develop the scenario for the moral intensity construct, respondents in the
depth interviews were given two tasks. First, they were asked to describe what they do
at home to be “sustainable”. Several clear themes emerged:
Recycling household wastes, such as food scraps, newspapers and bottles
Saving or recycling water
Using recyclable bags when shopping
Driving a fuel efficient car/vehicle
Saving energy/electricity and gas
Other answers such as using window blinds and curtains for insulation.
Respondents were then presented with two drafts of potential moral intensity scenarios
developed by the author and based on the work of McMahon and Harvey (2006).
McMahon and Harvey (2006, p. 385) manipulated the moral intensity of their scenarios
to three conditions: “control, low intensity, high intensity” and randomly assigned the
participants to one scenario.
As the theme of this research was to study sustainable consumer behaviour, it was
decided to focus the scenario on a family’s sustainable behaviour in their daily lives.
5.9.2 164BDeveloping the moral intensity scenario
165
Further, it was decided to test two scenarios for this study in the depth interviews: one
that included a “positive” scenario and one that included a “negative” scenario. The
positive scenario described an “ideal” family who were very sustainable in their daily
lives and the negative scenario described a family who were very wasteful in terms of
their energy and lifestyle consumption. The original scenarios that were tested in the
depth interviews are included in appendix 8.
In order to choose which scenario would be included in the final questionnaire, it was
decided to use the one that generated most comments from the participants. This
response was judged both in terms of the participants’ reaction to the scenario and by
the way that they rated the six moral intensity statements on the 7-point Likert scale.
The author wanted to use a scenario where respondents chose a range of options when
rating the statements, from strongly agree to strongly disagree.
The findings of the depth interviews revealed that the participants generally felt that the
first “positive” scenario was too “perfect”. When asked to rate the six moral intensity
statements on the Likert scale, they used the extremes of the scale for all their ratings.
On the other hand, the second scenario generated angry responses:
“This scenario makes me angry – how could a family live like that!”
“I don’t associate with the Watson family at all – at least they could recycle something,
I mean, how hard is that?”
When rating the “negative” scenario, the participants used more than just the extremes
of the rating scale when they were rating the six moral intensity statements. They also
suggested that a stronger statement was needed at the start which should state that the
Watson family had no intention of changing their behaviour. This would reinforce the
strength second scenario, hence the addition of the following sentence:
“The Watson family has no intention of changing their habits to become more
sustainable in their daily living.”
166
The revised scenario was tested again with the depth interview participants. As well as
adding the introductory sentence, it was adapted to include the option that the family
would drive a “large inefficient car”, based on the findings of the depth interviews. The
final scenario for the questionnaire is shown below:
“The Watson family has no intention of changing their habits to become more
sustainable in their daily living. For example, they refuse to recycle anything or to
reduce their water or energy use or to take reusable bags when shopping. They drive a
large inefficient car, and they continue to water their garden most days. This is despite
water restrictions and the recent introduction of initiatives intended to make people
become more aware of sustainability and protecting the environment.”
Once the questionnaire was finalised, it was uploaded and tested online by two of the
interview participants. The researcher also tested the uploaded questionnaire and
consequently the final questionnaire was made available to the sample. A copy of the
final questionnaire is included in appendix 9.
Consideration was given to using a variety of quantitative research methods to collect
primary data. As the research required a random sample of Australian consumers,
personal interviews or self-completion surveys were appropriate methodologies. The
possible options for conducting personal interviews included using face to face and
telephone (CATI) interviews, and for a self-completion survey the most appropriate
option was to conduct an online survey. Face to face (in the home) and telephone
interview methodologies were not appropriate, because as well as being costly to
administer, they can be quite laborious to arrange and to conduct (Gruber et al. 2008).
An online survey was chosen to collect the data as this is “an effective way of
conducting Internet research whereby groups of people agree to participate in surveys
and exchange their views” (Aaker et al. 2010, p. 176). Increasingly, internet marketing
5.10 64BPrimary data collection
167
research is thriving in “virtually every area of marketing” (Schibrowsky, Peltier & Nill
2007, p. 730). In 2006, it was reported that about one-third of all marketing research in
the United States and Europe was conducted online (Callegaro & Disogra 2008),
accounting for about 17% of the US$7.7 billion spent on marketing research (Roster et
al. 2007). Anecdotal evidence suggests that the acceptance and participation rates for
surveys that use online data collection methods are increasing each year.
The increasing use of online surveys also applies to academic studies. Some examples
include a study reported by Sparrow (2006) who used both online and offline survey
methodologies to compare the results obtained when measuring voting intentions;
Jayawardhena, Wright and Dennis (2007) conducted an online survey to better
understand online shopping experiences and motivations; Gruber et al. (2008) used
online interviews to collect qualitative information about opinion leaders’ usage and
attitudes towards digital music players such as Apple’s iPod; and Park and Feinberg
(2010) conducted an online survey with a sample of consumers who belonged to at least
one virtual community about their online conformity.
The main advantages an online survey include: lower cost than personal interviews;
shorter response time; respondents are free to complete the survey in their own time
with no involvement from a third party such as an interviewer, reducing the likelihood
of socially desirable answers (Gruber et al. 2008); the data is directly loaded onto the
computer, thus saving time and resources (Ilieva, Baron & Healey 2002); respondents
can reveal more personal information than in personal interviews due to visual
anonymity and higher levels of private self-awareness (Gruber et al. 2008); and it can
reach a national or global audience in a reliable and cost effective manner for business
and academic research (Gurney et al. 2004; Schaefer 2005).
The ABS has reported that the incidence of access to the internet is high. In 2005-06,
70% of Australian households had access to a home computer (ABS 2006b). At the end
5.10.1 165BAdvantages and disadvantages of using online surveys
168
of the March quarter in 2007, there were 6.43 million Internet subscribers, comprising
761,000 business and government subscribers and 5.67 million households (ABS 2007).
Further, there has been discussion that the online population is younger and better
educated than the general population (Gurney et al. 2004). This was confirmed by the
ABS which reported that groups with the highest internet access were younger people,
particularly those under 45, people in households with an income of $2,000 or more per
week, people with postgraduate degrees and, consequently, households in the top two
socio-economic quintiles (http://www.ausstats.abs.gov.au/ausstats/free). This is
changing as internet usage increases across all demographic segments. Supporting this,
Fielding (2007) reports that online researchers should no longer be concerned about
leaving out significant segments of the population, and the increasingly wide reach of
the internet for the Australian population means that this is becoming less of an issue.
In order to meet the requirement that the sampling frame for this research included a
representative sample of Australian consumers aged 18 years and older, an online
consumer panel was chosen as its source. Online panels can be classified into pre-
recruited probability-based panels and panels where volunteers elect to opt in and
participate as required (Callegaro & Disogra 2008). The panel for this study comprised
a representative pre-stratified sample of compliant respondents aged 18 and older who
were part of a larger pool of willing panel members available for research studies.
The panel members were recruited using a variety of techniques including internet,
telephone and in-home surveys, as well as via focus groups. Having knowledge of the
sampling frame and the recruitment methodology enables the researcher to measure the
coverage of the study and the non-response error (Callegaro & Disogra 2008).
The panel was managed by an international marketing research company that has
offices in Australia. One of the advantages of using this particular panel was that the
5.10.2 166BThe sampling frame
169
author was able to maintain full control of the development, administration and
monitoring of the survey. There was a requirement by the managing company that panel
members did not participate in more than one online survey a month.
In order to collect the data, the researcher emailed the final questionnaire to the research
company and it was uploaded to the computer with the researcher’s assistance. Once the
formatting and the content of the questionnaire had been checked by the author, it was
distributed to the participants.
Another benefit of using the online panel was that the researcher could stop the study
when the required number of interviews had been completed. This was done when the
final sample size of 511 respondents was achieved. It was decided to include slightly
more than 500 completed questionnaires in the final sample as this would potentially
allow for some to be deleted if they were found to be incomplete or if it was felt that
some respondents had not shown discriminant validity in their answers. For example, if
a respondent “strongly agreed” with all questions that used the Likert scales, they could
be excluded from the final analysis. An initial review of the data file revealed that this
was not necessary and all 511 responses were included in the final data base.
The final anonymous excel data file was sent electronically to the researcher and
converted to a SPSS data file in preparation for the data analysis.
The primary aim of this research study was to test the research questions and
hypotheses using SEM. This required that EFA was conducted using SPSS, followed by
CFA and SEM using AMOS version 18 (Analysis of Moment Structures).
5.10.3 167BThe process for collecting the data
5.11 65BThe data analysis process
170
The data analysis used SPSS (now called PASW) version 18 and AMOS version 18.
Where appropriate, descriptive statistics, Chi-square analysis and t-tests were used to
investigate the research hypotheses. More details of the data analysis processes are
discussed in chapter 6.
The decisions made about the quantitative research are summarised in Table 5.4. This
includes a summary about why the online survey methodology using a panel of
consumers was chosen, how it would benefit the research, the methods of analysis and
the unit of analysis.
Table 5.4 Decisions made about the quantitative research approach Quantitative research approach – Online consumer survey Why this method was chosen
To enable the collection of a large sample (N=511) so that the constructs in the theoretical frameworks can be quantified and to allow for validation of the hypotheses and the research questions to examine the strength of the relationships
How it will benefit the research
The use of an online panel of consumers who have consented to participate in the survey will enable the collection of enough data to ensure that the statistical analysis can produce meaningful findings with a representative sample of Australians aged 18 years and older.
Method of analysis used
Statistical techniques using SPSS (PASW) for the EFA and AMOS for the CFA and the SEM
Unit of analysis Australian consumers aged 18+
Quantitative research studies are exposed to issues of reliability and validity which can
undermine their credibility and therefore it was important to examine the reliability and
validity of a quantitative research study, particularly for academic research. The
interdependence of these issues was also important, as the validity of a study depends
on it being reliable. These issues are discussed in the following sections.
5.12 66BSummary of the research methodology and design
5.13 67BReliability and validity
171
Reliability refers to the extent to which the findings would be the same if the research
was to be repeated at another time or with a different sample of subjects (Veal 2005).
The four factors that can affect reliability are subject or participant error, subject or
participant bias, observer error and observer bias (Schaefer 2005).
In this research study, several stages of reliability testing were implemented. Subject or
participant error refers to the effect that the time of questionnaire distribution may have
on the answers given when completing the questionnaire (Schaefer 2005). In order to
reduce the likelihood of this, participants were able to complete the questionnaire at
their convenience within a particular time frame.
Another way of improving reliability is to adopt or adapt questions used in other
studies, and such an approach was used in this research study. Construct reliability was
used to test the consistency, precision and repeatability of the constructs used in a study
(Schaefer 2005). Reliability analysis “generates reliability statistics for multiple item
additive scales, aiding in the selection of the ‘best’ scale” (Shaw & Shiu 2003, p. 1490).
To measure the internal consistency of the latent constructs, the discriminant analysis
procedure in SPSS was used to calculate the Cronbach alpha scores for the latent
constructs. The higher the Cronbach alpha score, the more reliable the construct is, with
a score of 1.0 representing perfect reliability. A high Cronbach alpha score was
important in this study as the validity of measurement scales (which was tested in the
CFA) depended on it being reliable. For this research study, a Cronbach alpha score of
0.7 and above was preferred.
The use of a 7-point Likert scale with a midpoint that enables respondents to express a
neutral opinion also improved the construct reliability of the study. In other words, this
scaling technique improves the reliability of the measurement in terms of the internal
consistency of the constructs being measured (Veal 2005).
5.13.1 168BReliability
172
Validity refers to the extent to which the data collected truly reflects the phenomena
being studied (Veal 2005). In other words, validity tests the way that the constructs
were operationalised by demonstrating that they measure what they were intended to
measure (Newholm 2007). The validity of a measure or a construct also depends on the
reliability of the measure or construct.
In order to check the validity of a research study, researchers need to ensure that the
interview situation was conducive to careful and thoughtful responses, that respondents
could recall the information accurately and that they were not trying to please the
researcher by giving the “right” answer (Veal 2005). The validation techniques
employed in this study were internal validity, as well as face and construct validity.
Internal validity concerns the likelihood that “any changes in the dependent variable can
only be attributed to manipulation of the independent variable” (Veal 2005, p. 188). In
particular, for this study, “instrumentation” and “selection” could affect the internal
validity of the study. Instrumentation refers to the “inconsistency or unreliability in the
measuring instruments during a study” and the “instrument” refers to the questionnaire
(Veal 2005, p. 189). The feedback from the pre-testing confirmed that such issues
associated with internal validity were not an issue in this study as the measures used
were consistent across all questions in the questionnaire.
“Selection” problems (or the external validity) refer to the “people factors” that can bias
a study (Veal 2005). This data was collected using an online consumer survey with a
consumer panel for the sampling frame. It seems that the increasingly high incidence of
the population with access to the internet means that concerns that might be raised about
the sample being biased towards people with higher socio-economic status is now less
of an issue. The anonymity guaranteed by using this research methodology also
confirms the strength of the external validity of this study.
5.13.2 169BValidity
173
Face or construct validity is concerned with the degree to which the scale items
represent the domain or the universe of the concept under study (Veal 2005) and ensures
that the measures actually measured or represented what they were expected to measure
(Collis & Hussey 2003). This was tested in two ways. Firstly, Podsakoff et al. (2003, p.
886) argued that factors such as ‘comprehension’ and ‘retrieval’ can affect the question
response process and, if not addressed, such issues in the questionnaire response process
were considered to be a form of common method bias. These factors were tested in the
pre-testing of the questionnaire. Secondly, the discriminant validity of the constructs in
a model has been measured by observing if there was a clear distinction between the
items in the pattern and the structure coefficients between the factors tested in the SEM
analysis (Cunningham 2008). As the estimated correlations of the factors that underlie
sets of indicators that were designed to measure different constructs were not
excessively high, then there was evidence for discriminant validity (Cunningham 2008).
This chapter examined the research methodology and design that was implemented to
gather the data for this study. A post-constructivist, positivist approach incorporating a
descriptive research design was used to collect the primary data. This allows for the
specific relationships between the constructs to be quantified to determine which of the
research hypotheses were supported and which were not supported.
Taking into account the data requirements for this study, the most appropriate
methodology to collect the quantitative data was to use an online survey with a sample
of about 500 Australians aged 18 years and older. An online consumer panel was
chosen as the sampling frame for this research, as this allowed for the collection of a
large amount of data from a representative sample. The large sample was required for
the statistical analysis of the data, which included SEM. The study has been framed
according to the code of ethics of Swinburne University of Technology, including
respecting the individual’s right to privacy in all aspects of the research. This was
considered when choosing the sample, as well as in the actual administration of the
5.14 68BChapter summary
174
questionnaire and the analysis of the data. To improve the reliability and validity of the
study, a lengthy pre-test of the questionnaire was undertaken using depth interviews.
The first section of the questionnaire measured important environmental issues facing
Australia today. The next sections measured capital and lifestyle behaviours and
intention, followed by the rating questions that measured the constructs that were
described in the theoretical frameworks. The latent exogenous constructs measured in
this study were attitudes, perceived behavioural control (PBC), subjective norm,
personal normative motives, internal ethics and moral intensity. The final questions
measured the demographics of the sample.
Now that the constructs and the methodology have been described, the analysis of the
research questions and the hypotheses that were identified in the theoretical models are
tested in chapter 6 and related to the theory in chapter 7.
175
Chapter 6: 5BAnalysis and results
This chapter presents the analysis and results of this research study. A reflection and
summary of the findings is presented in chapter 7. The total sample size was 511
Australians aged 18 years and older.
To give a background into the nature of the sample, the chapter begins with a
demographic profile of the survey respondents, which was compared to ABS population
statistics. This was followed by an analysis of the sample’s self-reported assessment of
their attitudes to the environment and living sustainably and a summary of what they
considered to be the most important issues facing Australia today.
Using the “Model development approach”, both exploratory factor analyses (EFA) and
confirmatory factor analyses (CFA) were used to develop and test the theoretical
models. The resultant measurement models were assembled sequentially according to
the theoretical models and analysed using SEM.
The findings which address the research questions and hypotheses outlined in chapter 4
are presented. This chapter concludes with the development of a best-fit model which
explains the relationships between the constructs in the theoretical model. Hypothesis
tests and invariance tests are performed and summarised and finally a chapter summary
is presented.
Figure 6.1 provides a roadmap of this chapter.
6.1 69BIntroduction
176
Figure 6.1 Roadmap of chapter 6
Source: Adapted from Perry (1995)
Attitudes PBC Control beliefs Normative measures Internal ethics Moral intensity Behavioural intention
Chapter 6: Analysis and
results
EFA
and
CFA
Summary of the statements
SEM
Demographic profile
Chapter summary
Capital and lifestyle behaviours
Invariance testing
Best-fit model Testing the hypotheses
Important issues and concern
Response to the questionnaire
177
Once the questionnaire was pre-tested and finalised, it was made available to an
Australia-wide sample of online panel members, in proportion to the population
statistics. The survey was terminated once the required sample size of about 500
participants was achieved.
The response to the questionnaire was very good. First, as “forced answering software”
was used, there is no missing data. Forced answering software means that the
programming of the questionnaire does not allow respondents to skip questions or to
answer incorrectly (Reichheld 2003). Thus, there is no “item non-response error”, and
the “unit non-response” where a respondent does not participate in the survey at all
(Saunders, Lewis & Thornhill 2008) was zero, as only compliant respondents attempted
the questionnaire.
The high level of interest in this research area was confirmed with some respondents
making comments in the open-ended section at the end of the questionnaire which
testified to the popular and sometimes contentious nature of the sustainability concept.
For some, comments suggest that they do not believe in issues such as global warming
and climate change:
We are being sold all these goods regarding global warming that is a pack of lies and
deception.
Climate change is all rubbish. The Earth was here long before we came and it will be
here long after we go. Of course we have to be sensible in our lives but this climate
change thing is just an issue that has been highlighted by the current generations.
6.2 70BResponse to the questionnaire
178
Other comments confirmed an interest in the topic and were related to the costs
associated with changing to a more sustainable lifestyle and the need for the
government to do more:
The costs associated with developing a sustainable lifestyle are somewhat prohibitive
for most at present even with government rebates etc. I believe that most people would
move quicker on achieving sustainability if they could afford it.
The government needs to do something serious about climate change before slugging
the consumer with more revenue raising climate taxes.
While others wanted a chance to voice their opinions on this topic:
I would love to do more of this stuff to help the environment and make others do the
same.
The final sample size included 511 Australians aged 18 years and older, living in capital
cities and other areas. In order to compare the demographics of the sample to the
general population aged 18 years and older, the demographic profile of respondents in
the sample was analysed. This was then compared to the demographic profile of the
population, as described by the ABS data, based on the 2006 census.
The analysis shows that demographic profile of the survey respondents was similar to
the demographic profile of the population. Half were male and half were female and
about two-thirds were married, which was in accordance with the population statistics.
Nearly half were aged between 50 and 69, specifically, 23% were aged 50 to 59 and
23% were aged 60 to 69. In the remainder of the sample, 19% were aged 18 to 39, 19%
were aged 40 to 49 and 16% were aged 70+. Comparing this to ABS statistics revealed
that the age of the sample was slightly older than that of the population.
6.3 71BDemographic profile of respondents
179
About half the sample worked full-time or part-time, and most were in white-collar
positions in accordance with the ABS statistics. 32% were employed full-time, 17%
part-time and 51% were not in paid employment. Compared to ABS population
statistics, a greater percentage were not in the labour force (51% compared to 39%) and
consequently a smaller percentage worked full-time (32% compared to 43%). About
one in five (21%) were employed as a professional, manager or “advanced clerical
worker”, a further 15% in an “other clerical” position and 11% in a blue-collar position.
About three-quarters of the sample lived in a house, with the remainder living in flats or
apartments. Most of the houses were owned and had three or more bedrooms. Most of
the sample lived in NSW, Victoria or Queensland, which was similar to the ABS
population statistics. Table 6.1 compares the percentage of the sample that was in each
of the demographic segments (survey data) with the ABS statistical data.
Table 6.1 Comparison of sample’s demographics and ABS population statistics
Demographic Survey data (%) ABS data (%) Male Female
50 50
49 51
Age 18-39 Age 40-49 Age 50-59 Age 60-69 Age 70+
19 19 23 23 16
40 19 17 11 13
Married Not married
68 32
59 41
Work full-time Work part-time Not in labour force
32 17 51
43 18 39
+Prof/manager/Advanced clerical Other clerical Blue-collar
44 32 24
44 26 30
Live in separate house Live in other dwelling
77 23
79 21
Own dwelling Mortgage Renting
42 28 30
35 35 30
NSW Victoria Queensland SA WA Tasmania ACT Northern Territory
34 21 20 8 12 2 2 1
33 25 20 7 10 2 2 1
Source: Pink (2009), ABS (2006a) + Note that work statistics were based on the total percentage of people who work full-time, part-time, or in a casual position.
180
In the first three questions, respondents were asked to nominate what they thought were
the first, second and third most important environmental and sustainable issues facing
Australia today. “Lack of water/water shortage” was most often ranked “1” indicating
that it was the most important issue facing respondents for over half of the sample. This
was followed by climate change (17%), greenhouse emissions/pollution (13%), loss of
species (7%), waste/rubbish disposal (3%) and recycling (2%).
To understand their top three concerns, the first, second and third most important
rankings were combined and similar patterns emerged. Nearly all of the sample (87%)
ranked lack of water as the first, second or third issue, 60% ranked climate change first,
second or third, 60% rated greenhouse emissions and pollution first, second or third and
40% rated loss of species first, second or third.
Analysis by demographic variables revealed few differences in the issues that were
rated the important issues facing Australia today, but there were significant differences
by state. In Victoria, where there was a severe water shortage at the time, a higher
percentage asserted that lack of water or a water shortage was the most important issue
facing Australia today. Climate change was more important in the less populated states
of SA, Tasmania, the ACT and the Northern Territory. Greenhouse emissions were an
important issue in WA, more so than in the other states. The Pearson Chi-square
confirmed there was a significant association between the state where respondents lived
and the issue that they considered to be the most important (Chi-square = 88.231, df
=42, p<0.001; Cramer’s V = 0.416, p<0.001).
In order to measure their attitudes to sustainability and the environment, respondents
were asked to state their level of agreement using a 7-point Likert scale, with two
6.4 72BImportant issues facing Australia today
6.5 73BConcern for the environment and sustainability
181
statements: “I have an environmentally friendly attitude” and “I lead a sustainable
lifestyle” (Q6). Most agreed that they have an environmentally friendly attitude (84%),
while about half of the sample (52%) agreed that they lead a sustainable lifestyle. These
findings are summarised in Table 6.2.
Table 6.2 Summary of lifestyle attitudes Construct (N = 511) Label %
agree Mean SD Mode
Lifestyle attitudes I lead a sustainable lifestyle Q6A_1 52 4.58 1.29 4 I have an environmentally friendly attitude Q6A_2 84 5.51 1.08 6
T-tests revealed that people aged 50+ years were significantly more likely to agree that
they lead a sustainable lifestyle (p<0.05), whereas females were significantly more
likely than males to have an environmentally friendly attitude (p<0.05). Not
surprisingly, there was a strong correlation between these two statements (p<0.000).
Table 6.3 summarises the mean scores, standard deviation (SD) and the mode for each
of the statements that were used to operationalise the constructs in the theoretical
frameworks. These scores were based on a 7-point Likert scale that ranged from 1 for
strongly disagree to 7 for strongly agree. While the mean score indicated the average
rating, the mode has also been included to reveal the most common rating given to each
of the statements.
Overall, the mode scores indicated that most respondents either “disagreed” (code 2) or
“agreed” (code 6) with the statements. Few gave the extreme answers of strongly agree
(code 7) or strongly disagree (code 1). Statements with a mode of “6” and a similar
mean score indicated that most respondents agreed that they had an environmentally
friendly attitude, appreciated the benefits of recycling, had control over what they did
with respect to the environment and sustainability and felt personally responsible for
protecting the environment. Most also agreed that they needed to adopt a sustainable
lifestyle to protect the environment.
6.6 74BSummary of the statements included in the constructs
182
The exceptions were the five statements that related to the “severity” of environmental
issues which had a mode of “1” and a similar mean score, meaning that the most
common answer was “disagree strongly”. This represents a general feeling that the
issues measured are severe.
Table 6.3 also includes the label used for each of the statements in the data file.
Table 6.3 Summary of mean, SD and mode for the statements in the study Statements and the latent constructs (N = 511) Label Mean SD Mode Behavioural beliefs: If we do NOT adopt a sustainable lifestyle this will… Damage the environment for future generations Q6B_1 5.78 1.34 6 Increase the cost of water and electricity Q6B_2 5.81 1.27 6 Have no affect on the way we live Q6B_3 2.38 1.44 2 Result in climate change Q6B_4 5.11 1.64 6 Attitudes: severity In our country, we have so much electricity and water that we do not have to worry about conservation
Q6A_5 1.75 1.04 1
Since we live in such a large country, any pollution that we create is easily spread out and therefore of no concern to me
Q6A_6 1.86 1.18 1
With so much water in this country, I don’t see why people are worried about saving water
Q6A_7 1.51 0.91 1
Our country has so many trees that there is no need to recycle paper
Q6A_8 1.57 0.93 1
The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state
Q6A_9 2.00 1.28 1
Attitudes: importance Recycling will reduce pollution Q6C_6 5.79 1.04 6 Recycling is important to save natural resources Q6C_7 6.07 0.90 6 Recycling will save land that would be used for landfill/rubbish
Q6C_8 5.98 0.96 6
Attitudes: inconvenience Keeping separate piles of rubbish for recycling is too much trouble
Q6C_9 2.13 1.25 2
Trying to control pollution is much more trouble than it is worth
Q6C_10 2.14 1.23 2
PBC It would be difficult for me to adopt a sustainable lifestyle Q6AA_1
0 3.42 1.41 4
If I wanted to, I would not have problems in adopting a sustainable lifestyle
Q6AA_11
4.68 1.36 4
I have full control over whether or not I adopt a sustainable lifestyle
Q6AA_12
4.87 1.44 6
It is completely up to me whether or not I adopt a sustainable lifestyle
Q6AA_13
5.05 1.46 6
Control beliefs: Which, if any, of the following affect whether or not you adopt a sustainable lifestyle? The availability of sustainable products Q8_1 69% The cost of sustainable products Q8_2 87% The amount of information available about sustainable Q8_3 62%
183
products The quality of sustainable products Q8_4 76% Normative beliefs My close friends think that I should live sustainably 6AA_16 3.87 1.30 4 My close family members think that I should live sustainably 6AA_17 3.95 1.35 4 Subjective norm Most people who are important to me think I should adopt a sustainable lifestyle
Q6C_1 4.05 1.31 4
Personal normative motives: PNM I feel personally responsible for helping to protect the environment
Q6AA_18
5.01 1.38 6
I feel morally obliged to take measures to help to protect the environment
Q6AA_19
5.31 1.24 6
Ethical obligation I feel that I have an ethical obligation to live sustainably Q6C_2 5.13 1.24 6 Self-identity I think of myself as someone who is very concerned about sustainable issues.
Q6C_3 5.02 1.23 5
I think of myself as someone who is very concerned about ethical issues.
Q6C_4 5.28 1.20 6
I think of myself as someone who is very concerned about green issues.
Q6C_5 4.97 1.29 6
Moral intensity The overall harm (if any) as a result of their behaviour would be very small (MC)
Q9_3 2.91 1.55 2
Their behaviour will not cause harm to the environment in the immediate future (TI)
Q9_4 2.71 1.53 2
Their behaviour will harm few, if any people (CE) Q9_6 2.78 1.46 2 Likely behavioural intention (LBI) How likely are you to engage in sustainable behaviours in the home?
Q7_1 5.27 1.13 5
How likely are you to engage in sustainable behaviours away from home?
Q7_2 5.12 1.20 5
When you are buying something or choosing between alternatives, how likely are you to choose the product or alternative that is more sustainable, even if it costs more?
Q7_5 4.60 1.36 5
How likely are you to pay a higher price for sustainable products?
Q7_8 4.30 1.45 5
Respondents were asked to nominate the capital and lifestyle behaviours that they have
done, as well as those they intend to do in questions 2, 3, 4 and 5.
6.7 75BSummary of the capital and lifestyle behaviour constructs
184
Table 6.4 summarises the percentage who now have the capital items installed (capital
behaviour) and the percentage who intend to do or install the items in the next two years
(capital intention). These percentages were based on a dichotomous (yes/no) scale
which asked the sample to nominate which behaviours they had done or intended to do.
The table demonstrates that energy efficient lighting, dual flush toilets and water
efficient shower heads were most likely to be already installed, while few respondents
had double-glazing or solar systems.
Table 6.4 Summary of capital behaviours and intention Capital behaviours and intention
Behaviour: Now have installed (%)
Intention: Intend to do/ install in next two years (%)
Energy efficient lighting 82 9 Dual flush toilets 78 8 Water efficient shower heads 68 12 Rain water tank(s) 31 27 Front loader washing machine 29 13 Dripper system in the garden 19 16 Recycling/grey water system 19 15 Solar hot water or solar electricity panels or solar heating 11 23 Double-glazing 4 4 None of these 4 36
In summary, the capital behaviours can be divided into three categories:
1. Those that have already been done (with over two thirds of the sample saying
that they had already installed them): energy efficient lighting, dual flush toilets, and
water efficient shower heads.
2. Those that will likely be done in the future (with over 15% of the sample saying
that they intended to install them): rain water tank(s), front loader washing machine,
dripper system in the garden, recycling or grey water system, and solar hot water or
solar electricity panels or solar heating.
3. Behaviours that are unlikely to occur, which applied to double glazing windows
and doors, where only 4% of the sample had already installed double glazing in their
house, and 4% intending to install double glazing in the future.
185
Table 6.5 summarises the percentage of respondents who have done the lifestyle items
in the last two weeks (lifestyle past behaviour) and the percentage who intend to do or
install the items in the next two weeks (lifestyle intention). It demonstrates that most
respondents had recycled household wastes, turned off lights and electrical goods that
were not necessary and tried to save water, but few had lobbied or taken direct action
about an issue, brand or product.
Table 6.5 Summary of lifestyle behaviours and intention Lifestyle behaviours and intention
Behaviour: Done in last two weeks (%)
Intention: Intend to do in next two weeks (%)
Recycled household wastes, e.g. Compost, newspapers, bottles 91 85 Turned off lights/electrical goods that are not necessary 91 85 Tried to save water 82 80 Restricted my use of plastic bags when shopping 70 74 Used energy efficient appliances 66 67 Tried to reduce what I buy and use 49 59 Thought about reducing my greenhouse emissions 23 38 Bought or did something positive to encourage sustainable behaviour 11 26 Had a shower for more than four minutes (Reversed) 36 33 Used non-phosphate detergents 37 42 Bought free range or organic products or fair trade products 31 38 Used public transport rather than driving 21 26 Lobbied or took direct action about an issue or brand or product 3 5 None of these 1 3
Similarly, the lifestyle behaviours can be divided into three categories:
1. Those that have already been done by the majority of the sample, with over two
thirds saying that they had done them in the last two weeks, and/or intended to do them
in the next two weeks: recycled household wastes such as compost, newspapers, bottles;
turned off lights/electrical goods that are not necessary; tried to save water; restricted
my use of plastic bags when shopping; and used energy efficient appliances.
2. Those that will likely be done which have been defined as behaviours where
there were more people who intended to do them in the next two weeks, than the
number who had done them in the last two weeks. These are: used non phosphate
detergents; had a shower for more than four minutes (reversed); bought free range or
organic products or fair trade products; tried to reduce what I buy and use; thought
186
about reducing my green house emissions; bought or done something positive to
encourage sustainable behaviour; and, used public transport rather than driving.
3. Behaviours that are unlikely to occur, which applied to lobbied or taken direct action
about an issue or brand or product’ which was mentioned by very few respondents.
The next section describes the process of splitting the sample of 511 responses to two
independent samples for the purposes of conducting the EFA and the CFA analyses.
As discussed in chapter 5, the “cross-validation strategy” suggests that the final data set
needs to be randomly split before conducting EFA, CFA and SEM analyses. The first
split of the data set is called the calibration data sample and this is used for the EFA,
while the second split is known as the validation sample and is used for the CFA and the
SEM (Reisinger & Mavondo 2006).
To obtain these two independent samples, the total sample of 511 respondents was
randomly split using the “split file” procedure in SPSS to form the two independent data
bases required for the analysis. The calibration sample of 200 respondents was used for
the EFA and the validation sample comprising the remaining 311 cases was used for the
CFA and the SEM. The rationale for choosing these sample sizes was discussed in
chapter 5.
The next sections report the results of the exploratory factor analyses.
Factor analysis was developed by psychologists to identify the latent variables or factors
that may not be apparent in the patterns of correlations of the observed variables in a
data set (Gilg, Barr & Ford 2005). For this research study, EFA is performed using
6.8 76BSplitting the sample
6.9 77BExploratory factor analysis (EFA)
187
SPSS on the calibration sample. The outcome is to determine the smallest number of
meaningful latent variables or factors that best reproduces the original correlations or
covariances between the larger set of variables (Gilg, Barr & Ford 2005). The ideal or
expected outcome is that the pattern of factor loadings exhibits a simple structure,
meaning that “each item loads strongly on only one factor and has near-zero loadings on
all other factors” (Swisher, Beckstead & Bebeau 2004, p. 787).
In performing the EFA, each construct in the theoretical model was analysed using
Principal Axis Factoring (PAF). In general PAF gives the best results, depending on
whether your data are generally normally-distributed or significantly non-normal,
respectively (Costello & Osborne 2005). Direct Oblimin with Kaiser Normalisation
was used for the rotation. A Direct Oblimin rotation assumes that the factors may be
correlated, and it is a common procedure in the social sciences where a degree of
correlation among factors is often expected. Using an orthogonal rotation results in the
loss of valuable information if the factors are correlated, therefore, using an oblique
rotation theoretically should generate a more accurate, and perhaps more reproducible
solution (Costello & Osborne 2005). The Kaiser criterion (Kaiser Normalisation) is
essentially a rule of thumb for omitting the least important factors from the analysis; in
this case, those with eigen values less than 1.0 were omitted.
Table 6.6 depicts a summary of the EFA analyses that were performed, as well as the
question labels and the latent construct names that are used. It demonstrates that a total
of nine EFA’s were performed and that each included between two and 13 items or
statements. The word “items” has been used to refer to the capital and lifestyle variables
that were based on dichotomous items, while the remaining statements were rated using
7-point Likert scales.
The first EFA was performed for the attitude construct. Attitudes were measured by
three constructs: “severity of problems”, “importance of recycling” and the
“inconvenience of being environmentally friendly”. These constructs were measured by
between two and five statements. Behavioural beliefs, PBC and control beliefs were
each measured by four statements, “normative beliefs/ PNM/ subjective norm” by five
statements and moral intensity by six statements.
188
There are five endogenous constructs that were measured in the EFA analyses. Capital
behaviour and intention were each measured by nine behaviours, and lifestyle behaviour
and intention were each measured by 13 behaviours. Likely behavioural intention was
measured by four statements.
Table 6.6 Summary of items used for the EFA analyses EFA No.
No. of items/ statements
Question labels in data file
Latent construct name
Attitudes and behavioural beliefs 1 5 Q6A_5 to Q6A_9 Severity of problems
3 Q6C_6 to Q6C_8 Importance of recycling 2 Q6C_9 to Q6C_10 Inconvenience of being environmentally
friendly 2 4 Q6B_1 to Q6B_4 Behavioural beliefs Other latent exogenous constructs 3 4 Q6AA_10 to Q6AA_13 PBC 4 4 Q8_1 to Q8_4 Control beliefs 5 5 Q6AA_16 to 6AA_19, 6C_1 Normative beliefs, PNM, subjective norm 6 4 Q6C_2 to Q6C_5 Internal ethics: ethical obligation and self-
identity 7 6 Q9A_1 to Q9A_6 Moral intensity Endogenous constructs: Behavioural intention and past behaviours Lifestyle and capital behavioural intention 8 9 Q2.1 to Q2.9 Capital behaviour
9 Q3.1 to Q3.9 Capital intention 13 Q4.1 to Q4.13 Lifestyle behaviour 13 Q5.1 to Q5.13 Lifestyle intention
Likely behavioural intention (LBI) 9 4 Q7.1, 7.2, 7.5, 7.8 Likely behavioural intention
A total of 10 statements were used to rate attitudes based on a 7-point Likert scale from
strongly agree to strongly disagree. Attitudes were measured by three latent constructs
called “severity of problems”, “importance of recycling” and “inconvenience of being
environmentally friendly”. EFA 1 revealed that the two statements that measured the
construct labelled as the “inconvenience” of being environmentally friendly loaded
weakly and they were deleted from the analysis. These statements were “Keeping
6.10 78BEFA for Attitudes
189
separate piles of rubbish for recycling is too much trouble” and “Trying to control
pollution is much more trouble than it is worth”.
The resulting pattern matrix suggested a two factor solution, namely that attitudes were
measured by the severity of the problems (statements 6A_5, 6A_6, 6A_7, 6A_8, 6A_9)
and the importance of recycling (statements Q6C_6, Q6C_7, Q6C_8). 62% of the
variance in the attitude construct was explained by these two factors, with strong
loadings on each of the two factors. The Cronbach alpha scores were 0.890 and 0.898
respectively, indicating that these two constructs were reliable measures of attitudes.
This is summarised in Table 6.7.
Table 6.7 Factor solution for the EFA for Attitudes
Statement label
Statements Loading (Pattern)
Correl-ation (structure)
Cron-bach Alpha
% variance
Attitudes: Severity of problems Q6A_5 In our country, we have so much
electricity and water that we do not have to worry about conservation
.924 .860 0.890 51% and 11% = 62% for the attitude construct
Q6A_6 Since we live in such a large country, any pollution that we create is easily spread out and therefore of no concern to me
.800 .786
Q6A_7 With so much water in this country, I don’t see why people are worried about saving water
.809 .762
Q6A_8 Our country has so many trees that there is no need to recycle paper
.716 .776
Q6A_9 The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state
.765 .777
Attitudes: Importance of recycling
Q6C_6 Recycling will reduce pollution .796 .799 0.898
Q6C_7 Recycling is important to save natural resources
.862 .885
Q6C_8 Recycling will save land that would be used for landfill/rubbish
.919 .917
190
Behavioural beliefs are the antecedents to attitudes, and EFA 2 was performed to
examine the behavioural belief statements as they were presented in the survey
instrument (statements Q6B_1, 6B_2, 6B_3 and 6B_4). The EFA revealed a one factor
solution, with a Cronbach alpha value of 0.821 indicating that these statements were
reliable measures of behavioural beliefs. 58% of the variance in behavioural beliefs was
explained by these four statements as shown in Table 6.8.
Table 6.8 Factor solution for the EFA for behavioural beliefs
Statement Label
Statements If we do NOT adopt a sustainable lifestyle this will…
Loading (Pattern)
Cronbach Alpha
% variance
Q6B_1 Damage the environment for future generations .983 0.821
58
Q6B_2 Increase the cost of water and electricity .683
Q6B_3 Have no affect on the way we live (R) .588
Q6B_4 Result in climate change .729
EFA 3 examined the four PBC statements as they were presented in the survey
instrument (statements 6AA_10 to 6AA_13). This EFA generated a one factor solution,
with a Cronbach alpha 0.791 revealing that these statements were reliable measures of
PBC. 50% of the variance in PBC was explained by these four statements. Note that the
scores for the statement “It would be difficult for me to adopt a sustainable lifestyle”
have been reversed (R) for the analysis. These findings are summarised in Table 6.9.
Table 6.9 Factor solution for the EFA for PBC
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
6AA_10 It would be difficult for me to adopt a sustainable lifestyle (R)
.657 0.791
50
6.11 79BEFA for behavioural beliefs
6.12 80BEFA for Perceived behavioural control (PBC)
191
6AA_11 If I wanted to, I would not have problems in adopting a sustainable lifestyle
.613
6AA_12 I have full control over whether or not I adopt a sustainable lifestyle
.862
6AA_13 It is completely up to me whether or not I adopt a sustainable lifestyle
.664
Control beliefs are the antecedents to perceived behavioural control (PBC) and EFA 4
was performed to test the control belief statements as they were presented in the survey
instrument (Q8_1, 8_2, 8_3, 8_4). The output revealed that the loadings for statement
Q8_2 the “cost of sustainable products” was low and it was deleted from the analysis.
The EFA also revealed that this construct was a reliable measurement, with a Cronbach
alpha of 0.708, and the loadings for the three statements were relatively strong. Only
35% of the variance in control beliefs was explained by these three measures, as shown
in Table 6.10.
Table 6.10 Factor solution for EFA for control beliefs
Statem-ent Label
Measures Loading (Pattern)
Cronbach Alpha
% variance
Q8_1 The availability of sustainable products
.708 0.708 35
Q8_3 The amount of information available about sustainable products
.539
Q8_4 The quality of sustainable products .777
6.13 81BEFA for Control beliefs
192
In this study, there were three normative measures, called normative beliefs, subjective
norm and personal normative motives (PNM). Normative beliefs were measured by two
statements (Q6AA_16, Q6AA_17), subjective norm was measured by one statement
(Q6C_1) and PNM were measured by two statements (Q6AA_18, Q6AA_19). Due to
the small number of measures for these constructs, and in order to provide a meaningful
analysis, the five statements measuring these three normative constructs were combined
for this analysis.
EFA 5 revealed a one factor model with strong loadings on each of the statements. The
Cronbach alpha (0.889) indicates that these five statements were reliable measures. 62%
of the variance in this construct was explained by these five statements, as shown in
Table 6.11.
Table 6.11 EFA for normative beliefs, subjective norm and PNM
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
Q6AA_16 My close friends think that I should live sustainably
.847 0.889
62
Q6AA_17 My close family members think that I should live sustainably
.891
Q6AA_18 I feel personally responsible for helping to protect the environment
.729
Q6AA_19 I feel morally obliged to take measures to help to protect the environment
.694
Q6C_1 Most people who are important to me think I should adopt a sustainable lifestyle
.763
6.14 82BEFA for normative beliefs, subjective norm and PNM
193
According to the literature, internal ethics is a latent constructs that includes measures
of ethical obligation and self-identity. Ethical obligation was measured by one statement
(Q6C_2) and self-identity was measured by three statements (Q6C_3 to Q6C_5).
EFA 6 examined the four internal ethics statements as they were presented in the survey
instrument. The Cronbach alpha score of 0.896 indicates that this was a reliable
measure, the pattern loadings were strong, and 70% of the variance in internal ethics
was explained by these four statements, as shown in Table 6.12.
Table 6.12 Factor solution for the EFA for internal ethics
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
Q6C_2 I feel that I have an ethical obligation to live sustainably
.855 0.896
70
Q6C_3 I think of myself as someone who is very concerned about sustainable issues
.855
Q6C_4 I think of myself as someone who is very concerned about ethical issues.
.714
Q6C_5 I think of myself as someone who is very concerned about green issues.
.865
In order to measure moral intensity, respondents were asked to rate six moral intensity
statements on the 7-point Likert scale from strongly agree to strongly disagree, based on
the scenario that was developed in chapter 5.
EFA 7 was performed on the statements that measured moral intensity (Q9A_1 to
Q9A_6) and the Proximity (PX), Social Consensus (SC) and Probability of effect (PE)
variables were deleted due to low pattern loadings. Therefore, the moral intensity
construct for the scenario presented in this research study was a latent construct with
6.15 83BEFA for Internal ethics
6.16 84BEFA for Moral intensity
194
three reflective indicators, which were Concentration of Effect (CE), Temporal
Immediacy (TI) and Magnitude of Consequences (MC), represented by the statements
Q9A_3, Q9A_4, Q9A_6.
Table 6.13 demonstrates that the loadings were quite high for the three statements, and
the Cronbach alpha (0.719) demonstrates that this is a reliable measure. 46% of the
variance in moral intensity was explained by these three statements.
Table 6.13 Factor solution for the EFA for moral intensity
The next section discusses the capital and lifestyle behaviour and intention constructs
which were measured by asking dichotomous (yes/no) questions.
The first EFA for behaviour and intention examines the constructs that were labelled
“capital behaviour” and “capital intention”, and “lifestyle behaviour” and “lifestyle
intention”.
To measure capital behaviour and intention and lifestyle behaviour and intention,
respondents were shown a list of behaviours and asked to say which of those behaviours
they had done or intended to do. In order to analyse the questions that related to capital
and lifestyle behaviours and intention (questions 2, 3, 4 and 5), computed scores were
calculated using SPSS. Therefore, these scores determine the number of lifestyle and
capital behaviours that respondents had done or intended to do.
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
Q9A_3 The overall harm (if any) as a result of their behaviour would be very small (CE)
.761 0.719
46
Q9A_4 Their behaviour will not cause harm in the immediate future (TI)
.598
Q9A_6 Their behaviour will harm a few, if any people (MC)
.681
6.17 85BEFA for capital and lifestyle behaviour and intention
195
EFA 8 was performed on these four items, and the two constructs that measured capital
behaviour and intention were deleted due to low loadings and low Cronbach alpha
scores. In other words, the ‘high involvement’ behaviours have been removed from this
analysis.
The resulting one factor solution revealed strong loadings for the two lifestyle
constructs, and the high Cronbach alpha value (0.824) demonstrates that these measures
were reliable measures of lifestyle behaviour and intention. The two lifestyle constructs
accounted for 73% of the variance in the lifestyle construct, as summarised in Table
6.14.
Table 6.14 Factor solution for the EFA for lifestyle behaviour and intention
Construct
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
Lifestyle
Q4
Lifestyle behaviour
.852
0.824
73
Q5
Lifestyle intention
.852
The next section discusses the LBI construct which was measured using a 7-point likert
scale.
EFA 9 was performed on the four statements that were used to measure the “likely
behavioural intention” (LBI) construct (statements Q7_1, 7_2, 7_5, 7_8). The analysis
revealed that all four statements measuring likely behavioural intention were internally
reliable measures with a Cronbach alpha score of 0.865, and the pattern loadings were
strong for each statement. These statements accounted for 63% of the variance in the
LBI construct, as shown in Table 6.15.
6.18 86BEFA for likely behavioural intention (LBI)
196
Table 6.15 EFA for likely behavioural intention (LBI)
Statement Label
Statements Loading (Pattern)
Cronbach Alpha
% variance
Q7_1 How likely are you to engage in sustainable behaviours in the home?
.826 0.865
63
Q7_2 How likely are you to engage in sustainable behaviours away from home?
.825
Q7_5 When you are buying something or choosing between alternatives, how likely are you to choose the product or alternative that is more sustainable, even if it costs more?
.810
Q7_8 How likely are you to pay a higher price for sustainable products?
.703
As a result of the exploratory factor analyses, a total of four statements were removed
from the analysis, as well as the capital behaviour and capital intention constructs. Of
the remaining constructs, between 35% and 78% of their variance was explained by the
statements or items that measured them.
Overall, the EFA analyses produced nine statistically reliable constructs with Cronbach
alpha values of at least 0.71, and eight of these had three or more statements measuring
them. The exception was the lifestyle construct which was a computed construct that
was measured by “lifestyle behaviour” and “lifestyle intention”. “Attitudes” which was
influenced by “severity” and “importance” was the only construct that comprised two
factors.
Table 6.16 summarises the outcomes of the EFA analyses. The numbering of the
statements relates to Table 6.6.
6.19 87BSummary of the latent constructs based on the EFA
197
Table 6.16 Summary of the EFA analyses Construct
Number retained
Statements retained
Statements removed
Cron-bach alpha
% variance explained
ATTITUDES Severity Importance Inconvenience
5 3 0
F1: Q6A_5, to Q6A_9 F2: Q6C_6, 6C_7, 6C_8 F3: Q6C_9, 6C_10
0 0 2
0.890 0.898
51 11 NA
(62)
Behavioural beliefs 4 Q6B_1, 6B_2, 6B_3, 6B_4 0 0.821 58 PBC 4 Q6AA_10 to Q6AA_13 0 0.791 50 Control beliefs 4 Q8_1, Q8_3, Q8_4 Q8_2 0.708 35 PNM, norm beliefs, subjective norm
5 Q6AA_16, Q6AA_17, Q6AA_18, Q6AA_19, Q6C_1
0 0.908 78
Internal ethics 4 Q6C_2 to Q6C_5 0 0.896 70 Moral intensity 3 Q9A_3, 9A_4, 9A_6 Q9A_1, 9A_2,
9A_5 0.719 46
Lifestyle intention and behaviour
2 Q4, 5 0 0.824 73
Capital intention and behaviour
2 0 Q2, 3 NA
Likely behavioural intention (LBI)
4 Q7.1, 7.2, 7.5, 7.8 0 0.865 63
Confirmatory factor analysis (CFA) is a general modelling approach that is designed to
test hypotheses about factor structures that have been defined through the EFA analysis.
Described as a “special case of SEM”, CFA can be used to evaluate designs for
construct validation and scale refinement; multi-trait multi-method validation; and
measurement invariance; and “to validate the hypothesised relationships” (Reisinger &
Mavondo 2006, p. 67).
CFA involves developing congeneric measurement models for each of the latent
constructs, which are used to assess the convergent validity of the constructs being
measured (Steenkamp & Van Trijp 1991). Once the model has been determined by the
CFA, it is then tested for consistency with the observed data using SEM (Byrne 2001)
and descriptive fit statistics.
6.20 88BConfirmatory factor analysis (CFA)
198
In a CFA model, no specific directional relationships are assumed between the
constructs, only that they are correlated with one another (Byrne 2001). Unlike EFA, a
CFA is not concerned with discovering a factor structure, but rather it is used to confirm
the existence of the factor structure that was determined by the EFA. As such, CFA
models are often used to examine patterns of interrelationships between constructs, all
of which are measured by their own set of observed indicators and descriptive fit
statistics.
In this study, the CFA was used to test the discriminant validity, covariances,
correlations and loadings of the indicators on the respective factors. In addition,
descriptive fit indices were used to assess the goodness-of-fit of the proposed model
based on the sample for this research study. The indices that were used to test the CFA
analyses were Chi-square, comparative fit index (CFI), goodness of fit (GFI), adjusted
goodness of fit (AGFI), root mean square residual (RMR) and root mean square error of
approximation (RMSEA).
The comparative fit index (CFI) is a measure of how much better the proposed model is
compared to another version (or the baseline) version of the model (Gilg, Barr & Ford
2005) and thus tests its validity. This index is constrained to fall between 0 and 1, where
values close to 1 indicate a model that fits the data well. In general, a CFI of about .95
or above is usually associated with models that provide a reasonable approximation of
the data. The goodness-of-fit index (GFI) is a measure of the proportion of variance and
covariance that the proposed model is able to explain. The adjusted goodness-of-fit
index (AGFI) differs from the GFI as it adjusts for the number of degrees of freedom in
the specified model (Byrne 2001). It is currently viewed that models with a GFI and
AGFI of about .90 or above represent a good approximation of the data.
The Root Mean Square Residual (RMR) is a measure of how well the model represents
the sample variations, and values less than 0.05 are preferred (Gilg, Barr & Ford 2005).
6.20.1 170BDescriptive fit indices
199
The Root Mean Square Error of Approximation (RMSEA) index measures how well the
model would fit the population covariance matrix, if it existed. Byrne (2001) suggests
that a RMSEA value of less than .05 indicates that a model has produced a reasonable
approximation of the data.
For this study, the squared multiple correlations were used as a measure of item
reliability for each of the statements (also called items). Factor score weights give the
weight of impact of each variable on the endogenous variables. Table 6.17 summarises
the descriptive fit statistics that were used to test the hypotheses.
Table 6.17 Descriptive fit statistics used to test the hypotheses Name Abbreviation &
preferred level Comments
Chi-square P > 0.05 P value should be not significant
Computed to test the null hypothesis that the model fits the data well.
Comparative fit index CFI > 0.95 Values between 0.90 and 0.95 indicate a reasonable fit. A value of 1 indicates a perfect fit.
Goodness of fit Adjusted goodness of fit
GFI > 0.95 AGFI >0.95
Values between 0.90 and 0.95 may also indicate a reasonable fit.
Root mean square residual
RMR <0.05 is preferred
Large values for RMR when other indices suggest good fit may indicate outliers in raw data. Values <0.10 indicate a reasonable fit
Root mean square error of approximation
RMSEA < 0.05 Values between 0.05 and 0.08 indicate a reasonable fit
Source: Byrne (2001), Holmes-Smith, Coote and Cunningham (2004), Cunningham (2005), Reisinger and Mavondo (2006)
In this study, a total of eight CFA measurement models were run using AMOS with the
validation sample of 311 respondents. This sample size was large enough to ensure that
derived models were based on substantive as well as statistical conclusions (Gilg, Barr
& Ford 2005).
6.21 89BFindings from the CFA and measurement models
200
The CFA’s that were performed are summarised in Table 6.18. As the CFA’s were
based on the factor structures that were determined by the EFA, the corresponding EFA
has also been included in Table 6.18.
Table 6.18 Summary of the CFA and EFA analyses EFA CFA Latent variable(s)
1 1 Attitudes
1 and 2 2 Attitudes and behavioural beliefs
3 and 4 3 PBC and control beliefs
5 4 Normative beliefs, subjective norm, PNM
6 5 Internal ethics
7 6 Moral intensity
8 7 Lifestyle intention and behaviour
9 8 Likely behavioural intention (LBI)
Using the findings of EFA 1, CFA 1 for attitudes was performed with the five
statements that measured the “severity” construct and the three that measured the
“importance” construct.
Based on this CFA, one statement was deleted from the “severity” construct due to low
loadings and high standardised residual covariances, and this improved the fit of the
measurement model. The statement that was removed was “since we live in such a large
country, any pollution that we create is easily spread out and therefore of no concern to
me” (6A_6). The descriptive fit indices indicated that this model was a good fit to the
data. This was clarified as the RMSEA value included zero, and the RMR demonstrated
that this model was doing a good job of representing sample variations. The GFI and
AGFI indicated that the model represented a good approximation of the data, and the
CFI suggested a well fitting model.
The CFA confirmed that the attitude construct was measured by two independent
constructs. It also revealed that there was a negative relationship between the severity
6.22 90BCFA for attitudes
201
and the importance constructs. This negative relationship was expected as the
statements that measure the severity construct describe the consequences of not caring
about the environment, while the importance statements refer to the importance of
adopting recycling practices. The CFA is shown in Figure 6.2
Figure 6.2 CFA for attitudes
Chi-sq = 18.38 (ns) (df=13), CFI =.996, GFI = .983, AGFI = .964, RMSEA = .037,
RMR = .021
The model demonstrated good discriminant validity, as confirmed by the implied
correlations, and all regression weights were significant, as shown in Table 6.19.
202
Table 6.19 Regression weights for attitudes
In order to test the hypothesis that behavioural beliefs had a positive influence on
attitudes, CFA 2 examined “behavioural beliefs” (which was measured by four
statements) and the two attitude constructs that were labelled “severity” and
“importance”. This CFA was based on the findings of EFA 1 and 2 as well as CFA 1
which was discussed in the previous section.
The initial model was a poor fit to the data with a significant Chi-square value. Further
investigation revealed that the statement labelled Q6B_3 from the “behavioural beliefs”
construct, and Q6A_9 from the “severity” construct needed to be removed due to high
standardised residual covariances. This was not surprising given that these statements
loaded weakly in their respective EFA’s.
The CFA was re-run and the statistics other than the Chi-square revealed that the
resulting measurement model was a good fit to the data. The total effect of behavioural
beliefs on attitudes was 0.71 and the loading (standardised weights) of attitudes on
“behavioural beliefs” was 0.51. The loading of “severity of problems” and “importance
of recycling” on attitudes were -0.67 and 0.84, respectively. The percentage of variance
explained by the constructs was 51% for behavioural beliefs, 45% for severity of
problems and 71% for importance of recycling. A further review of the descriptive fit
6.23 91BCFA for behavioural beliefs and attitudes
203
indices revealed that changing the model would not have a large effect; hence the model
shown in Figure 6.3 has been retained.
Figure 6.3 CFA for behavioural beliefs and attitudes
Chi-sq = 47.67 (s, p=0.003) (df=24), CFI = .986, GFI = .969, AGFI = .942, RMSEA =
.056, RMR = .053
This model demonstrated good discriminant validity and the regression weights were all
significant, as shown in Table 6.20.
204
Table 6.20 Regression weights for behavioural beliefs and attitudes
In conclusion, this analysis demonstrated that three of the “behavioural belief”
statements were good predictors of attitudes and that attitudes were best measured by
“severity of problems” and the “importance of recycling”, each of which was measured
by three statements.
CFA 3 was performed to understand the effect that control beliefs had on perceived
behavioural control (PBC). The modification indices suggested the removal of
Q6AA_11 from the PBC construct. This statement was “If I wanted to, I would not have
problems in adopting a sustainable lifestyle” and this improved the model fit and the
descriptive indices considerably. While the Chi-square indicated that the model was not
a good fit, the other descriptive fit indices indicated that the model was a good fit to the
data. The model demonstrated a weak and negative relationship between control beliefs
and PBC, and the regression weights confirmed that this relationship was not
significant.
6.24 92BCFA for Control Beliefs and Perceived Behavioural Control
(PBC)
205
The percentage of variation explained by the three statements on control beliefs ranged
from 30% to 49% and the percentage of variation in the three statements on PBC ranged
from 14% to 75%. This model is shown in Figure 6.4.
Figure 6.4 CFA for control beliefs and PBC
Chi-sq = 8.43 (ns, p=0.393) (df=8), CFI = .999, GFI = .991, AGFI = .977, RMSEA =
.013, RMR = .019
The model demonstrated good discriminant validity and the regression weights are
shown in Table 6.21.
Table 6.21 Regression weights for control beliefs and PBC
As control beliefs were shown to not be a good predictor of PBC, an additional CFA
was performed omitting control beliefs. The resultant model demonstrated good
discriminant validity, the loadings for three of the four constructs were high and all
regression weights were significant. The descriptive fit statistics indicated that the
model was a good fit to the data: Chi- sq = 3.074 (ns) (df=2), CFI = .991, GFI = .988,
206
AGFI = .963, RMSEA = .057, RMR = .058. However, as the fit of the model with the
inclusion of control beliefs was better, the model with both constructs has been retained.
As discussed previously, the three constructs that measured normative beliefs,
subjective norm and PNM were combined to form one latent construct for this study.
CFA 4 was performed for the construct labelled “normative beliefs, subjective norm and
PNM” and the modification indices suggested the removal of Q6AA_19 which was one
of the PNM statements. The resultant model was a better fit to the data, which was
clarified as the GFI and AGFI indicated that the model represented a good
approximation of the data and the CFI suggested a well fitting model.
The model demonstrated that the percentage of variance that was explained by the four
statements in this construct ranged from 17% to 91%. The two statements with the
highest percentages were “My close friends think that I should live sustainably” and
“My close family members think that I should live sustainably”. This model is shown in
Figure 6.5.
Figure 6.5 CFA for normative beliefs, subjective norm and PNM
6.25 93BCFA for normative beliefs, subjective norm and PNM
207
Chi-sq = 9.55 (s, p = 0.008) (df=2), CFI = .988, GFI = .986, AGFI = .928, RMSEA =
.110, RMR = .045.
The regression weights for the indicators in the final model were significant as shown in
Table 6.22.
Table 6.22 Regression weights for PNM, normative beliefs and subjective norm
Internal ethics comprised two components, self-identity and ethical obligation. CFA 5
was performed on the four statements that comprised this construct and the descriptive
fit indices indicated that this model was a good fit to the data. This was clarified as the
RMR revealed that this model was doing a good job of representing sample variations,
the GFI and AGFI indicated that the model represented a good approximation of the
data and the CFI suggested a well fitting model. The model demonstrated that the
percentage of variance explained by the four statements ranged from 56% to 86%. This
model is shown in Figure 6.6.
6.26 94BCFA for internal ethics
208
Figure 6.6 CFA for internal ethics
Chi-sq = 4.419 (ns, p = 0.110) (df=2), CFI = .997, GFI = .993, AGFI = .964, RMSEA =
.062, RMR = .019.
The regression weights were all significant as shown in Table 6.23.
Table 6.23 Regression weights for internal ethics
CFA 6 was performed using the three statements that were shown to describe moral
intensity based on the EFA. The resultant model demonstrated that the percentage of
variance explained by the three statements ranged from 51% to 66%. This saturated
model is shown in Figure 6.7.
6.27 95BCFA for Moral intensity
209
Figure 6.7 CFA for moral intensity
The regression weights were significant as shown in Table 6.24.
Table 6.24 Regression weights for moral intensity
CFA 7 examined the lifestyle intention and behaviour constructs as they were presented
in the survey instrument, as measured by Q4 (lifestyle behaviour) and Q5 (lifestyle
intention). In order to statistically test these two constructs, they were combined to form
the latent construct called “lifestyle behaviour and intention” for the purposes of the
CFA.
While the analysis of this construct was restricted as there were only two measures, the
resultant saturated model which is shown in Figure 6.8 demonstrated that the percentage
of variance explained by the two constructs was 61% to 84%.
6.28 96BCFA for lifestyle intention and behaviour
210
Figure 6.8 CFA for lifestyle intention and behaviour
CFA 8 was performed to examine the four measures of LBI, namely, Q7_1, Q7_2,
Q7_5 and Q7_8. The analysis revealed that this model was not a good fit to the data.
The modification indices suggested the removal of Q7_5, which improved the model fit.
This statement that was removed was “When you were buying something or choosing
between alternatives, how likely were you to choose the product or alternative that is
more sustainable, even if it costs more?”
The CFA model is shown in Figure 6.9 with the standard estimates. The percentage of
variance explained by the remaining three statements ranged from 33% for Q7_8, 81%
for Q7_2 and 96% for Q7_1. The two statements with the highest percentage of
variance explained were: “How likely are you to engage in sustainable behaviours in the
home?” and “How likely are you to engage in sustainable behaviours away from
home?”
Figure 6.9 CFA for likely behavioural intention
6.29 97BLikely behavioural intention (LBI)
211
The regression weights were significant as shown in Table 6.25.
Table 6.25 Regression weights for LBI
Based on the CFA’s that were performed in AMOS, a summary of the descriptive fit
statistics is shown in Table 6.26. This table demonstrates that all constructs had CFI
values above 0.986, GFI above 0.969 and AGFI above 0.928. The RMSEA values were
all less than 0.062 except for “Norm beliefs/Subjective Norm/PNM”, and the RMR
values were all 0.053 or less. The Chi-square values revealed that PBC and internal
ethics constructs were the best fit to the data.
Table 6.26 Summary of statistics from the CFA measurement models
Construct Statistic Behavioural
beliefs and attitudes
PBC and control beliefs
Normative Beliefs/ Subjective Norm/PNM
Internal ethics
Chi-sq 47.67 (s) 8.43 (ns) 9.55 (s) 4.419 (ns) df 24 8 2 2 CFI .986 .999 .988 .997 GFI .969 .991 .986 .993 AGFI .942 .977 .928 .964 RMSEA .056 .013 .110 .062 RMR .053 .019 .045 .019
Note that for the Chi-square, s = significant (p<0.05) which does not indicate a good fit
to the data and ns = not significant which indicates a good fit to the data.
The moral intensity and the two behavioural intention constructs were not included in
the table as there were less than four measures in each of those constructs.
6.30 98BSummary of latent constructs based on the CFA
212
In conclusion, as a result of the CFA five more statements were removed from the
analysis due to their high modification indices and high standard residual covariances.
One statement was deleted from the “severity” construct, one from the “behavioural
beliefs” construct, one from PBC, one from “control beliefs” and one from LBI. The
remaining constructs remained unchanged between the EFA and the CFA, as illustrated
in Table 6.27.
Table 6.27 Summary of statements based on the EFA and the CFA EFA: statements retained CFA: statements retained Construct No. Label No. Label
ATTITUDES Severity Importance
5 3
Q6A_5 to Q6A_9 Q6C_6, 6C_7, 6C_8
4 3
Q6A_5, Q6A_7, Q6A_8, Q6A_9 Q6C_6, Q6C_7, Q6C_8
Behavioural beliefs 4 Q6B_1, 6B_2, 6B_3, 6B_4 3 Q6B_1, Q6B_2, Q6B_4 PBC 4 Q6AA_10 to Q6AA_13 3 Q6AA_10, Q6AA_12,
Q6AA_13 Control beliefs 4 Q8_1, Q8_3, Q8_4 3 Q8_1, Q8_3, Q8_4 PNM, norm beliefs, subjective norm
5 Q6AA_16, Q6AA_17, Q6AA_18, Q6AA_19, Q6C_1
4 Q6AA_18, Q6AA_16, Q6AA_17, Q6C_1
Internal ethics 4 Q6C_2 to Q6C_5 4 Q6C_2, Q6C_3, Q6C_4, Q6C_5
Moral intensity 3 Q9A_3, Q9A_4, Q9A_6 3 Q9A_3, Q9A_4, Q9A_6 Lifestyle intention Lifestyle behaviour
2 Q4, 5 2 Q4, 5
Likely behavioural intention (LBI)
4 Q7_1, Q7_2, Q7_5, Q7_8 3 Q7_1, Q7_2, Q7_8
To evaluate the measurement models for the constructs in this study, covariance
structure analysis was performed using AMOS Version 18.
Structural equation modelling (SEM) is a multivariate technique that simultaneously
estimates and tests a series of hypothesised “interrelated dependency relationships
between a set of latent (unobserved) constructs, each measured by one or more manifest
(observed) variables” (Reisinger & Mavondo 2006, p. 42). Through testing the
credibility of hypothetical assertions about potential interrelationships among the
6.31 99BStructural Equation Modelling (SEM)
213
constructs, SEM also examines their relationships to the indicators or the measures
assessing them (Raykov & Marcoulides 2000).
SEM was used in many of the studies that have been referred to in this thesis and has
been recommended for use in future studies. For example, in their study of the effect of
“self-identity” on the TPB when purchasing organically produced vegetables, Sparks
and Shepherd (1992) suggested the need for SEM to provide a more sophisticated
modelling technique to examine the effects of the constructs in the TPB. Shaw and
associates used SEM to analyse the findings for their study on purchasing fair trade
products.
The SEM in this study was based on the latent constructs that were assessed using EFA
and CFA. It consists of a measurement model and a path model. In the SEM, the
measurement model “represents a set of p observable variables as multiple indicators of
a smaller set of m latent variables, which were usually common factors”. The path
model describes relations of dependency that were “usually accepted to be in some
sense causal between the latent variables” (McDonald & Ho 2002, p. 65). The final
structural model was a composite model that was a combination of the combined
measurement and path models (McDonald & Ho 2002).
The estimation procedures for SEM assume that data is normally distributed. In this
study, normality was checked in several ways. First, the skewness and kurtosis of the
measured variables were examined. In all cases the kurtosis values were close to zero,
indicating that the distribution’s peakedness was similar to a normal distribution. Some
variables exhibited slight positive or negative skewness. Box plots confirmed the
absence of outliers and extreme values, and the large sample size ensured that the
variances and covariances were stable. The normality assumption of the variables was
also examined using the Kolmogorov-Smirnov test of normality, which confirmed that
the null hypothesis for normality was accepted. For all constructs, the normality was
6.31.1 171BTesting for normality and multicollinearity
214
also confirmed by the Shapiro-Wilk test. The correlations of the variables in the models
reported in this analysis demonstrated no association greater than 0.7, indicating that
multicollinearity does not appear to be a problem in this study.
The initial consolidated SEM models were constructed by sequentially arranging the
final CFA measurement models according to the theoretical frameworks in chapter 4. In
this analysis, two SEM were run – one for LBI and one for lifestyle behaviour and
intention as depicted in the theoretical models displayed in Figures 4.2 and 4.3
respectively. SEM was not run for capital behaviour and intention as depicted in Figure
4.4 as the two capital constructs were eliminated in the process of EFA.
Before running the SEM for LBI, AMOS first required that all latent exogenous
constructs were correlated. The SEM was performed on the initial LBI model, and the
model was a poor fit to the data, as summarised by the following descriptive fit
statistics: Chi-sq= 910.658 (s) (df=358), CFI =.898, GFI =.838, AGFI=.803,
RMSEA=.071, RMR =.203.
The model needed to be revised and when doing so, the researcher considered the
theoretical perspectives of the constructs before making any changes (McDonald & Ho
2002). While some may have been considered by observing the output and goodness of
fit statistics, they were not implemented if they did not make sound theoretical sense.
The first change, based on the standardised residual covariances was to remove
Q6AA_18. This was logical given that this was the remaining statement that comprised
the original Personal Normative Motives (PNM) construct. The other PNM statement
had been removed in the CFA analysis. This improved the model fit slightly, as
summarised by the following descriptive fit statistics: Chi-sq=684.267 (s) (df=331), CFI
=.932, GFI =.869, AGFI=.839, RMSEA=.059, RMR =.164.
6.32 100BDeveloping the SEM for likely behavioural intention (LBI)
215
As the two statements that measured the PNM (personal normative motives) construct
were removed from the analysis, the “normative beliefs and subjective norm” construct
was consequently renamed.
Further examination of the modification indices suggested the removal of the three
control belief statements, which was a logical decision as control beliefs were shown to
be a poor predictor of its antecedent PBC, in the CFA analysis. While this improved the
model fit slightly, the fit indices were further improved by the removal of the PBC
construct. This was done as the regression weights were not significant and the
modification indices were high for the remaining three PBC measures.
With these changes made, the final model was run and the descriptive fit indices
revealed that this model was a good fit to the data, While the Chi-square statistic was
significant, the RMSEA value was close to 0.05, the GFI and AGFI indicated that the
model represented a good approximation of the data, and the CFI suggested a well
fitting model. The resulting descriptive fit statistics for the final LBI model were: Chi-
sq = 390.670 (s) (df=196), CFI = .957, GFI = .900, AGFI = .870, RMSEA = .057, RMR
= .118 and it showed good discriminant validity as confirmed by the implied
correlations. The standardised regression weights revealed that the internal ethics
construct was the best predictor of LBI (0.674), while attitudes, normative
beliefs/subjective norm and moral intensity were not good predictors of LBI.
Behavioural beliefs (0.584) were strong predictors of attitudes (0.584), and attitudes
were influenced by both “severity” (-0.66) and “importance” (0.85).
In analysing the correlations between the exogenous constructs, it was demonstrated
that the effect of moral intensity on the other three exogenous constructs was negative
and the correlations between internal ethics and the other constructs were the strongest.
Overall, the strongest correlations were between behavioural beliefs and internal ethics
(0.60), normative beliefs and subjective norm with internal ethics (0.45), moral intensity
and internal ethics (-0.41) and behavioural beliefs with moral intensity (-0.39).
Based on the data collected in this research study, the final model for LBI, with the
standardised regression weights is shown in Figure 6.10.
216
Figure 6.10 Final SEM for LBI
The regression weights indicated that the effect of internal ethics on LBI was significant
(p<0.05), while the effect of attitudes, normative beliefs and subjective norm, and moral
intensity on LBI was not significant. The effect of attitudes on “severity” and
“importance” was significant, and the effect of behavioural beliefs on attitudes was also
significant. These findings are summarised in Table 6.28.
Table 6.28 Regression weights for the final LBI model Constructs Estimate Severity of problems Attitudes -.273*** Importance Attitudes -.364*** LBI Attitudes .027 (ns) LBI Norm beliefs/ subjective norm .078 (ns) LBI Internal ethics .723*** LBI Moral intensity -.078 (ns)
217
The squared multiple correlations (R2) which indicate the percentage of variance
accounted for by each construct, demonstrated that 60% of the variance in LBI was
explained by the three statements in this model. 34% of the variance in attitudes was
explained by this model, with “importance” having a stronger effect (72%) than
“severity” (44%). The estimates were particularly high for the statements that measured
likelihood to engage in sustainable behaviours in the home (Q7_1) and away from home
(Q7_2). 91% of the variance in LBI was explained by likelihood to engage in
sustainable behaviours in the home and 81% by likelihood to engage in sustainable
behaviours away from home.
The constructs, labels, statements and estimates for the LBI model are summarised in
Table 6.29.
218
Table 6.29 Estimates of squared multiple correlations (R2) for LBI Construct Label Statement(s) Estimate Likely behavioural intention (LBI) .599 In the home Q7_1 Sustainable behaviours in the home .910 Away from home Q7_2 Sustainable behaviours away from home .816 Higher price Q7_8 Higher price for sustainable products .350 Construct Behavioural beliefs: If we do NOT adopt a sustainable lifestyle this will… Damage the environment for future generations .698 Increase the cost of water and electricity .459 Result in climate change .558 Attitudes: total .342 Attitudes: severity .442 In our country, we have so much electricity and water that we do not have to worry about conservation
.580
With so much water in this country, I don’t see why people are worried about saving water .719 Our country has so many trees that there is no need to recycle paper .833
Attitudes: importance .715 Recycling will reduce pollution .713 Recycling is important to save natural resources .874 Recycling will save land that would be used for landfill/rubbish .833 Normative beliefs My close friends think that I should live sustainably .809 My close family members think that I should live sustainably .894 Subjective norm Most people who are important to me think I should adopt a sustainable lifestyle .485 Internal ethics: ethical obligation I feel that I have an ethical obligation to live sustainably .600 Internal ethics: self-identity I think of myself as someone who is very concerned about sustainable issues. .836 I think of myself as someone who is very concerned about ethical issues. .706 I think of myself as someone who is very concerned about green issues. .732 Moral intensity The overall harm (if any) as a result of their behaviour would be very small (MC) .552 Their behaviour will not cause harm to the environment in the immediate future (TI) .643 Their behaviour will harm few, if any people (CE) .609
Note that ethical obligation and self-identity form the internal ethics construct.
Appendices 10, 11, 12 and 13 include some of the output from this analysis.
219
The next step was to run the SEM for lifestyle behaviour and intention, based on the
theoretical model presented in chapter 4. This initial model was a poor fit to the data, as
summarised by the following descriptive fit statistics: Chi-sq= 834.897 (s) (df=332),
CFI =.897, GFI =.846, AGFI=.811, RMSEA=.070, RMR =.225.
In revising the model, the theoretical perspectives of the constructs were again
considered before making any changes (McDonald & Ho 2002). As with the model for
LBI, the first change was to remove Q6AA_18 based on the high standardised residual
covariances. This was logical given that this was the remaining statement that
comprised the original Personal Normative Motives (PNM) construct and because the
other PNM statement had been removed in the CFA analysis. This improved the model
fit, as summarised by the following descriptive fit statistics: Chi-sq=609.161 (s)
(df=306), CFI =.935, GFI =.879, AGFI=.850, RMSEA=.057, RMR =.183.
As the two statements that measured the PNM (personal normative motives) construct
were removed from the analysis, the “normative beliefs and subjective norm” construct
has consequently been renamed.
Similar to the analysis for LBI, an examination of the modification indices suggested
the removal of the control belief construct and the PBC construct. This was done
because the regression weights were not significant and the modification indices were
high for these measures.
The final model showed good discriminant validity as confirmed by the implied
correlations, and the descriptive fit indices revealed that this model was a good fit to the
data. While the Chi-square statistic was significant, the RMSEA value was close to
0.05, the GFI and AGFI indicated that the model represented a good approximation of
the data, and the CFI suggested a well fitting model. The resulting descriptive fit
6.33 101BDeveloping the final SEM for lifestyle behaviour and
intention
220
statistics were: Chi-sq = 330.206 (s) (df=177), CFI = .962, GFI = .912, AGFI = .885,
RMSEA = .053, RMR = .150.
The final model displays that while the effect of lifestyle behaviour on lifestyle
intention was strong (0.713), the standardised regression weights were lower for this
model that for the LBI model. The “internal ethics” construct was the best predictor of
lifestyle behaviour (0.24). Attitudes (0.18), normative beliefs/subjective norm (0.14)
and moral intensity (-.14) were reasonably good predictors of lifestyle behaviour.
Further investigation revealed that the “behavioural beliefs” construct was a strong
predictor of attitudes, with a standardised regression weight of 0.593. Attitudes were
influenced by both “severity” (-.692) and “importance” (.813). However, as the effect
of attitudes on the LBI construct was low (0.184), this meant that the effect of
behavioural beliefs on LBI was also quite low (0.593 x 0.184 = 0.109).
The correlations between the five exogenous constructs were almost identical for the
two theoretical models. The findings demonstrated that the effect of moral intensity on
the other three constructs was negative, and the correlations between internal ethics and
the other constructs were the strongest. Overall, the strongest correlations were between
behavioural beliefs and internal ethics (0.59), normative beliefs and subjective norm
with internal ethics (0.44), moral intensity and internal ethics (-0.41) and behavioural
beliefs with moral intensity (-0.39).
Based on the data collected in this research study, the final model for lifestyle behaviour
and intention with the standardised regression weights is shown in Figure 6.11.
221
Figure 6.11 Final SEM for lifestyle behaviour and intention
Table 6.30 reveals that in the final model for lifestyle behaviour and intention, the
regression weights were all significant (p<0.05). The strongest weights were for the
relationship between lifestyle behaviour and lifestyle intention (.835) and between
internal ethics and lifestyle behaviour (.556). Behavioural beliefs were strong predictors
of attitudes (.810).
Table 6.30 Regression weights for final lifestyle behaviour and intention model Constructs Estimate Attitudes Behavioural beliefs .810 *** Severity of problems Attitudes -.288*** Importance Attitudes -.355*** Lifestyle behaviour Attitudes .217*** Lifestyle behaviour Norm beliefs/ subjective norm .272*** Lifestyle behaviour Internal ethics .556*** Lifestyle behaviour Moral intensity -.282*** Lifestyle intention Lifestyle behaviour .835 ***
The squared multiple correlations (R2), which indicate the percentage of variance
accounted for by each construct, demonstrated that 24% of the variance in lifestyle
222
behaviour was explained by this model and that 51% of the variance in lifestyle
intention was explained by lifestyle behaviour. 35% of the variance in attitudes was
explained by this model, with “importance” having a stronger influence (66%) than
“severity” (48%). Normative beliefs and self-identity were strong predictors of lifestyle
behaviour within this model.
The constructs, labels, statements and estimates for the lifestyle behaviour and intention
model are summarised in Table 6.31.
Table 6.31 Estimates of squared multiple correlations (R2) for lifestyle behaviour Construct Label Statement(s) Estimate Lifestyle behaviour .242 Lifestyle intention .509 Behavioural beliefs: If we do NOT adopt a sustainable lifestyle this will… Damage the environment for future generations .698 Increase the cost of water and electricity .459 Result in climate change .560 Attitudes: total .351 Attitudes: severity .478 In our country, we have so much electricity and water that we do not have to worry about conservation
.580
With so much water in this country, I don’t see why people are worried about saving water .719 Our country has so many trees that there is no need to recycle paper .762
Attitudes: importance .660 Recycling will reduce pollution .712 Recycling is important to save natural resources .874 Recycling will save land that would be used for landfill/rubbish .832 Normative beliefs My close friends think that I should live sustainably .810 My close family members think that I should live sustainably .894 Subjective norm Most people who are important to me think I should adopt a sustainable lifestyle .483 Internal ethics: ethical obligation I feel that I have an ethical obligation to live sustainably .581 Internal ethics: self-identity I think of myself as someone who is very concerned about sustainable issues. .843 I think of myself as someone who is very concerned about ethical issues. .702 I think of myself as someone who is very concerned about green issues. .743 Moral intensity The overall harm (if any) as a result of their behaviour would be very small (MC) .559 Their behaviour will not cause harm to the environment in the immediate future (TI) .642 Their behaviour will harm few, if any people (CE) .603
Note that ethical obligation and self-identity form the internal ethics construct.
Appendices 14, 15, 16 and 17 include some of the output from this analysis.
223
The next sections summarise the results of the hypothesis testing. The discussion
commences with the hypothesis tests that were not measured in the final SEM because
the constructs were shown to be not significant in either the EFA or the CFA.
Based on the three theoretical frameworks for this study, there were five constructs that
were not included in the final SEM analyses. These constructs were capital behaviour,
capital intention, PBC, control beliefs and PNM.
There were two capital constructs that were labelled “capital behaviour” and “capital
intention”. Capital intention was measured by asking respondents which behaviours
they intend to do in the next two years and capital behaviours were measured by asking
which behaviours they had already done. There were five hypotheses related to the
capital behaviour construct and one relating to the capital intention construct. As this
construct was not included in the final SEM, six hypotheses were not tested:
H11: Attitudes have a positive influence on capital behaviour.
H12: PBC has a positive influence on capital behaviour.
H13: Subjective norm/PNM/normative beliefs have a positive influence on capital
behaviour.
H14: Internal ethics has a positive influence on capital behaviour.
H15: Moral intensity has a positive influence on capital behaviour.
H17: Capital behaviour is a predictor of capital intention.
6.34 102BDiscussion of hypothesis tests – constructs not in final SEM
6.34.1 173BCapital behaviour and intention
224
Personal normative motives (PNM) refer to feelings of obligation and responsibility and
they were activated by an awareness the consequences of a behaviour and beliefs about
personal responsibility for the consequence (Wall, Devine-Wright & Mill 2007). The
PNM construct was used to explain the fact that behaviours that reduce personal utility
such as by decreasing convenience may be perceived as difficult and therefore not
achievable.
For this analysis, subjective norm, normative beliefs and personal normative motives
(PNM) were combined into the one “normative” construct. In successive iterations of
the CFA and in the initial version of the SEM, the PNM construct was removed;
suggesting that in the sustainable context, the effect of PNM on behaviour was not
significant. As the PNM construct was removed from the “subjective norm and
normative beliefs” construct, this construct was renamed. Therefore, for all hypotheses
that included PNM, it was shown that PNM did not have a significant effect on the
related construct.
The other two normative constructs (normative beliefs and subjective norm) did have a
significant effect on sustainable behaviour and they are discussed later in this chapter.
Control beliefs were determined by two measures: the power of a factor to assist the
desired action and the perceived access to the factor (Pickett-Baker & Ozaki 2008).
Control beliefs have been shown to be an antecedent to perceived behavioural control
(PBC). PBC refers to how easy or difficult a person believes that performing a
behaviour was likely to be (Routhe, Jones & Feldman 2005; Shaw, Shiu & Clarke 2000)
and reveals public perceptions of institutional barriers to pro-environmental action
(Jones 1991).
6.34.2 172BPersonal normative motives
6.34.3 174BControl beliefs and perceived behavioural control
225
As measured in this study, the CFA revealed that the total effect of control beliefs on
PBC was weak and not significant. Both these constructs were removed in the final
SEM for both LBI and lifestyle behaviour and thus, for this study, these constructs were
shown to be poor predictors of sustainable behaviour and intention.
Based on the findings in this chapter, the following hypotheses relating to PBC and its
effect on LBI and lifestyle behaviour were not tested:
H2: PBC has a positive influence on likely behavioural intention (LBI)
H7: PBC has a positive influence on lifestyle behaviour.
As mentioned in the previous section, the following hypothesis was also not tested:
H12: PBC has a positive influence on capital behaviour.
The following sections discuss the constructs and the related hypotheses that were
included in the final SEM, beginning with behavioural beliefs and attitudes.
Behavioural beliefs refer to a “person’s beliefs about the probability of specific
consequences occurring as a result of a given behaviour” and their outcome evaluations.
They represent “a person’s subjective evaluation of each outcome” (Routhe, Jones &
Feldman 2005, p. 879). For this study, respondents’ behavioural beliefs referred to their
beliefs that the consequences of not adopting sustainable behaviours will have the
following consequences: damage the environment for future generations, increase the
cost of water and electricity, and result in climate change. Behavioural beliefs have been
6.35 103BDiscussion of hypothesis tests – constructs included in the
final SEM
6.35.1 175BBehavioural beliefs and attitudes
226
shown to dictate consumers’ attitudes towards particular behaviours. In this research
study, attitudes were influenced by two latent constructs: the perceived “severity” of not
adopting sustainable behaviours and the “importance” of recycling, as defined by
Laroche at al. (2001). It was also hypothesised that they would also be influenced by the
“inconvenience” of being environmentally friendly; however, this hypothesis has not
been accepted (as discussed in the previous section).
The findings from this study revealed that for both the theoretical frameworks and for
the attitudes measured, behavioural beliefs were antecedents of attitudes. This
demonstrates that a person’s beliefs and their evaluations of the outcomes of their
actions dictated their attitudes towards sustainable behaviours, thus concurring with the
conclusions of authors such as Ajzen and Fishbein (1980) and Sparks et al. (1995).
Laroche et al. (2001) defined three composite attitudinal constructs that referred to the
“importance” of recycling, the “inconvenience” of being environmentally friendly, as
well as the “severity” of environmental problems. The importance of recycling was
measured by three statements, the inconvenience of being environmentally friendly was
measured by two statements and the severity of environmental problems was measured
by five statements. This study demonstrated that attitudes regarding sustainable
behaviour and intention were measured by the “severity” and “importance” constructs.
As attitudes were reliable predictors of LBI and lifestyle behaviour, the following
hypotheses were accepted:
H1: Attitudes have a positive influence on likely behavioural intention (LBI)
H6: Attitudes have a positive influence on lifestyle behaviour.
As the “inconvenience” construct was not shown to be a reliable influence on attitudes
in this study, it can be concluded that this study partially confirmed Laroche et al.’s
(2001) findings.
227
Normative beliefs were measured in this study to understand their impact on subjective
norm. Normative beliefs refer to the beliefs about what “significant others” including
family, close personal friends and neighbours were significant referents for the
individual. The subjective norm refers to the perception that intention to behave in a
particular way was influenced by a person’s belief about what important others think
that they should or should not do with respect to the behaviour in question (Ajzen &
Fishbein 1980). For this study subjective norm and normative beliefs were combined to
form the one “normative” construct. Initially, they were combined with personal
normative motives (PNM); however, the PNM construct was subsequently removed
from this construct due to its poor ability to predict sustainable behaviour and intention,
leaving just the two variables as measures of this construct.
The findings from the research indicated that, based on the revised hypotheses (with
PNM removed) that the construct labelled “subjective norm and normative beliefs” was
a significant predictor of lifestyle behaviour, but not of LBI. One hypothesis was
accepted and one not accepted, as shown below.
The following hypothesis was not accepted:
H3: Subjective norm and normative beliefs have a positive influence on likely
behavioural intention (LBI)
The following hypothesis was accepted:
H8: Subjective norm and normative beliefs have a positive influence on lifestyle
behaviour.
6.35.2 176BNormative beliefs and subjective norm
228
The internal ethics latent construct comprised two constructs: ethical obligation and
self-identity. Sparks et al. (1995), Shaw and Shiu (2003) and Chedzoy and Burden
(1999) demonstrated the importance of including ethical obligation and self-identity in
models of behavioural intention. They showed that consumers perceive they have an
ethical obligation to perform these behaviours and that ethical and sustainable
behaviours were a part of a consumer’s self-identity. The hypothesis tests revealed that
internal ethics has a strong influence on both lifestyle behaviour and LBI.
The following hypotheses were accepted:
H4: Internal ethics has a positive influence on likely behavioural intention (LBI)
H9: Internal ethics has a positive influence on lifestyle behaviour.
The moral intensity construct was proposed by Jones (1991) to explain the four stages
that described how an organisation engaged in moral behaviour, from recognition of the
issue through to making a judgement about the issue and establishing moral intent, to
engaging in moral behaviour. Jones (1991) described moral intensity as “the extent of
issue-related moral imperative in a situation” (p. 372).
Moral intensity consisted of six characteristics: Magnitude of consequences (MC),
Social consensus (SC), Probability of effect (PE), Temporal immediacy (TI), Proximity
(PX) and Concentration of effect (CE). In the EFA, the effects of MC, TI and CE were
shown to be significant indicators of the moral intensity construct for the scenario
presented in this research study.
6.35.3 177BInternal ethics – Self-identity and ethical obligation
6.35.4 178BMoral intensity
229
The findings from this study indicated that moral intensity had a strong negative effect
on lifestyle behaviour, but its effect on LBI was not significant. Hence, the following
hypothesis was accepted:
H10: Moral intensity has a positive influence on lifestyle behaviour.
The following hypothesis was not accepted:
H5: Moral intensity has a positive influence on likely behavioural intention (LBI)
In summary, a total of 17 hypotheses were proposed in chapter 4. Six of these were
accepted and 11 were not accepted.
A total of five constructs were deleted both before and as a result of the final SEM.
These were “capital behaviour”, “capital intention”, “personal normative motives”
(PNM), “perceived behavioural control” (PBC) and “control beliefs”. In addition, the
“personal normative motives” (PNM) construct was removed from the “normative”
construct and this construct was renamed “subjective norm and normative beliefs” in the
final SEM. Consequently the name of this hypothesis has also been modified in Table
6.32. Therefore, all hypotheses that were developed for capital behaviour and intention,
perceived behavioural control (PBC) and control beliefs have been not accepted.
As well as summarising the hypothesis testing, Table 6.32 includes the regression
weights (β values) and the outcome of the hypothesis testing (accepted or not accepted),
based on the SEM. In this table, “NA” means that these hypothesis tests were not
included in the final SEM.
6.36 104BSummarising the findings of the hypothesis testing
230
Table 6.32 Summary of the findings from the hypothesis testing Research hypotheses
Regression weights (β values)
Accepted or not accepted
H1: Attitudes have a positive influence on likely behavioural intention (LBI).
-.027 Not accepted
H6: Attitudes have a positive influence on lifestyle behaviour. .217 Accepted H11: Attitudes have a positive influence on capital behaviour. NA Not
accepted H2: PBC has a positive influence on likely behavioural intention (LBI)
NA Not accepted
H7: PBC has a positive influence on lifestyle behaviour. NA Not accepted
H12: PBC has a positive influence on capital behaviour. NA Not accepted
+ H3: Subjective norm and normative beliefs have a positive influence on likely behavioural intention (LBI).
.078 Not accepted
+ H8: Subjective norm and normative beliefs have a positive influence on lifestyle behaviour.
.272 Accepted
+ H13: Subjective norm and normative beliefs have a positive influence on capital behaviour.
NA Not accepted
H4: Internal ethics has a positive influence on likely behavioural intention (LBI).
.723 Accepted
H9: Internal ethics has a positive influence on lifestyle behaviour. .556 Accepted H14: Internal ethics has a positive influence on capital behaviour. NA Not
accepted H5: Moral intensity has a positive influence on likely behavioural intention (LBI).
-.078 Not accepted
H10: Moral intensity has a positive influence on lifestyle behaviour.
-.282 Accepted
H15: Moral intensity has a positive influence on capital behaviour.
NA Not accepted
H16: Lifestyle behaviour is a predictor of lifestyle behavioural intention.
.835 Accepted
H17: Capital behaviour is a predictor of capital behavioural intention.
NA Not accepted
+ note that PNM has been removed from the hypotheses
After completing the hypothesis testing, the next step was to analyse the original
statements that were included in the questionnaire to determine which were retained and
which were deleted. Of the 37 statements that were initially used to form the exogenous
constructs, 18 were deleted and 19 were retained.
6.37 Summary of the outcomes of the EFA, CFA and SEM
231
For the LBI construct, three of the statements were retained and Q7_5 was deleted. The
deleted statement was “when you are buying something or choosing between
alternatives, how likely are you to choose the product or alternative that is more
sustainable, even if it costs more?” Both of the constructs that were initially used to
measure lifestyle behaviour and intention were retained, while both of the constructs
that were initially used to measure capital behaviour and intention were deleted. These
findings are summarised in Table 6.33.
Table 6.33 Statements retained/deleted after the EFA, CFA and SEM analyses Construct and statements Label Retained/
deleted Behavioural beliefs: If we do NOT adopt a sustainable lifestyle this will… Damage the environment for future generations Q6B_1 Retained
Retained Deleted Retained
Increase the cost of water and electricity Q6B_2 Have no affect on the way we live Q6B_3 Result in climate change Q6B_4 Attitudes: severity In our country, we have so much electricity and water that we do not have to worry about conservation
Q6A_5 Retained Deleted Retained Retained Deleted
Since we live in such a large country, any pollution that we create is easily spread out and therefore of no concern to me
Q6A_6
With so much water in this country, I don’t see why people were worried about saving water
Q6A_7
Our country has so many trees that there is no need to recycle paper Q6A_8 The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state
Q6A_9
Attitudes: importance Recycling will reduce pollution Q6C_6 Retained
Retained Retained
Recycling is important to save natural resources Q6C_7 Recycling will save land that would be used for landfill/rubbish Q6C_8 Attitudes: inconvenience Keeping separate piles of rubbish for recycling is too much trouble Q6C_9 Deleted
Deleted Trying to control pollution is much more trouble than it is worth Q6C_10 PBC It would be difficult for me to adopt a sustainable lifestyle Q6AA_10 Deleted
Deleted Deleted Deleted
If I wanted to, I would not have problems in adopting a sustainable lifestyle
Q6AA_11
I have full control over whether or not I adopt a sustainable lifestyle Q6AA_12 It is completely up to me whether or not I adopt a sustainable lifestyle Q6AA_13 Control beliefs: Which, if any, of the following affect whether or not you adopt a sustainable lifestyle? The availability of sustainable products Q8_1 Deleted
Deleted Deleted Deleted
The cost of sustainable products Q8_2 The amount of information available about sustainable products Q8_3 The quality of sustainable products Q8_4 Normative beliefs My close friends think that I should live sustainably Q6AA_16 Retained My close family members think that I should live sustainably Q6AA_17 Retained Subjective norm Most people who were important to me think I should adopt a Q6C_1 Retained
232
sustainable lifestyle PNM I feel personally responsible for helping to protect the environment Q6AA_18 Deleted I feel morally obliged to take measures to help to protect the environment
Q6AA_19 Deleted
Ethical obligation I feel that I have an ethical obligation to live sustainably Q6C_2 Retained Self-identity I think of myself as someone who is very concerned about sustainable issues.
Q6C_3 Retained
I think of myself as someone who is very concerned about ethical issues. Q6C_4 Retained I think of myself as someone who is very concerned about green issues. Q6C_5 Retained Moral intensity There is a very small likelihood that their behaviour will actually cause harm to the environment (PE)
Q9_1 Deleted
Most people would agree that their behaviour is wrong (SC) Q9_2 Deleted The overall harm (if any) as a result of their behaviour would be very small (MC)
Q9_3 Retained
Their behaviour will not cause harm to the environment in the immediate future (TI)
Q9_4 Retained
The harmful effects (if any) of the decision will affect people that are close to the Watsons (PX)
Q9_5 Deleted
Their behaviour will harm few, if any people (CE) Q9_6 Retained Likely behavioural intention (LBI) How likely were you to engage in sustainable behaviours in the home? Q7_1 Retained How likely were you to engage in sustainable behaviours away from home?
Q7_2 Retained
When you were buying something or choosing between alternatives, how likely were you to choose the product or alternative that is more sustainable, even if it costs more?
Q7_5 Deleted
How likely were you to pay a higher price for sustainable products? Q7_8 Retained Lifestyle behaviour and intention Lifestyle behaviour Q4 Retained Lifestyle intention Q5 Retained Capital behaviour and intention Capital behaviour Q2 Deleted Capital intention Q3 Deleted
233
Invariance testing involves comparing the answers given to the survey questions by
more than one sample and considers whether the components of the measurement
model were invariant across these groups (Byrne 2001). It was included in the analysis
of the data set as the literature argued that the effects of demographics and values
segments were important determinants of behaviour and intention.
Measurement invariance (also called measurement equivalence) involves using multiple
group CFA’s to test if the relationships between the latent constructs and their indicators
were identical between groups (Gilg, Barr & Ford 2005). This demonstrates whether the
common factor model holds across multiple populations or samples. Similarly,
structural invariance is concerned with investigating if the standardised regression
weights for the latent constructs are identical between groups. In general, differences
greater than 0.2 in the structural and measurement weights for the invariant groups were
considered to be significant (Gilg, Barr & Ford 2005).
For this study, invariance testing was used to test the measurement and structural
invariance of the final two theoretical models for LBI and lifestyle behaviour and
intention. The groups that were tested for invariance in this study were gender, presence
of children, home ownership and where the person lives. In addition, as this thesis is
examining sustainable behaviour, invariance testing was conducted to compare people
who “agree or agree strongly” that they lead a sustainable lifestyle, compared to those
who “disagree or disagree strongly” that they lead a sustainable lifestyle. These factors
were examined to determine their effect on the measurement and structural weights in
the final two theoretical frameworks, based on the validation sample of 311
respondents.
6.38 105BInvariance testing
234
The invariance testing was conducted for the LBI model, as described in the following
sections.
The first invariance test revealed that there were no significant differences between
males and females, both in the measurement weights (Chi2 = 13.246, df = 15, p=.583)
and in the structural weights (Chi2 16.716, df = 21, p=.728), as shown in Table 6.34.
Table 6.34 Invariance tests for males and females df Chi-square p significance Measurement weights 15 13.246 .583 ns Structural weights 21 16.716 .728 ns
Table 6.35 illustrates that the structural weights (standardised regression weights) for
males and females were very similar. The exception was that males had higher
structural weights than females on the path labelled Attitudes importance, where the
difference was 0.276. As these three statements were related to the importance of
recycling to reduce pollution, saving natural resources and saving land used for landfill,
this suggests that these issues were more important for males than for females.
Table 6.35 Standardised structural weights for males and females Males Females Attitudes Behavioural beliefs 0.572 0.561 Severity of problems Attitudes -0.619 -0.726 Importance Attitudes .971 .695 LBI Attitudes .105 .042 LBI Norm beliefs/ subjective norm .118 .065 LBI Internal ethics .656 .650 LBI Moral intensity -0.070 -0.098
6.39 106BInvariance testing for the LBI model
6.39.1 179BInvariance testing – gender
235
The next invariance test was conducted to determine if there were significant
differences in the measurement and structural weights for households with one or more
children aged under 18 years, compared to those with no children aged under 18 years
in the household. The measurement weights revealed that the weight for the pathway
“Importance Q6C_7” was greater than 1. This suggested that the model was invalid
for these invariant groups as it implied that a negative variance existed in this model.
Further investigation revealed that the variance of Q6C_7’s error term “e9” was
negative, so the variance for the error term was set to zero (Byrne 2001) and the model
was re-run. A review of the standardised measurement weights in the modified model
indicated that no weights were greater than 1. Hence, this analysis is based on the
revised model.
This invariance test demonstrated that there was a significant difference both in the
measurement weights (Chi2 = 30.114, df = 15, p=.012) and in the structural weights
(chi2 = 33.653, df = 21, p=.039) for households with one or more children aged under
18 years, compared to those with no children aged under 18 years in the household.
These findings are summarised in Table 6.36.
Table 6.36 Updated invariance tests for people with child/no child under 18 df Chi-square P significance Measurement weights 15 30.114 .012 s Structural weights 21 33.653 .039 s
There were two main differences in the individual measurement weights for these two
groups. People living in households with one or more children aged under 18 had
significantly higher standardised measurement weights (greater than 0.2) on the
statement “In our country, we have so much electricity and water that we do not have to
worry about conservation” (Q6A_5, severity). On the other hand, people in households
with no children had significantly higher measurement weights on the statement “If we
do not adopt a sustainable lifestyle this will increase the cost of water and electricity”
(Q6B_2, behavioural beliefs). These measurement weights are shown in Table 6.37.
6.39.2 180BInvariance testing – child under 18 and no child under 18
236
Table 6.37 Standardised regression weights for households with child under 18 Construct Statement Child
U18 No child
LBI Likely to engage in the home .948 .953 LBI Likely to engage away from home .952 .899 LBI Likely to pay higher price .472 .623 Importance Recycling will reduce pollution .724 .907 Importance Recycling is important to save natural resources .999 .901 Importance Recycling will save land used for landfill .935 .901 Severity of problems So much electricity .925 .706 Severity of problems So much water .919 .801 Severity of problems So many trees .824 .898 Behavioural beliefs Damage the environment .757 .868 Behavioural beliefs Increase cost of water and electricity .314 .770 Behavioural beliefs Result in climate change .856 .732 Normative beliefs Close friends think I shd live sustainably .880 .907 Normative beliefs Close family think I shd live sustainably .887 .956 Moral intensity Overall harm very small (MC) .784 .726 Moral intensity Will not cause harm in future (TI) .820 .800 Moral intensity Behaviour will harm few (CE) .772 .792 Internal ethics Ethical obligation .726 .785 Internal ethics Very concerned about sustainable .865 .927 Internal ethics Very concerned about ethical .817 .842 Internal ethics Very concerned about green .875 .850 Subjective norm Important people think I should adopt sustainable
lifestyle .706 .693
An invariance test was conducted to test if there were significant differences in the
measurement and structural weights for people who owned their dwelling, compared to
those who do not own their dwelling. The “ownership” variable included people who
owned their dwelling outright and people who had a mortgage on their dwelling (218
respondents). The remainder was renting their dwelling (93 respondents).
This test demonstrated that while there was no significant difference in the measurement
weights (chi2 =19.456, df = 15, p=.194), that there was a significant difference in the
structural weights (chi2 =36.372, df = 21, p= 0.020), as shown in Table 6.38. This meant
that while these two groups (own and don’t own their dwelling) measured the
6.39.3 181BInvariance testing – own /don’t own their dwelling
237
statements that comprised these constructs in a similar way, the structure of the
constructs was different for the two groups.
Table 6.38 Invariance tests for people who own/don’t own their dwelling df Chi-square p significance Measurement weights 15 19.456 .194 ns Structural weights 21 36.372 .020 s
Investigating the standardised structural weights for people who own compared to those
who don’t own their dwelling revealed that the structural weights were higher for
people who don’t own their dwelling on the following pathways: Behavioural beliefs
attitudes, and Attitudes importance. This suggested that the main differences in the
two invariant groups can be described by the importance of recycling construct and in
the behavioural beliefs of the respondents. In other words, people who don’t own their
home were more concerned about these issues. These weights are summarised in Table
6.39.
Table 6.39 Standardised structural weights for people who own and don’t own
their dwelling Own Don’t
own Attitudes Behavioural beliefs .546 .759 Severity of problems Attitudes -.597 -.795 Importance Attitudes .78/ .952 LBI Attitudes .047 .017 LBI Norm beliefs/ subjective norm .056 .130 LBI Internal ethics .661 .733 LBI Moral intensity -.085 -.098
To test if there were significant differences in the measurement and structural weights
for people living in capital cities (city) and outside the capital cities (x-city), the
invariance test was conducted on the LBI model. This test indicated that there was no
significant difference between people living in capital cities and outside the capital
cities, both in the measurement weights (chi2 = 14.480, df = 15, p= 0.489) and in the
structural weights (chi2 = 28.370, df = 21, 0.130), as shown in Table 6.40.
6.39.4 182BInvariance testing – city and x-city
238
Table 6.40 Invariance tests for people living in capital cities and x-city df Chi-square p significance Measurement weights 15 14.480 .489 ns Structural weights 21 28.370 .130 ns
Table 6.41 demonstrates that while there were no significant differences in the structural
weights for these two invariant groups, the weights for people living outside the capital
cities were higher on the path internal ethics LBI and higher for people who lived in
the capital cities on the path behavioural beliefs attitudes.
Table 6.41 Standardised structural weights for people living in capital cities/x-city City X-city Attitudes Behavioural beliefs .731 .427 Severity of problems Attitudes -.648 -.638 Importance Attitudes .821 .931 LBI Attitudes .005 .130 LBI Norm beliefs/ subjective norm .104 .069 LBI Internal ethics .599 .828 LBI Moral intensity -.133 .042
The final invariance test for the LBI model compared the answers given by respondents
on the statement “I lead a sustainable lifestyle”. The two invariant groups were those
who said they “agreed or agreed strongly” with those who “disagreed or disagreed
strongly” with this statement. This test demonstrated that there was a significant
difference between these two groups in both the measurement weights (chi2 = 47.018, df
= 15, p= .000) and in the structural weights (chi2 = 56.492, df = 21, p=.000), as shown
in Table 6.42.
Table 6.42 Invariance tests for people who agree/disagree that they lead a
sustainable lifestyle df Chi-square p significance Measurement weights 15 47.018 .000 s Structural weights 21 56.492 .000 s
Table 6.43 indicates that while there was a significant difference overall in the
measurement weights for people who agree/disagree that they lead a sustainable
6.39.5 183BInvariance testing – lead a sustainable lifestyle
239
lifestyle, the individual weights were very similar. The main difference was that people
who agreed that they live a sustainable lifestyle had a higher measurement weight on the
likely sustainable intention construct (Q7_8) “How likely were you to pay a higher price
for sustainable products?”
Table 6.43 Standardised measurement weights for agree or disagree lead
sustainable lifestyle Label Statement Construct Agree Dis-
agree Q7_1 Likely to engage in the home
LBI 0.957 0.946
Q7_2 Likely to engage away from home LBI 0.908 0.881 Q7_8 Likely to pay higher price LBI 0.301 0.608 Q6C_6 Recycling will reduce pollution
Importance 0.837 0.833
Q6C_7 Recycling is important to save natural resources
Importance 0.839 0.951
Q6C_8 Recycling will save land used for landfill Importance 0.892 0.917 Q6A_5 So much electricity Severity of problems 0.767 0.763 Q6A_7 So much water Severity of problems 0.900 0.839 Q6A_8 So many trees
Severity of problems 0.848 0.887
Q6B_1 Damage the environment Behavioural beliefs 0.882 0.823 Q6B_2 Increase cost of water and electricity Behavioural beliefs 0.765 0.638 Q6B_4 Result in climate change Behavioural beliefs 0.785 0.730 Q6AA_16 Close friends think I should live
sustainably Normative beliefs 0.961 0.860
Q6AA_17 Close family members think I should live sustainably
Normative beliefs 0.926 0.949
Q9_3 Overall harm very small (MC) Moral intensity 0.742 0.729 Q9_4 Will not cause harm in future (TI) Moral intensity 0.748 0.813 Q9_6 Behaviour will harm few (CE) Moral intensity 0.772 0.779 Q6C_2 Ethical obligation Internal ethics 0.728 0.761 Q6C_3 Very concerned about sustainable issues
Internal ethics 0.863 0.914
Q6C_4 Very concerned about ethical issues Internal ethics 0.854 0.827 Q6C_5 Very concerned about green issues Internal ethics 0.722 0.868 Q6C_1 Important people think I should adopt
sustainable lifestyle Subjective norm 0.763 0.645
240
The invariance testing demonstrated that for the LBI model, the measurement weights
were significantly different in two of the invariance tests: by the presence of children
aged under 18 years in the household and by respondents’ level of agreement that they
live a sustainable lifestyle. There were significant differences in the structural weights
in three of the invariance tests that were conducted. As well as the structural weights
being invariant by the presence of children aged under 18 years in the household and by
respondents’ level of agreement that they live a sustainable lifestyle, they were also
invariant by ownership of the dwelling.
This demonstrates that for the LBI model there were significant differences between the
antecedents to behavioural intention by people who lived in households with children
aged under 18 years and among respondents’ self-declaration that they live a sustainable
lifestyle. The structure of the antecedents was also invariant by home ownership. These
findings are summarised in Table 6.44.
Table 6.44 Summary of invariance testing for LBI model Measurement weights Structural weights Chi2 df p Chi2 df p Males and females 15 13.246 .583 21 16.716 .728 1+ child U18/no child 15 30.114 .012 21 33.653 .039 Own /don’t own dwelling 15 19.456 .194 21 36.372 .020 City and x-city 15 14.480 .489 21 28.370 .130 Agree/disagree live sustainable lifestyle
15 47.018 .000 21 56.492 .000
6.39.6 184BOverview of the invariance testing for the LBI model
241
The next step was to conduct invariance testing for the lifestyle behaviour and intention
model, as described in the following sections.
To test if there were significant differences in the measurement and structural weights
for the lifestyle behaviour and intention model between males and females, the
invariance test was run. This analysis revealed that there were no significant differences
between males and females, both in the measurement weights (chi2 = 17.956, df = 17,
p=.392,) and in the structural weights (chi2 = 22.876, df = 20, p=.295), as shown in
Table 6.45.
Table 6.45 Invariance tests for males and females df Chi-square p significance Measurement weights 17 17.956 .392 ns Structural weights 20 22.876 .295 ns
Table 6.46 illustrates that the structural weights (standardised regression weights) for
males and females were very similar. The exception was that males had higher
structural weights than females on the path labelled Attitudes importance, where the
difference was 0.262. As these three statements were related to the importance of
recycling to reduce pollution, save natural resources and save land used for landfill, this
suggests that these issues were more important for males than for females.
6.40 107BInvariance testing for lifestyle behaviour and intention model
6.40.1 185BInvariance testing – gender
242
Table 6.46 Standardised regression weights for males and females Male Female Lifestyle intention Lifestyle behaviour .672 .759 Attitudes Behavioural beliefs .591 .557 Severity of problems Attitudes -.642 -.749 Importance Attitudes .935 .673 Lifestyle behaviour Attitudes .097 .239 Lifestyle behaviour Norm beliefs/ subjective norm .130 .167 Lifestyle behaviour Internal ethics .190 .324 Lifestyle behaviour Moral intensity -.171 -.071
The next invariance test was conducted to determine if there were significant
differences in the measurement and structural weights for households with one or more
children aged under 18 years, compared to those with no children aged under 18 years
in the household. Similar to the LBI model, the measurement weights revealed that the
weight for the pathway “Importance Q6C_7” was greater than 1, suggesting that the
model was invalid for these invariant groups as it implied that a negative variance
existed. Analysis of this revealed that the variance of Q6C_7’s error term “e9” was
negative, so the variance for this error term was set to zero (Byrne 2001) and the model
was re-run. A review of the standardised measurement weights in the modified model
indicated that there were no weights that were greater than 1. This analysis is based on
the revised model.
The invariance test on the revised model demonstrated that there was a significant
difference both in the measurement weights (chi2 = 39.049, df = 17, p = 0.002) and in
the structural weights (chi2 = 41.948, df = 20, p = 0.003). This meant that there was a
difference in the relationships between the constructs. These findings are summarised in
Table 6.47.
Table 6.47 Invariance tests for people with child/no child under 18 in household df Chi-square p significance Measurement weights 17 39.049 .002 s Structural weights 20 41.948 .003 s
6.40.2 186BInvariance testing – child under 18 and no child under 18
243
There were two main differences in the individual measurement weights for these two
groups. People living in households with one or more children aged under 18 had
significantly higher standardised measurement weights (greater than 0.2) on the
statement “In our country, we have so much electricity and water that we do not have to
worry about conservation” (Q6A_5, severity). On the other hand, people in households
with no children had significantly higher measurement weights on the statement “If we
do not adopt a sustainable lifestyle this will increase the cost of water and electricity”
(Q6B_2, behavioural beliefs). These structural weights are shown in Table 6.48.
Table 6.48 Standardised regression weights for households with child under 18 Construct Statement Child
U18 No child
Lifestyle behaviour Lifestyle intention .784 .692 Importance Recycling will reduce pollution .724 .907 Importance Recycling is important to save natural resources 1.00 .901 Importance Recycling will save land used for landfill .935 .901 Severity of problems So much electricity .919 .706 Severity of problems So much water .926 .801 Severity of problems So many trees .823 .898 Behavioural beliefs Damage the environment .779 .858 Behavioural beliefs Increase cost of water and electricity .305 .770 Behavioural beliefs Result in climate change .827 .734 Normative beliefs Close friends think I shd live sustainably .901 .905 Normative beliefs Close family think I shd live sustainably .874 .958 Moral intensity Overall harm very small (MC) .787 .730 Moral intensity Will not cause harm in future (TI) .813 .802 Moral intensity Behaviour will harm few (CE) .778 .786 Internal ethics Ethical obligation .713 .770 Internal ethics Very concerned about sustainable .876 .930 Internal ethics Very concerned about ethical .800 .843 Internal ethics Very concerned about green .888 .856 Subjective norm Important people think I should adopt sustainable
lifestyle .691 .692
An invariance test was conducted to test if there were significant differences in the
measurement and structural weights for people who owned their dwelling, compared to
6.40.3 187BInvariance testing – own /don’t own their dwelling
244
those who did not own their dwelling. “Home ownership” included people who own
their dwelling outright with those that own their dwelling and have a mortgage on their
dwelling (218 respondents). The remainder was renting (93 respondents).
This test demonstrates that there was no significant difference in the measurement
weights (chi2 = 24.160, df = 17, p= 0.115), but that there was a significant difference in
the structural weights (chi2 = 37.166, df = 20, p= 0.011), as shown in Table 6.49.
Table 6.49 Invariance tests for people who own/don’t own their dwelling df Chi-square p significance Measurement weights 17 24.160 .115 ns Structural weights 20 37.166 .011 s
The standardised structural weights for people who own/don’t own their dwelling were
similar. The exception was that the structural weights were higher for people who don’t
own their dwelling on the following pathway: Attitudes importance. These weights
are summarised in Table 6.50.
Table 6.50 Standardised structural weights for people who own their dwelling Own Don’t
own Attitudes Behavioural beliefs .559 .763 Severity of problems Attitudes -.639 -.791 Importance Attitudes .729 .957 Lifestyle behaviour Attitudes .167 .257 Lifestyle behaviour Norm beliefs/ subjective norm .100 .172 Lifestyle behaviour Internal ethics .218 .256 Lifestyle behaviour Moral intensity -.212 .013
To test if there were significant differences in the measurement and structural weights
for people living in capital cities (city) and outside the capital cities (x-city), the
invariance test was conducted. This test indicated that there was no significant
difference between people living in capital cities and outside the capital cities, both in
6.40.4 188BInvariance testing – city and x-city
245
the measurement weights (chi2 = 22.171, df = 17, p= 0.178) and in the structural
weights (chi2 = 28.368, df = 20, 0.101), as shown in Table 6.51.
Table 6.51 Invariance tests for people living in capital cities (city) and outside
capital cities (x-city) df Chi-square p significance Measurement weights 17 22.171 .178 ns Structural weights 20 28.368 .101 ns
Table 6.52 demonstrates that the structural weights for people living in capital cities
(city) and outside the capital cities (x-city) were similar. The exceptions were that the
weights for people living in the capital cities were higher on the paths between
behavioural beliefs attitudes and for attitudes lifestyle behaviour.
Table 6.52 Standardised structural weights for people living in capital cities/x-city City x-city Attitudes Behavioural beliefs .720 .454 Severity of problems Attitudes -.678 -.678 Importance Attitudes .799 .873 Lifestyle behaviour Attitudes .272 -.003 Lifestyle behaviour Norm beliefs/ subjective norm .138 .111 Lifestyle behaviour Internal ethics .258 .258 Lifestyle behaviour Moral intensity -.167 -.090
The final invariance test compared the answers given by respondents who said they
“agreed or agreed strongly” (codes 6 and 7) with those who “disagreed or disagreed
strongly” (codes 1 and 2) on the statement “I lead a sustainable lifestyle”. This test
demonstrated that there was a significant difference between these two groups in the
measurement weights (chi2 = 40.912, df = 17, p= .001) and in the structural weights
(chi2 = 45.042, df = 20, p=.001), as shown in Table 6.53.
6.40.5 189BInvariance testing – lead a sustainable lifestyle
246
Table 6.53 Invariance tests for lead a sustainable lifestyle df Chi-square p significance Measurement weights 17 40.912 .001 s Structural weights 20 45.042 .001 s
Table 6.54 indicates that while there was a significant difference in the measurement
weights for people who agree/disagree that they lead a sustainable lifestyle, the
individual weights were very similar.
Table 6.54 Standardised measurement weights for lead a sustainable lifestyle Label Statement Construct Agree Dis-
agree Life behaviour
Lifestyle intention Lifestyle behaviour 0.762 0.694
Q6C_6 Recycling will reduce pollution Importance 0.836 0.833 Q6C_7 Recycling is important to save
natural resources Importance 0.842 0.952
Q6C_8 Recycling will save land used for landfill
Importance 0.890 0.916
Q6A_5 So much electricity Severity of problems 0.766 0.762 Q6A_7 So much water Severity of problems 0.897 0.839 Q6A_8 So many trees Severity of problems 0.850 0.888 Q6B_1 Damage the environment Behavioural beliefs 0.883 0.823 Q6B_2 Increase cost of water and
electricity Behavioural beliefs 0.763 0.639
Q6B_4 Result in climate change Behavioural beliefs 0.787 0.731 Q6AA_16 Close friends think I should live
sustainably Normative beliefs 0.958 0.863
Q6AA_17 Close family members think I should live sustainably
Normative beliefs 0.929 0.946
Q9_3 Overall harm very small (MC) Moral intensity 0.740 0.737 Q9_4 Will not cause harm in future (TI) Moral intensity 0.758 0.811 Q9_6 Behaviour will harm few (CE) Moral intensity 0.764 0.773 Q6C_2 Ethical obligation Internal ethics 0.713 0.749 Q6C_3 Very concerned about sustainable
issues Internal ethics 0.867 0.917
Q6C_4 Very concerned about ethical issues
Internal ethics 0.865 0.823
Q6C_5 Very concerned about green issues Internal ethics 0.718 0.875 Q6C_1 Important people think I should
adopt sustainable lifestyle Subjective norm 0.763 0.644
247
The invariance testing demonstrated that the measurement weights were significantly
different in two of the invariance tests within the lifestyle behaviour and intention
model: by the presence of children aged under 18 years in the household and by
respondents’ level of agreement that they live a sustainable lifestyle. There were
significant differences in the structural weights for three of the invariance tests that were
conducted: by the presence of children aged under 18 years in the household, by
dwelling ownership and by respondents’ level of agreement that they live a sustainable
lifestyle.
These findings are summarised in Table 6.55, with the significant differences
highlighted in grey.
Table 6.55 Summary of invariance testing for lifestyle behaviour and intention Measurement weights Structural weights Chi2 df p Chi2 df p Males and females 17 17.956 .392 20 22.876 .295 1+ child U18/no child 17 39.049 .002 20 41.948 .003 Own /don’t own dwelling 17 24.160 .115 20 37.166 .011 City and x-city 17 22.171 .178 20 28.368 .101 Agree/disagree live sustainable lifestyle
17 40.912 .001 20 45.042 .001
6.40.6 190BOverview of the invariance testing for lifestyle model
248
The objective of this chapter was to summarise and test the theoretical models based on
the data collected from the sample of 511 Australians aged 18 years and over. The
demographics of this sample closely matched the demographics of the Australian
population as documented by the ABS. Most of the sample had an environmentally
friendly attitude and about half agreed that they lead a sustainable lifestyle. Most ranked
“lack of water” as one of the most important issues facing Australia today. The next
most important issues were climate change, greenhouse emissions and pollution, and
loss of species.
The three theoretical frameworks for this study theorised that sustainable behaviour and
intention was determined by five latent exogenous constructs. These five constructs
were behavioural beliefs and attitudes, control beliefs and perceived behavioural control
(PBC), subjective norm/personal normative motives (PNM)/normative beliefs, internal
ethics and moral intensity. The three theoretical frameworks were derived specifically
for the three measures of sustainable behaviour and intention that were labelled “likely
behavioural intention” (LBI), lifestyle behaviour and intention, and capital behaviour
and intention.
The EFA established that the “capital intention” and “capital behaviour” constructs
were not reliable determinants of sustainable intention and behaviour and they were
removed from the analysis. The findings of the EFA also suggested the removal of four
statements from the constructs that were to be tested in the CFA. One was removed
from the control beliefs construct and three from the moral intensity construct.
The CFA revealed that a total of five more statements needed to be removed from the
exogenous constructs, due to their low modification indices and high standard residual
covariances. One statement was removed from each of the constructs that were labelled
severity, behavioural beliefs, PBC, PNM and LBI. In the resulting measurement
models, the descriptive fit indices were quite strong as all constructs had CFI values
6.41 108BChapter summary
249
above 0.986, GFI above 0.969 and AGFI above 0.928. The RMSEA values were all less
than 0.62 except for the “PNM/norm beliefs/subjective norm” construct, and the RMR
values were all less than 0.053.
The initial SEM analyses based on the theoretical models for LBI and lifestyle
behaviour and intention were a poor fit to the data. For both models, subsequent
analysis demonstrated that the effects of PBC and control beliefs on the model were not
significant and these constructs were removed from the analysis. In addition, the effect
of PNM which was also shown to be not significant was removed from the analysis, and
the construct was renamed “subjective norm and normative beliefs”. This established
that in the sustainable context, the effects of control beliefs, PBC and PNM were not
determinants of either LBI or of lifestyle behaviour and intention.
The final structural models confirmed that sustainable behavioural intention can be
measured by two constructs – likely sustainable behavioural intention (LBI) and
lifestyle behaviour and intention – and that lifestyle behaviour is an antecedent to
lifestyle intention. The LBI construct was best measured by internal ethics; while
lifestyle behaviour was explained by all four exogenous constructs, namely, attitudes,
normative beliefs and subjective norm, internal ethics and moral intensity. While the
effect of moral intensity on lifestyle behaviour was negative, the other relationships
were positive.
Overall the findings demonstrated that the invariance tests were very similar for the two
models. In both instances, the measurement weights were significantly different by the
presence of children aged under 18 years in the household and by respondents’ level of
agreement that they live a sustainable lifestyle. There were significant differences in the
structural weights for three of the invariance tests that were conducted: by the presence
of children aged under 18 years in the household, by dwelling ownership and by
respondents’ level of agreement that they live a sustainable lifestyle.
The final chapter includes a discussion and reflection of the findings as they relate to the
literature. It also discusses the managerial implications and includes suggestions for
further research directions.
250
Chapter 7: 6BDiscussion, recommendations and conclusions
This chapter discusses and reflects on the findings presented in chapter 6 and relates
them to the theory presented in chapters 2 and 3. They are discussed in reference to the
theoretical frameworks, research questions and hypotheses presented in chapter 4, using
the research methodology and design presented in chapter 5. The chapter concludes
with a discussion about the managerial implications of the research study and
recommends further research directions.
The three theoretical frameworks for this study were based on an extended version of
Ajzen’s (1985) Theory of Planned behaviour (TPB). The three endogenous constructs
for this study are likely behavioural intention (LBI), lifestyle behaviour and intention,
and capital behaviour and intention. Three of the exogenous constructs were based on
the TPB and the additional three constructs were based on the extant literature. The
three constructs and their antecedents that were based on the TPB were behavioural
beliefs and attitudes, normative beliefs and subjective norm, and control beliefs and
perceived behavioural control (PBC). The three additional constructs were personal
normative motives (PNM), internal ethics and moral intensity. These endogenous
constructs were used to examine the determinants of the Australian population’s
behaviours and intentions with respect to sustainable behaviours.
Four research questions were articulated and 17 research objectives and 17 hypotheses
were developed to understand the effects of the latent exogenous constructs on each of
the endogenous behaviour and intention constructs. The findings were based on a total
sample of 511 Australian respondents, which was randomly split for the analysis. The
EFA was based on the calibration sample of 200 respondents, while the CFA and SEM
were based on the validation sample of 311 respondents.
Figure 7.1 presents a roadmap of chapter 7.
7.1 109BIntroduction
251
Figure 7.1 Roadmap of chapter 7
Source: Adapted from Perry (1995)
Chapter 7: Discussion,
recommendations and
conclusions
Contribution to theory
Exogenous constructs
Revisiting the theoretical models
Behaviour and intention constructs
Further research directions
Revisiting the research questions and
hypotheses
Interrelationships between the
exogenous constructs
Conclusions
Limitations of the study
252
After a rigorous process of EFA, CFA and SEM, the final theoretical models were
developed. This analysis established that two of the three latent endogenous behavioural
intention constructs were significant measures of sustainable behavioural intention.
These were “likely behavioural intention” (LBI) and “lifestyle intention”. LBI was
measured by asking respondents four questions that related to how likely they were to
perform sustainable behaviours; while lifestyle behaviour and intention was measured
by asking which behaviours had been done and which were likely to be done in the next
two weeks.
In the original theoretical frameworks, three of the exogenous normative constructs
were combined to form the one construct called “normative beliefs, subjective norm and
personal normative motives”. In the process of conducting the CFA and the SEM,
personal normative motives (PNM) was deleted due to its poor ability to predict
sustainable behaviour and intention. The construct was renamed “subjective norm and
normative beliefs” in the final SEM. Based on the CFA, perceived behavioural control
(PBC) and control beliefs (the antecedent to PBC) were also not included in the final
SEM due to their poor ability to predict sustainable behaviour and intention.
The final two theoretical models demonstrated that there were four latent exogenous
constructs that were determinants of behaviour and intention: attitudes (and their
antecedents called behavioural beliefs), subjective norm and normative beliefs, internal
ethics and moral intensity. Closer examination revealed that internal ethics was the only
significant determinant of LBI, while attitudes, subjective norm and normative beliefs,
internal ethics and moral intensity were all significant determinants of lifestyle
behaviour. In the lifestyle model, lifestyle behaviour was a significant determinant of
lifestyle intention.
7.2 110BRevisiting the theoretical models
253
The analysis also demonstrated two negative relationships in the final lifestyle model:
for the effect of moral intensity on lifestyle behaviour and for “severity of problems” on
attitudes. The effect of the other constructs on lifestyle behaviour was positive.
Figure 7.2 summarises the findings for LBI, and describes the constructs as measured
by the statements. It shows that internal ethics was the only determinant of LBI.
Figure 7.2 Overall conclusions for LBI
Source: Developed by the author
Internal ethics – ethical obligation
and concerned about sustainable,
green and ethical issues
Likely behavioural intention
(LBI) – likely to engage in
sustainable behaviours in and
away from home, and pay a
higher price for sustainable
products
254
Figure 7.3 summarises the findings for lifestyle behaviour and intention, and describes
the constructs as measured by the statements. It shows that attitudes, normative beliefs
and subjective norm, moral intensity and internal ethics were all significant
determinants of lifestyle behaviour, and that lifestyle behaviour was the antecedent to
lifestyle intention.
Figure 7.3 Overall conclusions for lifestyle behaviour and intention
Source: Developed by the author
Behavioural beliefs, we need to
adopt a sustainable lifestyle
Attitudes – the issues are severe
and it is important to recycle
Normative beliefs and subjective
norm – friends, family and
important people think I should
adopt a sustainable lifestyle
Internal ethics – ethical obligation
and concerned about sustainable,
green and ethical issues
Moral intensity – the
consequences of not behaving
sustainably were small, there will
be no harm in the immediate
future, and this behaviour will
harm few people
Lifestyle behaviour – recycle
household wastes, turn off
electricity and save water,
restrict use of plastic bags, and
use energy efficient appliances
Lifestyle intention – recycle
household wastes, turn off
electricity and save water,
restrict use of plastic bags, and
use energy efficient appliances
255
The following sections examine each of the constructs in the theoretical frameworks and
their role in explaining sustainable behaviour and intention as this relates to the
literature. The discussion begins with an analysis of the first research aim which was to
understand which latent exogenous constructs were the best predictors of sustainable
behaviour and intention.
In the original theoretical frameworks for this research study, there were a total of seven
exogenous constructs that were included as independent variables. This discussion
begins with an analysis of the findings that relate to behavioural beliefs and attitudes
and their effect on the latent endogenous constructs.
Behavioural beliefs refer to a person’s beliefs about the impact of doing (or not doing)
something and determine their attitudes towards a behaviour (Vitell & Patwardhan
2008). Attitudes reflect “an individual’s personal beliefs, positive or negative, about
enacting a target behaviour” (Hagger & Chatzisarantis 2006, p. 731). The strong
relationship between behavioural beliefs and attitudes in this study concurs with the
findings of Ajzen and Fishbein (1980), Sparks et al. (1995), Chang (2000), Routhe et al.
(2005), Chedzoy and Burden (1999) and Hughes, Ham and Brown (2009b) who found
that behavioural beliefs are antecedents to attitudes.
The behavioural beliefs measured in this study demonstrate that there is a strong feeling
among Australians in general that the community needs to work towards adopting a
sustainable lifestyle. There was a genuine concern that current unsustainable behaviours
are accelerating climate change, damaging the environment for future generations and
will ultimately result in an increase in the cost of water and electricity. Comparing the
findings of this study and Routhe et al.’s (2005) study with respect to behavioural
7.3 111BExogenous constructs
7.3.1 191BBehavioural beliefs
256
beliefs and building a new dam, slightly more of the variance in attitudes was explained
by behavioural beliefs in the current study (58% for LBI and 59% for lifestyle
behaviour) compared to Routhe et al.’s study (44%). While both studies demonstrate the
link between behavioural beliefs and attitudes, it can be deduced that behavioural
beliefs with respect to the environment were slightly stronger in the sustainable context,
than in relation to building a new dam.
Attitudes were influenced by three latent constructs that referred to the “importance” of
recycling, the “inconvenience” of being environmentally friendly and the “severity” of
environmental problems (Laroche, Bergeron & Barbaro-Forleo 2001). These highlight
the realisation in the community about the severity of environmental issues and also
emphasise the understanding that recycling has three important outcomes: to reduce
pollution, save natural resources and save land that would be used for landfill or
rubbish. While this study has reinforced the strength of the “importance of recycling”,
in particular, it also demonstrates that, as attitudes explained only about one-third of the
variance in both models, more work is needed to improve the ability of this construct to
explain behaviour and intention.
These findings confirmed the strength of the “importance of recycling” construct and
the “severity” of environmental problems as important attitudinal constructs, in
accordance with the findings of Laroche et al. (2001). However, the “inconvenience”
construct based on Laroche et al.’s. (2001) study was not a reliable predictor of attitudes
related to sustainability and was omitted from the final models. This suggests that
Australian consumers do not see tasks such as recycling or trying to control pollution as
“inconvenient”. Given that Laroche et al.’s (2001) sample included only people who
were “willing to pay more for environmentally friendly products” and that it was
conducted about 10 years ago, this may reflect a behavioural change over time.
7.3.2 192BAttitudes
257
The findings from the EFA in this research study were similar to the EFA loadings
reported in Laroche et al.’s (2001) study for the severity and importance constructs. The
current study has demonstrated slightly higher Cronbach alpha scores, as summarised in
Table 7.1.
Table 7.1 Comparing attitudes in this study and Laroche et al. (2001) Construct and Items
Loading (Pattern) This study
Loading (Pattern) Laroche et al. (2001)
Cron-bach Alpha This study
Cron-bach Alpha Laroche et al. (2001)
Severity
In our country, we have so much electricity and water that we do not have to worry about conservation
.924 .825 0.890 0.870
++Since we live in such a large country, any pollution that we create is easily spread out and therefore of no concern to me
.800 .812
With so much water in this country, I don’t see why people are worried about saving water
.809 .811
Our country has so many trees that there is no need to recycle paper
.716 .749
++The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state
.765 .623
Importance
Recycling will reduce pollution .796 .733 0.898 0.650
Recycling is important to save natural resources .862 .729
Recycling will save land that would be used for landfill/rubbish
.919 .605
++ These statements were not included in the final SEM
It was interesting to note that the effect of respondents’ attitudes on their LBI was
significantly stronger for people who live in the capital cities (p<0.05). This suggests
that in the capital cities there is a strong belief about the need to adopt a sustainable
lifestyle both at home and away from home. Not surprisingly, there was a strong
relationship between behavioural beliefs and attitudes and the sample’s self-reporting of
their agreement that they lead a sustainable lifestyle. It seems that people who are
committed to a sustainable lifestyle could early adopters of sustainable products and
services.
258
The effect of attitudes on lifestyle behaviour was particularly strong among people
living in households with children aged under 18 years. This concurs with Granzin and
Olsen (1991) and Brooker (1976) who concluded that the presence of children was a
significant determinant of behaviour with respect to the environment. In this case, it
seems that the presence of children aged under 18 years increases the likelihood that
households will engage in sustainable behaviours such as recycling, turning off
unnecessary lights and using non-phosphate detergents, possibly due to pressure from
their children.
In summary, this research study confirmed the findings that demonstrated the link
between behavioural beliefs and attitudes and behavioural intention (Ajzen & Fishbein
1980; Pickett-Baker & Ozaki 2008; Sparks, Shepherd & Frewer 1995). It seems that
Australians’ attitudes towards sustainability are partly explained by how severe and how
important they believe the issues are, in particular, with respect to saving water and
electricity, recycling paper and other products to reduce pollution, saving natural
resources and reducing the number of landfills. They believe that such measures result
in more positive than negative outcomes, particularly with respect to protecting the
environment and reducing the impact of climate change for future generations. This
reinforces the success of recent campaigns that have encouraged such behaviours and
suggests that some consumers may be ready to adopt a greater range of sustainable
behaviours in their daily lives.
Marketers need to change consumers’ attitudes with respect to the severity of
environmental problems and the importance of recycling so that they can influence
sustainable decision making with respect to their lifestyle sustainable behaviours.
Wall, Devine-Wright and Mill (2007) suggested that personal-normative motives
(PNM) be added to the TPB to explain the fact that behaviours that reduce personal
utility such as by decreasing convenience, may be perceived as difficult and therefore
7.3.3 193BPersonal normative motives
259
not achievable. Personal norms refer to feelings of obligation and responsibility as they
are activated by an awareness of the consequences of behaviours and beliefs about
personal responsibility for the consequences.
In this study, PNM was measured by asking respondents if they felt personally
responsible and morally obliged to take measures to help protect the environment. Most
agreed with the statements that measured PNM, with females significantly more likely
to do so than males (p<0.01). However, the effect on PNM on behaviour and intention
in the theoretical models was not significant and therefore this construct was removed
before the final SEM was performed. This indicates that in the sustainable context, the
effect of PNM on behaviour and intention was not significant. This demonstrates that
people in the sample do not consider that sustainable behaviours are difficult to adopt,
possibly because they do not believe that the consequences of not adopting these
behaviours are serious.
The normative constructs were included in this study as Spaargaren (2003) noted that
sustainable behaviour is a personal choice that is largely based on social norms, and
Bayne (2006) commented on the social pressure that exists to undertake (or not)
sustainable behaviours. Normative beliefs measure whether particular referents (such as
family and friends) think the respondent should or should not do the action in question
(Pickett-Baker & Ozaki 2008). They are the antecedent to subjective norm which was
described as “a function of the individual’s normative beliefs about whether salient
referents think he or she should engage in the behaviour and motivations to comply with
these referents” (Dubinsky & Loken 1989, p. 85).
Most of the sample was ambivalent about subjective norm and normative beliefs, as
they expressed an opinion of “neither agree nor disagree” with the statements measuring
these constructs. In other words, they were not committed to the idea that most people
who were important to them think they should adopt a sustainable lifestyle and that their
7.3.4 194BSubjective norm and normative beliefs
260
close friends and family members think that they should live sustainably. However,
those who said that they lead a sustainable lifestyle and those who agreed or agreed
strongly that they were environmentally friendly were more likely to agree or agree
strongly that most people who were important to them think they should adopt a
sustainable lifestyle. Similarly, people living in households with no children aged under
18 years were significantly more likely to agree that their close family members think
that they should live sustainably (p<0.05).
Despite most people being uncommitted to these two constructs, they were shown to be
important determinants of lifestyle behaviour and intention, particularly the statements
measuring normative beliefs. However, subjective norm and normative beliefs were not
significant determinants of LBI. This study concurred with the findings of Spaargaren
(2003), Bayne (2006) and Pickett-Baker and Ozaki (2008) who demonstrated the strong
normative influences from family and friends with respect to ethical and sustainable
behaviours for actual behaviours done, but this did not hold for the LBI dependent
construct. Of interest is the high RMSEA value (.110) for this construct. The RMSEA
index measures how well the model would fit the population covariance matrix, if it
existed, thus indicating that a model has produced a reasonable approximation of the
data. This high RMSEA value suggests that despite normative beliefs and subjective
norm being important determinants of lifestyle behaviour and intention, that more work
is needed to reduce the RMSEA values.
Contrary to the findings of Pickett-Baker and Ozaki (2008), this study did not
demonstrate that the presence of children aged under 18 in the household had any
influence on the statement “My close family members think that I should live
sustainably”.
This research study supports the inclusion of subjective norm and normative beliefs as
determinants of sustainable behavioural intention and identifies that the construct had a
strong predictive power when normative beliefs and subjective norm were combined. In
particular, this demonstrates the importance of acknowledging peer group pressure from
friends and family in the uptake of sustainable behaviours. These findings concur with
research by authors such as Ajzen and Fishbein (1980) and Routhe et al. (2005) who
261
showed that intention to behave in a particular way can be influenced by a person’s
belief about what important others think that they should or should not do. Extending
this finding, this research study has confirmed Hagger and Chatzisarantis’ (2006)
finding that if both the attitude and the subjective norm were favourable, there was a
greater likelihood that the person will intend to perform the behaviour in question. But,
in this study, this finding applied only to lifestyle behaviour, as the association between
subjective norm and normative beliefs with LBI was not significant.
Perceived behavioural control (PBC) reflects the ease of performing an action (Routhe,
Jones & Feldman 2005, p. 886) and refers to how easy or difficult a person believes this
is likely to be (Shaw, Shiu & Clarke 2000). Kraft et al. (2005) described these two
components of PBC as “self-efficacy” or “perceived difficulty” and “controllability” or
“perceived control”. Linking this to pro-environmental actions, Jones (1991) found that
PBC reveals public perceptions of institutional barriers to action. This was based on the
theory that consumers who lack the necessary confidence or opportunities to perform a
particular behaviour were unlikely to form strong behavioural intentions despite the fact
that their attitude and subjective norm may be favourable (Pickett-Baker & Ozaki
2008).
In analysing the findings relating to the PBC construct from this research study,
respondents generally agreed that it was completely up to them whether or not they
adopted a sustainable lifestyle and believed that they had full control over whether or
not they could do so. There was also a level of agreement with the statement that
respondents would not have problems in adopting a sustainable lifestyle if they wanted
to and a slight perception that it would be difficult for other people to adopt a
sustainable lifestyle.
Control beliefs, which were the antecedents of PBC, were measured by asking
respondents to say which of the following affected whether or not they adopted a
7.3.5 195BPerceived behavioural control and control beliefs
262
sustainable lifestyle, using a dichotomous scale: availability of sustainable products,
cost of sustainable products, amount of information available about sustainable products
and quality of sustainable products. The cost of sustainable products had the largest
influence, with 87% of the sample giving this answer. This was followed by quality
(76%) and availability (69%) of sustainable products and amount of information
available (62%). While there was little difference between males and females and where
people live, people who agreed or agreed strongly that they lead a sustainable lifestyle
and who were environmentally friendly were more likely to be concerned about the
amount of information available. People who considered that they were environmentally
friendly were more concerned about availability, while those who did not consider
themselves to be environmentally friendly were more concerned about cost.
The EFA and CFA showed that the total effect of control beliefs on PBC was weak and
the SEM revealed that the PBC construct was not predictive of sustainable behavioural
intention. Therefore, while some authors such as Chang (2000) found that PBC was the
most important construct when predicting unauthorised software copying, this study
concurred with Routhe et al. (2005) who reported that “perceived control” was not a
significant predictor of public support for building a new dam. In other words, in the
sustainable context, PBC was not predictive of any of the three behavioural intention
constructs. This supported Routhe et al. (2005) who commented that “theoretically
speaking this was not an expression of environmental concern since it reflects
perceptions of the ease of performing an action”. It seems that the effect of PBC can
depend on the type of ethical behaviour being measured.
Ethical obligation represents an individual’s internalised ethical rules which reflect their
beliefs about what is right or wrong, and self-identity accounts for the fact that ethical
issues were not considered in isolation (Shaw & Shiu 2002). Based on studies by Shaw
and associates, ethical obligation and self-identity were combined to form the one
construct called “internal ethics”.
7.3.6 196BInternal ethics
263
Most of the sample “agreed slightly” or “agreed” with the statements measuring internal
ethics. While there were few differences within the sample for the statement “I think of
myself as someone who is very concerned about sustainable issues”, females rated the
statement “I feel that I have an ethical obligation to live sustainably” significantly
higher than males (p<0.01). Of the four statements that measured this construct, “I think
of myself as someone who is very concerned about sustainable issues” explained the
greatest amount of variance.
This research study confirmed the significant effect that internal ethics has on
behavioural intention, as demonstrated by Sparks et al. (1995), Shaw and Shiu (2002)
and Chedzoy and Burden (1999). It extends this by demonstrating that internal ethics
has a significant effect on both LBI and lifestyle behaviour. In addition, people living
outside the capital cities had a higher weight on the path between internal ethics and
LBI, and people with children aged under 18 years had a significantly higher weight on
the path between internal ethics and lifestyle behaviour. In summary, this demonstrates
that, with respect to sustainable behaviours and intention, Australians believe that they
have an ethical obligation to live sustainably as they are concerned about sustainable,
ethical and green issues.
Moral intensity is “the extent of issue-related moral imperative in a situation” (Jones
1991, p. 372). Jones’ (1991) original “issue contingent” model described the
relationship between moral intensity and the moral or ethical decision-making process
and this has been confirmed in subsequent studies (Paolillo & Vitell 2002; Singhapakdi
et al. 1999; Singhapakdi, Vitell & Kraft 1996). Importantly for this study, Singhapakdi,
Vitell et al. (1996), May and Pauli (2002), Tanner and Kast (2003) and McMahon and
Harvey (2006) used the moral intensity construct to demonstrate that a feeling of moral
obligation is a powerful motivator of environmental behaviour.
7.3.7 197BMoral intensity
264
Moral intensity requires the development of a scenario that depicts the issue being
investigated and then respondents are asked to rate the scenario on six dimensions. The
scenario for this study was based on McMahon and Harvey’s (2006) study, and a
fictitious family called the “Watson’s” were described as being very wasteful in their
daily lives. For the scenario presented in this research study, moral intensity was best
described by three of the six dimensions of moral intensity, which were labelled
concentration of effect (CE), temporal immediacy (TI) and magnitude of consequences
(MC). This was similar to Singhapakdi et al.’s. (1996) findings who suggested a two
factor structure for moral intensity and labelled the first factor “harm” which included
MC, PE, TI and CE.
This demonstrates that there is a strong relationship between the “anti-sustainable”
behaviour by the Watson family and the feeling that their actions would have a high
magnitude of consequences. The level of disagreement with the “temporal immediacy”
statement indicates a feeling that we need to protect the environment now, and the
“concentration of effect” demonstrates that their actions are perceived to have the
potential to harm other people. This suggests that for this scenario, the overall harm of
these actions was considered to be small when compared to the “big picture” of the
whole environment. The strength of the moral intensity construct in explaining
sustainable behaviour was only confirmed by this study to a certain extent. While this
construct was a significant predictor of lifestyle behaviour (p<0.05), it was not a
significant predictor of LBI.
In conclusion, this research confirms that the moral intensity construct influences
ethical decision making in different ways, depending on the nature of the ethical and
moral issue being addressed and on the scenario used. It also confirms the importance of
emphasising that there is an expectation that people have a moral obligation to behave
in a manner that is agreeable to others.
265
The original TPB demonstrated that attitudes, PBC and subjective norm were
antecedents to behavioural intention, but it gave no indication of the interrelationships
that can also exist between these three constructs. Subsequent studies have indicated
that interrelationships can also exist between attitudes and PBC and subjective norm
(Follows 2000; Hughes, Ham & Brown 2009a; Vallerand et al. 1992; Wall, Devine-
Wright & Mill 2007; Whiteman 1999).
While this study has established the link that exists between attitudes and behavioural
beliefs with normative beliefs and subjective norm, it has also demonstrated that the
four exogenous constructs in both of the final SEM models were all significantly
correlated to each other. In other words, there is a link between the effects of
behavioural beliefs and attitudes, with normative beliefs and subjective norm, and
internal ethics and moral intensity. This demonstrates that there is a connection between
a person’s concerns about the environment, their attitudes towards sustainability and
recycling, the influence of close friends and family, and self-identity and moral
intensity. It seems that changing even one of these constructs will have a flow-on effect
in the strengthening of the others, and that this would improve the incidence of
sustainable behaviour and intention, and inevitably the future adoption of sustainable
behaviours. However, this study has not demonstrated the interrelationships that exist
between these constructs and PBC or PNM, as they were not included in either of the
final SEM models.
Three of the constructs that were included in the original theoretical frameworks for this
research study were measures of sustainable behavioural intention and two were
measures of actual behaviours done in the past. These endogenous constructs were
7.4 112BInterrelationships between the exogenous constructs
7.5 113BBehaviour and intention constructs
266
included in this study to understand the second aim which was to determine how to
measure sustainable behaviour and intention.
In the first instance, the measures of lifestyle and capital behaviour and intention were
included to determine which of these measures of examples of actual behaviours were
most applicable to studies of sustainable behaviours. The discussion begins with the
identification and classification of capital and lifestyle behaviours.
In choosing which sustainable behaviours needed to be measured in this study,
consideration was given to choosing those that related to individual consumers in their
daily lives. The examples were sourced from a variety of refereed and non-refereed
sources. Of particular interest was the work done by authors such as Granzin and Olsen
(1991), Ouellette and Wood (2000), Petts et al. (1998), Laroche et al. (2001), Tan
(2002), Shaw and Shiu (2003), Spaargaren (2003), Jackson (2005), Kraft et al. (2005),
Voronoff (2005), Hagger and Chatzisarantis (2006) and Peattie and Peattie (1997) who
included different kinds of sustainable behaviours in their studies. These included using
non-phosphate detergents, avoiding throw-away plastic bags and packaging, recycling
household wastes, taking a shorter shower, installing tanks and solar systems and using
bicycles, public transport or walking for short-distance travel.
Once a list of sustainable behaviours that related to the consumer’s daily lifestyle was
compiled, the author proposed that these be classified into “capital” and “lifestyle”
behaviours. For the purposes of this research, lifestyle behaviours were defined as those
that required little or no capital outlay, and capital behaviours as those that required a
more substantial capital outlay. The questionnaire included nine capital behaviours and
13 lifestyle behaviours, measured using a dichotomous (yes/no) measurement.
Based on the percentage of respondents who had already done or who intended to do
each of the behaviours included in the survey, the analysis reveals that the capital and
7.5.1 198BClassifying capital and lifestyle behaviours
267
lifestyle behaviours can be divided into three adoption categories: those that most
consumers had done, those that were likely to be done in the future and those that were
unlikely to be done.
The “behaviours done” category included behaviours that at least 66% of the sample
had done. The “likely to do this behaviour” category included behaviours that had been
done by about one in five respondents or were likely to be done in the next two years by
at least 15% of the sample, and behaviours where there were more people who intended
to do them in the next two weeks than the number who had done them in the last two
weeks. The “unlikely to do this behaviour” category included behaviours that had a very
low incidence (less than 5%) of current use or intention to do in the next two years.
The definitions of these three categories for both capital and lifestyle behaviours are
summarised in Table 7.2.
Table 7.2 Adoption categories for capital and lifestyle behaviours Behaviour done Likely to do this behaviour Unlikely to do this
behaviour Capital behaviours
Behaviours already done by the majority (over two-thirds) of the sample.
Behaviours that had been done by about one in five respondents or were likely to be done in the next two years by at least 15% of the sample
Behaviours that had a very low incidence of current use or intention to do in the next two years. These behaviours had an incidence of less than 5%.
Lifestyle behaviours
Behaviours done in the last two weeks by the majority (over two-thirds) of the sample.
Behaviours where there were more people who intended to do them in the next two weeks than the number who had done them in the last two weeks
Behaviours that had a very low incidence of current use or intention to do in the next two weeks. These behaviours had an incidence of less than 5%.
In the literature review, the author proposed that the sustainable behaviours in this study
could be classified into categories by adapting Spaargaren’s (2003) Social practices
classification. The four categories that best described the behaviours measured in this
study were “housing and sustainability at home”, “food and shopping”, “transport” and
“actions” that a person could take to reduce consumption or to influence other people’s
behaviours. To add value to this classification, the definitions from Table 7.2 have also
been included in the revised “Sustainable behaviours classification”, resulting in Table
7.3. This demonstrates that all capital behaviours fell into the “housing and
sustainability at home” category. For example, energy efficient lighting, dual flush
268
toilets and water efficient shower heads fell into the category of “behaviours done” by
over 66% of the sample, while double-glazing windows and doors fell into the category
of “unlikely to do this behaviour”.
The lifestyle behaviours included examples in each of the four classifications, namely
“housing and sustainability at home”, “food and shopping”, “transport” and “actions”,
and in each of the three adoption categories. For example, “recycled household wastes”,
“turned off lights and electrical goods that were not necessary”, “tried to save water”
and “used energy efficient appliances” fell into the categories of “housing and
sustainability at home” and “behaviours done”. “Lobbied or took direct action about an
issue or brand or product” fell into the categories of “actions” and “unlikely to do this
behaviour”, as shown in Table 7.3
Table 7.3 The sustainable behaviours classification New classification
Capital or lifestyle behaviours
Behaviours done
Likely to do this behaviour
Unlikely to do this behaviour
Housing and sustain-ability at home
Capital behaviours
Energy efficient lighting Dual flush toilets Water efficient shower heads
Rain water tank(s) Front loader washing machine Dripper system in the garden Recycling/grey water system Solar hot water or solar electricity panels or solar heating
Double-glazing windows and doors
Lifestyle behaviours
Recycled household wastes, e.g. compost, newspapers, bottles Turned off lights/electrical goods that were not necessary Tried to save water Used energy efficient appliances
Used non-phosphate detergents Had a shower for more than four minutes (reversed)
Food and Shopping
Lifestyle behaviours
Restricted my use of plastic bags when shopping
Bought free range or organic products or fair trade products
Transport Lifestyle behaviours
Used public transport rather than driving
Actions Lifestyle behaviours
Thought about reducing my greenhouse emissions Tried to reduce what I buy and use Bought or did something positive to encourage sustainable behaviour
Lobbied or took direct action about an issue or brand or product
269
Analysis of the lifestyle and capital behaviours indicated that current campaigns in
Australia to get households to install energy efficient lighting, dual flush toilets and
water efficient shower heads have largely been successful. There were still many
households in the “likely” category that intended to install rain water tanks, front loader
washing machines, dripper systems in the garden, recycling/grey water systems and
solar hot water, solar electricity panels or solar heating in the near future. Promotions
are needed to encourage more households to take this step. This is not an impossible
task, because at least 15% of households intend to do so in the next two years.
Double-glazing was an unlikely behaviour, as only 4% of the sample had already
installed double-glazing in their house and 4% intended to do so. In a country such as
Australia which has such a diverse climate, it was not an option for many households,
except those with extremes of heat and cold. It was interesting that there were few
significant differences between people who lived in the capital cities and other areas,
with the exception of rain water tanks and grey water systems which were more popular
outside capital cities.
This classification has both supported and extended existing research, as not only does
it include a range of sustainable behaviours from those that most households have done
to those that few have done, but the behaviours that were included in this study also fit
into the proposed classification well.
Computed scores were calculated using SPSS to determine the number of lifestyle and
capital behaviours that respondents had done or intended to do. These four computed
scores (two for the lifestyle constructs and two for the capital constructs) formed the
basis for the analysis of these constructs.
7.5.2 199BPromoting the identified sustainable behaviours
7.5.3 200BCapital and lifestyle behaviours as predictors of intention
270
The EFA revealed that the lifestyle behaviour and intention constructs were reliable
measures of sustainable behavioural intention. The capital behaviour and intention
constructs were deleted on the basis of low loadings, and the Cronbach alpha scores
indicated that they were not reliable measures of sustainable behaviour. Therefore,
sustainable behaviours and intention are best described as they relate to a person’s
lifestyle intention and behaviour rather than to their capital intention and behaviour.
Future research studies that are designed to predict sustainable behaviour and intention
need to measure the lifestyle behaviours that people have done or that they intend to do,
rather than asking them about what they have purchased or intend to purchase (capital
behaviours and intention). It could be argued that lifestyle behaviours were easier to
adopt than capital behaviours as Australians are not prepared to pay large amounts for
sustainable items. This premise was supported by the measurement of the LBI construct
described in the next section.
The second way of measuring behavioural intention was based on studies by authors
such as Kraft et al. (2005), Laroche et al. (2001) and Shaw et al. (2000, 2003) who
measured likelihood to perform or engage in different behaviours by asking respondents
to rate four statements using a Likert scale from “very likely” to “not at all likely”. For
this research, the construct obtained by measuring behavioural intention using a 7-point
Likert scale to rate the four statements was labelled “likely behavioural intention”
(LBI). Of the four original LBI statements, the statement that measured the likelihood
“to choose the product or alternative that is more sustainable, even if it costs more”
loaded weakly and was removed in the CFA. This resulted in the final LBI construct
being derived from three statements that measured the likelihood to engage in
sustainable behaviours in the home and away from home, as well as the likelihood of
paying a higher price for sustainable products. These three statements loaded strongly in
the final SEM, suggesting that they were important determinants of sustainable
behavioural intention.
7.5.4 201BLikely behavioural intention (LBI)
271
Comparing the findings to the study by Laroche et al. (2001) revealed some similarities.
Table 7.4 indicates that while Laroche et al.’s (2001) behavioural intention construct
comprised three statements that all measured the likelihood to pay more for
environmentally friendly products, the pattern loadings and Cronbach alpha scores were
similar for the two studies.
Table 7.4 Comparing behaviour constructs in this study and Laroche et al. (2001)
Statements Loading (Pattern)
Crony-ach Alpha
Current study
How likely are you to engage in sustainable behaviours in the home? .826 0.865
How likely are you to engage in sustainable behaviours away from home? .825
When you are buying something or choosing between alternatives, how likely are you to choose the product or alternative that is more sustainable, even if it costs more?
.810
How likely are you to pay a higher price for sustainable products? .703
Laroche study
I would be willing to spend an extra $10 a week in order to buy less environmentally harmful products
.776 0.840
I would accept paying 10% more taxes to pay for an environmental cleanup program
.797
It is acceptable to pay 10% more for groceries that are produced, processed and packaged in an environmentally friendly way
.856
Another finding from this study was that there were no differences in the answers given
by males and females, and by the presence of one or more children living aged 18 years
and under at home with respect to paying more for sustainable products. This was
contrary to the findings of Laroche et al. (2001) who suggested that these two segments
were willing to pay more for environmentally friendly products, and contrary to Granzin
and Olsen’s (1991) finding that the number of children in a household was negatively
related to willingness to pay more for matters related to environmental clean-up. Again,
the different context of these two studies could have accounted for these differences.
For example, the Laroche study was concerned about buying ‘environmentally friendly’
products only, whereas the current study was concerned with a range of different
sustainable products and services.
272
In conclusion, this study has revealed that consumers are generally not prepared to pay
more for products that relate to sustainable living. This was evident both in the
measures of the LBI constructs and in the poor predictive power of the constructs that
measured capital behaviour and intention. While Bennett et al. (2002) and Shaw and
Shiu (2003) demonstrated that people were willing to pay more for locally killed meat
and for fair trade products, respectively, it seems that this does not hold for products
such as solar panels and double-glazing which cost considerably more. This means that
future campaigns should encourage consumers to engage in sustainable behaviours both
in the home and away from home, and this needs to be depicted as an achievable goal
and a good investment that will have long-term benefits for all.
This study has demonstrated that the lifestyle model and the LBI model are both reliable
and valid models for understanding sustainable behaviour and intention. Each of the
four antecedents to lifestyle behaviour had a significant effect of lifestyle behaviour,
and lifestyle behaviour was shown to be a significant predictor of lifestyle intention.
Closer examination reveals that internal ethics was the only significant determinant of
LBI. While behavioural beliefs and the two measures of attitudes had a significant effect
on each other, their combined effect on LBI was not significant. Further, the three
measures of LBI explained about half of the variance in LBI, suggesting that more work
is needed to better define the antecedents to LBI.
Therefore, an important contribution of this study is the need for the inclusion of
measures of lifestyle behaviour and intention, as well as measures of LBI in studies that
are designed to predict sustainable behaviours.
7.5.5 202BSummarising the behaviour and intention constructs
273
The invariance testing was conducted to understand the third aim of the research study:
to understand the effect of control variables on the ability of the theoretical models to
predict sustainable behavioural intention.
The invariance analysis demonstrates that the two final models are very similar in terms
of the significant pathways across the invariant groups. Not surprisingly, people who
agreed that they had already adopted a sustainable lifestyle were more concerned about
all the issues such as recycling and being committed to adopting sustainable practices in
their daily lives, as were people who owned their dwelling. What is more interesting is
that the measurement weights were negatively invariant in both the models for
households that had one or more children aged under 18 years on the statement “In our
country, we have so much electricity and water that we do not have to worry about
conservation”. This concurs with the findings of Granzin and Olsen (1991) and Brooker
(1976) that the number of children in a household is a significant determinant of
behaviour with respect to the environment. Their studies described that this occurred
because families were more likely to have children in school where environmental
issues are discussed, thus encouraging parents to conform to such behaviours with
respect to the environment.
On the other hand, people in households with no children had significantly higher
measurement weights on the statement “If we do not adopt a sustainable lifestyle this
will increase the cost of water and electricity”. This could relate to the finding that older
people are more concerned about the environment (Petts, Herd & O'Heocha 1998), and
potentially it could also relate to their concern about saving money on commodities due
to fixed incomes. This could be another topic for future research.
7.6 Summarising the invariance testing
274
The first research question was developed to understand the antecedents to likely
behavioural intention (LBI) and revealed that consumers’ internal ethics was the only
significant determinant of their LBI. The effects of attitudes, subjective norm and
normative beliefs, moral intensity perceived behavioural control (PBC) and personal
normative motives (PNM) are not significant determinants with respect to sustainable
behaviours in the LBI model.
The second research question was developed to understand the antecedents to lifestyle
behaviour, and part of the fourth research question was to understand the effect of
lifestyle behaviour on lifestyle intention. This study has revealed that attitudes,
subjective norm and normative beliefs, internal ethics and moral intensity are significant
determinants of lifestyle behaviour, and that lifestyle behaviour is a significant
determinant of lifestyle intention. Neither perceived behavioural control (PBC) nor
personal normative motives (PNM) were significant determinants of lifestyle behaviour
and intention.
The third research question was developed to understand the antecedents to capital
behaviour, and part of the fourth research question was to understand the effect of
capital behaviour on capital intention. As capital behaviour and intention were not
included in the final analysis, these effects could not be determined.
In summary, a total of 17 hypotheses were proposed in this study. Six of these were
accepted and 11 were not accepted. For the hypotheses that were accepted, the strongest
weights were for the effect of lifestyle behaviour on lifestyle intention (.835), and for
the effect of internal ethics on LBI (.723) and on lifestyle behaviour (.556). In other
words, a person’s past behaviour is a strong indicator of their future behaviour, and
consumers need to feel that they have an ethical obligation to engage in sustainable
behaviours so that ethical and sustainable behaviours become a part of their self-
7.7 115BRevisiting the research questions and hypotheses
275
identity. The six hypotheses that were accepted and the regression weights (β values)
are summarised in Table 7.5.
Table 7.5 Summary of findings from accepted hypotheses
Research hypotheses Regression
weights H6: Attitudes have a positive influence on lifestyle behaviour. .217 H8: Subjective norm and normative beliefs have a positive influence on lifestyle behaviour.
.272
H4: Internal ethics has a positive influence on likely behavioural intention (LBI) .723 H9: Internal ethics has a positive influence on lifestyle behaviour. .556 H10: Moral intensity has a positive influence on lifestyle behaviour. -.282 H16: Lifestyle behaviour is a predictor of lifestyle behavioural intention. .835
In conclusion, internal ethics is the only exogenous construct that has a significant
effect on both lifestyle behaviour and LBI. This establishes the need for behavioural
change programs to convince consumers that they have an ethical obligation to engage
in sustainable behaviours, so that ethical and sustainable behaviours become a part of
their self-identity. As the five paths between each of the four exogenous constructs in
the final two models were found to be statistically significant and theoretically
plausible, this establishes that changing one or more of these constructs will have a flow
on effect for some or all of the other constructs. For example, changing consumers’
attitudes with respect to sustainable issues could also increase their normative beliefs,
and their internal ethics and their moral intensity. This is good news for marketers in
their quest to increase the adoption of these behaviours.
This study has provided several contributions to theory, which are elaborated in the next
section.
276
Contribution 1: An extended version of the TRA is a more appropriate model for
sustainable behavioural intention
This study has demonstrated that rather than modelling sustainable behaviours on an
extended version of the TPB, they are more appropriately modelled on an extended
version of the TRA, particularly for lifestyle behaviours and intention. The TRA was
developed to explain behavioural intention for volitional behaviours. The TPB was
developed as an extension of the TRA to account for non-volitional behaviours and
included an additional construct called PBC which was a measure of the amount of
control that one has over non-volitional behaviours. As PBC was deleted from the final
theoretical models in this study, in effect this is showing that the TRA is more
appropriate to use as the basis for understanding sustainable behaviours and intention.
Hence, this study concurs with the findings of Routhe et al. (2005) who used the TRA
to model attitudes towards building a new dam. It also extends their findings by
showing that predicting a multidimensional construct such as sustainable behaviours
and intention is possible not only from attitudes, norms and underlying beliefs, but also
from their internal ethics and their moral intensity, and that this depends on the
endogenous behaviour and intention construct that is being measured.
Contribution 2: Studies of sustainable behavioural intention should use two measures of
behaviour and intention
The literature has demonstrated that behaviour and intention can be measured in two
ways: by asking respondents to rate statements on a Likert scale, and by asking them to
say which actual behaviours they have done or intend to do.
This study has highlighted the importance of using the two measures of sustainable
behaviour and intention, as they both explained different aspects of the measured
behaviours. LBI is best measured by rating respondents’ agreement with adopting
7.8 116BContributions to theory
277
sustainable behaviours in the home, away from home and paying a higher price for
sustainable products; while lifestyle behaviour and intention is best measured by using
the classification of actual examples of lifestyle behaviours that is proposed in this
study.
Contribution 3: Internal ethics is a strong predictor of sustainable behaviour and
intention
Of all exogenous constructs included in this study, internal ethics was the one that
explained the greatest proportion of variance in the behaviour and intention constructs
in both of the final models. While internal ethics was the only significant predictor of
LBI in this study, an extended version of the TRA with the addition of internal ethics
and moral intensity provides a sound basis for modelling lifestyle behaviour and
intention. Hence, more work is needed to better understand the antecedents to LBI in
particular, as well as to lifestyle behaviour and intention.
Table 7.6 summarises the findings from the discussion in this chapter. It compares the
previous research with the findings in the current study and summarises the
contributions made by the current study.
Table 7.6 Summary of contributions made by the current study Previous research Findings from current study Contributions by current study Examples of sustainable behaviours Many examples of sustainable behaviours exist in the literature. For example, Voronoff (2005) studied behaviours such as taking a shorter shower or restricting the watering of gardens; Peattie and Peattie (1997) discussed behaviours such as recycling, lawn-watering and installing tanks and solar systems. But there are no studies that examined a range of behaviours including solar panels and classified these behaviours
Lifestyle behaviours and capital behaviours were defined and classified according to Spaargaren’s (2003) Social practices classification with new categories “housing and sustainability at home”, “food and shopping”, “transport” and “actions”. Also included a range of behaviours from those that most had done, to those that few had done.
This classification of lifestyle and capital behaviours was both supported and extended by this research. The study demonstrates that behaviours can be divided into three categories: those that most consumers have done, those that are likely to be done and those that are unlikely to be done. These behaviours fitted the proposed classification well, with the behavioural examples fitting into each category.
Measuring behavioural intention Studies by authors such as Ouellette and Wood (2000), Laroche et al. (2001), Tan (2002), Shaw and Shiu (2003), Spaargaren
Three methods were used to measure behavioural intention, labelled likely behavioural intention (LBI), lifestyle
Research studies that include sustainable behaviours need to measure the lifestyle behaviours that people are doing or
278
(2003), Jackson (2005), Kraft et al. (2005) and Hagger and Chatzisarantis (2006) showed that behaviours can be measured in two ways: by asking which behaviours have been done and intended to do, and by asking about likelihood to perform behaviours on a Likert scale.
intention and capital intention. This study showed that LBI and lifestyle behaviours and intention are the best predictors of sustainable behavioural intention.
considering, rather than asking them about what they have purchased or intend to purchase (capital behaviours and intention). They also need to include statements that measure likely behavioural intention (LBI).
Attitudes It is the combination of a person’s behavioural beliefs and their evaluations of those outcomes that leads to the development of attitudes (Sparks, Shepherd & Frewer 1995). Laroche et al. (2001) showed that the relative “importance of recycling”, “severity” and “inconvenience” of being environmentally friendly were important influences on the attitude construct.
While attitudes are influenced by importance and severity, they were not influenced by the inconvenience of being environmentally friendly. Hence, this partially confirmed Laroche et al.’s. (2001) research findings.
This study has shown that a person’s concerns about the environment and their attitudes towards the importance of behaving sustainably and recycling (importance) determine lifestyle behaviour and intention, as they contributed significantly to the attitude construct. These attitudes were not significant determinants of LBI.
Behavioural beliefs The TRA and TPB describe that people behave according to their beliefs and their evaluation of the possible outcomes. Behavioural beliefs can influence a person’s attitudes or feelings about the object and this dictates their attitudes towards the behaviour (Vitell & Patwardhan 2008).
Identification of three measures that describe a person’s behavioural beliefs with respect to sustainable attitudes: if we do not adopt a sustainable lifestyle this will damage the environment for future generations; increase the cost of water and electricity; result in climate change.
These findings confirm the strength of the relationship of behavioural beliefs as an antecedent to attitudes and they describe the concerns that dictate behavioural beliefs in the sustainable context.
Subjective norm and normative beliefs Ajzen and Fishbein (1980) and Routhe et al. (2005) showed that intention to behave in a particular way can be influenced by a person’s beliefs about what important others think that they should or should not do with respect to the behaviour in question.
Both normative beliefs and subjective norm were measured. This study has confirmed Hagger and Chatzisarantis’ (2006) finding that if both the attitude and the subjective norm are favourable, there is a greater likelihood that the person will intend to perform the behaviour in question, thus supporting the inclusion of subjective norm and normative beliefs as determinants of behavioural intention.
This study could not confirm that normative beliefs are an antecedent to subjective norm due to the lack of statements measuring these constructs. It showed that two of the normative measures can be combined to improve their predictive power. The construct was measured by asking: my close friends think that I should live sustainably; my close family members think that I should live sustainably (normative beliefs); and most people who are important to me think I should adopt a sustainable lifestyle (subjective norm).
Internal ethics Ethical obligation represents an individual’s internalised ethical rules, which reflect their beliefs about what is right or wrong, and self-identity accounts for the fact that ethical issues were not
This research study confirms the significant effect that internal ethics has on behavioural intention, as demonstrated by Sparks et al. (1995), Shaw and Shiu (2002)
This research extends theory by demonstrating that internal ethics has a significant effect on both likely behavioural intention and on lifestyle behaviour and intention.
279
considered in isolation (Shaw & Shiu 2002). Based on the studies conducted by Shaw and associates, ethical obligation and self-identity were combined to form the one construct called “internal ethics”.
and Chedzoy and Burden (1999).
Moral intensity Jones (1991) described moral intensity as “the extent of issue-related moral imperative in a situation” (p. 372) and used this construct to explain the four stages of Rest’s 1986 model of the ethical decision-making process, with respect to how an organisation engages in moral behaviour.
Based on the scenario presented in this research study, the overall harm of these actions was considered to be small when compared to the “big picture” of the whole environment. In this study, moral intensity was described by Concentration of Effect (CE), Temporal Immediacy (TI) and Magnitude of Consequences (MC).
This study concurred with studies by authors such as May and Pauli (2002) and Singhapakdi et al. (1996) who showed that the outcome of using moral intensity in a research study depends on the scenario used. It also demonstrated the effect of moral intensity on lifestyle behaviour and intention.
PBC and control beliefs The TPB showed that control beliefs were the antecedents of PBC and that together they were determinants of behavioural intention.
In the CFA, the total effect of control beliefs on PBC was shown to be weak and not significant. SEM revealed that the PBC construct was not predictive of sustainable behavioural intention which concurred with Routhe et al. (2005) who reported that “perceived control” was not a significant predictor of public support for building a new dam.
These findings do not support the premise that control beliefs were an antecedent to PBC, nor do they support the hypothesis that PBC is a determinant of sustainable behaviour and intention.
Personal normative motives (PNM) Wall, Devine-Wright and Mill (2007) suggested the inclusion of PNM to the TPB to explain the fact that behaviours that reduce personal utility, such as by decreasing convenience, may be perceived as difficult and therefore not achievable.
In the sustainable context, the effect of PNM on behavioural intention was not significant.
This finding was in accordance with the finding that rejected the inclusion of “inconvenience” from the attitude construct. It seems that the sustainable behaviours measured in this research study were not seen as being necessarily difficult, which means that they were achievable.
Interrelationships between the latent constructs The TPB developed by Ajzen (1985) demonstrated that the exogenous constructs of attitudes and subjective norm and PBC determine behavioural intention. Subsequent studies demonstrated the interrelationships that can also exist between attitudes and PBC and subjective norm.
This study measured the correlations between attitudes and behavioural beliefs with normative beliefs and subjective norm, as well as internal ethics and moral intensity in predicting behavioural intention. However, it has not demonstrated the inter relationships between these constructs and PBC or PNM, which were not included in the final SEM.
This study has contributed to theory by showing that internal ethics and moral intensity were correlated with each other and to attitudes and subjective norm. This suggests that changing even one of these constructs will have a flow-on effect in the strengthening of the other constructs and could improve the incidence of sustainable behavioural adoption.
280
This study has demonstrated that while many Australians have started their journey
towards adopting sustainable practices, the theory does not provide a complete account
of the reasons that underpin sustainable intention and behaviour. The key driver of
sustainable behaviour and intention was found to be consumers’ internal ethics which
reflects their beliefs that they have an ethical obligation to live sustainably as they are
concerned about sustainable, ethical and green issues. Their attitudes, subjective norm
and normative motives, and moral intensity had a lesser effect on their behaviour and
intention. Hence, this study has demonstrated that the TPB is not necessarily the most
appropriate to model sustainable behaviour and intention, but that the TRA is more
appropriate, with the inclusion of internal ethics and moral intensity.
Campaigns that encourage the adoption of some sustainable behaviours seem to be
working. Many Australians have adopted practices such as taking a shorter shower,
and using recyclable bags when shopping, and it is shown the sample does not consider
that behaviours such as recycling are inconvenient. However, consumers still need to
be convinced of the need to adopt behaviours and products that require a more
substantial capital outlay such as front loader washing machines, solar panels and
double-glazing of windows and doors.
As existing behaviours tend to be maintained and/or adopted because of the ease with
which they can be executed, changing behaviour requires that these new and desired
behaviours are prompted by an understanding of their importance. Reiterating the
knowledge that a potential point of failure in implementing behavioural change arises
when the behaviour has a long-term rather than a short-term reward (Ouellette & Wood
1998), marketing campaigns need to convince consumers to spend money on adopting
sustainable practices that will have a long-term benefit to the planet. However, they
also need to demonstrate some form of short-term benefit to the consumer. This concurs
7.9 117BConclusions
281
with the findings of Bekin et al. (2006) who showed that changing consumers’
behaviours so that they could achieve their environmental goals means that they need
affordable and skilled resources to assist with adopting such practices. They also need
to be encouraged to take a less disposable view of their possessions.
In conclusion, to achieve a behaviour change towards a more sustainable lifestyle,
marketers need to consider that it is the cost, the perceived benefit, and the sense of
ethical obligation that exists in the community to undertake such behaviours. As well as
driving behavioural change, these factors also overcome the limiting factors that prevent
their adoption. A starting point could be to target people with children aged under 18
years, as it is this group who are more likely to undertake socially acceptable
sustainable behaviours.
The main limitation of this study is that the data was collected when there was a drought
and a severe water shortage throughout most of Australia. Hence, the findings may
over-emphasise the need to save water.
This study was based on a sample of Australians aged 18 and over. Therefore, it is
applicable to the population in general and may not reflect the opinions of specific
target markets such as committed environmentalists and those people who are not
interested in adopting the practices discussed herein. This could be addressed by further
research which is discussed in the final section.
7.10 118BLimitations of the study
282
Based on this study, there are many suggestions for further research. One of the most
evident is the need to test the final structural models in different countries, to compare
the findings to Australia. The models could also be tested in more specific contexts,
such as for the adoption of specific kinds of behaviours such as the adoption of solar
energy panels which are now mandatory in some new buildings in Australia.
Paradoxically, while the Australians expressed an interest in conserving water and
electricity, they were also concerned about increases in the cost of such commodities
and were not always prepared to adopt sustainable practices such as using water tanks,
solar panels and double-glazing. Understanding the factors that would make consumers
pay more for sustainable products and services, as well as the factors that would
increase their likelihood of adoption could be a topic for future research.
In this study, three adoption categories for lifestyle and capital behaviours were
proposed. These were “behaviours done”, “likely to do this behaviour” and “unlikely to
do this behaviour”. In the study by Frame (2004), three values-and-actions segments
were described, based on the Big Clean Up in New Zealand: “will not shift (change)”,
“will shift (change) through increased awareness, knowledge, skills and participation”
and already “with us in values and actions” (Frame 2004, p. 518). Further research
could relate these three values-and-actions segments to better understand the kinds of
people who are likely or not likely to adopt sustainable behaviours, based on the
adoption categories described in this research. Examples could include research to
demonstrate what percentage of consumers who were in the category of “will not
change their behaviour” were also in the “behaviours done” segment. Another example
is to examine what percentage of consumers in the “with us in values and actions”
segment had already adopted the “unlikely” behaviours such as installation of double-
glazing.
7.11 119BFurther research directions
283
Further research could investigate the relationship between lifestyle and capital
behaviours, for both future behavioural intention and past behaviours, to understand the
extent to which they are linked to and drive a sustainable lifestyle. It could be
hypothesised from this study that consumers who have already adopted “lifestyle”
behaviours could be more likely to adopt “capital” behaviours in the future, and that
measures of lifestyle behaviours are good predictors of lifestyle and capital behaviours
that will be adopted in the future. Such studies could link the antecedents of behaviour
with intention with actual examples of sustainable behaviours using a longitudinal study
to extend existing models of ethical decision making in the sustainable context.
This study has demonstrated that engaging in sustainable practices is a highly complex
topic. Further research is needed to understand which constructs need to be included in
models of sustainable behaviour and intention in order to better explain the variance in
the models. For example, the finding that the PBC construct is not a reliable
determinant of behaviour and intention suggests that the TRA is a better model than the
TPB in predicting the variance between the exogenous constructs with the behaviour
and intention constructs. Another example is the need to develop the “attitude”
construct so that it determines a greater proportion of the variance accounted for in the
model. This is particularly true for LBI, as in this study, the attitude construct was not a
significant determinant of LBI. The invariance testing could be conducted with the age
variable, to determine its influence in the decision making process. A final example is
to investigate why PBC and PNM were not significant determinants of behavioural
intention.
In conclusion, this study has provided a strong direction for future quantitative studies
on sustainability. It should be used by marketers and policy makers to conduct research
and to develop initiatives and policies to drive successful sustainability and social
marketing campaigns in the future.
284
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Appendix 1: Conceptual Model of Buyer Behaviour, Howard and Sheth (1969)
Appendix 2: Theory of Ethics, Hunt and Vitell (1986)
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Appendix 3: Issue contingent model of ethical decision making in organisations,
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Appendix 6: Ethics approval letter
To: Dr Antonio Lobo/Ms Judy Rex, FBE __________________________________________ Dear Tony and Judy SUHREC Project 2008/021 Understanding the factors that affect consumers' decision making about sustainable consumption Dr Tony Lobo Ms Judy Rex FBE Approved Duration: 01/09/2008 To 31/08/2009 I am pleased to advise that the Chair of SHESC3 (or delegated member) has approved the revisions and clarification as emailed by you on 12/08/2008 in response to previous communication (SHESC email of 08/08/2008). Unless otherwise notified, human research activity in the project may commence in line with standard on-going ethics clearance conditions here outlined. - All human research activity undertaken under Swinburne auspices must conform to Swinburne and external regulatory standards, including the current National Statement on Ethical Conduct in Research Involving Humans and with respect to secure data use, retention and disposal. - The named Swinburne Chief Investigator/Supervisor remains responsible for any personnel appointed to or associated with the project being made aware of ethics clearance conditions, including research and consent procedures or instruments approved. Any change in chief investigator/supervisor requires timely notification and SUHREC endorsement. - The above project has been approved as submitted for ethical review by or on behalf of SUHREC. Amendments to approved procedures or instruments ordinarily require prior ethical appraisal/ clearance. SUHREC must be notified immediately or as soon as possible thereafter of (a) any serious or unexpected adverse effects on participants and any redress measures; (b) proposed changes in protocols; and (c) unforeseen events which might affect continued ethical acceptability of the project. - At a minimum, an annual report on the progress of the project is required as well as at the conclusion (or abandonment) of the project. - A duly authorised external or internal audit of the project can be undertaken at any time. Please contact me if you have any queries or concerns about on-going ethics clearance. The SUHREC project number should be cited in communication. Best wishes for the project. Yours sincerely Anne Cain Secretary, SHESC3
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Appendix 7: Summary of constructs in questionnaire Construct & question no.
Scales used to measure the construct Verbal scale and issues that were measured
Short-term behaviours that involve a capital investment, referred to as ‘capital behaviours’ and ‘capital commitment’ Q2, 3
Sustainable consumption can be applied to short-term solutions, such as recycling or buying organic foods. In accordance with Hagger and Chatzisarantis (2006), behaviours performed in the last 2 weeks will be measured. The behaviours that will be measured in this study are those related to housing, recycling and consumption in the household, as well as food and shopping.
Double-glazing Dripper system in the garden Dual flush toilets Energy efficient lighting Front loader washing machine Rain water tank(s) Recycling/grey water system Solar hot water or solar electricity panels or solar heating Water efficient shower heads
Source: Jackson (2005), Routhe et al. (2005), Voronoff (2005), Laroche et al. (2001), Spaargaren (2003) Short-term behaviours that involve lifestyle, referred to as ‘lifestyle behaviours’ and ‘lifestyle commitment’. Q4, 5
The behaviours that will be measured in this study are those related to housing, recycling and consumption in the household, as well as food and shopping. In accordance with Hagger and Chatzisarantis (2006), behaviours performed in the last 2 weeks will be measured.
Save water Use energy efficient appliances Lobby or take direct action about an issue or brand or product Recycle household wastes, e.g. compost, newspapers, bottles Think about reducing my greenhouse emissions Turn off lights/electrical goods that are not necessary Use public transport rather than driving; Have a shower for more than 4 minutes; Buy free range or organic products or fair trade products; Buy or do something positive to encourage sustainable behaviour; Use non phosphate detergents; Restrict my use of plastic bags when shopping; Try to reduce what I buy and use
Jackson (2005), Routhe et al. (2005), Voronoff (2005), Laroche et al. (2001), Spaargaren (2003) Behavioural intention Q7
7-point likely unlikely scale How likely are you to engage in sustainable behaviours?
How likely are you to engage in sustainable behaviours in the home? How likely are you to engage in sustainable behaviours away from home? In your opinion, do your family members think that it is likely or unlikely that you will adopt sustainable behaviours? Do your close friends think that it is likely or unlikely that you will adopt sustainable behaviours? When you are buying something or choosing between alternatives, how likely are you to choose the product or alternative that is more sustainable, even if it costs more? How likely are you to pay a higher price for sustainable products?
Shaw et al. (2000), Shaw and Shiu (2003), Ajzen (2002, p. 4; 2003), Wall et al. (2007), Kraft et al. (2005, p. 484), Hagger and Chatzisarantis (2006, p. 736), Chedzoy and Burden (2007), Shaw et al. (2000), Shaw and Shiu (2003) Attitudes Q6
7-point Likert scale from strongly agree to strongly disagree measured the following
In our country, we have so much electricity and water that we do not have to
304
issues: Severity of environmental problems Importance of being environmentally friendly Inconvenience of being environmentally friendly
worry about conservation Since we live in such a large country any pollution that we create is easily spread out and therefore of no concern to me With so much water in this country, I don’t see why people are worried about leaking taps and flushing toilets Our country has so many trees that there is no need to recycle paper The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state Recycling will reduce pollution Recycling is important to save natural resources Recycling will save land that would be used for landfill Keeping separate piles of rubbish for recycling is too much trouble Recycling is too much trouble Trying to control pollution is much more trouble than it is worth
Laroche et al. (2001, p. 509) Control beliefs Q8
Which, if any, of the following affect whether or not you adopt a sustainable lifestyle?
The availability of sustainable products The cost of sustainable products The amount of information available about sustainable products The quality of sustainable products
Shaw and Shiu (2003), Sparks and Shepherd (1992) PBC
For each behaviour, PBC was assessed by nine indicators, all measured by 7-point scales.
It would be difficult for me to adopt a sustainable lifestyle (Wall, Devine-Wright & Mill 2007) If I wanted to, I would not have problems in adopting a sustainable lifestyle I have full control over adopting a sustainable lifestyle It is completely up to me whether or not I adopt a sustainable lifestyle
Kraft et al. (2005, p. 484), Wall et al. (2007), Hagger and Chatzisarantis (2006, p. 736), Shaw et al. (2000), Shaw and Shiu (2003), Ajzen (1985), Malhotra and Miller (1998), Carson et al. (2004, p. 53), Sparks and Shepherd (1992, p. 392) Normative beliefs
7-point Likert scale from strongly agree to strongly disagree.
My close friends think that I should live sustainably My close family members think that I should live sustainably
Shaw et al. (2000), Shaw and Shiu (2003), Ajzen (1988), Routhe et al. (2005, p. 889) Beliefs about outcomes/ perceptions/ behavioural beliefs
7-point Likert scale from strongly agree to strongly disagree. The outcome beliefs were summed to likelihood of happening.
If we don’t adopt a sustainable lifestyle this will: Damage the environment for future generations Increase the cost of water and electricity Have no effect on the way we live Result in climate change (this was added by the researcher as a result of the pre-test of the questionnaire)
Routhe, Jones and Feldman (2005, p. 885), Ajzen (1988), Ajzen and Fishbein (1980), Sparks, Shepherd and
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Frewer (1995, p. 274), Shaw et al. (2000), Shaw and Shiu (2003) Moral intensity Q9
The Watson family has no intention of changing their habits to become more sustainable in their daily living. For example, they refuse to recycle anything, or to reduce their water or energy use, or to take re usable bags when shopping. They drive a large inefficient car, and they continue to water their garden most days. This is despite water restrictions and the recent introduction of initiatives intended to make people become more aware of sustainability and protecting the environment.
There is a very small likelihood that their behaviour will actually cause harm to the environment Most people would agree that their behaviour is wrong The overall harm (if any) as a result of their behaviour would be very small Their behaviour will not cause harm to the environment in the immediate future The harmful effects (if any) of the decision will affect people that are close to the Watsons.
McMahon and Harvey (2006, p. 384), Vitell and Patwardhan (2008)
Subjective norm
7-point agree disagree scale Most people who are important to me think I should adopt a sustainable lifestyle
Shaw et al. (2000) Shaw and Shiu (2003), Routhe et. al. (2005, pp. 885, 888), Kraft et al. (2005, p. 484), Hagger and Chatzisarantis (2006, p. 736), Wall et. al. (2007) EO and SI together form the latent variable called ‘internal ethics’ Ethical obligation
7-point agree disagree scale “I feel that I have an ethical obligation to purchase fair trade grocery products” (agree to disagree).
Shaw et al. (2000), Shaw and Shiu (2003). Self identity Response scales were marked disagree very
strongly and agree very strongly. I think of myself as an ethical consumer I think of myself as a sustainable consumer I think of myself as a green consumer
Sparks and Shepherd (1992, p. 392), Shaw et al. (2000), Shaw and Shiu (2003), Hagger and Chatzisarantis (2006, p. 736) Concern for the environment
Very concerned to not at all concerned How concerned are you about the environment?
Petts, Herd and O'Heocha (1998, pp. 712, 717) Personal -normative motives (PN)
5-point Likert scale – changed to 7-point Likert scale for this study
I feel personal responsibility for helping to protect the environment I feel morally obliged to take measures to help to protect the environment
Wall et al. (2007) Values/ commitment Q6
7-point agree disagree scale I am strongly committed to adopting a sustainable lifestyle If I tried, I could adopt a sustainable lifestyle
Frame (2004), Arnould et al. (2004) Behaviours Q6
7-point agree disagree scale I have an environmentally friendly attitude
Spaargaren (2003, p. 689) Demographics Age
An ethical consumer can range from aged 35+, to 55+, and over-65’s were more likely than younger people to ‘do what they can’ with respect to ethical consumption The 18-54 year old cohort showed the greatest levels of support for environmental
Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65-74
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issues Age 75-84 Age 85+
(Carrigan, Szmigin & Wright 2004, p. 403) (Petts, Herd & O'Heocha 1998) Marital status Married persons were more committed to
conservation Married/ de facto Divorced Widowed Single
Granzin and Olsen (1991). Number of children
The number of children in a household was positively related to the purchase of ecology-oriented products, and negatively related to a person’s willingness to pay more for matters related to environmental cleanup. The number of children was a significant determinant of behaviour with respect to the environment
How many children aged under 30 years are now living in this household? That is, how many give this as their permanent address? Aged <5 years Aged 5-9 years Aged 10-14 years Aged 15-19 years Aged 20-29 years
Granzin and Olsen (1991), Brooker (1976) Socio economic status
Higher social class was related to a greater political participation in environmental causes, a greater likelihood of joining or supporting environmental groups, stronger attitudes towards environmental protection, and greater support for energy conservation.
Need to ask income, education and occupation to derive the socio-economic status of respondents
Granzin and Olsen (1991). Education Higher levels of education and higher
income levels have been linked to greater concern for the environment and a greater likelihood of participation in environmental protection activities.
What is the highest level of education you have reached? Primary, some secondary Completed secondary Some tafe/uni completed tafe completed uni degree – bachelor degree completed higher uni degree – masters, MBA, PhD, DBA Another level of education?
Schaper (2002). Occupation What is your current occupation?
Professional e.g. Doctor, Teacher, nurse manager of a business Other white collar, e.g. Clerical, Blue collar, e.g. Trades person, Unskilled worker, Student, Home duties, Not currently employed, Other
Income
What is your approximate annual income from all sources before tax? <$30,000 $30 – 49,999 $50 – 74, 999 $75 - $99,999 $100, 000 – 149, 000 $150, 000+
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Appendix 8: Moral intensity scenarios tested in depth interviews
The first ‘positive’ scenario that was tested was:
The Watson family are very conscious about the environment. They recycle most of their
food scraps, bottles and newspapers, they constantly turn off lights, and they take re
usable bags when shopping. Garden watering is a thing of the past and they have
replanted their garden with native plants that are drought tolerant.
The second ‘negative’ scenario that was tested was:
The Watson family are not very conscious of the environment. For example, they refuse
to recycle anything, or to reduce their water or energy use, or to take re usable bags
when shopping, and they continue to water their garden most days. This is despite water
restrictions and the recent introduction of initiatives intended to make people become
more aware of sustainability and protecting the environment.
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Appendix 9: Final questionnaire
Survey on Issues facing the community today
Swinburne University of Technology Faculty of Business & Enterprise
December 2008
Project Title: Understanding the factors that affect consumers’ decision making about
sustainable consumption
This survey is designed to understand current issues facing Australian consumers in their daily lives, in particular relating to sustainability and ethical issues. It should be completed by people aged 18+ who are Australian citizens, and by the person to whom the email was addressed. If this person is not available, then the questionnaire should be completed by a person of a similar age in the household.
Sustainability refers to protecting the environment for the long-term benefit of the planet. Sustainability aims to encourage people to recycle items such as organic materials, paper and bottles; to save water and electricity; to change people’s shopping and consumption habits, so that economic growth and environmental protection work together, rather than in competition with each other.
Ethical issues are broader than sustainable issues. They include concerns for the third world, the environment and animal issues, and they have lead to the development of products and services such as fair trade products. Fair trade products are those that are purchased under equitable trading agreements, ensuring a fair price and fair working conditions for the producers and suppliers of those products. Fair trade coffee is a good example of this.
Bearing this in mind, can you please answer the following questions to the best of your ability? Please note that we do not expect that all people participating in the survey will engage in ethical or sustainable practices. What is more important is that you answer
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this questionnaire honestly. The questionnaire will take about 12 minutes to complete and it is anonymous. The findings of the survey will be used for my PhD thesis, and as the basis of academic journal articles. All the information from the survey will be summarised in aggregate and no individual responses will be recorded. This research can then be used to understand current issues facing the community today and to develop policies and procedures that could assist in changing current practices.
Your participation is voluntary and you are free to stop answering the questions at any time. All information you provide will be used for aggregated results. Agreeing to take part in this survey is taken as your informed consent. It would be appreciated if you could complete this questionnaire in the next 7 days.
Completion of this questionnaire is taken as your Informed Consent to participate in this research. Informed Consent means that:
all questions about the research have been answered to your satisfaction
your participation in the research is voluntary
you understand that the answering the questions ensures your anonymity, confidentially and privacy.
If you have any questions about the survey please phone Judy Rex on 03-92148055 or [email protected], or Dr Antonio Lobo on 03-9214 8535 or [email protected].
This project has been approved by or on behalf of Swinburne’s Human Research Ethics Committee (SUHREC) in line with the National Statement on Ethical Conduct in Research Involving Humans. If you have any concerns or complaints about the conduct of this project, you can contact: Research Ethics Officer, Office of Swinburne Research (H95),
Swinburne University of Technology, P O Box 218, HAWTHORN VIC 3122.
Tel (03) 9214 5218 or +61 3 9214 5218 or [email protected]
We thank you for your co-operation and we hope that you enjoy completing the survey.
Judy Rex and Tony Lobo
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Q1a Thinking about issues relating to the environment. What do you think is the one most important environmental issue facing Australia today?
General issues Label Climate change Q1A Lack of water Q1A Waste/rubbish disposal Q1A Recycling Q1A Loss of species (animals, birds, etc) Q1A Greenhouse emissions/pollution Q1A Other (please state what this is) ……………………………….. Q1A
Q1b and what do you think is the second most important environmental issue facing Australia today?
Climate change Q1B Lack of water Q1B Waste/rubbish disposal Q1B Recycling Q1B Loss of species (animals, birds, etc) Q1B Greenhouse emissions/pollution Q1B Other (please state what this is) ……………………………….. Q1B Don’t know Q1B
Q1c and what do you think is the third most important environmental issue facing Australia today?
Climate change Q1C Lack of water Q1C Waste/rubbish disposal Q1C Recycling Q1C Loss of species (animals, birds, etc) Q1C Greenhouse emissions/pollution Q1C Other (please state what this is) ……………………………….. Q1C Don’t know Q1C
Q2 which, if any, of the following do you now have where you live?
Capital behaviour Double-glazing Q2_1 Dripper system in the garden Q2_2 Dual flush toilets Q2_3 Energy efficient lighting Q2_4 Front loader washing machine Q2_5 Rain water tank(s) Q2_6 Recycling/Grey water system Q2_7 Solar hot water or Solar electricity panels or Solar heating Q2_8 Water efficient shower heads Q2_9 Other (Please describe what you have)………………………………… Q2_10 None of these Q2_99
Q3 which, if any, of the following do you intend to install or do in the next 2 years, where you live? Capital intention Double-glazing Q3_1
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Dripper system in the garden Q3_2 Dual flush toilets Q3_3 Energy efficient lighting Q3_4 Front loader washing machine Q3_5 Rain water tank(s) Q3_6 Recycling/Grey water system Q3_7 Solar hot water or Solar electricity panels or Solar heating Q3_8 Water efficient shower heads Q3_9 Other (Please describe what you have)………………………………… Q3_10 None of these Q3_99 Q4 which of the following have you, yourself, done in the last 2 weeks? Please read the entire list and select all that apply below. Lifestyle behaviour
Done in last 2 weeks
Tried to save water Q4_1 Used energy efficient appliances Q4_2 Lobbied or taken direct action about an issue or brand or product Q4_3 Recycled household wastes, e.g. compost, newspapers, bottles Q4_4 Thought about reducing my greenhouse emissions Q4_5 Turned off lights/electrical goods that are not necessary Q4_6 Used public transport rather than driving Q4_7 Had a shower for more than 4 minutes Q4_8 Bought free range or organic products or fair trade products Q4_9 Bought or done something positive to encourage sustainable behaviour Q4_10 Used non phosphate detergents Q4_11 Restricted my use of plastic bags when shopping Q4_12 Tried to reduce what I buy and use Q4_13 None of these Q4_99 Q5 which of the following do you intend to do in the next 2 weeks? Please read the entire list and select all that apply below Lifestyle intention/commitment
Intend to do in next 2 weeks
Save water Q5_1 Use energy efficient appliances Q5_2 Lobby or take direct action about an issue or brand or product Q5_3 Recycle household wastes, e.g. compost, newspapers, bottles Q5_4 Think about reducing my greenhouse emissions Q5_5 Turn off lights/electrical goods that are not necessary Q5_6 Use public transport rather than driving Q5_7 Have a shower for more than 4 minutes Q5_8 Buy free range or organic products or fair trade products Q5_9 Buy or do something positive to encourage sustainable behaviour Q5_10 Use non phosphate detergents Q5_11 Restrict my use of plastic bags when shopping Q5_12 Try to reduce what I buy and use Q5_13 None of these Q5_99
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Q6a Please indicate whether you agree or disagree with the following statements…
Lifestyle attitudes I lead a sustainable lifestyle Q6A_1 I have an environmentally friendly attitude Q6A_2 There is nothing that we can do about climate change. It is already too late. Q6A_3 I would only use sustainable products if I was told that I had to Q6A_4 Attitudes - severity In our country, we have so much electricity and water that we do not have to worry about conservation
Q6A_5
Since we live in such a large country any pollution that we create is easily spread out and therefore of no concern to me
Q6A_6
With so much water in this country, I don’t see why people are worried about saving water
Q6A_7
Our country has so many trees that there is no need to recycle paper Q6A_8 The earth is a closed system where everything eventually returns to normal, so I see no need to worry about its present state
Q6A_9
PBC It would be difficult for me to adopt a sustainable lifestyle Q6AA_10 If I wanted to, I would not have problems in adopting a sustainable lifestyle Q6AA_11 I have full control over whether or not I adopt a sustainable lifestyle Q6AA_12 It is completely up to me whether or not I adopt a sustainable lifestyle Q6AA_13 Commitment – not used in final analysis I am strongly committed to adopting a sustainable lifestyle Q6AA_14 If I tried, I could adopt a sustainable lifestyle Q6AA_15 Normative beliefs My close friends think that I should live sustainably Q6AA_16 My close family members think that I should live sustainably Q6AA_17 PNM I feel personally responsible for helping to protect the environment Q6AA_18 I feel morally obliged to take measures to help to protect the environment Q6AA_19 Q6b Please indicate whether you agree or disagree with the following statements… If we do NOT adopt a sustainable lifestyle this will… Behavioural beliefs Damage the environment for future generations Q6B_1 Increase the cost of water and electricity Q6B_2 Have no affect on the way we live Q6B_3 Result in climate change Q6B_4 Q6c Please indicate whether you agree or disagree with the following statements… Subjective norm Most people who are important to me think I should adopt a sustainable lifestyle Q6C_1 Ethical obligation I feel that I have an ethical obligation to live sustainably Q6C_2 Self identity I think of myself as someone who is very concerned about sustainable issues. Q6C_3 I think of myself as someone who is very concerned about ethical issues. Q6C_4 I think of myself as someone who is very concerned about green issues. Q6C_5 Attitudes - importance Recycling will reduce pollution Q6C_6 Recycling is important to save natural resources Q6C_7 Recycling will save land that would be used for landfill/rubbish Q6C_8 Attitudes – inconvenience Keeping separate piles of rubbish for recycling is too much trouble Q6C_9
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Trying to control pollution is much more trouble than it is worth Q6C_10 Q7. How likely or unlikely are you to do the following? Likely behavioural intention
How likely are you to engage in sustainable behaviours in the home? Q7_1 How likely are you to engage in sustainable behaviours away from home? Q7_2 When you are buying something or choosing between alternatives, how likely are you to choose the product or alternative that is more sustainable, even if it costs more?
Q7_5
How likely are you to pay a higher price for sustainable products? Q7_8 Q8. Which, if any, of the following affect whether or not you adopt a sustainable lifestyle? Select all answers that apply to you. Control beliefs Q8_1, Q8_2, Q8_3, Q8_4, Q8_5, Q8_9 The availability of sustainable products .. .. .. ..1 The cost of sustainable products .. .. .. .. ..2 The amount of information available about sustainable products ..3 The quality of sustainable products .. .. .. .. ..4 Other factors? Please describe them………………………………….5 None of these affect whether or not I adopt a sustainable lifestyle ...9 Q9. PLEASE READ THIS: The Watson family has no intention of changing their habits to become more sustainable in their daily living. For example, they refuse to recycle anything, or to reduce their water or energy use, or to take re usable bags when shopping. They drive a large inefficient car, and they continue to water their garden most days. This is despite water restrictions and the recent introduction of initiatives intended to make people become more aware of sustainability and protecting the environment. Based on this scenario, can you please answer the questions below, and select one number beside each statement. There is a very small likelihood that their behaviour will actually cause harm to the environment (PE)
Q9_1
Most people would agree that their behaviour is wrong (SC) Q9_2 The overall harm (if any) as a result of their behaviour would be very small (MC) Q9_3 Their behaviour will not cause harm to the environment in the immediate future (TI) Q9_4 The harmful effects (if any) of the decision will affect people that are close to the Watsons (PX)
Q9_5
Their behaviour will harm few, if any people (CE) Q9_6 This scenario presents an ethical dilemma Q9_7 I would be likely to behave in the same way as the Watson family Q9_8 Q9_1a When you are seeking information about sustainable decisions or products, who or where would you seek information from first? Parents/family/spouse .. ..1 Friends/word of mouth ..2 Online/ the internet ..3 Print media, e.g. newspapers ..4 Shops/retail outlets .. ..5 It would be my own decision ..5 Somewhere else (specify) ..6 Q10. About how much was your household’s last water bill/account? Your best guess will do.
<$50 ..1 $350 – 399 ..8 $50-99 ..2 $400 – 449 ..9
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$100 – 149 ..3 $450 – 499 ..10 $150 – 199 ..4 $500 – 549 ..11 $200 – 249 ..5 $550 - 599 ..12 $250 – 299 ..6 $600 - 649 ..13 $300-349 ..7 $650 or more ..14 We don’t pay it/landlord ..15
Q11. About how much was your household’s last gas bill/account? Your best guess will do .
<$50 ..1 $350 – 399 ..8 $50-99 ..2 $400 – 449 ..9 $100 – 149 ..3 $450 – 499 ..10 $150 – 199 ..4 $500 – 549 ..11 $200 – 249 ..5 $550 - 599 ..12 $250 – 299 ..6 $600 - 649 ..13 $300-349 ..7 $650 or more ..14 We don’t pay it/landlord ..15
Q12. About how much was your household’s last electricity bill/account? Your best guess will do. <$50 ..1 $350 – 399 ..8 $50-99 ..2 $400 – 449 ..9 $100 – 149 ..3 $450 – 499 ..10 $150 – 199 ..4 $500 – 549 ..11 $200 – 249 ..5 $550 - 599 ..12 $250 – 299 ..6 $600 - 649 ..13 $300-349 ..7 $650 or more ..14 We don’t pay it/landlord ..15
Finally some questions to help classify the answers. D1. Including yourself, how many people currently live in your household in the following age groups? Aged 0-17 years ____ Aged 18-25 years ___ Aged 26 or over? ____ D2 What type of dwelling do you live in? 1 Separate house 2 Semi-detached townhouse, row, terrace house, villa etc 3 Flat/Unit/Apartment 4 Other (specify) D3. Which of these best describes your situation? We own this dwelling .. .. ..1 We have a mortgage on this dwelling ..2 We are renting this dwelling .. ..3 Another: (please specify)_________ ..4 D4. How many bedrooms do you have where you live? ________ D5. Which of these age groups are you in? 1 18-19 2 20-29 3 30-39 4 40-49 5 50-59
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6 60-69 7 70-79 8 80+ 99 Prefer not to answer D6. Are you… Male ..1 Female ..2 D7. Are you… 1 Married/De facto 2 Separated 3 Divorced 4 Widowed 5 Single (never married) D8. Are you the main income earner in your household? 1 Main income earner 2 Shared equally 3 Not the main income earner 9 Prefer not to say D9. What is your current work status? Work full time (for money) ..1 Work part time (for money) ..2 Unemployed .. .. ..3 Household duties only ..4 Retired (self supporting) ..5 Full time student .. ..6 Other pensioner .. ..7 Other (specify) .. ..9 D10 What is the highest level of education you have reached? Primary, some secondary.. ..1 Completed secondary .. ..2 Some TAFE ..3 Some University .. ..4 Completed TAFE/Uni degree ..5 Other Please describe:__________________________________6 D11. What is your approximate total annual income from all sources before tax? Under $30, 000 ..1 $30,000-$39,999 ..2 $40,000-$49,999 ..3 $50,000-$59,999 ..4 $60,000-$69,999 ..5 $70,000-$79,999 ..6 $80,000-$89,999 ..7 $90,000-$99,999 ..8 $100,000-$109,999 ..9 $110,000-$111,999 ..10 $120,000-$129,999 ..11 $130,000-$139,999 ..12 $140, 000 - $149, 999 ..13 $150,000 or more per annum..14 Prefer not to say .. ..99
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ANSWER IF D11b (TOTAL IN HOUSE) >1 D11b: What is your household’s approximate total annual income from all sources before tax? Under $30, 000 ..1 $30,000-$39,999 ..2 $40,000-$49,999 ..3 $50,000-$59,999 ..4 $60,000-$69,999 ..5 $70,000-$79,999 ..6 $80,000-$89,999 ..7 $90,000-$99,999 ..8 $100,000-$109,999 ..9 $110,000-$111,999 ..10 $120,000-$129,999 ..11 $130,000-$139,999 ..12 $140, 000 - $149, 999 ..13 $150,000 or more per annum..14 Prefer not to say .. ..99 D12. Do you live… In a Capital city ..1 Large regional centre ..2 Small regional centre ..3 Rural/country area ..4 D13. What state or territory do you live in? NSW .. ..1 Victoria ..2 Queensland ..3 SA .. ..4 WA .. ..5 Tasmania ..6 ACT .. ..7 Northern Territory ..8 Thank you for your time and help. If you have further comments to make about any of the issues discussed in this questionnaire, can you please write them on the lines below.
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Appendix 10: Final SEM for LBI
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Appendix 11: Regression weights
Appendix 12: Squared multiple
correlations
Appendix 13: Fit indices
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Appendix 14: Final model lifestyle behaviour and intention
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Appendix 15: Regression weights
Appendix 16: Squared multiple correlations
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Appendix 17: Fit indices
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Conference papers presented by the candidate
based on this research study
Rex, J 2008, Getting It Right – Is it Ethical, Environmental, Green or Sustainable
Consumption?, paper presented to ANZMAC conference, Sydney, 1-3
December.
Rex, J 2010, Re-visiting Sustainability: The ‘Sustainable Behaviours Model’ as a Guide
for Measuring Intention and Adoption of Sustainable Behaviours, paper
presented to Academy of World Business, Marketing and Management
Development conference, Oulu, Finland, 12-15 July.
Rex, J & Lobo, A 2011, Investigating Sustainable Behavioural Intentions Using a
Modified Version of the Theory of Planned Behaviour, paper presented to
ANZMAC conference, Perth, 30 November to 2 December.
