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    Understanding consumerresponses to retailers cause

    related voucher schemesEvidence from the UK grocery sector

    Matthew Gorton Newcastle University Business School, Newcastle University,

    Newcastle upon Tyne, UK

    Robert AngellCardiff Business School, Cardiff University, Cardiff, UK

    John White Plymouth University Business School, Plymouth University, Plymouth, UK, and

    Yu-Shan Tseng Newcastle University Business School, Newcastle University,

    Newcastle upon Tyne, UK

    AbstractPurpose The purpose of this paper is to present and test a conceptual model for understandingconsumer responses to cause related voucher schemes (CRVS), considering the initiatives of twoUK-based grocery retailers (Tesco and Morrisons).Design/methodology/approach The conceptual model incorporates six theoretically derivedexogenous constructs, i.e. status of the cause, company-cause t, personal involvement with the cause,

    attitudes to the company, perceived sincerity of the company and perceived ubiquity. These arehypothesized to inuence consumer responses to three primary endogenous variables: interest in thecompany, favourability of attitudes to the company and use (impact on purchasing intentions). Themodel is tested using survey data ( n 401) collected in two UK cities.Findings All but two of the hypothesized path relationships were conrmed and the percentage of explained variance for the primary endogenous variables compares well against previous models.Attitudes to the company, perceived ubiquity and favourability were identied as signicantpredictors of behavioural intentions (use).Practical implications In selecting a cause, managers need to think carefully about the status of the cause, its degree of t with the company and how to build personal involvement. CRVS initiativesshould be focused, with consistency in communication. If a company suffers from negative consumerattitudes, a CRVS alone is unlikely to turn around their business performance.Originality/value The paper represents the rst academic assessment of consumer responses to

    CRVS, introducing and validating a conceptual model.Keywords Cause related voucher schemes, Structural equation modelling, Grocery retail, Vouchers,RetailingPaper type Research paper

    IntroductionWestern markets have witnessed increased practitioner and academic interest incause-related marketing (CRM) (Adkins, 1999; Barone et al., 2007; Docherty and

    The current issue and full text archive of this journal is available atwww.emeraldinsight.com/0309-0566.htm

    Responses tovoucher schemes

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    European Journal of MarketingVol. 47 No. 11/12, 2013

    pp. 1931-1953q Emerald Group Publishing Limited

    0309-0566DOI 10.1108/EJM-06-2011-0286

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    Hibbert, 2003; Folse et al., 2010; Mekonnen et al., 2008). Larson et al. (2008, p. 272) deneCRM as any marketing activities in which company donations to a specied cause arebased upon sales of specied goods or services. The Economist (2010, p. 74) denes itmore simply as trying to win and retain customers by doing good. CRM is therefore astrategic marketing tool which seeks to achieve corporate and social/charitableobjectives. While CRM initiatives have been implemented in a range of industries, it isparticularly common in retailing (Barone et al., 2007). Major retailers that have recentlyoperated CRM initiatives include IKEA (Unicef) and gap (Project RED).

    In the UK, when measured by customer involvement, multiple grocery retailersoperate the largest CRM schemes (Barda, 2010). The leading grocery retailers haveadopted initiatives with similar structural characteristics customers receivevouchers linked to their total spend, which can be donated to, for example, schools andsporting clubs. Schools and clubs then redeem these vouchers, at levels set by theretailers, for equipment and other goods. These schemes therefore do not involve asingle product or single designated cause, and the cause related activity is indirect schools and clubs will only benet if customers accept and pass on vouchers receivedin store. These initiatives can be labelled cause related voucher schemes (CRVS). Todate, there has been no academic evaluation, to the best of our knowledge, of this novelform of CRM.

    This paper introduces and tests a conceptual model for understanding consumerresponses to CRVS using structural equation modelling (SEM). In presenting and justifying the model, we argue it transcends previous frameworks by modelling therelationships between, and predictors of, three endogenous constructs (interest,favourability and use). Previous research has largely depended on a single outcomeconstruct, combining attitudinal response and behavioural intentions, or assumed thatall independent variables affect endogenous constructs in a homogenous manner. Wemodel a sequential relationship between the endogenous constructs of

    interest.

    favourability.

    use, seeking to unpack the black box of consumerresponses and provide a greater understanding of how various independent andendogenous constructs interact. Validation of the model draws on data relating to theCRVS of two UK-based food retailers (Tesco and Morrisons). Based on the empiricalndings we set out lessons for the practical management of CRVS. The next sectionoutlines in greater detail how the paper builds on, and contributes to, the wider CRMliterature.

    Previous researchTable I summarizes the ndings of 18 key papers in the CRM literature. The aim is notto provide a comprehensive assessment of all previous research on CRM, but rather tofocus on empirical research, adopting a quantitative approach, which has identiedsignicant determinants of consumer responses. Table I also includes the work of Speed and Thompson (2000), which despite not focusing on CRM specically,ascertained predictors of consumer responses to cultural sponsorships (Olson, 2010)and, consequently has relevance here.

    To date, most research on consumer responses to CRM initiatives has followed anexperimental design, evaluating the impact on consumer attitudes/purchase intentionsof altering a key attribute. Key attributes studied include hypothetical donationamounts (Folse et al., 2010), the nature of the cause (Barone et al., 2007; Ellen et al.,

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    S t u d y

    C a u s e c o n t e x t

    M

    e t h o d

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    F i c t i o n a l c o m p a n y s c e n a r i o s

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    A N O V A

    A t t i t u d e t o c a u s e , a t t i t u d e t o

    r e t a i l e r , p u r c h a s e , d

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    F i t ( ) , c a u s e a f n i t y ( ) , r e t a i l e r

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    H y p o t h e t i c a l c o m p a n y c a u s e s

    a l l i a n c e s

    A

    N O V A

    A t t i t u d e t o C R M a l l i a n c e , a t t i t u d e

    c h a n g e t o r m

    P r e - e x i s t i n g a t t i t u d e s t o r m ( ) ,

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    2 0 0 0 )

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    S t a t u s o f c a u s e ( f o r d i s a s t e r

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    ( 0 )

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    c o m p a n y a n d c o n t r a s t i n g c a u s e s

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    A N O V A

    ,

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    c o m p a n y a n d c a n c e r c h a r i t y

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    a n d c h i l d r e n s h o s p i t a l

    A

    N O V A

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    p a n y ( )

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    c h a r i t i e s a n d c o m p a n i e s

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    2 )

    H o e k a n d G e n d a l l

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    F i c t i o n a l a l l i a n c e s f o r c o f f e e b r a n d s

    a n d c h i l d s a f e t y / w i l d l i f e c a u s e s

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    u n f a m i l i a r b r a n d o n l y

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    c a u s e s

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    c o m p a n y

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    , f o r a t t i t u d e t o c o m p a n y

    o n l y )

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    c u l t u r a l , t w o s p o r t )

    S E M

    A t t i t u d i n a l c h a n g e ( s p o n s o r e q u i t y ) S i n c e r i t y ( ) f o r s p o n s o r e q u i t y

    .

    F i t , s p o n s o r i n v o l v e m e n t , o

    b j e c t

    a t t i t u d e a l l i n u e n c e s i n c e r i t y

    ( c o n t i n u e d )

    Table I.Summary of CRM

    research identifyingdeterminants of

    consumer responses

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    et al. (2007) incorporated cause afnity as a predictor but this is indistinct frompersonal involvement with the cause. Similarly, Simmons and Becker-Olsens (2006)notion of clarity of positioning is indistinct from perceived ubiquity.

    Model constructs and hypothesesStatus of the cause relates to the degree to which it is viewed as signicant andimportant by consumers regardless of whether they directly benet. Previous researchon charitable giving (Bennett, 2003) suggests status of the cause is a predictor of personal involvement. If consumers perceive a cause as unimportant or irrelevant, they

    are unlikely to be a strong supporter or regard the cause as important to themselves. If a cause is regarded as unimportant and irrelevant, consumers are also likely to regardthe companys actions as inappropriate and insincere (Hoefer et al., 2010), andtherefore question the validity of the initiative. In addition, Lafferty (2009) argues thatcauses with a high status are more likely to stimulate consumer interest. In contrast, if consumers deem the cause irrelevant, interest in an initiative is likely to be low. On thisbasis, we propose:

    H1. Status of cause will positively inuence personal involvement.

    H2. Status of cause will positively inuence perceived sincerity.

    H3. Status of cause will positively inuence interest.

    Company cause t relates to the degree of similarity and compatibility thatconsumers perceive between a social cause and brand (Bigne -Alcan iz et al., 2012, p. 3).Where the rm and cause are viewed as compatible, the CRM initiative is more likely tobe regarded as appropriate and genuine (Basil and Herr, 2006), with the companysactions perceived as sincere (Ellen et al., 2006; Olson, 2010). Conversely, low perceivedt is likely to be at odds with prior knowledge, resulting in greater consumerscepticism (Menon and Kahn, 2003), since the alliance is more difcult to integrate intoexisting memory structures (Becker-Olsen et al., 2006).

    Figure 1.Conceptual framework formodeling responses to

    CRVS

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    The associated learning model (Mackintosh, 1975; Hall, 1991) assumes thatlong-term memory is a network of nodes connected by associative links that can bereconstructed as a result of experience and learning. In the context of CRM, Till andNowak (2000) argue that companies and brands attempt to reconstruct the associativenetworks of their target market by forming or strengthening an associative linkbetween the company and a particular cause. It is assumed that higher perceived tbetween two stimuli (in this case cause and company) facilitates the establishment of associative links (Gupta and Pirsch, 2006) and that people prefer consistency, or whatTill and Nowak (2000) refer to as high perceived belongingness between two stimuli.Gupta and Pirsch (2006) and Nan and Heo (2007) both found that high company-causet was positively correlated with favourable attitudinal responses. This implies that:

    H4. Company cause t will positively inuence perceived sincerity.

    H5. Company cause t will positively inuence favourability.

    Personal involvement with the cause relates to consumers identication with aparticular cause (Olson, 2010). This is usually conceptualised as a personal connectionor bridging experience for an individual (Grau and Folse, 2007, p. 20). Identicationwith a cause varies according to its perceived intensity (arousal, interest), direction(level of generality) and relevance (Broderick et al., 2003). Previous research (Baroneet al., 2007; Sargeant, 1999) suggests that psychological involvement with the cause is asignicant determinant of interest, with higher levels of involvement leading to moreefcient and favourable processing of charitable marketing messages (Grau and Folse,2007). Similarly, qualitative research undertaken by Broderick et al. (2003, p. 601) onreactions to CRM initiatives linked to breast cancer, indicated that respondents had tofeel a certain degree of involvement in the campaigns and it is clear that the speciccause was an important factor in stimulating interest and favourable responses to a

    particular companys activities. This implies that: H6. Personal involvement will positively inuence interest.

    H7. Personal involvement will positively inuence favourability.

    Perceived sincerity of the company refers to consumers evaluation of a companysmotives underpinning a CRM initiative (altruistic versus self-interested). Research onCSR activity notes that it is na ve to assume that all consumers always take at facevalue a companys pro-social intentions (Strahilevitz and Myers, 1998; Yoon et al.,2006). Rather, consumers are likely to vary in their perceptions of a companys motives.Osterhus (1997) argues that unless consumers trust the company, they will beunwilling to engage with any CRM initiative, so that it fails to stimulate their interest

    or generate a favourable change in attitudes. In fact if consumers are suspicious of acompanys motives, a CRM initiative may even backre, resulting in moreunfavourable attitudes than if it was absent (Yoon et al., 2006). In keeping with this,a recent empirical study conrmed that perceived sincerity has a positive inuence onsponsor equity (Olson, 2010). We therefore propose:

    H8. Perceived sincerity will positively inuence interest.

    H9. Perceived sincerity will positively inuence favourability.

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    Perceived ubiquity relates to consumers assessment of the focus and clarity of positioning in a companys CRM initiatives. Firms could attempt to build associationswith multiple or single causes. Following associative learning theory, brands andcauses represent nodes (concepts) in memory with which consumers have builtassociations with other nodes (concepts) (Till and Nowak, 2000, p. 477). Theassociative network for a particular brand is the sum of all these connected nodes. Forinstance, a consumer may associate Cadburys with chocolate, childhood,Birmingham and Quakers. Associative networks will vary between consumers, forinstance some consumers may associate Cadburys with Quakerism but others may beunaware of the origins of the brand. In CRM, companies attempt to develop additionalassociations (with a particular cause). However, this process may be subject toblocking (the presence of impediments to building an associative link). The larger theassociative network of a brand and the more varied the causes endorsed, the moredifcult it becomes to add additional associations (Till and Nowak, 2000). Thissuggests that when perceived ubiquity is high, blocking prevents CRVS initiativesfrom stimulating favourable attitudinal change or impact on purchasing intentions, sothat:

    H10. Perceived ubiquity will negatively inuence favourability.

    H11. Perceived ubiquity will negatively inuence use.

    Attitudes to the company captures consumers degree of liking for the organisation.Basil and Herr (2006), Gupta and Pirsch (2006), Olson (2010) and Sen and Bhattacharya(2001) all found that attitudes to the company affect responses to CRM initiatives, withconsumers more likely to react favourably to rms they already hold in high regard.Conversely, negative attitudes to the company/brand will limit the extent to which aCRM initiative generates favourable attitudinal change (Basil and Herr, 2006). Severalpractical cases of failed CRM t with this proposition; for instance, Berglind andNakata (2005) ascribe the negative consumer responses generated to a proposed CRMpartnership between the Sunbeam Corporation and the American Medical Associationin part to negative prior attitudes of the rm and its CEO. It is therefore assumed that:

    H12. Attitude to the company will positively inuence favourability.

    H13. Attitude to the company will positively inuence use.

    The relationship between the constructs interest, favourability and use assumes ahierarchical sequence of effects akin to, for example, the attention, interest, desire,action (AIDA) model of consumer behaviour. Such hierarchy of effect models supposeconsumers pass through a series of response levels before any potential action thepurchase or use of a product or service (Kitchen, 1999). The adjusted version of thisframework, outlined in the study of Speed and Thompson (2000), speciesfavourability as an alternative construct for desire, and employs the term use inplace of action. While describing a sequential relationship of interest . favourability . use, Speed and Thompson (2000), however, model thethree dependent constructs independently of each other. This overlooks the potentialfor interest and then favourability to explain variation in the highest order of the model in this case use. We therefore explicitly model the sequential relationships betweeninterest, favourability and use, so that:

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    voucher scheme, a sport for schools and clubs initiative with similar rules onaccumulation and redemption of vouchers, albeit not restricted to schools. In 2008 theseschemes were merged into Tesco for Schools and Clubs. In 2001, Tescos CRVSreceived endorsements from the then British Prime Minister and Minister forEducation but were criticised by the consumer watchdog Which? The latter arguedthat 1,000 ( < e 1,195) worth of computer equipment supplied by Tesco requiredvouchers equating to 250,000 ( e 298,750) of spending by shoppers ( Marketing , 2002).Tesco (2010) reported that in 2009 more than 33,000 schools and clubs participated, andit donated equipment worth approximately 13.6 million ( e 16.25 m), amounting tomore than half a million items.

    Morrisons is the smallest of the big 4 grocery retailers and was the last tointroduce a CRVS, Lets Grow, in 2008. Under this initiative customers receive onevoucher for every 10 spent. Vouchers can be redeemed by schools for seeds andgardening equipment. Morrisons designed the Lets Grow campaign to strengthen itsassociation with fresh food (Barda, 2010). It worked with the National SchoolsPartnership to design accompanying teaching resources and lesson plans. In 2009,direct mail to 10,000 schools and a TV advertising campaign promoted the initiative.The campaign budget was 2.5 million ( e 2.99 m) and the company calculated that thescheme generated 116 press articles with a value of 463,000 ( e 553,285) (Barda, 2010).The company reported in 2008/2009 that 18,000 schools registered, of which 15,000placed orders for gardening equipment (relating to 5.5 million children). Morrisonsdonated gardening equipment worth 3.2 million ( e 3.82 m) and customers collected 39million vouchers.

    MethodologyTo understand responses to CRVS, a questionnaire was designed in keeping with theconceptual framework presented above. Respondents were randomly assigned toanswer either a version of the questionnaire relating to Morrisons Lets Grow or Tescofor Schools and Clubs.

    Appendix lists the items for scales used in the conceptual model. While thequestions in Appendix refer to Morrisons and Lets Grow, the Tesco version of thequestionnaire was identical apart from the difference in cause and company. Status of the cause, company-cause t, personal involvement with the cause, perceived sincerityand perceived ubiquity were measured using seven-point Likert scale questions.Respondents indicated their degree of agreement with each statement. The wording of

    RetailerMarketshare

    Number of stores CRVS scheme title

    Date of introduction

    Tesco 25.9 2,715 Tesco computers for schools, then sportfor schools and clubs

    1992, 2005

    J Sainsbury 13.7 934 Active kids 2005Asda 14.0 385 Go green for schools 2008 onlyMorrisons 10.4 439 Lets Grow 2008Total 64.0 4,473

    Source: Own composition, market data from Mintel (2011)

    Table II.Prole of main groceryretailers in the UK andengagement with CRVS

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    items for personal involvement drew on those proposed by Grau and Folse (2007).Company-cause t was measured on a ve-item scale. The scale avoids implying anyparticular basis for t but rather, following the associative learning model, abstractnotions of similarity, appropriateness and logical connection (Fleck and Quester, 2007).The battery of items for status of the cause, perceived sincerity and perceived ubiquityfollow the validated scales of Speed and Thompson (2000). Semantic differential scalescaptured attitudes to the company following items presented in Mitchell and Olson(1981). These have been used by, amongst others, Folse et al. (2010)(e.g. unfavourable/favourable, bad/good).

    Respondents also indicated the extent to which the CRVS initiative sparked aninterest in the company and its promotions (interest), affected their longer-termattitudes toward the company (favourability), and caused a higher willingness to buythe companys products (use). Interest, favourability and use were all measured on aseven-point Likert scale in which respondents were instructed to assign their level of agreement to three items for each construct. These measures were also adopted from

    Speed and Thompson (2000).The dataset comprised a total of 401 responses. Data collection took place in two UKcities: Newcastle upon Tyne ( n 204) and Plymouth ( n 197). All respondents wereadults of working age (18-65), although not necessarily in employment, and undertookfood shopping. To avoid prior exposure/non-exposure biases, only those familiar withthe stores in question (though not necessarily regular customers of Morrisons andTesco) were included in the study. Questionnaires were collected using street levelintercepts, conducted on different days and at varying times in selected locations. Bushand Hair (1985) noted that consumer data from street interviews are of equivalent orsuperior quality to that of alternative methods.

    Table III summarises the key characteristics of the sample. 62.8 percent of respondents are female, reecting, in part, the requirement for respondents to be

    responsible for food shopping. Regarding the age prole, the sample over-representsthose aged between 21 and 30 and under-represents those aged over 41. This perhapsmirrors the student demographic of both Plymouth and Newcastle upon Tyne assignicant university cities the latter has a student body of approximately 57,700 out

    Mean n % of sample

    Male 149 37.2Female 252 62.8Under 21 24 6Aged 21-30 213 53.1Aged 31-40 85 21.2

    Aged 41-50 38 9.5Aged 51-60 32 8Aged 61-65 9 2.2

    Mean % of total grocery shopping accounted for by Asda 8.5Mean % of total grocery shopping accounted for by Morrisons 21.6Mean % of total grocery shopping accounted for by J Sainsbury 20.1Mean % of total grocery shopping accounted for by Tesco 22.8Mean % of total grocery shopping accounted for by others 26.6

    Table III.Characteristics of the

    sample

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    of a total population of 277,800 (ONS, 2010). The equivalent gures for Plymouth are47,600 students and a total population of 255,600 (ONS, 2010). The four main UKgrocery retailers account for 73 percent of the samples total food spending. Thiscompares against a national market share of 73.3 percent (Table I). In the sample,Tesco is the market leader but its share is lower compared to the national gures, whileMorrisons and J Sainsbury perform better in the sample. Morrisons strength in thenorth-east and Sainsburys position in the south of England inuences this pattern.

    AnalysisConrmatory factor analysis (CFA)The CFA followed the process of specication, estimation, modication andre-estimation, recommended by Brown (2006). The objective was to validate each of the nine constructs in keeping with standard practices of unidimensionality (Andersonand Gerbing, 1988). Data were analysed using Mplus 6.1 (Muthe n and Muthen, 2010).

    The t of the initial CFA model was slightly below recommended criteria (Hu and

    Bentler, 1999). The goodness of t indices were: comparative t index (CFI)

    0.93,Tucker Lewis index (TLI) 0.92 and root mean square error of approximation(RMSEA) 0.07.

    In this initial model, four items were identied as the cause of the poorly ttingmeasurement model. These were traced using the Lagrange modication indices andby checking for areas of strain through inated standardised residuals. Concurrentwith the ndings of Speed and Thompson (2000), from which the measure is adopted,two indicators in the perceived ubiquity construct did not converge with theirunderlying factor (i.e. low factor loadings). As such, this company is clearly focusedon certain causes and this company is very selective in what causes it sponsors wereremoved. To retain the congeneric measurement properties of the model, two furtheritems were found to be problematic. In the company-cause t measure, CCF4 (thecompany and the cause stand for similar things) was found to cross-load on analternative construct (i.e. status of the cause), without being more substantivelyexplainable. In the perceived sincerity scale, PS4 (this company would probablysupport the cause even if it had a lower prole) was found to load on its correspondingfactor at a level below recommended thresholds demonstrating low internal validity(Brown, 2006). Consequently, both items had their factor loading parameters set to zero(Anderson and Gerbing, 1988).

    The model was re-estimated. Each of the factor loadings for every construct wasfound to be signicant, at an acceptable level for interpretation (Table IV). The t of the re-estimated model was still slightly below universally ideal thresholds (Hu andBentler, 1999), but demonstrated both a substantively explainable solution and indeeda better tting model than in the rst attempt of tting the measurement model to thedata. The goodness of t indices were CFI 0.94, TLI 0.93 and RMSEA 0.06.

    Next we performed a multi-group CFA to test for invariance in our measurementmodel across the two CRVS programmes (Tesco and Morrisons). This was undertakento conrm whether adjoining cases into a single measurement model was empiricallyappropriate. We specied a baseline model in which no equality constraints wereupheld ( x 2 1,298.55; df 526) and compared this to a constrained model in whichfactor loadings, variances and covariances were equal ( x 2 1,317.76; df 543). A x 2

    difference test revealed that freeing equality constraints did not signicantly improve

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    model t ( x 2 19.21; D df 17; p . 0.1). Further we tested a second model in whichintercepts were held equal ( x 2 1,335.76; df 560). Once again, no signicantdifferences were found between this and the constrained model ( Dx 2 18; df 17; p . 0.1). Similar to De Luca and Auhene-Gima (2007), we compared mean differencesacross the two CRVS for each latent construct. Only three signicant mean differenceswere observed (namely perceived sincerity, status and attitude) whereby Morrisonsscored slightly below Tesco. Given these results we proceeded with the aggregatedmeasurement model and tested for construct validity.

    Factors Standardised estimates Standard errors Signicance ( p )

    Company-cause t (CCF)CCF1 0.718 0.029 *CCF2 0.774 0.025 *CCF3 0.815 0.023 *CCF4 EliminatedCCF5 0.801 0.024 * Personal involvement (PI)PI1 0.542 0.047 *PI2 0.865 0.041 * Attitude towards the company (AC)AC1 0.933 0.008 *AC2 0.949 0.006 *AC3 0.931 0.008 *AC4 0.923 0.009 * Perceived ubiquity (PU)

    PU1 EliminatedPU2 0.865 0.058 *PU3 0.616 0.050 *PU4 Eliminated Perceived sincerity (PS)PS1 0.618 0.035 *PS2 0.869 0.019 *PS3 0.835 0.021 *PS4 EliminatedStatus of cause (SC)SC1 0.782 0.030 *SC2 0.644 0.039 * Interest (INT)INT1 0.872 0.015 *

    INT2 0.921 0.011 *INT3 0.887 0.014 * Favourability (FA)FA1 0.919 0.009 *FA2 0.955 0.006 *FA3 0.937 0.008 *Use (USE)USE1 0.914 0.010 *USE2 0.943 0.007 *USE3 0.943 0.008 *

    Note: Signicant at: * p , 0.01 level

    Table IV.Measurement model

    estimates

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    Construct validityWe assessed convergent and discriminant validity and Fornell and Larckers (1981)method for average variance extracted (AVE) was used for both. AVE assumes thatthe average variance explained by each latent construct is greater than itscorresponding residual error 50 percent of total variance must be explained. As such,factor loadings are squared, summed, and divided by the error. Discriminant validityassumes that the amount of variance explained by each factor is higher than thesquared correlation of that factor with all other constructs in the model (Fornell andLarcker, 1981).

    Table V presents the factor correlation matrix with estimates for convergent anddiscriminant validity. Convergent validity was sufcient in all factors all were abovethe 50 percent (0.50) threshold (Fornell and Larcker, 1981). Similarly, discriminantvalidity was conrmed by the square-root of AVE scores exceeding correspondingfactor correlations.

    Structural equation modelling (SEM)Each of the exogenous factors specied in the conceptual model (Figure 1) were testedvia SEM). As three indirect paths were hypothesized in our model we rst tested theconditions of mediation (Baron and Kenny, 1986; Prussia and Kinicki, 1996). Using theapproach of Aryee et al. (2002), three conditions were assessed. Initial evaluation of factor correlation coefcients (Table V) indicated that independent variables wererelatively strongly associated with outcome variables (i.e. status of cause with interestand favourability; company cause t and favourability). Similarly, independentvariables were found to correlate to a similar extent with hypothesised mediatorvariables (i.e. perceived involvement and perceived sincerity). Lastly we specied thehypothesized relationships in our model to include fully mediated (status of cause onfavourability through perceived sincerity) and partially mediated (status of cause on

    interest through personal involvement; company cause t on favourability throughperceived sincerity) parameters[2]. The results are shown in Table VI.We found support for all of our mediated paths ( H16 , H17 , H19 ) although not for

    the direct path between company cause t and favourability ( H5 ) suggesting fullmediation through perceived sincerity rather than partial mediation. In fact of thedirect effects in the model, 13 of our 15 hypothesised predictions were conrmed( p , 0.05). The only other non-signicant path was between perceived ubiquity andfavourability ( H10 ). The largest predictor of interest was status of cause ( b 0.43), forfavourability was interest ( b 0.60), and for use was favourability ( b 0.73). Theexogenous constructs were found to explain variance ( R 2 ) in the primary endogenousfactors to a high level (i.e. interest 54 percent; favourability 73 percent; use 70percent).

    DiscussionThis study is the rst to model the relationships between, and predictors of, threeendogenous constructs (interest, favourability, use), providing the basis for a morecomplete understanding of how CRVS works. All but two of the hypothesized pathrelationships were conrmed and the percentage of explained variance for the primaryendogenous variables compares favourably against previous models (Folse et al., 2010;Olson, 2010).

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    1

    2

    3

    4

    5

    6

    7

    8

    9

    C o m p a n y - c a u s e t

    0 . 6 1 ( 0

    . 7 8 )

    P e r s o n a l i n v o l v e m e n t

    0 . 3 2

    0 . 5 3 ( 0

    . 7 2 )

    A t t i t u d e t o w a r d s t h e c o m p a n y

    0 . 5 2

    0 . 3 1

    0 . 8 7 ( 0

    . 9 3 )

    P e r c e i v e d u b i q u i t y

    0 . 4 2

    0 . 2 6

    0 . 3 2

    0 . 5 8 ( 0

    . 7 6 )

    P e r c e i v e d s i n c e r i t y

    0 . 5 8

    0 . 3 8

    0 . 4 7

    0 . 4 0

    0 . 6 1 ( 0

    . 7 8 )

    S t a t u s o f c a u s e

    0 . 6 3

    0 . 5 1

    0 . 6 0

    0 . 5 1

    0 . 7 1

    0 . 5

    2 ( 0

    . 7 2 )

    I n t e r e s t

    0 . 4 7

    0 . 4 6

    0 . 4 3

    0 . 3 6

    0 . 6 4

    0 . 7 0

    0 . 7 9 ( 0

    . 8 9 )

    F a v o u r a b i l i t y

    0 . 5 1

    0 . 5 1

    0 . 5 0

    0 . 3 2

    0 . 6 6

    0 . 6 8

    0 . 8 2

    0 . 8 8 ( 0

    . 9 3 )

    U s e

    0 . 5 0

    0 . 4 4

    0 . 5 1

    0 . 3 6

    0 . 5 9

    0 . 6 2

    0 . 6 9

    0 . 8 3

    0 . 8 8 ( 0

    . 9 3 )

    N o t e s : L o w e r s e g m e n t

    f a c t o r c o r r e l a t i o n s ; d i a g o n a l A V E

    ( p A V E )

    Table V.Factor correlation matrix

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    H

    P a t h r e l a t i o n s h i p s

    R e s u l t s u m m a r y

    S t a n d a r d i s e d e s t i m a t e s ( S E )

    D i r e c t e f f e c t s

    H 1

    S t a t u s o f c a u s e w i l l p o s i t i v e l y i n u e n c e p e r s o n a l i n v o l v e m e n t

    0 . 5 1 ( 0

    . 0 6 ) * *

    C o n r m e d

    H 2

    S t a t u s o f c a u s e w i l l p o s i t i v e l y i n u e n c e p e r c e i v e d s i n c e r i t y

    0 . 6 3 ( 0

    . 0 7 ) * *

    C o n r m e d

    H 3

    S t a t u s o f c a u s e w i l l p o s i t i v e l y i n u e n c e i n t e r e s t

    0 . 4 3 ( 0

    . 1 1 ) * *

    C o n r m e d

    H 4

    C o m p a n y - c a u s e t w i l l p o s i t i v e l y i n u e n c e p e r c e i v e d s i n c e r i t y

    0 . 1 9 ( 0

    . 0 8 ) * *

    C o n r m e d

    H 5

    C o m p a n y - c a u s e t w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y

    0 . 0 5 ( 0

    . 0 5 )

    N o t c o n r m e d

    H 6

    P e r s o n a l i n v o l v e m e n t w i l l p o s i t i v e l y i n u e n c e i n t e r e s t

    0 . 1 4 ( 0

    . 0 5 ) * *

    C o n r m e d

    H 7

    P e r s o n a l i n v o l v e m e n t w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y

    0 . 1 3 ( 0

    . 0 4 ) * *

    C o n r m e d

    H 8

    P e r c e i v e d s i n c e r i t y w i l l p o s i t i v e l y i n u e n c e i n t e r e s t

    0 . 2 7 ( 0

    . 0 9 ) * *

    C o n r m e d

    H 9

    P e r c e i v e d s i n c e r i t y w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y

    0 . 1 7 ( 0

    . 0 5 ) * *

    C o n r m e d

    H 1 0

    P e r c e i v e d u b i q u i t y w i l l n e g a t i v e l y i n u e n c e f a v o u r a b i l i t y

    2 0 . 0 6 ( 0

    . 0 4 )

    N o t c o n r m e d

    H 1 1

    P e r c e i v e d u b i q u i t y w i l l n e g a t i v e l y i n u e n c e u s e

    2 0 . 0 9 ( 0

    . 0 4 ) *

    C o n r m e d

    H 1 2

    A t t i t u d e t o t h e c o m p a n y w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y

    0 . 1 2 ( 0

    . 0 4 ) * *

    C o n r m e d

    H 1 3

    A t t i t u d e t o t h e c o m p a n y w i l l p o s i t i v e l y i n u e n c e u s e

    0 . 1 0 ( 0

    . 0 4 ) * *

    C o n r m e d

    H 1 4

    I n t e r e s t w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y

    0 . 6 0 ( 0

    . 0 5 ) * *

    C o n r m e d

    H 1 5

    F a v o u r a b i l i t y w i l l p o s i t i v e l y i n u e n c e u s e

    0 . 7 3 ( 0

    . 0 3 ) * *

    C o n r m e d

    I n d i r e c t e f f e c t s

    T o t a l i n d i r e c t

    H 1 6

    S t a t u s o f c a u s e w i l l p o s i t i v e l y i n u e n c e i n t e r e s t t h r o u g h p e r s o n a l

    i n v o l v e m e n t

    0 . 0 8 * * ( P M )

    C o n r m e d

    H 1 7

    S t a t u s o f c a u s e w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i l i t y t h r o u g h p e r c e i v e d

    s i n c e r i t y

    0 . 1 3 * * ( F M )

    C o n r m e d

    H 1 8

    C o m p a n y c a u s e t w i l l p o s i t i v e l y i n u e n c e f a v o u r a b i i t y t h r o u g h

    p e r c e i v e d s i n c e r i t y

    . 0 4 * ( F M )

    C o n r m e d

    E n d o g e n o u s c o n s t r u c t e x p l a i n e d v a r i a n c e

    P e r s o n a l i n v o l v e m e n t R

    2

    0 . 2 7

    P e r c e i v e d s i n c e r i t y R

    2

    0 . 5 8

    I n t e r e s t R

    2

    0 . 5 4

    F a v o u r a b i l i t y R

    2

    0 . 7 3

    U s e R

    2

    0 . 7 0

    N o t e s : S i g n i c a n t a t :

    * p , 0 . 0 5 a n d * * p , 0 . 0 1 l e v e l s ; F M f u l l y m e d i a t e d ; P M p a r t i a l l y m e d i a t e d ; ( m o d e l t : C F I 0 . 9 3 ; T L I 0 . 9 2 ;

    R M S E A 0 . 0 7 )

    Table VI.Research modelparameter estimates forhypothesised paths

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    Managers indicate that important benets sought from CRM campaigns are enhancingcorporate reputation and increasing sales (Docherty and Hibbert, 2003). The analysisindicates that CRVS can stimulate favourable attitudinal change and behaviouralintentions. Consumer responses are thus not limited to CRVS being perceived merelyas a good thing and the results are encouraging for the retailers concerned and, morewidely, those interested in creating a CRVS. Attitudes to the company, perceivedubiquity and favourability were identied as signicant predictors of the constructuse.

    In selecting a cause, rms need to think carefully about the status of the cause andits degree of t with the company. Consumers perceptions of the status of the causematter as they are a signicant predictor of interest, personal involvement andperceived sincerity. If the cause is perceived as important, it is more likely to stimulateconsumer interest and view the companys actions in a positive light.

    Another important contribution is that the ndings shed new light on theimportance of personal involvement, conrming the relationships between personalinvolvement and interest and favourability and its moderating role on the relationshipbetween status of the cause and interest. Conventional CRM activities typically involvethe company choosing to partner with a single cause. CRVS provide customers withgreater exibility, allowing them to choose to which organisation they donatevouchers. For instance, 18,000 schools registered for Lets Grow and one may expectpersonal involvement to be higher if a customer can benet a local school and/or theeducational establishment which the customers children or grandchildren attendcompared to a distant school with which the customer has no direct connection. Thegreater exibility CRVS provide to customers is likely to enhance personalinvolvement and hence improve the effectiveness of CRM activities.

    No direct relationship between company-cause t and favourable attitudinalresponse is observed but, in keeping with the results of Olson (2010) and Ellen et al.

    (2006), company-cause t is a signicant predictor of perceived sincerity. A highdegree of t appears to inhibit scepticism as consumers regard the company causealliance as natural and genuine. In contrast, low t arouses consumer suspicions aboutthe motives of the rm with the danger that the initiative appears opportunistic andpurely guided by a desire for prot. Thus, as Simmons and Becker-Olsen (2006, p. 164)contend, a well-liked cause is not enough to ensure a good outcome, a poor tbetween cause and company can lead to a negative outcome if it heightens consumercynicism.

    CRVS will be more successful where consumers believe companies have theinterests of the cause at heart (high perceived sincerity). In other words, to use theterminology of Ellen et al. (2006) companies must demonstrate that the CRVS is othercentred, caring for customers and communities, rather than purely self-centred. Theresults are thus consistent with those of Olson (2010) and Lafferty (2007), who foundthat the effect of CRM on consumer attitudes and purchase intentions was signicantlystronger in the case of rms with high perceived sincerity/corporate credibility.

    Importantly, perceived ubiquity is identied as a signicant predictor of behavioural intentions (use). This highlights the worth of focus in operating a CRVSand consistency in communication. Partnering with too many varied causes andactivities weakens the effectiveness of CRVS. The results are thus in harmony withIntegrated Marketing Communications theory, with CRVS being more effective when

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    applied consistently. For instance, while Morrisons partners with thousands of educational establishments as part of Lets Grow it does so in a coherent and focusedmanner, linking gardening equipment for schools with the companys objective of being perceived by customers as offering fresh food.

    Some advocates of CRM write as though it can aid all rms, turning around anegative brand image and business performance (Adkins, 1999). However, in keepingwith the ndings of Basil and Herr (2006), the importance of the construct attitudes tothe company indicates that CRVS are likely to garner more positive outcomes whereattitudes to the rm are already positive. This suggests that CRVS work best as astrategic tool to enhance already favourable attitudes toward the company. Executivesseeking to address unfavourable attitudes should address rst the root cause of suchnegative perceptions rather than hoping that a CRVS can provide the basis for anyturnaround in fortunes.

    Limitations and further research

    This study draws on examples of actual CRVS initiatives. While care was taken toensure that all respondents were familiar with the grocery retailers in question, toavoid prior non-exposure/exposure biases, respondents will vary in terms of the degreeof prior exposure and the information they possess about the companies. Nonethelesswe are able to conrm that intercept scores for observed variables do not differsignicantly amongst our two CRVS conrming measurement invariance. However,further research using real cases of CRVS in different contexts (countries, products,companies) could verify/augment the conceptual framework and ndings presented.

    The research identied attitudes to the company as a signicant predictor of bothfavourability and use. In this study, attitudes to the company were measured using theveried scale of Mitchell and Olson (1981). Recent work in a CRM context(Bigne -Alcan iz et al., 2012) distinguishes between corporate ability (CA) associations,which relate to a companys record in producing goods and services, and CSRassociations which refer to notions of a companys value system and character. BothCA and CSR may inform consumer attitudes to a company. Having demonstrated theimportance of attitudes to the company as a predictor, future modelling of responses toCRM initiatives may benet from distinguishing between CSR and CA associations of the rm.

    The paper contributes to the literature by unpacking the relationships betweeninterest, favourability and use. This assumes a hierarchical sequence of effects, asindicated (but not modelled) by Speed and Thompson (2000). While this ts with theAIDA model of consumer behaviour, it may be that for varying products/shoppingexperiences other sequences prevail, for instance use . interest . favourability for anexperiential product.

    This study does not investigate consumers knowledge of the nancial value of CRVS to supported causes. For instance we do not measure expectations regarding theworth of the vouchers to schools and clubs in terms of redemption options. In the casesstudied here, neither Tesco nor Morrisons in promoting the scheme focus on thenumber of vouchers required for receiving particular equipment by schools. Folse et al.(2010) identify that the level of rm donation impacts positively on participationintentions. It would be interesting to verify in this case if providing respondents withinformation on their real worth alters outcomes.

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    Finally, Morrisons and Tesco both market their CRM schemes as providing top upresources to schools/clubs. It would be fruitful to analyse consumer responses if CRVSprovided core resources such as textbooks and teachers. This may generate a morefundamental debate on the engagement of companies with what are typically regardedas essential public services. Such research could generate an understanding of whatconsumers regard as appropriate boundaries, if any, between public sector provisionand retailers CRM activities.

    Notes1. For consistency, Speed and Thompsons (2000) terminology of use is retained here but

    purchase intention may be considered to be a more accurate label for the construct.

    2. Although not hypothesized in our model we also ran an alternative model in which a directeffect was specied between status of cause and favourability. This was included to conrmthat this relationship ( H17 ) was best explained as a mediated path through perceivedsincerity. An insignicant path conrmed this assertion.

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    Appendix. Description of measures

    Corresponding authorMatthew Gorton can be contacted at: [email protected]

    Mean (all onseven point

    scales)

    Independent measuresStatus of cause (SC)SC1: this is a signicant cause 4.15SC2: this cause is important to where I live 4.08Company-cause t (CCF)CCF1: there is a logical connection between Lets Grow and Morrisons 3.81CCF2: the image of Lets Grow and the image of Morrisons are similar 3.53CCF3: Morrisons and Lets Grow t well together 3.82CCF4: Morrisons and Lets Grow stand for similar things 3.28CCF5: it makes sense to me that Morrisons backs Lets Grow 4.14 Personal involvement with the cause (PI)PI1: I am a strong supporter of this cause 5.47PI2: this cause is important to me 4.26

    Perceived sincerity (PS)PS1: this cause would benet the grassroots level 4.57PS2: the main reason Morrisons would be involved is because it believes the cause deservessupport 3.72PS3: Morrisons is likely to have the best interests of the cause at heart 3.60PS4: Morrisons would probably support the cause even if it had a much lower prole 3.94 Perceived ubiquity (PU)PU1: Morrisons sponsors many different causes 3.85PU2: Morrisons sponsorship is clearly focused on certain causes 4.21PU3: Morrisons is very selective in what causes it sponsors 4.20PU4: it is very common to see Morrisons sponsoring different causes 3.73 Attitude to the company (AC)AC1: what is your attitude to Morrisons? bad-good 4.70AC2: what is your attitude to Morrisons? Dislike like 4.72AC3: what is your attitude to Morrisons? Negative positive 4.64AC4: what is your attitude to Morrisons? Unfavourable favourable 4.62

    Dependent measures Interest (INT)INT1: this initiative makes me more likely to notice Morrisons 4.01INT2: this initiative makes me more likely to pay attention to Morrisons advertising 3.71INT3: this initiative makes me more likely to remember Morrisons promotions 3.96 Favourability (FA)FA1: this sponsorship makes me feel more favourable toward Morrisons 3.95FA2: this initiative improves my perception of Morrisons 3.97FA3: this initiative makes me like Morrisons more 3.84Use (USE)USE1: this initiative makes me more likely to buy Morrisons products 3.42USE2: this initiative makes me more likely to consider Morrisons products the next time Ibuy 3.52USE3: I am more likely to buy from Morrisons as a result of this initiative 3.30 Table AI.

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