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Int. Journal of Business Science and Applied Management, Volume 4, Issue 1, 2009

Reverse logistics for recycling: The customer service

determinants

Patricia Oom do Valle

Faculty of Economics, University of Algarve

Edificio Ciencias I, Campus de Gambelas, 8005-139 Faro, Portugal

Tel: +351 289800915

Email: [email protected]

Joao Menezes

ISCTE - Business School, Lisbon University Institute

Avenida das Forcas Armadas, 1649-026 Lisbon, Portugal

Tel: +351 217935000


Elizabeth Reis

ISCTE - Business School, Lisbon University Institute

Avenida das Forcas Armadas, 1649-026 Lisbon, Portugal

Tel: +351 217935000


Efigenio Rebelo

Faculty of Economics, University of Algarve

Edificio Ciencias I, Campus de Gambelas, 8005-139 Faro, Portugal

Tel: +351 289800915


Abstract

Customer service is a central concern in the logistics practice and a study topic in the forward logistics

research. This article investigates the elements of customer service and their importance in reverse

logistics for recycling. Since consumer is the first intervenient in any reverse system that aims to

recycle household residues, the provision of an adequate customer service gains an increased

importance. Applying multivariate statistical methods (exploratory factor analysis, confirmatory factor

analysis and discriminant analysis) to the data from a sample of 267 Portuguese citizens, this study

identifies the levels of customer service in this reverse logistics chain and evaluates their relative

importance in achieving consumers’ participation. The study finds that, as in forward logistics, the

customer service in reverse channels for recycling also has a hard and a soft level, being the former

more important than the later. The results of this research suggest important guidelines to improve such

a complex logistics service.

Keywords: reverse logistics, customer service, multivariate statistics

Acknowledgements: The authors acknowledge Susy Rodrigues for providing proofreading support.

Int. Journal of Business Science and Applied Management / Business-and-Management.org

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1 INTRODUCTION

Reverse logistics is the continuous logistic process through which shipped products move from the

consumer back to the producer for possible reuse, recycling, remanufacturing or disposal (Johnson,

1998). The European Working Group on Reverse Logistics (RevLog, 2002) describes reverse logistics

as “the process of planning, implementing and controlling the flows of raw materials, in process

inventory, and finished goods, from a manufacturing, distribution or usage point to a point of proper

disposal”. The purpose of a reverse logistics process is to regain the value of returned materials or

provide the means for proper disposal (Rogers and Tibben-Lembke, 1999, 2001). Forward logistics, in

contrast to reverse logistics, focuses on the flow of goods from the producer to the consumer.

As Maltz and Maltz (1998) propose, customer service in the forward logistics channels is a

multifaceted concept that can encompass either objective or perceptual elements. Objective elements

correspond to basic customer service (or hard service) such as inventory availability, on time delivery

and order cycle time reliability. Perceptual elements (or soft service) are those related to the suppliers’

ability to respond to specific customer requests such as after-sale service and effective handling of

information requests. Several authors recognize that customer service is an issue of central concern in

logistics research and practice (Byrne and Deeb, 1993; Emerson and Grimm, 1998; Fuller, 1978;

Giuntini and Andel, 1995; Kopicki et al., 1993; Maltz and Maltz, 1998; Marien, 1998; Murphy, 1986;

Stock, 1992; Zikmund and Stanton, 1971).

Reverse logistics systems for recycling begin with the consumer and finishes with the end market

(Jahre, 1995). These systems can be more or less complex depending on whether they possess

intermediate levels, such as, the collection level, the transfer level and the processing level. Consumers

have a particularly important role in this reverse logistics system since they are the first link in the

overall logistics chain. Without consumer participation (through the sorting and disposing of recyclable

materials), this system would not be possible. By providing a convenient system, customer service

becomes the touchstone in creating value for consumers as well as in securing their participation

(Turner et al., 1994).

As recently pointed out, most research in the reverse logistics field is essentially descriptive and

based on subjective evidence rather than on theoretical bases (Alvarez-Gil et al., 2007). In terms of the

reverse logistics systems for recycling, one gap that remains open is the comprehensive investigation of

the main elements of customer service that explain the consumer involvement in selective-collection

programs. This analysis would provide fundamental information about the most important customer

service elements and, thus, that require more attention and investment. The contribution of this study

lies in bridging this research gap.

Data for this research results from the outcome of a structured questionnaire collected from a

random sample of 267 Portuguese citizens. This study uses a three-step procedure to assess the

elements that comprise customer service. First, an exploratory factor analysis identifies the main levels

of customer service (both hard and soft) that shape consumer participation in the Portuguese recycling

program. Second, a confirmatory factor analysis validates the underlying levels and the corresponding

elements. Third, a discriminant analysis identifies the level of customer service that strongly predicts

consumer involvement, in this way offering future guidelines for the reverse logistics system at the

collection stage.

The structure of this paper is as follows. Section 2 summarizes the background literature in terms

of: (1) concept and origins of reverse logistics and (2) reverse logistics for recycling. Section 3

proposes a conceptual model that forms the basis for this research and puts forward a set of research

hypotheses. Section 4 describes the research methods used including data information and statistical

techniques. Section 5 presents the results and provides conclusions based on the research hypotheses.

Section 6 discusses the study’s theoretical and managerial implications, identifies its limitations and

proposes guidelines for further research.

2 BACKGROUND ON REVERSE LOGISTICS FOR RECYCLING

Recycling is a resources recovery option that enables the use of part or all materials from returned

goods, either by their original producer(s) or by other industries (RevLog, 2002). The recycling process

essentially encompasses two stages (Jahre, 1995). The first is the collection service stage and includes

all the necessary procedures that make recyclables possible for further reprocessing. The second is the

reprocessing stage from the collection of materials to the replacement of primary raw materials. Table 1

lists the studies that explore particular issues on reverse logistics for recycling.

Patricia Oom do Valle, Joao Menezes, Elizabeth Reis and Efigenio Rebelo

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Table 1: Summary of articles on reverse logistics for recycling

Reference Main topics

investigated

Material (in) Material (out) Driver(s)

Guiltinan and

Nwokoye (1975)

Reverse logistics

networks

Recyclables in

general

Materials Social benefits

Economic benefits

Pohlen and Farris

(1992)

Reverse logistics

networks

Transportation

issues

Plastics (*) Environmental

concerns

Bronstad and

Evans-Correia

(1992)

Purchase of

recycled materials

Paper Paper (*)

Kopicki et al.

(1993)

Logistic

implications of

recycling (and

reuse) programs

Recyclables in

general

Materials Social benefits

Economic benefits

Gupta and

Chakraborty (1994)

Planning and

control of recovery

activities

Glass scrap Raw materials Cost savings

Jahre (1995) Reverse logistics

networks

Household waste Substitutes for

primary

materials

Legislation

Faria de Almeida

and Robertson

(1995)

Incentives to

stimulate recovery

(timely and clear

information)

Batteries Materials (*)

Spengler et al.

(1997)

Reverse logistics

networks (private

networks)

Steel products Reusable

products

Disposal cost saving

Public waste

management

Fuller and Allen

(1997)

Reverse logistics

networks

Post-consumer

recyclables

Substitutes for

primary

materials

Legislation

Yender (1998) Incentives to

stimulate recovery

(Easy and simple

method of supply)

Batteries Raw materials

Batteries

(*)

Barros, Dekker and

Scholten (1998)

Reverse logistics

networks (public

networks)

Construction waste Sand Waste disposal

Environmental

regulation

Nagel and Meyer

(1999)

Information and

communication for

reverse logistics

End-of-use

refrigerators

Plastics

Metals

No longer needed

Legislations

Costs savings

Lowers, Kip,

Peters, Souren and

Flapper (1999)

Reverse logistics

networks (private

networks)

Carpets Fibres, etc. Image

Expected legislation

Economic advantages

Realff, Ammons

and Newton (2000)

Reverse logistics

networks (private

networks)

Carpets Fibres (*)

Chang and Wei

(2000)

Reverse logistics

networks (public

networks)

Household waste (*) Waste disposal

Reducing costs

Environmental

concern

Note: (*) Not mentioned.

Although the concept of reverse logistics arises in the 1990s, the discussion on the structure of

logistics channels begins much earlier. Guiltinan and Nwokoye (1975) identify the main types of

logistics structures, functions and members that form part of the distribution channel. The study also

points out a number of key factors for the future development of recycling channels, such as “[the need

to expand] efforts in identifying potential markets and buyers of recycled materials; more extensive

contact with, and promotion to, final buyers; [in expanding] capacity for moving increased volumes of

material to achieve and maintain scale economies; and [in improving] flexibility in transportation”

(Guiltinan and Nwokoye, 1975: 35).

While the study of Guiltinan and Nwokoye (1975) does not focus specific recyclable materials,

Table 1 presents other contributions that address particular reverse logistic networks for recycling.


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Pohlen and Farris (1992), for instance, analyze the set-up of recycling networks for plastics and

propose a more complex structure for the reverse channel when compared to the general Guiltinan and

Nwokoye (1975) approach. Pohlen and Farris (1992) discuss the main issues that affect reverse

logistics channels for recycling, namely, efficiency improving factors in terms of existing channels and

common forms of improving recyclables.

As Table 1 shows, some of the studies that address the organization of recycling networks focus

on public networks, while others describe private systems. In the first case, environmental concerns and

waste disposal legislation are the main motivations underlying reverse logistics. Contrary to this notion

are private reverse logistics networks that handle residues or end-of-life products in which recycling is

economically more attractive. Private processors finance the transportation of these materials as well as

the recycling process itself. For recycling to be economically viable, a significant amount of discarded

products (or parts) need to be processed.

The reverse logistics literature for recycling also explores the planning and control of recovery

activities (i.e., the decisions about what to collect, disassemble and process, and in what quantities,

how, when and where), the available information and communication systems (e.g., software, data

requirements), the logistical implications of recycling, and the implementation of programs to increase

the demand of recyclable materials. As Table 1 shows, the studies examining these issues explore only

one type of recyclable material.

Finally, the scope of this research explores the incentives that may stimulate a desired behavior in

specific members who form part of the reverse channels. These incentives look for encourage / impose

cooperation either in terms of reception or delivery of goods for recovery. In the first case, companies

may have some goods that they wish to dispose of, and, through incentives, influence others (e.g., the

goods’ providers) in accepting such requests, in order to avoid high disposable costs. The second case

includes situations in which the purpose is to encourage others (final consumers) to take part in efforts

which allow companies to manage goods (products, parts, packaging) for recovery. Table 1 identifies

three types of non-economic incentives: timely and clear information, general convenience, and an easy

and simple method of supply.

Table 1 evidences that only two studies on reverse logistics for recycling have specifically focused

on household residues and they address the topic of how to design and manage the logistics networks

(Jahre, 1995; Chang and Wei, 2000). In other words, despite the significant amount of research on

reverse logistics during the last years, no study has so far identified what elements of customer service

are important predictors of consumer involvement in the reverse logistics system for recycling. To

fulfil this research gab is the overall objective of the current study.

3 CONCEPTUAL FRAMEWORK AND RESEARCH HYPOTHESES

Incentives are of particular relevance in the context of encouraging consumer to separate and

properly dispose of household packaging residues for recycling. In this case, the consumer is the

starting point of any reverse logistics for recycling household waste and, therefore, his or her

participation is a needed condition for a recycling system to exist. Although this topic has not been

explored in the reverse logistics literature, in the field of environmental social-psychology, some

studies address the predictive effect of a convenient recycling program in articulation with other

potential determinants of environmentally friendly behavior. Essentially, the review of the literature

shows that an increase in consumer involvement can result from the following aspects: (1) closer

proximity of disposal recipients, (2) minimal complexity in storing and storage of recyclable materials,

(3) accessible information on what is recyclable and the location of collection points, and (4) reliable

frequency of collection. Table 2 summarizes the main characteristics and conclusions from these

studies.


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Table 2: Customer service elements as predictors of recycling behavior

Consumer-service

levels

Reference Variable under

analysis

Participants Finding (*)

Proximity of disposal

recipients

De Young (1990) Self-reported

recycling

Residential

households

+

Folz (1991) Participation in

recycling

Residential

households

+

Folz and Hazlett

(1991)

Participation in

recycling

Residential

households

+

Vining and Ebreo

(1992)

Self-reported

recycling

Residential

households

+

Pelton, Strutton,

Barnes and True

(1993)

Willingness to

participate in a

recycling program

Residential

households

+

Margai (1997) Self-reported

frequency of recycling

and observed amount

of collected materials

Residential

households

+

Ludwig, Gray and

Rowell (1997)

Participation in

recycling

College students +

Saphores, Nixon,

Oladele, Ogunseitan

and Shapiro (2006)

Self-reported

recycling

Residential

households

+

Minimal complexity in

separating and storing

Gamba and Oskamp

(1994)

Self-reported

recycling

Residential

households

+

Reliable frequency of

collection

Jacobs, Bailey and

Crews (1984)

Participation in

recycling

Residential

households

+

Foshay and Aitchison

(1991)

Amount of collected

material

Residential

households

+


recycling

Residential

households

0

0’Connor (1993) Amount of collected

material

Residential

households

+

Availability of

information about

Luyben and

Cummings (1981-82)

Amount of collected

material

College students +

what to recycle and

where

Jacobs, Balley and

Crews (1984)

Participation in

recycling

Residential

households

+

Burn and Oskamp

(1986)

Participation in

recycling

Residential

households

+


recycling

Residential

households

+


recycling

Households from

communities with

recycling education

programs

+

Diamond and Loewy

(1991)

Observed participation

in recycling

College students +

Hopper and Nielsen

(1991)

Self-reported


Residential

households

+


recycling

Residential

households

0

Folz and Hazlett

(1991)

Participation in

recycling

Residential

households

0

Austin, Hatfield,

Grindle and Balley

(1993)

Amount of collected

material

College students +

Thogersen (1994) Self -reported and

observed recycling

Residential

households

+

Nyamwange (1996) Self-reported


Residential

households

+

Leroux (2000) Rate of waste

reduction

Residential

households

+

Note:(*) Legend +: significant positive relationship; -: significant negative relationship; 0: non-significant

relationship.


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Based on the literature review, Figure 1 depicts the proposed model of consumer involvement in

the reverse logistics system for recycling. The model establishes a direct causal-effect relationship of

customer service in terms of consumer involvement. The following hypothesis establishes this

connection:

Figure 1: Conceptual model of customer service in the reverse logistics system for recycling

Hypothesis 1: Customer service explains consumer involvement in the reverse logistics system

for recycling household packaging.

In terms of forward distributor channels, Maltz and Maltz (1998) state that the concept of

customer service includes two common levels: (1) hard level that corresponds to objective or basic

customer services, and (2) soft level that refers to perceptual customer service elements, besides those

of basic service. The logistics literature widely accepts this classification of customer service levels

(Dadzie et al., 2005; Mentzer et al., 1989; Stock and Lambert, 2001).

Earlier research is clear about the meaning of basic customer service in forward reverse logistics.

As Dadzie et al. (2005) summarize, this construct includes in-stock availability and cycle time. The

literature on reverse logistics for recycling does not address this issue. This study proposes that the hard

elements of customer service lie in the accessibility to the selective collection recipients. By providing

this basic element to consumers, the reverse logistics system for recycling can operate. The remaining

customer service elements that Table 2 presents depend on this element, that is, they are important only

if communities have specific recipients for separated materials at their disposal. Consumers may

perceive the separation process as satisfactory, understand how and why to separate, believe that, in

general, the collection frequency is adequate, but without a collection service in place (well located and

not too distant) they will not participate in the recycling program. The second research hypothesis

represents these considerations:

Hypothesis 2: The hard level of customer service in the reverse logistics system for recycling

household packaging consists in the access to the selective collection facilities.

Identifying the soft elements of customer service in the forward reverse logistics systems is not as

clear as identifying hard elements. According to the definition proposed by Dadzie et al. (2005), soft

elements are those other than in-stock availability or time cycle, that is, those that are not basic service.

These elements are not objective but instead perceptual and result from suppliers’ ability to respond to

specific customer requests (Maltz and Maltz, 1998). In forwards reverse logistics systems, soft

customer service elements include error correction, follow up on customer complaints, after sales

services, and effectiveness in the handling of information (La Londe and Zinszer, 1976).

The current study on the elements of customer service in reverse logistics for recycling follows a

similar approach and considers that the soft elements go beyond just basic service, that is, beyond the

easy access to specific disposal recipients for recyclable materials. As Maltz and Maltz (1998) refer,

soft elements result from consumers’ perceptions about customer service rather than from the objective

characteristics of this service. Therefore, soft elements should necessarily include the perceived

Customer

service

Hard level (Access to disposal

containers)

Consumer

commitment

Soft level (Elements other

than accessibility to

disposal recipients)

H1

H2

H3

H4

H4


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complexity in storing and separating the recyclable materials, the availability of information on how to

recycle and where to dispose of the recyclable materials and a reliable periodic collection. Table 2

summarizes the existing research on these elements. Besides these elements, this study explores

whether hygiene, design and security at the disposal locations, as well as available support and claim

services have an important soft elements of customer service. Based on this discussion, the study

establishes a third research hypothesis:

Hypothesis 3: The soft level of customer service in the reverse logistics system for recycling

household packaging includes all elements beyond accessibility to the selective collection facilities.

As Table 2 shows, research has focused mostly on the proximity element of disposal recipients

and, according to studies, has a consistent and positive effect on consumer participation in terms of

recycling. This Table also suggests that the effect of the remaining elements (soft elements, as this

study looks to show) on consumer participation is only moderately apparent. In fact, some studies show

that the more complex the sorting process is, together with limited recycling information, the lower the

recycling participation rates. However, a small number of studies find a non-significant relationship

between these variables. Given these considerations, and the fact that soft level of customer service can

only exist after the provision of the hard level, the final research hypothesis is as follows:

Hypothesis 4: The hard level of customer service is the main determinant for consumer to commit

to the reverse logistics systems for recycling, followed then by the soft level.

4 METHODS

4.1 Setting

The Green Dot Society (GDS) is a private company, created in 1997 with the purpose of managing

the Integrated Recovery System of Packaging Waste Management (IRSPWM). Currently, GDS is the

only company that develops this type of activity in Portugal. GDS is essentially a reverse logistics

aggregator with a shareholder structure composed of three holdings that represent almost 200

companies. The first holding represents the packagers/importers, the second represents the distribution

and retail trade, and the third represents the manufacturers and recyclers of packaging material. In

compliance with national legislation, GDS aims to recover 60% of the overall packaging weight and

recycle 55% of this material by the end of 2011. Recyclable materials include glass, paper/cardboard,

lightweight packaging (plastic, metal) and wood. With the exception of this last type of material, drop-

off systems, often referred to as eco-points, allows for the collection of packaging residues.

As in other European countries, the IRSPWM relies on the principle of shared environmental

responsibility. Packers and importers finance the system, based on the polluter-pays principle in which

the amount and weight of the corresponding packaging material, commonly known as the green spot

value, regulates the fee they must pay. In turn, packers and importers receive permission to mark their

packaging with the Green Spot symbol, which shows that these companies transfer their recovery

responsibility to GDS and the IRSPWM. The distribution role ensures that their commercial confines

only sell non-reusable packaging through the Integrated System. The GDS’s business structure does not

include municipalities though they are responsible through contract agreement for the multi-material

collection and sorting of household packaging residues.

Consumers should necessarily separate and dispose of their packaging waste at the eco-point. The

packaging manufacturers complete the cycle by securing the recycling of collected household

packaging. The GDS’s overall mission is to manage the reverse supply chain, finance and guarantee the

functioning of the entire system. This corporation invests a major part of its annual overall income to

compensate for the additional costs that municipalities incur with multi-material collection and sorting.

GDS also sub-contracts transportation services that handle packaging residues for recycling companies

and ensures that they receive, store and recycle recovered material.

4.2 Questionnaire

Data of this research result from personal interviews performed in April and May of 2006 based

on a structured questionnaire (appendix 1). The questionnaire design took into account an extensive

review of scientific and practitioner publications on recycling behavior, interviews on key elements of

GDS management and benchmark studies carried out in other European countries (Spain, Italy and

Belgium). The questionnaire encompasses three sections. Section 1 conducts an inquiry of the socio-

demographic characteristics: gender, age, educational qualification, marital status, occupation,


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residence type, home ownership and family monthly income. Section 2 involves eleven elements

(included in the earlier study) characterizing customer service in the reverse logistics system for

recycling: (1) location of disposal recipients, (2) frequency of waste collection, (3) distance to the

disposal recipients, (4) number of disposal recipients, (5) cleaning and maintenance of disposal

recipients, (6) local safety, (7) emptying regularity, (8) available information, (9) support and claim

service, (10) system adequacy to lifestyle, and (11) number and type of suitable waste materials. A

Likert five-point scale assesses these elements, ranging from 1 – very unsatisfied to 5 – very satisfied.

Section 3 looks to measure consumer involvement in the recycling program and considers two

questions. The first measures the self-reported household recycling behavior (scale: 1 – separates and

selectively discards recyclable waste, 0 – does not separates and selectively discards recyclable waste).

The second evaluates the frequency of separation and disposal of recyclable materials at the eco-points

(scale: 1 – never, 2 – sometimes, 3 – always).

4.3 Sample and data

The study population encompassed the adult Portuguese citizens living in Faro city. Faro is the

capital of Algarve, located in the southern Portugal, comprehending six parishes. Faro has a total

population of 58 350 inhabitants and its most important economic activities are tourism and services.

From this population, the study selected a random sample of 267 citizens. The calculation of the sample

used the most conservative estimate for a single proportion (p = 0.5), a confidence level of 95% and a

maximum error of 6%. The study used stratified sampling and the distribution of the interviews

according to parishes was proportional to the resident population. In each parish the most important

shopping street was selected as the location to perform the interviews. College students administered

the questionnaires to respondents in those streets, with respondents chosen at random, according to a

systematic procedure. A questionnaire was delivered to the first person (older than 14) passing near the

interviewer at a defined hour. Then, a sampling interval of 5 people was established in order to select

the remaining respondents and, thus, to fill the sample stratum defined to each parish. Each respondent

received an explanation of the nature of the questionnaire.

Table 3 summarizes the socio-demographic characteristics of the respondents along with some

household features and participation patterns. Around 61% of respondents replied as being active

participants in the recycling program. The profile of the respondents corresponds roughly to that in the

previous national study (GDS, 2000). Most respondents were females (59.4%), between the ages of 26–

35 (27.2%) and 36–45 (18.2%), married (51.1%) and university degree holders (34.2%).

Table 3: Characteristics of the sample

Variables Distribution of answers

Gender 59.4 % female 40.6% male

Age 14 – 25: 15.1%

26 – 35: 27.2%

36 – 45: 18.2%

46 – 55: 17.0%

56 – 65 :11.0%

66 – 94: 11.5%

Education level 4 years: 10.1%

6 years: 7.3%

9 years: 9.0%

12 years: 26.7%

technical/ professional: 12.7%

College or higher: 34.2%

Median education level: 12 years

Occupation Farmer/fisher: 1%

Workman: 14.1%

Services worker: 22.4%

Public worker: 8.2%

Teacher: 7.3%

Liberal worker: 5.4%

Manager: 9.2%

Retired: 5.1%

Housewife: 4.3%

Student: 18.0%

Other: 5.1%

Marital status Married: 51.1%

Single: 34.0%

Divorced: 9.8%

Widow:5.1%

Residence type Apartment: 63%

House: 27%

Farm: 10%

Home ownership Own/are buying: 75%

Renting: 18%

Familiar: 7%

Monthly family income Less than 324 €: 2.1%

324 € – 499 €: 10.3%

500 € – 999 €: 39.3%

1000 € – 1999 €: 31.2%

2000 € – 2999 €: 11.7%

At least 3000 €: 5.4%

Self-reported recycling

behavior

Uses to separate and selectively

dispose of: 61%

Do not separate nor selectively

dispose of: 39%

Frequency of separation and

disposal of recyclable materials

Never: 22%

Sometimes: 27%

Always: 51%


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4.4 Data analysis methods

This study uses the following methods of multivariate data analysis: exploratory factor analysis

(EFA), confirmatory factor analysis (CFA) and discriminant analysis (DA). EFA and CFA enable the

assessment of hypotheses 2 and 3. DA permits to test hypotheses 1 and 4.

The application of EFA with varimax rotation on the set of eleven elements of customer service

allows for the reduction of the proposed instrument’s dimensionality (Hair et al., 1998; Reis, 1997).

The computation of the Kaiser-Meyer-Olkin (KMO) statistic and the results from the Bartlett test

establishes whether using EFA is possible in this research. The KMO statistic is a ratio that ranges from

0 to 1, and should be at least 0.7 for EFA be acceptable. The Bartlett test examines whether the

correlation matrix of the variables is significantly different from the identity matrix. The use of EFA is

adequate if this test rejects the null hypothesis that these matrices are equal. The Alfa Cronbach

coefficients evaluate the reliability of the final customer service factors that result from the EFA.

CFA evaluates the factors’ psychometric properties in terms of reliability and validity, based on

the AMOS 6 software package. The prior EFA defines the model that CFA requires to associate the

latent factors to the observed customer service elements (the observed variables). Given the absence of

normality in the data, this analysis uses the weighted least squares estimation method (Schumacker and

Lomax, 1996).

The analysis of the overall model fit relies on three types of measures: absolute fit, incremental fit

and parsimonious fit (Hair et al., 1998). The absolute fit evaluation adopts the Chi-square goodness-of-

fit test, the goodness of fit index (GFI) (Joreskog and Sorbom, 1986) and the root mean square residual

of approximation (RMSEA) (Steiger, 1990). The Chi-square test is a general indicator of how well the

estimated model fits with the data. The Chi-square value should be low and not statistically significant

to achieve goodness of fit. Similarly, the GFI should exceed 0.9 (GFI range from 0 to 1 with 1 meaning

perfect fit) and the RMSEA show be low (zero suggests a perfect fit). This study considers the

following incremental fit measures: the adjusted goodness of fit index (AGFI) (Joreskog and Sorbom

1986), the normed fit index (NFI) (Bentler and Bonnet, 1980), the Tucker and Lewis index (TLI)

(Tucker and Lewis, 1973), the incremental fit index (IFI) (Bollen, 1988) and the comparative fit index

(CFI) (Bentler, 1990). These measures range from 0 (no fit) to 1 (perfect fit). The parsimonious fit

index that this study observes is the normed Chi-square measure (Joreskog, 1969) that should range

from 1 to 5, ideally.

The interpretation of the results of CFA follows with a reliability assessment of the proposed

measurement model. Reliability analysis refers to whether the observed variables (i.e., the customer

service elements), chosen to indicate each latent variable (i.e., each customer service factor or level),

are actually measuring the same concept. This study considers two measures of reliability: composite

reliability and variance extracted. Composite reliability shows the degree to which the observed

variables adequately represent the corresponding latent variable. Variance extracted complements the

composite reliability and expresses the total variance of the observed variables that the latent variable

explains. The latent variables present appropriate levels of reliability if composite reliability and

variance extracted exceeds the acceptance level of 0.7 and 0.5, respectively (Scharma, 1996).

Next, the analysis focuses on the evaluation of the convergent and discriminant validity of each

latent variable (customer service level). Convergent validity evaluates whether the observed variables

really measure the corresponding latent construct. The significance and the size of the observed

variables’ weights permit evaluating of this type of validity (Bollen, 1989). Discriminant validity

focuses on whether strong correlations exist between the latent constructs (which indicates poor

discriminant validity) or weak correlations (which suggests strong discriminant validity). Within the

CFA method, the matrix of standardized correlations between the latent variables allows assessment of

this type of validity. This study expects a significant correlation between the latent constructs since

they represent the dimensions of a general construct, the customer service. Another expected result is

that these correlations, although statistically significant, are not very high, because the latent constructs

should be measuring different levels of customer service (hard and soft). Hair et al. (1998) suggest that,

for purposes of discriminant validity, the correlations between latent variables should not exceed 0.7.

DA uses the final customer service levels that EFA and CFA suggest as discriminant variables.

This study carries out two DAs. In the first one, the dependent variable represents self-reported

recycling behavior, with two categories (1 – separates and selectively discards reusable waste, 0 – does

not separate nor selectively discards reusable waste), giving rise to one discriminant function. For the

second DA, the dependent variable is the frequency of separation and disposal of recyclable materials

at the eco-points, which is tri-categorical (1 – never, 2 – sometimes, 3 – always), producing two

discriminant functions. In each case, the Box M’s test assesses the underlying assumption of the DA,

that is, that the matrices of variances and covariances for all groups that the dependent variable defines

are equal.


10

For each DA, the estimation of the discriminant functions uses a random sample of half of the

cases (the analysis sample). The other half (holdout sample) allows validation of DA (Fernández and

Martinez, 2000). For each analysis, the Wilks’s lambda statistics test whether the discriminating

function(s) significantly differentiates the groups defined by the dependent variable. In this test, the

null hypothesis is that the groups defined by the dependent variable have the same mean in the

discriminating function(s).

To assess the predictive ability of the discriminant function(s), this study analyses the

classification matrix that results from each DA. Inside this matrix, the number of cases that the analysis

correctly classifies within each group appears on the principal diagonal. The overall hit ratio is the

global percentage of correct classifications in all the groups.

Two procedures evaluate the classification accuracy of the discriminant functions (Huberty, 1994;

Klecka, 1980). The first procedure compares the overall hit ratio for both samples (the analysis sample

and the validation sample) either with the maximum chance criterion or with the proportional chance

criterion. The maximum chance criterion is the percentage of cases in the larger group. Alternatively,

the proportional chance criterion takes into account the proportion of cases in all groups. In particular,

for a dependent variable with k categories (i.e., k groups), the expression is as follows: k

2

pro i

i 1

C p

where pi is the percentage of cases in group i (i=1,2,…k). The second procedure is to establish and

evaluate the Press' Q statistic. This statistic tests the null hypothesis which states that the discriminating

ability of the classification function(s) is not significantly different than the classification by chance.

The null hypothesis in this test is that the number of cases correctly classified resulting from the

discriminant analysis does not exceed the number of cases correctly classified by chance. The Press' Q

statistic should be high and statistically significant for the purpose of DA’s validation.

5 RESULTS

5.1 Exploratory factor analysis

EFA allows the reduction of the original eleven elements into two factors, in which both account

for 71.3% of the total variance (KMO = 0.87; Bartlett test p = 0). Table 4 summarizes the main results

of this analysis. The observation of the elements with higher loadings for each factor justifies the

corresponding chosen label. Factor 1, hard level, gathers the customer services elements (CSE) that

reflect the availability and accessibility to selective collection recipients: the distance to the disposal

recipients, their location and the available quantity. Factor 2, soft level, includes the remaining elements

such as aspects relating to disposal conditions (indicated by local safety, cleaning and maintenance and

frequency of waste collection), available information on recycling (indicated by information

availability, support and claim services) and system adequacy (indicated by system adequacy to

lifestyle and number and type of accepted materials). The high Cronbach’s alpha coefficients for each

factor suggest that they have a very good degree of internal consistency. The factors take into account

the hypothesized customer service elements, a sign in support of hypotheses 2 and 3.

Table 4: Customer service elements (CSE) and factors (After varimax rotation)

Factors Loadings % of Explained Variance

and Cronbach

Factor 1 – Hard level

CSE3 – Distance to the disposal recipients 0.86 42.1%

CSE1 – Location of disposal recipients 0.78 Cronbach =0.92

CSE4 – Number of disposal recipients 0.56

Factor 2 – Soft level

CSE2 – Frequency of waste collection 0.84 29.2%

CSE6 – Local safety 0.81 Cronbach =0.87

CSE11 – Number and type of accepted waste materials 0.73

CSE7 – Emptying regularity 0.71

CSE5– Cleaning and maintenance of disposal recipients 0.69

CSE8 – Available information 0.64

CSE9 – Support and claim service 0.62

CSE10 – System adequacy to lifestyle 0.59


11

5.2 Confirmatory factor analysis

Figure 2 shows the standardized estimates on the CFA model. Regarding the absolute fit

evaluation, the Chi-square statistic reports a low and not statistically significant value (p > 0.05),

suggesting that the model adequately describes the data. The remaining measures of overall fit also

present favorable results, indicating an adequate incremental and parsimonious fit: the GFI exceeds 0.9

and the RMSEA are close to 0; the AGFI, the NFI, the TLI, the IFI and the CLI exceed 0.9; the normed

Chi-square lies in the 1 to 5 interval.

For the latent variable hard level, the composite reliability coefficient is 0.76 and the variance

extracted is 0.51. For the soft level, the reliability measures are 0.89 and 0.50, correspondingly. For

both latent variables, these values exceed the minimum threshold of 0.7, in terms of composite

reliability, and are at least 0.5, in terms of the variance extracted. These results support the EFA

findings concerning the factors’ reliability, according to the Cronbach’s alpha coefficients. In terms of

the convergent validity analysis, Figure 2 shows that all observed variables have positive weights that

exceed the acceptable level of 0.4 (Hair et al., 1998). All weights are statistically significant (t tests: p =

0.00). In terms of discriminant validity, Figure 2 reveals that the correlation level between the latent

variables is 0.58. This correlation is moderately high, indicating a correlation between the two latent

variables (i.e., both represent levels of the same construct: customer service) which is not too strong

(i.e., each level captures a somewhat different perspective of the customer service construct).

Thus, EFA and CFA specify two final customer services levels whose contents provide support to

research hypotheses 2 and 3.

Figure 2: Confirmatory factor analysis of customer service elements. Standardized estimates

Note: Chi-square = 59.6 (p = 0.07), GFI = 0.94, RMSEA = 0.03, AGFI = 0.91, NFI = 0.89, TLI = 0.97, IFI =

0.97, CFI = 0.98, Normed Chi-square = 1.32.

5.3 Discriminant analysis

The first DA uses the two factors produced by the EFA as independent or discriminating variables

and the self-reported recycling behavior as the dependent variable (Box’s M test p = 0.17). For the

second DA, the dependent variable indicates participation frequency (Box’s M test p = 0.08). In both

cases, the Wilks’s lambda tests reveal that the groups, defined by the dependent variables, are

statistically different in terms of the customer service satisfaction level (Wilks’s lambda tests: p = 0).

The two discriminant functions arising from the second DA, are both significant in separating the

groups (canonical correlation for the first discriminant function = 0.93; canonical correlation for the

second discriminant function = 0.86; explained variance for the first discriminant function = 68.8%;

explained variance for the first discriminant function = 31.2%). Thus, these findings support the

research hypothesis that variables related to customer service elements determine consumer

involvement in the reverse logistics system for recycling (Hypothesis 1).

The overall hit ratio for both the analysis and holdout samples evaluates the predictive accuracy of

the discriminant functions (one in the first DA, two in the second DA). These ratios (72% and 68.2%,

respectively, in the first DA and 69% and 65.4%, in the second DA) significantly exceed the levels of

the proportional chance criterion and the maximum chance criterion (in both analyses, and in terms of

both criteria, Press Q statistic > χ2

(1) for a significance level of 0.05).

Table 5 reports the structural coefficients, representing the correlations between the discriminating

variables and the discriminant functions. Both levels are statistically significant in discriminating the

Hard level

CSE1

Soft level

CSE3 CSE2 CSE6 CSE11 CSE7 CSE5 CSE4 CSE8 CSE9 CSE10

0.89 0.87 0.60 0.81 0.77 0.87 0.86 0.78 0.52 0.56 0.63

0.58

e3 e1 e4 e2 e6 e11 e7 e5 e8 e9 e10

0.48 0..61 0.71 0.52 0.48 0.42 0.59 0.61 0.65 0.54 0.50


12

groups because in the both DAs and in all the discriminant functions, the structural coefficients exceed

the minimum absolute value of 0.3 (Hair et al., 1998). However, as this table shows, of the two

variables in the first DA, the hard level has the highest structural coefficient and, thus, this factor

discriminates the most; on the contrary, the soft level reports the lowest structural coefficient and,

therefore, this factor discriminates the least. The same finding occurs in the second DA in terms of the

first discriminant function, this of which is the most important. In other words, the fourth research

hypothesis (Hypothesis 4) should not be rejected.

Table 5: Structure matrix of discriminant analyses

Discriminating Variables Structural Coefficients

DA1 DA2

Discriminant function 1 Discriminant function 2

Hard level 0.75 0.71 -0.33

Soft level 0.62 0.54 0.68

6 DISCUSSION AND CONCLUSION

Consumers are the foremost and decisive link in a reverse logistics chain that aims to recycle

household packaging residues. In fact, without consumers’ involvement and continuous collaboration,

this system cannot exist. This article explores the importance of consumer motivation to participate in

the IRSPWM by ensuring that the recyclable materials are available for the recycling industries. By

using a combination of multivariate statistical methods, this study shows the importance of providing

consumer convenience in order to gain greater involvement in reverse logistics systems for recycling.

On the whole, the research supports the conceptual model of customer service (Figure 1). As in the

traditional forward logistics systems, customer service in the reverse logistics system for recycling

comprises hard and soft levels (hypotheses 2 and 3). As hypothesized, both levels explain consumer

involvement (hypothesis 1), with the hard level representing the most important predictor (hypothesis

4).

This study has theoretical contributions and managerial implications.

Previous studies in forward logistics identify the elements that form the customer service construct

and explore the importance of providing an adequate level of customer service. The first theoretical

contribution of this article lies in exploring this issue in the specific context of reverse logistics for

recycling. The EFA and CFA that this study employs show that the hard level of customer service in

the reverse logistics chain also corresponds to the basic service, which, in this case, means easy access

to specific disposal recipients for recyclable materials. These analyses also show that other customer

service elements form the soft level. These findings support those found in the forward logistics

research. The second theoretical contribution of this study concerns a comprehensive analysis of a

service based on convenience in order to enhance recycling behavior. In fact, existing literature in the

field of environmental social psychology addresses some customer service elements individually

(Table 2). This study focuses on the various elements as a whole, combining them into a single

analysis, and adding new elements (hygiene, security at the disposal sites and the existence of support

and claim services), revealing to be significant factors.

Overall, this study substantiates that consumers are sensitive to several customer service elements

and that their evaluation of this service determines the current self-reported recycling behavior and the

frequency of involvement. These results have managerial implications. The first one is that meeting

customer service demands in terms of customer service requirements must be a priority in planning this

type of reverse logistics networks. This is not difficult to carry out because the customer service

elements of the reverse logistics system for household packaging are manageable variables. Therefore,

their evaluation reveals opportunities and insight to improve the effectiveness of the customer service

concept and, as a consequence, increase consumer involvement in the system.

The study also observes the customer service levels by taking into account their relative

importance in fostering consumer involvement: the hard level is relatively more important than the soft

level. This finding also has managerial implications since it helps prioritize the overall logistics needs

for a more effective selective-collection system. Although the overall organization and performance of

the Portuguese reverse logistics system for recycling requires global improvement, an important

priority us defining the location of the eco-points in terms of easier and more convenient population

access. In establishing this, focus should turn to aspects such as available support and claim service,

more recycling awareness campaigns, and general disposal conditions (cleaning, maintenance, safety,

etc).


13

Reverse logistics systems with centralized the disposal facilities (as is the case with the eco-points

in Portugal) are more inconvenient because consumers must transport and deposit recyclable materials

at drop-off points. However, these systems are also less expensive than the curbside alternative. In

curbside schemes, collection is door-to-door, which increases convenience but also collection costs and

ultimately the overall cost of the system. A less expensive collection option is to maintain eco-points

and invest in more convenient locations. However, considering the relative importance of the hard

customer service level as the main determinant of consumer involvement, the possibility of providing

curbside collection, at least temporarily and in a few municipalities, should be considered. As this study

shows, shortening the distance that consumers have to travel to reach the collection points is the best

way to obtain greater involvement. The improvement of the quality and quantity of the collected

materials may compensate the additional collection costs of curbside collection. This is as aspect that

clearly deserves further investigation.

As this study demonstrates, the soft level also explains consumer involvement in the reverse

logistics system. Systems based on eco-points reduce the monetary separation costs because consumers

do not receive financial compensation for their sorting and discarding activities. Given that the current

system demands significant efforts on the part of consumers, this may reduce their willingness to

recycle. A more convenient alternative would be not to expect consumers to separate recyclables, that

is, to allow them to discard all the recyclable materials into a single recipient and assign the

responsibility of the separation process to Material Recovery Facilities. Although such a strategy can

reduce the system’s complexity from the consumer perspective this substantially increases separation

costs and, thus, the total cost of the system. A similar problem would incur if the improvement of

customer service implies a change to a commingled collection system (in contrast to multi-material

collection) or the implementation of a more frequent collection system. These strategies are likely to

improve the soft level of customer service in terms of reducing the perceived sorting complexity and

solving the (lack of) maintenance and design appeal of disposal recipients. The potential of these

strategies and their effects on separation and transportation costs is also a future research avenue.

An additional alternative and intermediate strategy that can improve the soft level of customer

service is to maintain the current multi-material collection based at the eco-points and promote

marketing campaigns to increase consumer awareness for greater involvement. Campaigns can also

demystify exaggerated negative expectations about the recycling system. Implementing curbside

collection, on a larger scale, is also a solution for reducing the sorting complexity, since information

exchange is possible on a one-to-one basis. However, and as referred, the implementation of such a

collection system requires a detailed cost-benefits analysis.

On the whole, this study clarifies the need to address all customer service elements. An important

limitation, however, is the fact that the sample is small and drawn from a single city and, as a

consequence, the generalization of the conclusions needs additional research. Furthermore, the

improvement of customer service brings challenges whose overcoming requires additional research.

Entities that manage the system must weight the need of increasing consumers’ involvement without

compromising the system’s economic viability. Therefore, an important challenge that such a reverse

logistics system needs to overcome is to find the best way to minimize the strategic costs of the

collection system without affecting consumer service performance. Another challenge that arises in the

reverse logistics systems for recycling is to guarantee that the market absorbs the recycled materials.

The quality of collected packaging residues affects the performance of the system because most soiled

materials either cannot be further recycled or may lead to increased reprocessing costs. In this sense,

additional support should be given to research that promotes the development of new products using

recycled materials and also marketing campaigns that aim to increase consumer awareness in using

such materials.


14

APPENDIX: SURVEY ON CONSUMERS’ MOTIVATIONS TOWARDS HOUSEHOLD

PACKAGING RECYCLING

I – CHARACTERIZATION OF THE RESPONDENT

Gender: Female Male Age: …..… years old

Education level:

4 years 6 years 9 years 12 years

Technical –professional College or higher

Marital status:

Married Single Divorced Widow

Occupation:

Farmer/fisher Workman Services worker Public worker Teacher

Liberal worker Manager Housewife Student Retired Other

Residence type: House Farm Apartment

Home ownership: Own/Are buying Renting Familiar Monthly family income:

Less than 324 € 324 a 499 € 500 a 999 € 1000 a 1999 €

2000 a 2999 € At least 3000 €

II – SATISFACTION WITH THE RECYCLING SYSTEM OF HOUSEHOLD WASTE

Indicate your satisfaction level with the following aspects concerning the selective-collection

system of recyclable materials. Use the following answer scale:

Very unsatisfied = 1 … Very satisfied = 5

Location of disposal containers

Frequency of waste collection

Distance to the disposal recipients

Cleaning and maintenance of disposal recipients

Local safety

Emptying regularity

Available information

Support and claim service

System adequacy to lifestyle

Number and type of suitable waste materials

III – INVOLVEMENT IN THE RECYCLING PROGRAM

Do you usually separate and selectively discard recyclable waste?

Yes No

With what frequency do you separate and selectively discard recyclable waste?

Never Sometimes Always

Thank you very much for your participation


15

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Teleworking in United Arab Emirates (UAE): An empirical

study of influencing factors, facilitators, and inhibitors

Mohamed G. Aboelmaged

Ajman University of Science and Technology

Po Box 346, Ajman, UAE

Tel: +971 (50) 6300652


Abdallah M. Elamin

King Fahd University of Petroleum and Mineral (KFUPM)

Po Box 488, Dhahran 31261, Saudi Arabia

Tel: +966 (5) 98509634


Abstract

This research constitutes an empirical study of influencing factors, facilitators, and inhibitors to the

choice of teleworking mode in the UAE context. The research reveals that gender, marital status,

nationality, residence location, and work profession are relevant, whereas educational level, Internet

use, number of children, age, and years of experience are irrelevant influencing factors for the choice of

teleworking mode. Furthermore, the research identifies six distinct facilitators and seven distinct

inhibitors. The perceived importance of most identified facilitators and inhibitors to the choice of

teleworking mode in the UAE context are found almost similar among the respondents. An exception,

however, is made to the association between choice of teleworking mode and individual freedom,

travel overload, cost reduction, and union resistance. The study outlines the limitations of the present

research and suggests some practical implications and recommendations for managers.

Keywords: teleworking, information technology, facilitators, inhibitors, UAE

Mohamed G. Aboelmaged and Abdallah M. Elamin

19

1 INTRODUCTION

Teleworking has recently received a considerable amount of attention both at the academia and

professional world, as one of the remarkable changes in business practices (Morgan, 2004). The last

few years have witnessed an increasing interest in the concept of teleworking, particularly in Europe

and USA. Current predictions suggest that teleworking may become a common mode of working in

future, as Knight (2004) points out that 20 million people in Europe will be teleworking by 2007,

taking the enterprise boundary with them.

The concept of using information technology to work at a distance from the regular work site,

referred to initially as telecommuting working and later as teleworking. The term first came to wider

public attention in the USA in the early 1970s, when it was initially coined by Nilles in 1973 (Nilles,

1994), and it has been described as a growing trend and the future way of organizing work. In some

publications, telecommuting and teleworking are often used interchangeably, but telework is generally

used in a broader sense, covering a wider array of distributed work. In general, the motives of

telecommuting are mainly aimed at achieving travel-time savings, while teleworkers (which may

include telecommuters) attempt to work in alternative workplaces.

2 LITERATURE REVIEW

Various authors (e.g. Mann, 2000) have pointed out the diverse meanings assigned to the term

"teleworking". Accordingly, several researchers have tried to establish their own definition. For

example Nilles (1994) states that teleworking is ―...the partial or total substitution of

telecommunications technologies, possibly with the aid of computers, for the commute to work‖. In the

same vein, Mokhtarian (1991) contends that the term refers to ―...working at home or at an alternate

location and communicating with the usual place of work using electronic or other means, instead of

physically traveling to a more distant work site‖. Due to such an inconsistency shaping the definition of

the term, one could argue that the definitions applied to telework can be grouped in two main blocks;

on the one hand those that emphasize the location of the teleworker and on the other hand, those that

stress the use of information communication technologies (ICT).

The empirical literature on teleworking has grown significantly over the last decade and most

studies are western-based. Researching teleworking in developing world is unsurprisingly new, an Arab

world being no exception. According to Cooper and Schindler (2003), literature can be descriptive,

conceptual, empirical, or case study in nature. This section reviews the mainstream empirical

teleworking literature.

On empirical side of teleworking research, researchers present results from surveying and

analyzing large number of teleworkers, prospected teleworkers, or companies. Golden (2006), for

example, use a sample of 393 professional-level teleworkers in one organization to investigate the

intervening role of work exhaustion in determining commitment and turnover intentions. Similarly,

Neufeld and Fang (2005) conduct two-phased research study to point out that teleworker beliefs and

attitudes, and the quality of their social interactions with managers and family members, were strongly

associated with productivity. In the similar thought, Thériault et al., (2005) assess differences between

home-based working and teleworking behavior among genders and professions considering age groups,

household status, car access location within the city and travel distances. They conclude that gender,

professional status, and age are influencing factors to the choice to teleworking. For example, older

workers are more likely to telework than younger ones, with the exception of lone parents which are

seeking for more flexibility. Furthermore, Carnicer et al. (2003) analyze the results of a survey about

labor mobility of a sample of 1,182 Spanish employees. Their study indicates that women have lower

mobility than men, and that the mobility of men and women is explained by different factors such as

employee‘s perceptions about job satisfaction, pay fairness, and employment stability. In a study of

emotional impact of teleworking, Mann (2000) found that respondents of two service industries in the

UK perceive teleworking advantages as follows: less travel (57%); more freedom/flexibility (57%);

better working environment (50%); fewer distractions (43%); cheaper (29%); freedom to choose

comfortable clothes (14%); freedom from office politics (7%); and easier to complete domestic chores

(7%). On the other hand, Mann (2000) found the perceived disadvantages of teleworking include

isolation (57%); longer hours (50%); lack of support (28%); less sick leave (21%); career progression

(14%); and cost (7%). Similarly, Mannering and Mokhtarian (1995) explored the individual's choice of

teleworking frequency as a function of demographic, travel, work, and attitudinal factors. They show

that the most important variables in explaining the choice of frequency of teleworking from home were

the presence of small children in the household, the number of people in the household, gender of


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respondent, number of vehicles in the household, whether respondent recently changed departure time

for personal reasons, degree of control over scheduling of different job tasks, supervisory status of

respondent, the ability to borrow a computer from work if necessary, and a family orientation. In

addition, Yap and Tng (1990) conducted a survey of the attitudes of female computer professionals in

Singapore towards teleworking. The study reveals that 73% of the 459 respondents were in favor of

teleworking. Most would prefer to work at home 1 to 3 days a week and at the office on the other days,

rather than working at home full time. They would telework only in times of need (e.g. when they have

young children) and were concerned with work and interaction-related problems which might arise

from teleworking. Furthermore, Yap and Tng (1990) suggest that teleworking will be of particular

interest to employees who are married, those with a high proportion of work that can be done at home,

those who find their journey to work frustrating, and those with supervisors and coworkers who are

supportive of teleworking.

3 RESEARCH OBJECTIVES

The objective of this research is twofold:

1. To examine the influence of specific demographic and individual variables on the choice

for teleworking mode.

2. To examine the differences in employees' perception of importance of the facilitators and

inhibitors based on their choice of the teleworking mode.

4 RESEARCH RATIONALE

The rationale behind the study was driven by the fact that most of the teleworking literature has

generally taken their roots in the developed countries, most notably North America and Western

Europe (Kowalski and Swanson (2005). This point indicates that there is a gap worth filling in the

literature resulting from the lack of studies in developing contexts. Considering the uniqueness of the

UAE economical, political and socio-cultural contexts, this study would contribute to filling that

identified gap.

Though the benefits of teleworking are widely accepted within the literature, there is very scarce

empirical research about how demographic and individual variables influence teleworking choice (full-

time, part-time, not to telework) in non-western contexts. Examining such relationships between

teleworking choice for both actual and prospective teleworker and various demographic and individual

variables as well as facilitators and inhibitors in an Arab context, namely UAE will add to the body of

knowledge in this regard.

Finally, the outcome of the present study will provide employees, managers and practitioners with

important insights that help them make better decisions concerning teleworking programs aiming at

improving organizational processes and fostering strategic goals.

5 DEVELOPMENT OF RESEARCH HYPOTHESES

5.1 The role of demographic and individual variables

The extant literature has shown that there are numerous demographic and individual variables

influence the choice of teleworking mode, including gender, age, martial status, profession, educational

level, internet use, nationality, residence, number of children, and years of experience. The subsequent

paragraphs review some of the relevant literature on this regards.

Peters et al. (2004) indicate that socio-demographic variables, such as gender and age, are found

to influence teleworking adoption and its preference. Similarly, Thériault et al., (2005) suggest that

gender and professional status influence teleworking choice, and older workers are more likely to

telework than younger ones. Moreover, Yeraguntla and Bhat (2005) show that women households with

children are likely to be part-time teleworkers, reinforcing the notion that women are the primary

caregivers of children. All in all, they consider age as one of the important individual socio-

demographic variable that turned out to be significant predictor of teleworking. The age effect indicates

that young adults (less than 25 years) are more likely to prefer part-time employment than older adults.

These results are also consistent with the findings of Bagley and Mokhtarian (1997). Moreover, they

reveal that race, job type, and length of service are also important influential factors for the choice of

teleworking mode. Caucasians and Hispanics, For instance, are more likely to telework than other races

(African-Americans, Asians and other). As for job type, their study indicates that employees working


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for an educational institution are more likely to be part-time teleworkers than employees in other kinds

of organizations. For the length of service, Yeraguntla and Bhat‘s (2005) study reveals that employees

who have worked less than a year in the firm are more likely to be part-time teleworkers than those

who have been working for longer periods of time.

A survey conducted by Mokhtarian and Salomon (1996) for the employees of the city of San

Diego about teleworking, revealed that only 3% of the sample report that they face no constraints to

telework but do not have a preference for it and do not currently do it. Based on such a survey they

conclude that people who have longer commutes are more likely to report that they want to telework,

especially if they are women and younger people. Having children, however, seems to have no effect

on the desire to telework.

In the same vein, Mannering and Mokhtarian (1995) use survey data collected from employees of

three government agencies in California to model the frequency of teleworking. The results show that

being a mother of small children had a positive influence on teleworking, as did the number of vehicles

per capita in the household.

Similarly, Wells et al. (2001) conduct surveys of employees at a public agency and a private firm

in Minnesota. They find that 43% of the surveyed employees engaged in teleworking. Furthermore,

they report that Public agency workers teleworked, on an average, three days a week, while private

firm workers teleworked, on an average, 1.92 days a week. The authors find that teleworkers are more

likely to be women, married, and have children.

It is worth noting that, Popuri and Bhat (2003) use data from a national survey of 14,441

households conducted by the New York Metropolitan Transportation Council to show factors that

increase the likelihood that an individual telework. Such factors include women with children, college

education, a driver‘s license, being married, working part-time, household income, working for a

private company (rather than government), and having to pay parking fees at work. Also, it has been

found that the longer an individual has worked at her current place of employment, the greater the

probability she teleworks.

In their analysis of the telework Survey conducted by the Southern California Association of

Governments (SCAG), Safirova and Walls (2004) confirm that having high educational level, more

professional experience in general, and a longer tenure with one‘s current company and one‘s current

supervisor will boost the probability of teleworking. Such a study has also revealed a very surprising

finding that teleworkers are more likely to be male and have smaller households than non-teleworkers,

which is inconsistent with other studies' findings that have shown women, and especially women with

children, to be likely teleworkers.

In the view of the aforementioned discussion, the following hypothesis seems to be relevant for

studying the teleworking in the UAE.

Hypothesis 1: There is no difference among employees in their choice for teleworking based on

their:

H1a: Gender

H1b: Marital status

H1c: Educational level

H1d: Internet use

H1e: Nationality

H1f: Residence

H1g: No of children

H1h: Age

H1i: Years of experience

H1j: Profession

5.2 Facilitators of Teleworking

Teleworking was originally seen as part of a solution to an energy crisis involving the reduction of

commuting (Gray et. al., 1993). In this regard, Kurland and Cooper (2002) show that employees choose

teleworking to reduce lengthy commutes, to decrease work-related stress, to balance work and family

responsibilities, to work longer hours but in more comfortable environments, and to provide

uninterrupted time to focus on their work. Organization-wise, teleworking improve employee morale

and productivity (Kurland and Bailey, 1999). Interestingly, Gray et al. (1993) find that teleworkers are

more productive than office-bound staffs that have to travel to work and tend to suffer a higher level of

stress. In addition, Productivity will increase through teleworking if employees are well motivated and

satisfied when they are able to manage their own time and assume greater responsibility for their own


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work. And also because teleworking contributes to the reduction of costs of absenteeism, stress related

to traffic congestions, train delays and continuous office interruptions (Lim et al., 2003).

Lupton and Haynes (2000) identify four significant driving forces for teleworking: (1) a change in

management attitudes; (2) savings in office costs; (3) demand from staff; and (4) improvements in

technology. Other facilitators include improved productivity, improved staff retention, improved

morale/motivation, and improved staff recruitment opportunities. These forces are confirmed by Mann

(2000) who also points to less travel, more freedom/flexibility, better working environment, fewer

distractions, freedom to choose comfortable clothes, freedom from office politics, and easiness to

complete domestic chores.

Another classification of teleworking facilitators can be found in the literature is adopted by Mills

et al (2001) and Tung and Turban (1996) who distinguish among three categories of facilitators include

organizational, individual, and societal facilitators.

According to Mills et al (2001) and Tung and Turban (1996) organizational facilitators for

teleworking adoption may include securing skilled employees, saving office space, reducing turnover

and absenteeism, computer literacy and usage, productivity gains, overcoming limitations of distance

and time, providing service from home terminals, and reducing operating cost. Individual facilitators

for teleworking, on the other hand, include initiating personal freedom, autonomy, and flexibility

(Feldman and Gainey (1997), support no conflicting working environment (Pulido and Lopez, 2005),

increasing personal productivity, avoiding a commute, working with fewer interruptions, working in

more pleasant surroundings, wearing informal casual clothes, saving the costs of meals, clothes, and

commuting, greater time flexibility, greater job satisfaction, and bridging the career gap by avoiding a

long career break staying at home (Mills et al., 2001; Tung and Turban, 1996).Community or societal

related teleworking facilitators may include reduction of air pollution and dependence on fuel, enable

disabled people to work from home, conserve energy and reduce traffic during rush hours and demand

on transportation, and solving the problem of rural depopulation (Mills et al., 2001; Tung and Turban,

1996).

Although all these facilitators can support the trend of teleworking implementation, there is still a

literature gap about the role of teleworking choice (full-time, part-time, not to telework) in influencing

perceived importance of teleworking facilitators. In conjunction with this line of reasoning, the

following hypothesis is developed:

Hypothesis 2: There is no difference among employees in the perceived importance of teleworking

facilitators based on their choice for teleworking.

5.3 Inhibitors of teleworking

Despite the potential facilitators, teleworking raises two important inhibitors: supervisors‘

resistance to manage employees that they cannot physically observe (managerial control), and

employees‘ concerns about professional and social isolation (Kurland and Cooper, 2002). Studies,

which have addressed these issues, are largely surveys (e.g., Mokhtarian et al., 1995). One exceptional

is made to the study conducted by Baruch and Nicholson (1997). They gathered interview data from 62

teleworkers representing five different companies. However, they only noted that isolation and

managerial reluctance were factors that could hinder teleworking. In line with this, Reid (1993) cites

loss of status and professional isolation as potential dangers for workers moving into teleworking. The

likely outcome of isolation is the lack of interaction with colleagues, which stands as a serious

inhibitor.

As far as management control is concerned, Kurland and Cooper (2002) has demonstrated that

managers may lose control over employees‘ behavior as employees gain autonomy by teleworking.

Teleworking can diminish a manager‘s perceived control as it physically removes the employee from

the conventional work environment. At the same time the employees believe that the isolation may

result in lack of promotional opportunities.

Other inhibitors may include cost of implementation and resistance of management to change,

longer hours, lack of support, less sick leave, career progression (Lupton and Haynes, 2000; Mann,

2000).

Another classification of teleworking inhibitors is adopted by Mills et al (2001) and Tung and

Turban (1996) who distinguish among three categories of inhibitors include organizational, individual,

and societal inhibitors. According to Mills et al (2001) and Tung and Turban (1996) organizational

inhibitors of teleworking adoption may include technology cost inefficiencies, managing out-of-sight

employees, need for collaboration with other employees, security risks, problems of supervision,

performance control difficulty, work coordination difficulty, legal liability, maintenance of equipment.

From the individual point of view, inhibitors may include isolation, doubts and lack of knowledge of


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the state of a task, unavailability of necessary supplies or equipment, family interruptions and

household distractions, no separation of work and home life, lack of interactions with co-workers, and

potential lack of loyalty to company, not having a regular routine, workaholics, impedes career

opportunities, and missing ―what‘s going on‖, problem of 'guilt', and increase in cost of equipment and

utilities at home (Mills et al., 2001; Tung and Turban, 1996; Pulido and Lopez, 2005). From the

community perspective, teleworking may be inhibited as a result of promoting dispersion of housing,

increasing commuting distances, slowing down of real estate market, and declining clothing industry

(Mills et al., 2001; Tung and Turban, 1996).

Although all these inhibitors can hinder teleworking implementation, there is a notoriously

unfilled literature gap about the role of teleworking choice (full-time, part-time, not to telework) in

influencing perceived importance of teleworking inhibitors. Based on the above discussion, the

following hypothesis is suggested:

Hypothesis 3: There is no difference among employees in the perceived importance of teleworking

inhibitors based on their choice for teleworking.

6 RESEARCH METHODOLOGY

This research follows the underlying principles of quantitative research methodology. It entails the

collection of numerical data as exhibiting a few of the relationships between theory and research as

deductive, and as having an objectivist conception of social reality (Bryman, 2008). A survey research

method was applied to obtain insight about the issues explored in the study. Primary research data are

collected through structured questionnaire on a voluntary basis. To ensure the right level of teleworking

awareness, several studies recommend sampling employees from organizations involved in information

technology profession, when studying teleworking (Teo and Lim, 1998; Tung and Turban 1996). The

researchers, therefore, consider an employee in an organization within information technology sphere

as the unit of analysis in this research. Organizations in Dubai Media City (DMC) and Dubai Internet

City (DIC) are selected as target. Both cities include more than 500 organizations in the field of

networking, software development, programming, consultancy, broadcasting, publishing, advertising,

public relations, research and development, music and creative services. A total of 350 questionnaires

are distributed; of these, 148 were returned. 12 questionnaires are ignored due to ignoring complete

section(s) or missing data in certain sections, leaving a balance of 136 useful questionnaires for this

study, with a valid response rate of 39%. Respondents represent eleven ICT and media organizations

specialized in media organization and dissemination, software development, wireless technology,

communication tools and equipment, media production, and consultancy services. All organizations are

small to medium in size varying from 20 to 300 employees. Questionnaire data were aggregated, and

no analysis was conducted linking individual responses to a specific organization.

6.1 Measurement development, reliability, and validity

The survey instrument included several statements designed to measure the research constructs.

First, choice for teleworking is presented in a nominal scale with three options: (1) not to telework; (2)

part-time teleworking; and (3) full-time teleworking. Second, the perceived importance of each of

teleworking facilitators and inhibitors is measured based on a four-point Likert scale from ‗‗strongly

disagree‘‘ to ‗‗strongly agree‘‘. The survey also gathers demographic information on the respondents‘

gender, marital status, educational level, internet use, nationality, residence location, number of

children, age, years of experience, and work profession. A nominal scale is developed for each of these

constructs.

Content validity is assessed by examining the process that is used in generating scale items, and its

translation into other languages (i.e., Arabic in this study). The determination of content validity is

judgmental and can be approached through careful definition of the topic of the concern, the scaled

items, and used scales (Cooper and Schindler, 2003). Teleworking facilitators and inhibitors are

developed based on extensive review of teleworking literature, and then reduced using a varimax

rotated principal component factor analysis. Furthermore, Cooper and Schindler (2003) suggest another

way to determine content validity through panel of persons to judge how well the instrument meets the

standards. Thus, the researchers conducted independent interviews with two professors of human

resources and one professor of information technology applications to evaluate whether research covers

relevant constructs. They suggested that the procedure and Arabic translation of the questionnaire were

generally appropriate, with some modifications in the translated version of the questionnaire.


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6.2 Data Presentation and Analysis

Responses from the surveys were coded and entered into SPSS spreadsheets for data analysis. For

a descriptive analysis, means, SD, cross tabulation, factor analysis, and Kruskal-Walllis test were

applied to the sample.

6.3 Profile of research demographics

The survey‘s demographic descriptive statistics are presented in Table 1. Of the 136 respondents,

54.4% select part-time teleworking option, 33.1% decide not to telework, and 12.5% choose full-time

teleworking option. 50.7 % of the respondents are male and 49.3 % are female. 67.6% are single and

32.4% are married. 31.7% of married respondents have one child, 26.8% have two children, 22.0%

have three children, and 19.5% have four or more children. The research respondents are relatively

young; the majority of survey respondents age is between 20 and 29 years (44.9 %), while 25.7% are

between 30 – 39 years, 18.4% are less than 20, and only11% are above 40 years old. The education

level reported by respondents showed that 75.7% had university degree or equivalent. Respondents

were mainly non-UAE national (66.2%), national Respondents are only represent 33.8%. 40.4% of

research respondents live in the emirate of Sharajah 40.4%, Ajman 25.7%, Dubai 22.1%, Abu Dhabi

6.6%, and UmQuin 5.1%. The description shows that 39% of the respondents are internet users for 1-3

times a week, 34.6% use the internet 7 or more times a week, 19.8% use the internet 4-6 times a week,

and 6.6% are not using the Internet. According to years of experience, most of the respondents (72.8%)

had less than 7 years, and approximately 27.2% had more than 7 years of experience. Respondents in

ICT professions are 18.4%, while 27.2% of respondents are in media professions, 27.2% are in

management and marketing professions, and 27.2% are in accounting professions.

In conclusion, majority of respondents in this study prefer part-time teleworking, graduate male,

single, between 20 – 29 years of age, care for one child if married, with non UAE nationality, live in

Sharjah, use the internet 1-3 times a week, working in different ICT and media professions, with less

than 7 years of experience.

Table 1: Profile of research respondents (N=136)

% N % N

Marital status Teleworking choice

67.6 92 Single 12.5 17 Full-time

32.4 44 Married 54.4 74 Part-time

33.1 45 No choice

Nationality Gender

33.8 46 UAE 49.3 67 Female

66.2 90 Non UAE 50.7 69 Male

Freq. of internet use Educational level

34.6 47 7 or more times /week 7.4 10 Postgraduate

19.8 27 4-6 times /week 75.7 103 Graduate

39.0 53 1-3 times /week 16.9 23 Undergraduate

6.6 9 No use /week

Children

Residence 31.7 13 1

6.6 9 Abu Dhabi 26.8 11 2

22.1 30 Dubai 22.0 9 3

40.4 55 Sharjah 19.5 8 4 or more

25.7 35 Ajman

5.1 7 UMQ Years of experience

36.8 50 0-3

Age 36 49 4-6

18.4 25 Less than 20 17.6 24 7-9

44.9 61 20 – 29 9.6 13 9 or more

25.7 35 30 – 39

11 15 40 or more Profession

18.4 25 IT

27.2 37 Media

27.2 37 Mgt. & Marketing

27.2 37 Account. & Finance


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6.4 Testing the first hypothesis

A cross tabulation analysis is conducted to assess whether there is no difference among employees

in their choice for teleworking based on specific demographic variables. Tables 2 presents frequencies,

percentages, and associations of teleworking choice (i.e., full-time, part-time, and not to telework) with

a number of selected demographic and individual variables including gender, marital status,

educational level, internet use, nationality, residence, number of children, years of experience, and

occupation.

Table 2 indicates that there is a significant difference among employees in their teleworking

choice based on their gender (χ2 = 12.06, p < 0.01). It is clear from the cross tabulation presented in

Table 2 that females constitute the majority of employees who select full-time teleworking option

(88.2%), while males are the majority who select part-time teleworking (58.1%) as well as not to

telework (53.3%). It also shows the association between marital status and teleworking. In that sense,

employees‘ marital status does significantly influence teleworking choice (χ2 = 6.69, p < 0.05). The

table demonstrates that single employees are over represented among non teleworkers (80%). On the

other side, married employees are over represented among full-time teleworkers (52.9%). Educational

levels and their distribution cross teleworking choices are illustrated in also reflected in the Table. The

analysis suggests no significant difference among employees in their teleworking choice based on their

educational level (χ2 = 1.451, n.s). The analysis shows that graduate employees with a university degree

or equivalent are over represented in each of teleworking groups; full-time (76.5%), part-time (75.7%),

and no teleworking group (75.6%). Similarly, the table suggests no significant difference among

employees in their teleworking choice based on their level of Internet use (χ2 = 11.19, n.s.). Employees

who use the internet 1-3 times weekly form the majority of two contradictory teleworking groups; full-

time teleworking (70.6%) and no teleworking (42.2%). While the majority of employees who prefer

part-time teleworking are using the Internet for 7 or more times per week (39.2%). Further, the table

indicates that there is a significant difference among employees in their teleworking choice based on

their nationality (χ2

= 6.33, p < 0.05). It is clear from the cross tabulation presented in Table 2 that

employees with UAE nationality are over represented among full-time teleworkers (58.8%), while

employees with non UAE nationality (e.g., Egyptians, Indians, etc.) are over represented among part-

time teleworkers (73.0%) as well as non teleworkers (64.4%). Surprisingly, difference among

employees in their teleworking choice based on their city of residence is significant (χ2 = 33.99, p >

0.001). Moreover, the table illustrates that part-time teleworking is the main choice of employees living

in emirates of Dubai, Sharjah, and Ajman, while the main teleworking choice of employees living in

UmQuin emirate is full time. However, employees who are living in Abu Dhabi tend to prefer not to

telework. Distribution of number of children cross teleworking choices is also illustrated in the table

suggesting that there is no significant difference among employees in their teleworking choice based on

their number of children (χ2 = 5.65, n.s.). Employees who select full-time teleworking are equally

distributed among those who have two (28.6%), three (28.6%), and four or more (28.6%) children,

while part-time teleworking choice is dominated by employees who have one child only (38.5%).

Similarly, the table suggests no significant difference among employees in their teleworking choice

based on their age (χ2 = 3.78, n.s.). Employees between 20-29 years dominate the majority in every

teleworking group; full-time teleworking (47.1%), part-time teleworking (43.2%), and not to telework

(46.7%). Moreover, the relationship between employees‘ teleworking choice and their years of

experience is not significant (χ2 = 11.11, n.s.) as demonstrated by the table which indicates that

employees who have 4-6 years of experience represent the majority of employees who choose two

contradictory options; to telework full-time (56.8%) and not to telework (44.4%), while part-time

teleworking choice is dominated by employees who have less than four years of working experience

(45.9%). Finally the table illustrates the relationship between teleworking choice and profession. It

shows that employees‘ profession does significantly influence teleworking choice (χ2 = 21.95, p <

0.01). The table demonstrates that 46.7% of employees who prefer not to telework are in accounting

and finance profession, 28.4% of employees who prefer part-time teleworking are in management and

marketing profession, while employees in media profession are over represented among full-time

teleworkers (52.9%).


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Table 2: Cross tabulation results

p

value χ2 Total

Teleworking Choice

No Part-time Full-time

0.002 12.06** Gender

69 (50.7) 24 (53.3) 43 (58.1) 2 (11.8) Male

67 (49.3) 21 (46.7) 31 (41.9) 15 (88.2) Female

0.03 6.69* Marital status

92 (67.6) 36 (80) 48 (64.9) 8 (47.1) Single

44 (32.4) 9 (20) 26 (35.1) 9 (52.9) Married

0.83 1.45 Educational level

23 (16.9) 9 (20) 11 (14.9) 3 (17.6) Undergrad.

103 (75.7) 34 (75.6) 56 (75.7) 13 (76.5) Graduate

10 (7.4) 2 (4.4) 7 (9.5) 1 (5.9) Postgrad.

0.08 11.19

Internet Use

9 (6.6) 4 (8.9) 5 (6.8) 0 (0) No use

53 (39) 19 (42.2) 22 (29.7) 12 (70.6) 1-3 times

27 (19.9) 7 (15.6) 18 (24.3) 2 (11.8) 4-6 times

47 (34.6) 15 (33.3) 29 (39.2) 3 (17.6) 7 or more

0.04 6.33* Nationality

46 (33.8) 16 (35.6) 20 (27) 10 (58.8) UAE

90 (66.2) 29 (64.4) 54 (73) 7 (41.2) Non UAE

0.00 33.99** Residence location

9 (6.6) 7 (15.6) 2 (2.7) 0 (0) Abu Dhabi

30 (22.1) 12 (26.7) 16 (21.6) 2 (11.8) Dubai

55 (40.4) 16 (35.6) 34 (45.9) 5 (29.4) Sharjah

35 (25.7) 9 (20) 21 (28.4) 5 (29.4) Ajman

7 (5.1) 1 (2.2) 1 (1.4) 5 (29.4) UMQ

0.58 4.65 No. of Children

13 (31.7) 2 (25) 10 (38.5) 1 (14.2) One

11 (26.8) 1 (12.5) 8 (30.8) 2 (28.6) Two

9 (22) 2 (25) 5 (19.2) 2 (28.6) Three

8 (19.5) 3 (37.5) 3 (11.15) 2 (28.6) Four or more

0.706 3.78 Age

25 (18.4) 9 (20) 15 (20.3) 1 (5.9) > 20

61 (44.9) 21 (46.7) 32 (43.2) 8 (47.1) 20 - 29

35 (25.7) 12 (26.7) 17 (23) 6 (35.3) 30 - 39

15 (11) 3 (6.7) 10 (13.5) 2 (11.8) 40 ≤

0.085 11.11 Years of experience

50 (36.8) 14 (31.1) 34 (45.9) 2 (11.8) 0-3

49 (36) 20 (44.4) 19 (25.7) 10 (56.8) 4-6

24 (17.6) 8 (17.8) 13 (17.6) 3 (17.6) 7-9

13 (9.6) 3 (6.7) 8 (10.8) 2 (11.8) 9 or more

0.001 21.95** Profession

25 (18.4) 3 (6.7) 18 (24.3) 4 (23.5) IT

37 (27.2) 9 (20) 19 (25.7) 9 (52.9) Media

37 (27.2) 12 (26.7) 21 (28.4) 4 (23.5) Mgt. & Market.

37 (27.2) 21 (46.7) 16 (21.6) 0 ( 0) Account. & Finance

136

(100.0%)

45

(100.0%)

74

(100.0%)

17

(100.0%)

Total

In conclusion, results from ensuing presentation show significant association between teleworking

choice and gender, marital status, nationality, residence, and profession. On the other hand, there is no

significant association between teleworking choice and educational level, Internet use, number of

children, age, and years of experience. Accordingly, hypothesis H1 is partially supported.

6.5 Testing the Second and Third hypotheses

The data collected concerning employees‘ perception of teleworking facilitators and inhibitors are

reduced using a varimax rotated principal component factor analysis. Tables 3 and 4 display the various

facilitators and inhibitors used in this study and show the factor loadings for each of the items. The

loadings indicate a significant relationship between items in each of the factors since all but three are

greater than .50, the critical value for significant loadings (Hair et al., 1992).


27

Table 3: Factors analysis of teleworking facilitators *

7 6 5 4 3 2 1

Community concerns (α = 0.85)

0.093 -0.046 0.202 0.046 0.122 0.097 0.753 Environmental pollution F20

-0.125 0.235 0.087 -0.055 0.193 0.257 0.749 Working opport. for disabled F21

0.005 0.169 0.094 0.220 0.008 0.174 0.724 Traffic Jams F22

0.038 0.088 0.232 0.305 0.141 0.238 0.676 Increasing oil prices F19

0.169 0.067 -0.059 0.379 -0.020 -0.072 0.647 Severe weather conditions F24

0.281 -0.082 0.069 0.103 0.320 0.072 0.629 Family care F23

Individual freedom (α = 0.78)

-0.076 -0.066 0.125 0.089 0.143 0.782 0.122 Flexible working time and location F11

0.246 0.214 0.109 0.075 0.190 0.749 0.120 Personal freedom F9

0.255 -0.041 0.064 0.036 0.146 0.745 0.178 Avoid work stress F10

0.178 0.108 -0.039 0.368 0.267 0.427 0.152 No absenteeism F14

Productivity improvement (α = 0.78)

-0.107 0.167 0.073 0.046 0.785 0.158 0.130 Developing ICT usage F17

0.109 -0.165 0.221 0.077 0.727 0.007 0.056 Better utilization of working time F8

-0.018 0.093 0.174 -0.024 0.603 0.439 0.203 Improving output quality and quantity F13

-0.170 0.284 -0.034 -0.081 0.593 0.419 0.152 Increasing employees loyalty F16

0.417 0.180 0.176 0.015 0.481 0.237 0.101 Paperless work F18

Travel load (α = 0.71)

0.076 0.180 -0.047 0.797 -0.035 -0.126 0.146 Travel preparation F6

0.036 -0.178 0.132 0.724 0.153 0.247 0.219 Travel time F5

-0.087 0.049 0.368 0.624 0.007 0.298 0.298 Travel effort and cost F3

Cost reduction (α = 0.66)

-0.025 0.017 0.821 0.022 0.180 0.193 0.137 Saving org. space and equipments F2

0.279 -0.100 0.671 0.136 0.134 -0.003 0.365 Increasing cost of real states F1

-0.158 0.469 0.518 0.460 0.017 0.102 0.121 Increasing cost of clothes and accessories F4

Empowering people (α = 0.51)

0.226 0.801 0.033 0.0091 0.103 0.096 0.102 Minimizing supervisory functions F15

0.012 0.471 -0.282 0.313 0.355 -0.158 0.217 Task focus F7

0.831 0.158 0.023 0.042 -0.076 0.209 0.161 Doing other more things F12

1.382 1.529 1.893 2.346 2.743 2.826 3.512 Eigenvalue

5.76 6.37 7.89 9.77 11.43 11.78 14.63 Percentage of variance explained

67.63 61.87 55.50 47.61 37.84 26.41 14.63 Cumulative percentage of total var. explained

0.993 0.710 0.716 0.743 0.589 0.665 0.645 Standard deviation

Correlation Matrix Determinant = 0.0000179

Kaiser-Meyer-Olkin Measure of Sampling Adequacy = 0.814

Bartlett's Test of Sphericity (χ2 = 1378.98 , df = 276 , p < 0.001)

* Principal components analysis; varimax rotation with Kaiser Normalization


28

Table 4: Factors analysis of teleworking inhibitors *

* Principal components analysis; varimax rotation with Kaiser Normalization

Cumulative percentage of total variance explained for factor analysis of perceived teleworking

facilitators is 67.63% with Kaiser-Meyer-Olkin measure of sampling adequacy = 0.814, while

cumulative percentage of total variance explained for factor analysis of perceived teleworking

inhibitors is 65.97% with Kaiser-Meyer-Olkin measure of sampling adequacy = 0.794. The Cronbach

alpha coefficient is used to assess reliability of the generated facilitators and inhibitors. As shown in

Tables 3 and 4, the alpha reliabilities range from a low of 0.51 to a high of 0.86. All the reliability

figures, except two variables, were higher than 0.6, the lowest acceptable limit for Cronbach‘s alpha

suggested by Hair et al. (1992), variables with reliabilities lower than 0.6 deserve a further refinement

in future research.

7 6 5 4 3 2 1

Management concerns (α = 0.77)

-0.132 0.164 0.055 0.013 -0.201 0.161 0.727 Org. vision and mission are misplaced B15

0.102 0.060 0.199 0.029 0.224 0.028 0.714 Safety criteria are not guaranteed B16

0.156 0.147 0.012 0.228 0.045 0.192 0.683 Inapplicable work rules and regulations B13

0.039 0.261 0.032 0.447 0.088 0.098 0.569 Access difficulty to decision info. B17

0.265 - 0.029 - 0.056 0.154 -0.054 0.392 0.559 Hard to control and evaluate performance B14

Isolation (α = 0.79)

0.169 -0.015 - 0.020 0.124 0.111 0.766 0.089 Misguidance regarding use of org. resources B11

0.077 0.009 0.257 0.295 0.330 0.672 0.149 Need to interact with work colleagues B8

-0.167 0.433 0.063 0.199 0.014 0.596 0.265 Lack of teleworking experience B10

0.205 0.135 0.120 0.062 0.187 0.528 0.385 Feeling guilty toward the organization B7

0.048 0.293 - 0.037 0.480 0.124 0.509 0.194 Missing promotional opportunities at work B9

Union resistance (α = 0.77)

-0.207 -0.097 0.139 -0.016 0.800 0.115 -0.045 Union resistance B23

0.148 0.017 0.027 0.073 0.793 0.104 0.026 Clothing and makeup industry loss B22

-0.008 0.194 0.036 0.170 0.705 0.196 -0.066 Negative impact on real state sector B21

-0.010 0.144 -0.020 0.218 0.672 - 0.157 0.227 Unclear insurance B24

Home inadequacy (α = 0.71)

0.017 0.112 0.192 0.664 0.266 0.053 -0.068 Increased home noise B20

0.017 -0.091 0.142 0.631 0.150 0.261 0.213 Data insecurity B19

0.236 -0.148 0.106 0.568 -0.021 0.336 0.438 Coordination difficulty B12

0.276 0.318 -0.150 0.531 0.020 0.239 0.317 Inapplicable team working B18

ICT cost (α = 0.86)

0.134 0.073 0.900 0.017 0.017 0.117 0.130 ICT acquisition cost B1

0.036 0.145 0.871 0.219 0.125 0.074 0.062 ICT maintenance and upgrading cost B2

Time mismanagement (α = 0.51)

0.208 .802 0.068 -0.046 0.021 0.199 0.169 Home time mismanaged B6

0.094 .594 0.323 0.152 0.289 -0.109 0.091 Org. time expansion B3

Family intervention (α = 0.62)

0.835 0.106 0.105 0.217 -0.087 0.111 0.046 Family rights B4

0.612 0.303 0.187 -0.117 0.095 0.266 0.350 Family – work intervention B5

1.570 1.747 1.969 2.307 2.595 2.639 3.010 Eigenvalue

6.54 7.28 8.20 9.61 10.81 10.99 12.54 Percentage of variance explained

65.97 59.43 52.15 43.95 34.34 23.53 12.54 Cumulative percentage of total var. explained

0.710 0.694 0.745 0.661 0.688 0.611 0.579 Standard deviation

Correlation Matrix Determinant = 0.00002334

Kaiser-Meyer-Olkin Measure of Sampling Adequacy = 0.794

Bartlett's Test of Sphericity (χ2 = 1345.59, df = 276, p < 0.001)


29

6.6 Study-based generated facilitators

The ensuing factor analysis generates six distinct perceived facilitators for teleworking, including

community concerns, individual freedom, productivity improvement, travel load, cost reduction, and

empowering people (see Table 3).

(1) Community concerns: this factor includes a number of community concerns such as reducing

environmental pollution; provision of working opportunities for disabled; reducing traffic jams;

continuous increasing of oil prices; severe weather conditions all over the year; and family care issues.

No doubt, these concerns make adoption and implementation of teleworking programs in UAE is an

appealing option, particularly in case when distance from home to the workplace is far or when traffic

congestion is a problem.

(2) Individual freedom: Items in this factor reflect the notion that teleworking is forced by the

need to reduce stress level and increase job commitment and quality of work life. One likely reason is

that the flexibility in working schedule of teleworkers offers opportunities for them to engage in non-

work activities to a much larger extent than otherwise possible. Such scheduling freedom may allow

time for personal interests.

(3) Productivity improvement: Items in this factor suggest that improving productivity is

perceived as a driving force for teleworking adoption since individuals can avoid interruptions at the

office and get work done in an effective and efficient manner. In addition, teleworking also allows the

individual‘s autonomy by enabling individuals to work during hours where they are most productive

(Teo and Lim, 1998).

(4) Travel load: Items in this factor suggest that the adoption of teleworking will reduce travel

burden, including travel preparation time and effort, time of travel, effort consumed in the travel, and

cost of travel preparation and expenses.

(5) Cost reduction: Items in this factor reflect the notion that teleworking is a cheap work mode,

since it contributes to saving office space and equipments, cost of real states, and cost of clothing and

accessories (Mills et al., 2001; Tung and Turban, 1996).

(6) Empowering people: Items in this factor show that teleworking is perceived as a method to

empower employees through minimizing supervisory functions and giving the employee opportunity to

focus on task at hand.

6.7 Study-based generated inhibitors

The ensuing factor analysis generates seven distinct perceived inhibitors for teleworking,

including management concerns, isolation, union resistance, home inadequacy, ICT cost, time

mismanagement, and family intervention (see Table 4).

(1) Management concerns: Items in this factor propose that managers may find placing

organizational vision and mission, control, supervision, and designing an equitable compensation

scheme for teleworker and appraising their performance are difficult (Teo and Lim, 1998).

(2) Isolation: Items in this factor illustrate the concept of professional and physical isolation which

is reflected in misguidance regarding use of organizational resources, need to interact with work

colleagues, lack of teleworking experience, feeling guilty toward the organization, and missing

promotional opportunities at work. This isolation is found to be one of the key inhibitors of teleworking

implementation (Kurland and Cooper, 2002; Rognes, 2002).

(3) Union resistance: This factor reflects the power of union resistance supported by clothing and

makeup industry loss, negative impact on real state sector, and unclear insurance. This inhibitor may

hinder the implementation of teleworking.

(4) Home inadequacy: Items of this factor shows that home is inadequate place to telework, when

teleworkers face increasing home noise, data insecurity at home, work coordination difficulty, and

missing the chance of team working.

(5) ICT cost: Items in this factor suggest that accountability for repairs / maintenance of

equipment placed at employees‘ homes may be a problem. Furthermore, the initial investment in

equipment to enable employees to telework may be substantial.

(6) Time mismanagement: Items in this factor suggest teleworking time is mismanaged and

expanded since it intervenes with organization‘s working time and follows flexible working mode.

(7) Family intervention: This factor proposes that teleworking may be hindered by the introduction

of family rights and family – work intervention process.

Kruskal-Wallis nonparametric test is applied to assess the relationship between employees‘

perceived teleworking facilitators and inhibitors as ordinal variables and teleworking mode choices as a

nominal variable. Results are illustrated in Tables 5 and 6. Table 5 shows Kruskal-Wallis test result of


30

the relationship between perceived teleworking facilitators and teleworking choice. With regard to

teleworking facilitators, the analysis demonstrates that there is significant difference among employees

in their perceived importance of individual freedom (χ2 = 17.11, p < 0.01), travel load (χ2 = 6.76, p <

0.05), and cost reduction (χ2 = 10.67, p < 0.01) based on their teleworking choice.

On the other hand, there is no significant difference among employees in their perceived

importance of community concerns (χ2 = 5.62, n.s.), productivity improvement (χ2 = 4.98, n.s.), and

empowering people (χ2 = 4.13, n.s.) based on their teleworking choice. Consequently, hypothesis H2

is partially supported for teleworking facilitators related to individual freedom, travel load, and cost

reduction.

Kruskal-Wallis test result of the relationship between perceived teleworking inhibitors and

teleworking choice is presented in Table 6 The analysis shows that there is significant difference

among employees in their perceived importance of teleworking inhibitors related to union resistance

(χ2 = 6.65, p < 0.01). However, there is no significant difference among employees in their perceived

importance of teleworking inhibitors related to all other categories. Accordingly, hypothesis H2 is only

supported for teleworking inhibitors related to union resistance.

Table 5: Kruskal-Wallis test result of the relationship between perceived teleworking facilitators

and teleworking choice

* p < 0.05, ** p <0.01

χ2 Perceived teleworking facilitators

5.62 Community concerns

5.54 Environmental pollution F20

0.52 Working opportunity for disabled F21

13.28** Traffic Jams F22

9.87** Increasing oil prices F19

3.45 Severe weather conditions F24

0.63 Family care F23

17.11** Individual freedom

10.77** Flexible working time and location F11

9.63** Personal freedom F9

13.17** Avoid work stress F10

6.34* No absenteeism F14

4.98 Productivity improvement

1.41 Developing ICT usage F17

0.87 Better utilization of working time F8

10.15** Improving output quality and quantity F13

0.81 Increasing employees loyalty F16

9.36** Paperless work F18

6.76* Travel load

2.54 Travel preparation F6

10.33** Travel time F5

5.88 Travel effort and cost F3

10.67** Cost reduction

15.65** Saving org. space and equipments F2

2.85 Increasing cost of real states F1

3.21 Increasing cost of clothes and accessories F4

4.13 Empowering people

5.26 Minimizing supervisory functions F15

0.34 Task focus F7


31

Table 6: Kruskal-Wallis test result of the relationship between perceived teleworking facilitators

and teleworking choice

* p < 0.05, ** p <0.01

7 DISCUSSION AND REFLECTION

7.1 Demographic variables

The results have manifested the important role of selected demographic variables in influencing

teleworking choice, namely, the role of gender. Accordingly, results of the test have shown that

females in the UAE tend to prefer full-time teleworking. Women are found to be motivated by some

considerations such as work flexibility, convenience and increased personal freedom (O‘Connor,

2001). UAE females have perceived telework as promising avenue to change their traditional work

orientation and prove their personal freedom in handling work responsibilities. This is in harmony with

Popuri and Bhat (2003), Yap and Tng (1990), and Wells et al. (2001) who suggest that teleworking will

be of particular interest to women employees. However, in contradiction to the result generated by this

research, some studies show that women employees are not interested in teleworking because they

perceived work, not home, as the less stressful and more emotionally rich environment (Hochschild,

1983). In the same thought, Teo and Lim‘s (1998) study shows that males tend to perceive teleworking

as enabling improvement in the quality of life and improvement in productivity/reduction of overheads

to a greater extent than females. In line with this argument, Peters et al. (2004) suggest that three out

of four teleworkers were male in EU member states, and that this stands in sharp contrast to the

widespread opinion that telework was predominantly female. Moreover, research confirms the

association between marital status and teleworking choice found in previous research. This is in

χ2 Perceived teleworking inhibitors

0.84 Management concerns

1.40 Org. vision and mission are misplaced B15

0.67 Safety criteria are not guaranteed B16

2.13 Inapplicable work rules and regulations B13

1.25 Access difficulty to decision info. B17

2.55 Hard to control and evaluate performance B14

2.93 Isolation

3.91 Misguidance regarding use of org. resources B11

1.76 Need to interact with work colleagues B8

4.28 Lack of teleworking experience B10

1.27 Feeling guilty toward the organization B7

0.31 Missing promotional opportunities at work B9

6.65* Union resistance

6.78* Union resistance B23

1.78 Clothing and makeup industry loss B22

0.99 Negative impact on real state sector B21

9.38** Unclear insurance B24

0.40 Home inadequacy

2.82 Increased home noise B20

1.80 Data insecurity B19

1.73 Coordination difficulty B12

3.79 Inapplicable team working B18

0.74 ICT cost

2.57 ICT acquisition cost B1

1.16 ICT maintenance and upgrading cost B2

0.67 Time mismanagement

1.83 Home time mismanaged B6

0.71 Org. time expansion B3

1.17 Family intervention

0.11 Family rights B4

4.16 Family – work intervention B5


32

harmony with Popuri and Bhat (2003), Yap and Tng (1990), and Wells et al. (2001) who suggest that

teleworking will be of particular interest to employees who are married. Furthermore, with regard to

the educational level, the study indicates no association between educational level and teleworking

choice. This result challenges Peters et al., (2004) when mention that well-educated employees were

found to be more likely to practice teleworking. Consequently, this research finding is inconsistent with

the notion that well-educated individuals are able to telework as they exercise more control over their

work schedule than are their co-workers (Yeraguntla and Bhat, 2005).

The present research proves that there is an insignificant association between frequency of Internet

use and teleworking choice. Such a finding falsifies the widely held claim that employees master

certain level of IT skills including Internet skills are typically suited for teleworking. This research

results are inconsistent with the result obtained from the Euro survey 2000, which alleged that telework

was most widespread among employees, who used IT frequently in their job (Peters et al., 2004).

Nationality is also found to be significantly associated with teleworking choice. Non-UAE

national employees prefer part time and no teleworking compared to UAE national employees who

prefer fulltime teleworking. Such findings could be attributed to the fact that Non-UAE national

employees attempt to be present at the traditional workplace and establish good work records in order

to renew their working contracts, rather than asking for teleworking scheme, though they may prefer.

UAE national, on the other hand, are not subject to the stress of being present at the traditional

workplace as non UAE employees. This result is in agreement with Yeraguntla and Bhat (2005) who

indicate that resident Hispanics are more likely to telework than other races such as immigrants African

and Asian who need to demonstrate their working skills, and support their legibility to work and follow

work regulations. Similarly, the study shows that residence is associated with teleworking choice.

Employees living in Sharjah, Ajman and Umquin are over presented among part-time and full-time

teleworkers. This may be interpreted as employees living in these northern emirates always face severe

traffic jams in their way to work in Dubai, so that teleworking is perceived as the magic solution for

them. This result is consistent with Yen and Mahmassani (1997) when they suggest that the greater the

distance from home to workplace, the more likely the employee is to prefer teleworking. Also,

Mokhtarian and Salomon (1996) show that people who have longer commutes are more likely to report

that they want to telework. This contrasts with Drucker and Khattak (2000) who find that distance to

work is negatively correlated with working at home—that is, the farther the individual lives from his

job, the less likely he/she to work from home.

Number of children is found to be not associated with teleworking choice. This result confirms

Mokhtarian and Salomon (1996) when propose no effect of having children on the desire to telework.

Nevertheless, this is in disagreement with Popuri and Bhat (2003), Yap and Tng (1990), Wells et al.

(2001) who suggest that teleworking will be of particular interest to employees who have children.

Although, working parents may highly value the time-savings of teleworking due to the elimination of

commuting time and allow a parent to stay at home with a sick child (Peters et al., 2004), albeit, this is

not the case of UAE. In UAE culture, parents (working and not working) depend entirely on foreign

maids to take care of their children regardless how many children they may have. Similarly, age is

found to be not associated with teleworking choice. In consistent with that, Belanger (1999) does not

reveal significant age differences between those practicing telework and those not doing so in her study

of a high technology organization in USA. Nevertheless, many studies have revealed contradictory

results with regard to the relationship between age and teleworking. Mokhtarian and Salomon (1996),

and Bagley and Mokhtarian (1997) show that younger people are more likely to report that they want to

telework. Yeraguntla and Bhat (2005) indicate that young adults (less than 25 years) are more likely to

be in part-time employment than older adults. This is perhaps a reflection of the fact that many young

adults are studying and working part-time at the same time. Inconsistently, the EU member states

survey data indicated that the age group 30–49 was over represented among teleworkers (Peters et al.,

2004).

Research result related to years of experience tends to be not in agreement with Yeraguntla and

Bhat (2005) who suggest that employees who have worked less than a year in the firm are more likely

to be part-time teleworkers than those who have been working for longer periods of time. In UAE

context, the situation may be different since employees with less working experience try to prove their

skills, establish good impression, and get supervisor‘s support through being presenting at the

traditional workplace. After long years of experience, employees may consider teleworking as an

alternative work scheme that facilitate managing other concerns such as managing own small business.

The results of the present research prove the existence of an association between employees‘

profession and teleworking choice. While employees with accounting and finance professions tend to

avoid telework, employees with IT, media and management profession tend to telework either on part-

time or full-time basis. This result is consistent with Gray et al. (1993) who suggest that computer


33

programmers, systems analysts, catalogue shopping telephone order agents, and data entry clerks fit

full-time telework category.

7.2 Facilitator and inhibitors

This research confirms the importance of individual freedom, community concerns, and

productivity as key teleworking facilitators perceived by employees. This is in agreement with the

mainstream literature that support the perceived importance of personal freedom and autonomy as an

immediate symbolic result of employees‘ interaction with teleworking adoption (Feldman and Gainey

(1997; Pulido and Lopez, 2005). In addition, teleworking impact on the society as expressed by

employees is clear and tangible on the short run. Mills et al. (2001) and Tung and Turban (1996)

consider community and societal related teleworking facilitators such as reduction of air pollution and

dependence on fuel, conserve energy housebound and disabled people can work from home, and

reduced traffic during rush hours and transportation demand as important determinants of teleworking

success in the short run. Moreover, increasing productivity gains is also considered as key derivers for

organizations to adopt teleworking (Kurland and Bailey, 1999; Lim et al., 2003; Mills et al., 2001;

Tung and Turban, 1996). However, a recent study analyzed the findings of over 80 previous studies,

indicating that ―little clear evidence exists that telework increases job satisfaction and productivity, as it

is often asserted to do‖ (Bailey and Kurland, 2002: p. 383).

As far as teleworking inhibitors are concerned, the present research confirms the importance of

isolation as a key inhibitor of teleworking. Recent research indicates that isolation is perceived as one

of the key factors that may hinder the implementation of teleworking (Kurland and Cooper, 2002;

Rognes, 2002). Isolation is a factor that may result in lack of interaction with colleagues and lack of

commitment (Hobbs and Armstrong, 1998). Besides isolation, this research also points to the perceived

importance of home inadequacy as a place of working. Although teleworking is treated as working

from home, home is perceived by employees as inadequate place for work. Many reasons contribute to

this claim involve lack of needed collaboration with other employees, security risks, difficulty of

performance control and work coordination (Mills et al., 2001; Tung and Turban, 1996).

Based on the analysis of test results related to hypotheses two and three, most of teleworking

facilitators and inhibitors are not associated with teleworking choice. This means that employees with

different teleworking modes (i.e., full-time, part-time, not to telework) do not differently perceive the

importance of teleworking facilitators and inhibitors. In other words, teleworking facilitators and

inhibitors are visible for all employees regardless of their teleworking preference mode. However,

teleworking choice is found to be associated with the perception of specific teleworking facilitators and

inhibitors. This implies that employees who prefer not to telework tend to perceive less importance for

such teleworking facilitator or inhibitor, while employees who prefer to telework part-time or full-time

tend to perceive higher importance. Such teleworking facilitators which are associated with

teleworking choice include individual freedom, travel overload, and cost reduction. . Union resistance

is the only teleworking inhibitor that is associated with teleworking choice. This is consistent with

other teleworking studies such as Feldman and Gainey (1997) and Pulido and Lopez (2005) who

suggest that individual freedom is highly perceived among part-time teleworkers. In addition,

teleworkers are more likely to report longer commutes to workplace (Yen and Mahmassani, 1997;

Mokhtarian and Salomon, 1996). Finally, perception of cost saving is also over presented among part-

time and full time teleworkers in other context (Kurland and Bailey, 1999; Reid, 1993)

8 RESEARCH LIMITATIONS

There are several limitations of the present study that may restrict its generalizability. First,

sample size is relatively small compared to other studies that have nation-wide samples. Second, the

descriptive and exploratory nature of the topic does not allow the researchers to go into the depth of

predicting the discovered relationships. Despite that, this study is the first of its kinds to examine

teleworking choice and related facilitators and inhibitors in UAE, and in the Arab context. Third, eight

out of eleven organizations do not allow the researchers to collect organization‘s related data such as

income of employees, managerial level, degree of computer use in the organization, level of autonomy,

decentralization, etc. Consequently, such organization‘s related variables are eliminated from the

original questionnaire in order to maintain access to the respondents. Fourth, as the study focuses on

prospective teleworkers in ICT context, results cannot be generalized to other non-ICT contexts.


34

9 PRACTICAL IMPLICATIONS AND RECOMMENDATIONS

The following are some practical implications and recommendations that have emerged from the

study of teleworking choice in the UAE:

Firms employ relatively large percentages of married, female, IT profession, individuals

living in remote areas are recommended to adopt flexible work practices such as

teleworking.

Managers are advised to adopt part-time or full-time teleworking scheme in order to

integrate and maintain two contradictory strategies; individual freedom and productivity

improvement.

Successful implementation of teleworking requires managers to effectively manage

professional and physical isolation of teleworkers through regular office visits and

meetings with colleagues. Other practical strategies could include regular e-mail intranet

systems, news bulletins and social events. They should also take measures to allow social

comparisons to be made, perhaps through use of newsletters, as well as helping

teleworkers maintain visibility (perhaps with on-line discussions). Given that these

measures are implemented the part-time teleworking is highly recommended compared

with full-time teleworking.

If home is inadequate place for teleworking, managers can rely on telecenters as a

substitute. In telecenters, collaboration with other employees can be conducted, and

performance control can be facilitated.

Managers should ensure that any teleworking initiatives are backed up with the

appropriate technical support in such way that technicians are available and able to

respond quickly to technical problems and equipment failure.

When initiating teleworking schemes, managers should devise a teleworking policy

document that would cover issues such as expectations regarding working when sick,

hours to be worked, salary, meetings and visits, deadlines, continuing training,

opportunities for career development, management by distance, responsibility for hidden

costs (such as electricity) and no hidden costs (such as postage), etc. The aim of such a

document is to let workers feel that they have ―permission‖ to call when they are sick or

to switch off the computer at the end of the working day, as well as helping managers

manage by outlining to distant workers what is expected of them.

The importance of data security, privacy, and confidentiality cannot be overlooked when

work is performed at home. An organization should invest in the appropriate security

measures needed to ensure the confidentiality of data.

It is necessary to provide training both to the teleworkers and their managers or

supervisors. Training areas may include information technologies and networking

procedures as well as psychological preparation to work in a new environment.

10 CONCLUSION

This study examines the concept of teleworking choice as it applies to UAE context. The

relationship between demographic and individual variables, and teleworking choice is investigated. The

research reveals that there is no difference among employees in their teleworking choice based on their

educational level, Internet use, number of children, age, and years of experience. On the other hand,

there is a difference among employees in their teleworking choice based on their gender, marital status,

nationality, residence location, and work profession. In addition, the research identifies six distinct

teleworking facilitators and seven distinct teleworking inhibitors in the UAE context. Generated

facilitators are community concerns, individual freedom, productivity improvement, travel load, cost

reduction, and empowering people, while generated inhibitors are management concerns, isolation,

union resistance, home inadequacy, information and communication technology (ICT) cost, time

mismanagement, and family intervention. Perceived mean importance of these facilitators and

inhibitors is computed and ordered. Individual freedom, community concerns, and productivity are

perceived by employees as the most important facilitators, while isolation and home inadequacy are

perceived as the most important inhibitors. A further statistical test has revealed that there is no

difference among employees in the perceived importance of most teleworking facilitators and inhibitors

based on their teleworking choice. An exception is the association between teleworking choice and

individual freedom, travel overload, cost reduction, and union resistance. The study points out the


35

limitations of the present research and suggests some practical implications and recommendations for

managers.

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Strategic management and entrepreneurship:

Friends or foes?

Sascha Kraus

Helsinki University of Technology, Finland

& University of Liechtenstein, Fürst-Franz-Josef-Str., FL-9490 Vaduz, Liechtenstein


Ilkka Kauranen

School of Management¸ Asian Institute of Technology

Office room 236, Phathumthani 12120, Thailand

Tel: +66-89 (0) 6890560


Abstract

The objective of this article is to create a better understanding of the intersection of the academic fields

of entrepreneurship and strategic management, based on an aggregation of the extant literature in these

two fields. The article structures and synthesizes the existing scholarly works in the two fields, thereby

generating new knowledge. The results can be used to further enhance fruitful integration of these two

overlapping but separate academic fields. The article attempts to integrate the two fields by first

identifying apparent interrelations, and then by concentrating in more detail on some important

intersections, including strategic management in small and medium-sized enterprises and start-ups,

acknowledging the central role of the entrepreneur. The content and process sides of strategic

management are discussed as well as their important connecting link, the business plan. To conclude,

implications and future research directions for the two fields are proposed.

Keywords: strategy, strategic management, entrepreneurship, small and medium-sized enterprises,

SMEs, intersection


38

1 Introduction

In a new competitive landscape (1995), entrepreneurial strategies are becoming more and more

important for both new as well as established enterprises. Due to e.g. increasing environmental

dynamics and intensifying global competition, enterprises, regardless of their age or size, are forced to

build more entrepreneurial strategies in order to compete and survive (Hitt, Ireland, & Hoskisson,

2001; Meyer, Neck, & Meeks, 2002). These entrepreneurial strategies are said to be related to better

company performance. They aim to build on the identification of opportunities and develop them

towards competitive advantages (Hitt, Ireland, Camp, & Sexton, 2002). This is where the fields of

entrepreneurship and strategic management intersect.

Both academic fields are focused on the process of adapting to change and exploiting

opportunities. Despite this shared focus, they have developed largely independently of each other (Hitt

et al., 2001). Recently, scholars have called for the integration of these two fields (Meyer & Heppard,

2000; McGrath & MacMillan, 2000). The need for integration emerges as strategists, on the one hand,

need to use resources in order to exploit opportunities (mostly under uncertain conditions) – and

entrepreneurs, on the other hand, need to include a strategic perspective in their planning and actions.

In times of growing uncertainty and increasing speed of change, both new threats and new

opportunities emerge (Brown & Eisenhardt, 1998; Shane & Venkataraman, 2000). The identification

and exploitation of these opportunities is the essence of entrepreneurship – whereas the essence of

strategic management is in how these opportunities can be transformed into sustainable competitive

advantages (Zahra & Dess, 2001; Venkataraman & Sarasvathy, 2001; Kuratko, Ireland, Covin, &

Hornsby, 2005). The call for the integration of these two fields is a surprisingly new phenomenon.

Both disciplines are concerned with value creation, acknowledging it as a major organizational

goal. Entrepreneurial actions and strategic actions can contribute to value creation independently, but

they can contribute even more when they are integrated. Indeed, entrepreneurial opportunity-seeking is

at the same time also strategic behaviour with the aim of value creation (Ireland, Hitt, & Simon, 2003;

Ramachandran, Mukherji, & Sud, 2006). A central interest of researchers in strategic management is to

explain differences of enterprises in their value creation – an interest which is increasingly shared by

researchers in the field of entrepreneurship as well (Ireland, Hitt, Camp, & Sexton, 2001).

In addition to “classical” variables that describe entrepreneurship, such as the characteristics and

motivations of entrepreneurs, many authors favour a greater emphasis on organizational and strategic

variables (e.g., Zahra, 1991; Entrialgo, Fernández, & Vázquez, 2000). Zahra & Dess (2001) argue that

the integration of different views is a key to more fruitful research in entrepreneurship, and specifically

name strategic management as a most promising area to be integrated into entrepreneurship research.

The positive outcomes of such an integration can be observed in real business life, where

entrepreneurial enterprises are more inclined to engage in strategic management practices than more

established enterprises which are by nature more conservative (Shuman, Shaw, & Sussmann, 1985;

Bracker, Keats, & Pearson, 1988; Woo, Cooper, Dunkelberg, Daellenbach, & Dennis, 1989).

Entrepreneurship and strategic management both have made their unique and valuable

contributions to management theory. Although their foci differ, both are inevitably interrelated, and are

often complementarily supportive of each other (Ireland et al., 2003). Meyer & Heppard (2000) remark

that the two fields are in fact even inseparable, forming two sides of the same coin, since the research

results of the one cannot fully be understood without the other (Barney & Arikan, 2001).

Nevertheless, the evident intersection between these two research fields has been largely left

uncovered so far. Thus, the objective of this article is to create a better understanding of this

intersection, based on an aggregation of the extant literature in these two fields. The article attempts to

structure and synthesize the existing scholarly works on this topic, thereby generating new knowledge.

The results can be used to further enhance fruitful integration of the two academic fields.

2 THE FIELDS OF ENTREPRENEURSHIP AND STRATEGIC MANAGEMENT

2.1. Entrepreneurship

Entrepreneurship was emerging as an academic field of study when Karl Vesper founded an

interest group within the Academy of Management‟s (AoM) Business Policy and Strategy division in

1974. Five years later, David Birch (1979) reported that small enterprises created about 90 percent of

all new jobs, and thereby highlighted entrepreneurship as the engine of growth in the economy. In

1987, entrepreneurship finally became a separate division of the AoM (Meyer et al., 2002). At present,

entrepreneurship is acknowledged as one of the major driving forces of the economy of every modern

society (Brock & Evans, 1989; Carree & Thurik, 2000) and is considered as the instrument to cope

with the new competitive landscape and its enormous speed of changes (Hitt & Reed, 2000).

Sascha Kraus and Ilkka Kauranen

39

Entrepreneurship entails far more than starting up a new venture (Stevenson & Jarillo, 1990). It

can also take place in established organizations where renewal and innovation are a major goal

(Sharma & Chrisman, 1999). Entrepreneurial behaviour can accordingly be found in all kinds of

enterprises, regardless of their size, age or profit-orientation (Kraus, Fink, Rößl, & Jensen, 2007).

Entrepreneurship describes the process of value creation through the identification and exploitation of

opportunities, e.g. through developing new products, seeking new markets, or both (Lumpkin, Shrader,

& Hills, 1998; Shane & Venkataraman, 2000; McCline, Bhat, & Baj, 2000). It focuses on innovation

by identifying market opportunities and by building a unique set of resources through which the

opportunities can be exploited, and is usually connected with growth (Ireland et al., 2001; Davidsson,

Delmar, & Wiklund, 2002). Reynolds et al. (1999) e.g. proposed that 15 percent of the highest growth

enterprises created 94 percent of all new jobs. One of the key challenges for entrepreneurs is to deal

with the strategic changes required with the growth of their enterprise (Thompson, 19999). Many

scholars have thus decided to separate (growth-oriented) entrepreneurship from small business

management (i.e. mom and pop enterprises or lifestyle businesses), describing growth as “the essence

of entrepreneurship” (Sexton & Smilor, 1997, p. 97).

Entrepreneurial enterprises identify and exploit opportunities that their competitors have not yet

observed or have underexploited. An appropriate set of resources is required to exploit entrepreneurial

opportunities with the greatest potential returns (Hitt et al., 2002). An entrepreneurial enterprise‟s

resources are often intangible, such as unique knowledge or proprietary technology. According to

Ireland et al. (2001), entrepreneurial behaviour arises through the “…concentration on innovative,

proactive, and risk-taking behaviour” (p. 51). In real business life, though, there is not yet a cogent,

direct treatise to formally recognize entrepreneurial behaviour as a new “dominant logic” in enterprises

(Meyer & Heppard, 2000).

2.2. Strategic management

The “birth” of strategic management as an academic field can be traced to the 1960s (Furrer,

Thomas, & Goussevskaia, 2007). Chandler‟s “Strategy and Structure” (1962) and Ansoff‟s “Corporate

Strategy” (1965) are among the first seminal publications in this field. In its first decades of existence,

strategic management almost solely investigated strategic issues in large, established enterprises

(Analoui & Karami, 2003).

The basis of strategic management is the notion that strategy creates an alignment between the

enterprise‟s internal strengths and weaknesses on the one hand and its opportunities and threats

(SWOT) in its external environment on the other (Andrews, 1987). Schendel and Hofer (1979)

identified the following six “major tasks” of strategic management: 1) goal formulation, 2)

environmental analysis, as well as the 3) formulation, 4) evaluation, 5) implementation and 6) control

of strategies. Sandberg (1992) lists an enterprise‟s resources, processes, strategy and field of industry as

the primary variables of strategic management.

Strategic management deals with how enterprises develop sustainable competitive advantages

resulting in the creation of value (Ramachandran et al., 2006). An underlying basis of the Austrian

school in strategic management (Schumpeter, 1993 [1934]) is the temporary nature of such competitive

advantages. Accordingly, strategic management can be regarded as setting the context for

entrepreneurial behaviour, i.e. the exploitation of opportunities (Ireland et al., 2001).

Strategic management research is for a large part concerned with identifying differences among

enterprises‟ performance by examining their efforts to develop sustainable competitive advantages as

determinants of their ability to create value (Ireland et al., 2003). A competitive advantage results from

a long-lasting value difference in the product or service compared to those of its competitors as

perceived by the customers (Duncan, Ginter, & Swayne, 1998). The possession of valuable, rare, non-

imitable and non-substitutable resources (Prahalad & Hamel, 1990) as well as a favourable market

position (Porter, 1985) are regarded as major sources for sustainable competitive advantages. This

builds the basis for the resource-based view (RBV) of strategic management, which regards an

enterprise as a bundle of resources that needs to be deployed strategically in order to add value

(Wernerfelt, 1984; Barney, 1991). Small and medium-sized enterprises (SMEs) and start-ups (which

typically are small in the beginning, and therefore a subset of the former), have almost by definition

fewer resources than larger enterprises, and the types of resources of these two groups of enterprises

are different (Mosakowski, 2002). SMEs possess such capabilities as niche filling, speed and flexibility

that allow them to exploit certain opportunities faster and more effectively than established enterprises

(Li, 2001). Nevertheless, so far the RBV lacks the insights provided by creativity and entrepreneurial

behaviour (Barney, 2001). Therefore, the role of entrepreneurial behaviour in corporate strategy is

increasingly emphasized (Mosakowski, 1998; Alvarez & Barney, 2000; McCarthy, 2003).


40

A major differentiation in strategic management is between content and process, i.e. the strategy

itself (content) and its implementation (process) (Stacey, 1993). On the content side, there are three

“levels” of strategy within enterprises: 1) the corporate strategy which defines what businesses the

enterprise is in and how all of its activities are structured and managed, 2) the business level strategy

which is concerned with creating a competitive advantage in each of the enterprise‟s product levels or

strategic business units, and 3) the functional level strategy examples of which are marketing strategy,

human resources strategy and research and development strategy (Thompson, 1995; Analoui &

Karami, 2003). In SMEs, level 1 and level 2 mentioned above are usually the same.

Strategy can also be classified into different “schools”. Table 1 shows Mintzberg‟s (1990a)

categorization of strategies, which was done after a review of about 1,500 published articles on

strategic management.

Table 1: Mintzberg’s Schools of Strategy

Prescriptive Schools Descriptive Schools I Descriptive Schools II

Design school

Conceptual strategy development

through achievement of a “fit”

between internal strengths and

weaknesses and external

opportunities and threats.

Main instrument: SWOT analysis.

Entrepreneurial School

Visionary strategy formation, vision

and intuition of the entrepreneur

instead of precise plans. Implicit

perspective (vision) which is

personal and unique

Main instruments: Start-up, niche or

turnaround strategies.

Political School

Power-based strategy formation:

The development of strategies

within the organization is

determined by politics and power,

micro power.

Main instruments: Strategy

development is based on self-

interest and fragmentation or tactics

and positioning.

Planning School

Strategy as a formal process with

single clear steps and techniques.

Main instruments: Scenario

planning, check lists, strategic

control.

Cognitive School

Regards strategy formation as a

mental process, based on individual

perceptions.

Main instruments: Deals with the

origin of strategies and the mental

processes of strategy development.

Cultural School

Strategy formation is a social

process which builds on culture.


development is based on mutual

interests and integration; strategy

has a collective perspective and it is

unique and mostly implicit.

Positioning School:

Analytical strategy formation,

strategy being regarded as a generic

competitive position depending on

the industry situation.

Main instruments: Boston

Consulting Group matrix,

McKinsey matrix, PIMS study.

Learning School

Strategy development as an

emergent learning process.


formulation and development mesh

with each other; frequently applied

in intrapreneurship.

Environmental School

The environment is not only seen as

a factor, but moreover as the central

actor which determines the strategy.

Main instruments: Examination of

the environmental conditions and

the specific position, termed niche

in population ecology.

Sources: Mintzberg (1990a); Sandberg (1992); Mintzberg & Lampel (1999).

Only the first three – the so-called “prescriptive” – schools have developed their own specific sets

of strategic management instruments; the other schools are not bound to any particular instruments.

The basis of all the schools is the design school‟s SWOT analysis from the early 1960s (Mintzberg &

Waters, 1985), which is also most applicable in SMEs. The design school sees the responsibility for

strategy development as being with the top manager. In SMEs, this mostly is the entrepreneur himself.

The high importance of formalization as well as the control function in strategic planning (e.g. in the

business plan) can be derived from the planning school, which usually defines strategy as a static

formal plan, where planners perform a detailed analysis of the enterprise, its product-market

relationship and the environment (Chandler, 1962; Ansoff, 1965). Check lists or scenario planning are

characteristic strategic management instruments of the planning school. Within the positioning school,

Porter‟s niche strategy seems to be particularly relevant for SMEs. Some of the most important

strategic management instruments of the positioning school are portfolio analyses such as the Boston

Consulting Group matrix or the McKinsey matrix. The use of these instruments in SMEs is applicable

once the enterprise has grown and developed more than one single product or service.

Later, scholars began to concentrate more on the process side (Mintzberg & Waters, 1985;

Pettigrew, 1992), and highlighted the emergent nature of strategic planning due to cognitive limitations,


41

learning, organizational politics, and cultural biases. The view emerged that strategy was not simply

based on formality, but moreover also reflected experimentation, intuition and learning, and thereby

reflected the increasingly dynamic changes in the outside business economy (Hamel, 1996; Hayashi,

2001; Miller & Ireland, 2005). The entrepreneurial school e.g. emphasizes the central role of the

entrepreneur in strategic management. The vision and intuition of the entrepreneur are said to be more

important than precise and formal plans. The cognitive school deals with the origin of strategies as well

as with the mental processes of strategy development. It regards strategy formulation as a mental

process, which is partly based on individual perceptions. In the complex reality, the “via regia” can be

assumed to lie somewhere in between formal planning on the one side, and flexibility and intuition on

the other. Accordingly, the learning school sees strategy development as a learning process. This

includes the view that a formalized plan is not static, but needs to be revisited and adjusted, e.g. when

environmental conditions change.

The political school claims that the development of strategies within the organization is

determined by politics and power. This goes along with the “power promoter” of Hauschildt &

Kirchmann‟s (2001) promoter model, which states that in innovation processes, different persons with

different powers are needed to overcome the barriers of unwillingness and of ignorance. The cultural

school again considers strategy formulation as a social process which builds on culture. An

“entrepreneurial culture” within an enterprise which supports learning or innovation is an example of

this. The environmental school examines the environmental conditions of the enterprise. It attempts to

discover the enterprise‟s specific optimal position within this environment, e.g. a niche.

All of the nine schools presented in Table 1 are important for strategic management, and they have

also shown obvious intersections with entrepreneurship. In addition to the presented schools, Mintzberg

has developed a tenth school, the configurational school, which can be regarded as an integration of all

the other nine schools. In this school, certain characteristics and behaviours of enterprises and

entrepreneurs are clustered towards an optimal configuration. In this process, all of the named strategic

management instruments of the other schools can be used, depending on the respective situation

(Kohtamäki, Kraus, Kautonen, & Varamäki, 2008).

3 INTEGRATING ENTREPRENEURSHIP AND STRATEGIC MANAGEMENT

3.1. Interrelated fields

Strategic management research has often given the impression that entrepreneurship can be treated

as a subset of strategic management. The fact that the Entrepreneurship Division of the AoM was a

“spin-off” of the Business Policy and Strategy Division contributes to this image. The more recent calls

for the integration of these two fields are mainly due to the reasons that 1) researchers in both fields use

company performance as a major dependent variable, and 2) the new competitive landscape makes

entrepreneurial strategies more and more important (Meyer et al., 2002).

Stevenson and Jarillo (1990) remark that there is a need to establish links between the fields of

entrepreneurship and strategic management. As Dess et al. (1999) put it, “understanding

entrepreneurial processes has been a central theme in a good deal of both the entrepreneurship and

strategic management literatures” (p. 85). Schendel and Hofer (1979) had already linked both research

fields in the late 1970s when defining strategic management as “a process that deals with the

entrepreneurial work of the organization, with organizational renewal and growth…” (p. 11), and

furthermore stating that “the entrepreneurial choice is at the heart of the concept of strategy” (p. 6).

One of the most obvious linkages between entrepreneurship and strategic management are

opportunities. Opportunities are both at the very heart of entrepreneurship and part of e.g. the SWOT

analysis of strategic management. Enterprises create value by identifying opportunities in their external

environment and by subsequently developing competitive advantages to exploit them (Hitt et al., 2001;

Ireland et al., 2001).

Venkataraman and Sarasvathy (2001) used a metaphor based on Shakespeare‟s Romeo and Juliet

saying that strategic management research without an entrepreneurial perspective is like the balcony

without Romeo, and entrepreneurship research without a strategic perspective like Romeo without a

balcony.

Six “natural” domains where the intersection between entrepreneurship and strategic management

exist have been proposed: 1) innovations, 2) networks, 3) internationalization, 4) organizational

learning, 5) top management teams and governance, and 6) growth (Covin & Miles, 1999; Hitt &

Ireland, 2000; Ireland et al., 2001).

Cooper (1979) was the first to place start-ups into the field of strategic management by

investigating the relationships between the characteristics of entrepreneurs, venture strategies and


42

performance. He argued that strategic management researchers should study established enterprises and

growth-oriented start-ups, but not “mom and pop” small businesses. This later led to the distinction

between “entrepreneurs” and “small business managers” by Carland et al. (1984). From this point on,

more and more scholars have studied the relationship between strategic management and business

performance in SMEs (Schwenk & Shrader, 1993, Kraus, Harms, & Schwarz, 2006). SMEs are thought

to be so unique that standard textbook approaches of strategic management, which have originally been

developed for large enterprises, are not considered suitable for them. On the other hand, corporate

entrepreneurship (intrapreneurship), i.e. entrepreneurial behaviour within established organizations, is

closer to such a “standard” strategic management (Sandberg, 1992). SMEs have always been skilful in

identifying entrepreneurial opportunities, but less effective in developing and sustaining competitive

advantages for exploiting them. It is mostly the other way around with established enterprises (Ireland

et al., 2003).

It has been found that many of the key topics in entrepreneurship research, e.g. new venture

creation, innovation and opportunity-seeking do in fact apply to the strategic management paradigm as

well. New venture creation e.g. is in most cases about acquisition, mobilization and deployment of

resources and the integration of the resources with opportunities, and can thus be linked to Mintzberg‟s

design school, which is about matching resources with opportunities (Sandberg, 1992). Also,

innovation, being understood in the Schumpeterian sense as new combinations of factors of production,

builds on resources, which again build the basis of many strategic management instruments (e.g.

Wernerfelt, 1984; Barney, 1991). If the creation of innovations is understood as an individual process,

both the cognitive school and the entrepreneurial school of Mintzberg can be applied (e.g. in exploring

how innovations appear and in explaining the strategic nature of innovations), and the learning school,

where creation of innovations is seen as an organizational phenomenon (e.g. by the way an innovation

leads its way through the organization).

3.2. Strategic management in SMEs and young SMEs

The application of strategy in SMEs is a main part of the intersection between entrepreneurship

and strategic management (e.g. Chan & Foster, 2001). Next to the content and process side (which are

always interrelated, e.g. in the form of a business plan) of strategy within SMEs, the role of the

entrepreneur is particularly important. The following table as well as the following sub-chapters

exemplarily show four major constitutive elements of SME strategy and their characteristics.

Table 2: Constitutive Elements of SME Strategy

Entrepreneur Strategy Content Strategy Process Business Plan

Characteristics The Entrepreneur or

the SME manager

is the main

strategist and

decision maker

develops the vision,

mission and

strategies for the

enterprise

implements the

vision, mission and

strategies

Most promising market

entry strategies for

SMEs

niche strategy: allows

targeting of customer

needs by focusing the

limited resources on a

narrow market segment

differentiation strategy:

offers the customer a

special advantage

along a valued

dimension (e.g. quality

or price leadership)

Strategic

instruments which

are suitable for

SMEs

SWOT analysis

PEST analysis

industry analysis

product life-cycle

analysis

Business portfolio

matrixes

Written or formal

documentation of the

SME‟s strategy and

strategic planning

means of

communication with

external stakeholders

internal control

mechanism

leads to actual

company founding,

ongoing strategic

planning and

employment growth

Other Issues

and Challenges

Personal goals,

traits and strategic

orientation having a

significant impact

on the SME‟s

strategy.

Daily business is

customarily

regarded as more

important than

long-term

strategies.

Other dimension of

assessing an

enterprise‟s market

entry: product/market

strategy (four-field

matrix with different

combinations for

implementing existing

or new products in

present or new

markets).

Other strategic

instruments (e.g.

benchmarking,

GAP analysis,

BSC), which could

also be used in

SMEs, are often

unknown in SMEs.

Business plans are

rarely existent in

young SMEs.

The question of

whether to write a

business plan is the

entrepreneur‟s

decision, reflecting

his thoughts and

ideas.

(Main) Sources McKenna (1996);

Berry (1998);

Vesper (1980); Ibrahim

(1993); Lee et al.

Andrews (1987);

Zahra & Dess,

Kraus & Schwarz

(2007); Liao &


43

McCarthy (2003);

Analoui & Karami

(2003)

(2001); Gruber (2004)

(2001); Analoui &

Karami (2003);

Kraus (2007)

Gartner (2008);

Schulte (2008)

Research Gaps

and Areas for

Future Work

Changes in strategy

when the SME

grows and the

entrepreneur is no

longer the only

decision maker (e.g.

entrepreneurial

teams)

Possible correlations

between the applied

strategy and corporate

success; industry-

specific surveys

Possible

correlations

between the

instruments and

corporate success

Quality, quantity and

content of the

business plan and

their possible

correlations with

corporate success

3.2.1. The entrepreneur’s role in SME strategy

Empirical evidence suggests that entrepreneurs in SMEs plan in a way that is quite different from

the standard textbook approaches (McCarthy, 2003). In the multitude of SMEs, not top management

teams, but the entrepreneur himself is the enterprise‟s main strategist and decision maker, developing

the vision, mission and strategies, and also implementing them (Analoui & Karami, 2003). Strategic

decisions reflect the subjective orientations and attitudes of the entrepreneur. The role of the

entrepreneur and his attitude towards strategic issues are therefore often critical for the implementation

of strategy (Kraus, 2007).

Likewise, the entrepreneur‟s personal goals, traits and strategic orientation will have a significant

impact on the enterprise‟s strategy (McKenna, 1996). Many entrepreneurs routinely operate their daily

business, but do not believe that strategic management applies to them. However, it has been argued

that no business is too small to have a solid strategy (Sandberg, Robinson, & Pearce, 2001). The

question of whether or not to use sophisticated strategic management instruments again depends on the

entrepreneur‟s previous experience (Berry, 1998).

3.2.2. Strategy content

The market entry of a start-up is of major importance because it determines the strategic basis

from which the enterprise tries to achieve competitive advantages in the market place (Gruber, 2004).

The enterprise‟s relative position within the market strongly influences its performance. Within the

spectrum of the generic strategies by Porter (1985), there are (at least) three options: 1) cost leadership,

2) differentiation, and 3) focus on a market niche. Whether there is a cost advantage or a differentiation

potential for the enterprise is the result of the enterprise‟s ability to cope with the five competitive

forces (industry competitors, potential entrants, buyers, substitutes, and suppliers) better than its

competitors. Young SMEs can seldom develop cost advantages, as these are often based on economies

of scale. For these enterprises, most researchers recommend the niche strategy (e.g. Vesper, 19800).

Besides, young SMEs can hardly target a market as a whole, but more likely have to target certain

narrow market segments which larger competitors ignore (Lee, Lim, Tan, & Wee, 2001). A niche

strategy allows an enterprise to target customer needs by focusing the enterprise‟s limited resources on

a narrow segment of the market. This gives time for establishing a market position and developing both

the necessary resources to survive (Bamford, Dean, & McDougall, 1997). Numerous empirical studies

confirm that the niche strategy is often the most successful initial entry strategy. Ibrahim (1993) made

this observation with small enterprises and Bantel (1996) with 166 small technology-based enterprises.

Still, the niche strategy leaves several risks for SMEs, since larger enterprises can easily launch an

attack on the market niche simply by making the choice to do so.

The differentiation strategy is also possible for SMEs. The core of this strategy is to offer the

customer a special advantage along dimensions that are highly valued by the customers (Porter, 1985).

This could be e.g. quality leadership where the enterprise aims to offer the market the best quality

compared to its competitors. The differentiation potential of SMEs is mostly imbedded in the business

idea of the enterprise or in a technical innovation. A common mistake of entrepreneurs is being

enthusiastic about their new ideas, neglecting the market, and failing to assess if there is a target group

for the new products or services.

Another dimension of assessing an enterprise‟s market entry is the product/market strategy. The

decision within this strategy is whether to implement existing or new products in present or new

markets. The original matrix concept of the product/market strategy by Ansoff (1965) consists of four

different strategies: 1) present product in present market, representing status quo, 2) present product in

new market, e.g. through internationalization, 3) new product in old market, usually based on some

innovation, and 4) new product in new market, which is the most risky and most expensive strategy


44

option. These strategies can be useful for young SMEs as well, despite the fact that these enterprises

are usually restricted in their actions because of their limited resources. The product/market matrix can

be an efficient management instrument for identifying new strategies and for planning resources

accordingly. For achieving the highest performance, each strategy option needs to be linked with

appropriate resources (Borch, Huse, & Senneseth, 1999).

3.2.3. Strategy Process

With regard to the strategy process, several different strategic management instruments can be

applied in SMEs, depending on the respective situation the enterprises are in. For instance, any

enterprise needs to assess its position within its environment and within the market (Zahra & Dess,

2001). A common instrument for this is the SWOT analysis, which aims at studying internal strengths

and weaknesses and matching them with the enterprise‟s external opportunities and threats (Andrews,

1987). A SWOT analysis can be used as a basis for developing future strategies as well as for

developing the business plan. Another part of the environmental analysis is the PEST analysis, which

tries to identify political and legal (P), economical (E), socio-cultural (S), and technological (T) factors

influencing the enterprise. Finally, the industry analysis tries to assess the attractiveness of a specific

industry for the enterprise (Analoui & Karami, 2003). The industry analysis again can use sub-

instruments, such as market analyses (e.g. Wickham, 2001) and Porter‟s (1985) five forces analysis.

The product life-cycle (PLC) concept can be utilized in enhancing the effectiveness of operative

instruments and in changing the strategies, especially in young SMEs. The basic idea of the PLC

concept corresponds to the law of birth and death of all biological existence. This idea can be

transferred to man-made systems, such as products or markets. Even if the forecasting ability of the

PLC concept has been deemed rather limited (Levitt, 1965; Cox, 1967), it provides a good overview of

marketing decision options, especially in the implementation phase and growth phase of an enterprise

(Kraus et al., 2007).

Business portfolio models, such as the Boston Consulting Group (BCG) matrix or the McKinsey

matrix rely, on the one hand, on the PLC concept as a predictor for the axis of market attractiveness

and, on the other hand, on the concept of the learning curve as an indicator for the relative market share

(Hedley, 1977). Originally, these matrixes were designed to facilitate recourse allocation between

different strategic business units (SBUs) of an enterprise. In this sense, portfolios are not applicable for

young SMEs which, due to their small-scaled structure and age, typically do not consist of SBUs.

However, transferring the concept to the range of different products, these matrixes can be useful

strategic management instruments for young SMEs as well. The ideal distribution of products within

the portfolio can especially be interpreted as the optimal structure of the product line, as it shows

opportunities and threats of each single product in relation to both the market share and the maturity of

the market. Such analyses can reveal when a new product should be introduced into the market in order

to rejuvenate the product line, and furthermore when measures need to be taken to boost a product into

a market dominating position (to make a cash cow out of a star).

Other well-known strategic management instruments, such as e.g. benchmarking, GAP analysis or

Balanced Scorecard, which can also be used in SMEs, are often unfamiliar to entrepreneurs, especially

if the entrepreneurs do not have an educational background in management (Kraus, 2007).

3.2.4. The business plan

Every business, regardless of its size, has some form of a strategic plan. In small enterprises, this

may include e.g. the general ideas put forward by the entrepreneur; with increasing size of the

enterprise, however, the strategic plan usually becomes more formal and elaborate. Such a document is

called a business plan. It is the document which describes the enterprise‟s strategy, i.e. content and

process, thereby presenting the vision of the enterprise and how the enterprise is going to attain its

vision (Honig & Karlsson, 2004). The business plan can particularly serve as the basis of the strategy

itself and as its formalized documentation. Usually, it is written to serve as a means of communication

with external stakeholders, especially potential investors (Castrogiovanni, 1996). In addition, it can

serve as a mechanism for internal control and goal-achievement.

Entrepreneurs who prepare a business plan become more conscious of their business instruments

and their assumptions about how to become successful. In some cases, after devising the business plan,

especially after making the financial calculations, the entrepreneur might even find that his business is

not likely to succeed, and thereby gets the chance to not go into business rather than engaging in one

which is ex ante deemed to fail. This can be seen as a most positive outcome of the pre-start-up

planning process.

The pure existence of a business plan and the quality of the business plan are commonly regarded

as indicators of the enterprise‟s attitude towards strategic planning. They also provide insight into how


45

much the entrepreneur is committed to his venture (“signalling effect”). Research has indicated that the

probability of actually founding the new company is six times higher among entrepreneurs who have

written a business plan than among entrepreneurs who have not written a business plan (Heriot &

Campbell, 2004). Furthermore, the existence of a business plan has been positively associated with the

success of the enterprise e.g. in an Austrian study of 458 young SMEs by Kraus and Schwarz (2007)

and in a study of 312 nascent entrepreneurs from the USA by Liao and Gartner (2008). Similarly, a

study by Schulte (2008) of 585 business plans from Germany also regarded pre-start-up planning as an

important requirement for success.

The business plan can be regarded as one of the most important strategic management instruments

in young SMEs. Nevertheless, the actual process of decision making that can be observed in reality

often deviates substantially from the management‟s ideal picture of rationality – planning in SMEs

seems to be rather unstructured, sporadic, and incremental, due to e.g. limited resources, limited time,

or the entrepreneur‟s attitude towards formal planning (Kraus, 2007). As a consequence, the majority

of SMEs still do not have a written business plan (e.g., only 29.5% of the 468 young SMEs in the study

by Kraus & Schwarz, 2007 had a business plan).

3.2.5. Limitations of previous research studies

Previous research on the fields of strategic management in SMEs has numerous limitations that

need to be addressed in future research. First, it is often limited to those enterprises that have already

been identified as conducting strategic planning or to the surviving enterprises, whereas failed

companies are not considered (“survivor bias”). These studies‟ response rates have mostly been rather

low. It can be assumed that questionnaires are more frequently returned by such enterprises that apply

strategic management instruments more than the others. The results concerning the use of strategic

management instruments might therefore be unintentionally inflated. Furthermore, in previous studies,

the aggregation of single functional plans has often been a sufficient condition for categorizing an SME

as using strategic planning, which might give a questionable picture of the real nature of the strategic

management in the companies.

Furthermore, previous research studies are difficult to compare with each other due to their

differences in terms of enterprise type, field of industry, sample size, company size, or investigation

period. Likewise, previous studies are often limited to only one industry, which reduces the potential to

derive generalizable conclusions. In this respect, it would be interesting to examine whether there are

differences in the usage of strategic management instruments as it regards the industry sector. It can be

assumed that in these industries, in which product development and order processing have a shorter

time frame (e.g. in the services industry) or in those with a generally smaller range of products,

strategic management instruments are less frequently used.

4 DISCUSSION AND CONCLUSIONS

The objective of the present article was to create a better understanding of the intersection of the

academic fields of entrepreneurship and strategic management. The article was based on an aggregation

of the extant literature in these two fields. It has been shown that there are intersections between both

of these fields of studies, and this is pointed out e.g. by Mintzberg‟s schools of strategy. Obvious

intersections are strategy content and processes within SMEs, i.e. the development of strategic

management instruments for enterprises. The niche strategy has been shown to be a most successful

market entry strategy for new enterprises, whereas the differentiation strategy can also gain importance

once the enterprise grows. Success for any enterprise – regardless of its size or age – is highly

dependent upon its ability to find a valuable strategic position (Thompson, 1999).

Nonetheless, some authors have questioned the overall value of strategic management in SMEs

(e.g. Bhidé, 1994), and argued that it does not work in a dynamic environment where flexibility and

responsiveness are key conditions for survival (Mintzberg, Quinn, & Ghoshal, 1995). We are of a

different opinion. Many of the strategic management instruments which have originally been developed

for large enterprises, such as the SWOT analysis, can be important for SMEs as well, but need to be

adapted according to their particularities. Since SMEs considerably differ from large enterprises in their

amount of resources, it is doubtful that „standard‟ strategic management instruments work in the same

manner in SMEs as in large enterprises. The instruments therefore need to be aligned with the

personnel as well as the cultural, organizational, and financial conditions of the specific enterprise in

order to be successful. Since many strategic instruments are simply not known or applied in SMEs, a

consciousness regarding the virtue of the use of proper strategic instruments needs to be raised. This is


46

where politics and education have to take over. They both need to use their respective channels for

generating a greater strategic awareness, starting with SMEs, especially the young ones.

All in all, the integration of entrepreneurial (opportunity-seeking) and strategic (advantage-

seeking) perspectives seems to be a promising approach for contemporary management, and is

probably even a necessary approach for coping with the effects of the new competitive landscape. Both

perspectives can be regarded as essential for value creation, although neither is sufficient on its own

(McGrath & MacMillan, 2000; Ireland et al., 2001). Strategic management must therefore without a

doubt become more entrepreneurial, and shift from the traditional administrative approach to a

strategic entrepreneurship approach. This would characterize a new management philosophy that

promotes strategic agility, flexibility, creativity, and continuous innovation. It can also be used in

transforming administrative-oriented employees into intrapreneurs.

A concrete managerial implication of the strategic entrepreneurship approach is the possibility to

develop more entrepreneurial and innovative thinking, especially in young SMEs. This stands in

contrast with the traditional strategic management approach, which characteristically emphasizes

administrative management and focuses on day-to-day business. Intuition and utilizing “gut feelings”

are important elements of the entrepreneur‟s strategy development, although they have to be

supplemented by wise use of strategic management instruments. It is also generally acknowledged that

proper planning has its positive implications for successful implementation. Accordingly, planning

complements and enhances entrepreneurial behaviour or, as Liao and Gartner (2008) put it: “Planners

are doers!” (p. 18).

With regard to research, recent years have brought significant progress in the investigation of

strategic management in (young) SMEs (e.g. Kraus, Harms, & Schwarz, 2008). This has mostly taken

place only on a general, i.e. cross-sectoral level, and has been limited to one country at a time. Future

research regarding the intersection between the entrepreneurial approach and the strategic management

approach should concentrate on (quantitative) empirical investigations from different contexts, i.e. firm

sizes, industries, countries etc. Also, other entrepreneurial sub-groups such as family firms or spin-offs

(corporate venturing) should be investigated regarding their strategic management particularities.

Numerous areas are still under-researched. For example, the changes in enterprise strategies when the

SME grows and the entrepreneur has to delegate power should be investigated in more detail. Possible

correlations between the strategic management instruments applied and company success need more

research. One of the most promising areas for future research is the pre-start-up planning stage.

Strategic management of an enterprise before and during the phase of its foundation is a topic of

increasing interest. This includes research on the role of the business plan in the planning process,

another topic of growing academic interest.

The question of whether the formality of the business plan or the strategic management in general

is beneficial for the success of young SMEs seems to be promising. The dichotomous questions of

whether there is a plan and/or how the qualities of the plan relate to enterprise success should be

investigated. Other relevant research questions entail the content of a business plan, its single elements

and areas, as well as the quality and quantity of such a document. The timing in the preparation of the

business plan (e.g. prior, during or after the founding process) should also be investigated further. Both

quantitative and qualitative research studies, including case research, are called for.

Last but not least, the interplay between personal, structural, strategic and environmental factors in

SMEs, the so-called configurations, (e.g., Harms, Kraus, & Reschke, 2007) is a promising approach for

conceptualizing strategic entrepreneurship by integrating these elementary domains. Of these four

domains, this present article has tried to shed light on the personal and strategic elements of SME

strategy. Accordingly, the two remaining domains of the four in the configuration approach need more

attention. Both theoretical and empirical research work should be done on the (company) structure and

(industry) environment. We regard the configuration approach as one of the most promising avenues

for future research where valid questionnaires for quantitative empirical investigations can be

developed.


47

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Book Review: Exploring Corporate Strategy: Texts and

Cases

Dimitrios N. Koufopoulos

Brunel Business School, Brunel University

Uxbridge, London UB8 3PH

Tel: +44 (0) 1895 265250


Gabriella Spinelli

Brunel Business School, Brunel University

Uxbridge, London UB8 3PH

Tel: +44 (0) 1895 267544


Book Information

Book Title: Exploring Corporate Strategy: Texts and Cases

Author: Gerry Johnson, Kevan Scholes and Richard Whittington

Publisher: Prentice Hall: Financial Times Press, UK

Edition: 8th edition

Year: 2008

Pages: 878 pages

ISBN: 978-0-273-71192-6

Price: £43.69

Keywords: strategic management, corporate and business strategies


52

1 BOOK REVIEW

Having established a worldwide reputation with sales over 750,000 copies, the current edition of

this book -published for the first time in the early 80s – lives up to its popularity.

As in past editions the introductory chapter illustrates the strategy concept in a clear, well

organized and comprehensive manner. Alongside the well developed three lenses of strategy (design,

experience and ideas), already a feature of the past versions, this edition introduces an extra lens; this is

strategy as a discourse and ability to communicate and shape organisational objectives. The rest of the

book is then structured in three parts dedicated respectively to Strategic positioning; Strategic choices

and the principles of Strategy in action.

The four chapters of Part I discuss the issues, facets and factors that affect and influence

organizations into their quest for developing and managing their strategies. This part encompasses

considerations on the organisational environment, the capabilities, resources and assets, the purposes,

vision and organizational mission and the culture.

Part II focuses on the choices that eventually organizations are bound to take. Chapter 6 illustrates

the available strategies at the business level whereas Chapter 7 moves its attention to corporate level.

To respond to the disciplinary needs, Chapter 8 is introduced and reflects on the International aspects

of Strategies and strategic development. Chapter 9, also an addition of the latest edition, portrays the

increasing academic interest on Innovation and Entrepreneurship. Finally, Chapter 10 goes on to

consider the methods and ways that companies pursue in order to materialise their strategies.

Part III draws on the well known debate of deliberate vs. emergent approaches that has dominated

the discipline for the last 30 years. The chapters in this part of the book analyse and review issues

related to strategy development, planning, organisational configuration and the fundamental business

resources: people, information, finance and technology. Change and the management of change are

also examined within part III leading to the identification of key roles and stakeholder in strategy

practicalities.

As in previous editions, the main conceptual elements are supported by brief case examples within

the main text and by extended case studies, 17 brand new and 19 thoroughly revised, that feature at the

end of the book. Through this structure the authors uphold the narrative flow of the book still providing

the readers with extensive resources.

The structure of the book has been carefully planned and the guided tour section directs the

readers to effectively integrate the online and printed resources.

This is a superb book and a required addition to the library of students both at their undergraduate

and postgraduate studies or anyone who wishes to understand issues relating to well known but often

misused concepts of strategy, strategy development and strategy implementation.

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