Int. Journal of Business Science and Applied Management, Volume 6, Issue 1, 2011

Determinants of Customer Continuance Intention of Online

Shopping

Talal Al-maghrabi

Brunel Business School, Brunel University

Centre for Research in Marketing (CREAM), West London, UB8 3PH, UK

Telephone: +44 (0) 1895 267171

Email: talal.almaghrabi@brunel.ac.uk

Charles Dennis

Lincoln Business School, University of Lincoln

Brayford Pool, Lincoln, LN6 7TS, UK

Tel: +44 (0)1522 882000

Email cdennis@lincoln.ac.uk

Sue Vaux Halliday

School of Management, University of Surrey

Guildford, Surrey, GU2 7XH

Telephone: +44 (0) 1483 68 6353

Email: s.halliday@surrey.ac.uk

Abeer BinAli

Brunel University

West London, UB8 3PH, UK.

Email: abeer.binali @brunel.ac.uk

Telephone: +44 (0) 1895 274000

Abstract

The purpose of this study is to clarify theory and identify factors that could explain the level of continuance

intention of e-shopping. A revised technology acceptance model integrates expectation confirmation theory and

investigates effects of age differences. An online survey of internet shoppers in Saudi Arabia. Structural

equation modelling and invariance analysis confirm model fit. The findings confirm that perceived usefulness,

enjoyment and social pressure are determinants of e-shopping continuance. The structural weights are mostly

equivalent between young and old but the regression path from perceived usefulness to social pressure is

stronger for younger respondents. This research moves beyond e-shopping intentions to factors affecting e-

shopping continuance, explaining 55% of intention to continue shopping online. Online strategies cannot ignore

direct and indirect effects on continuance intentions. The findings contribute to literature on internet shopping

and continuance intentions in the context of Saudi Arabia.

Keywords: Internet shopping, e-shopping, technology acceptance, young and old examination, continuance e-

shopping, Saudi Arabia.

Acknowledgment: The authors thank the respondents, the editors, and the reviewers for their valuable

feedback. Special thanks to our families for their continued support.

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

1 INTRODUCTION

E-Commerce and e-shopping create opportunities for businesses to reach consumers globally and directly –

indeed, they are transforming retailing (Alden et al. 2006; Holt et al. 2004). Unsurprisingly, e-commerce

transactions are growing, not least because low cost gives both businesses and consumers a new and powerful

channel for information and communication. In turn, business and social science research increasingly focuses

on cross-national and cross-cultural Internet marketing (Griffith et al. 2006). This paper examines an aspect of

online retailing of increasing potential importance, the Saudi Arabian context.

Consumers now have various online and offline options from which to choose, and, without a compelling

reason to choose one retailer over another, they rotate purchases among multiple firms (Bhattacherjee 2001b;

Crego and Schiffrin 1995). Despite impressive online purchasing growth rates, evidence strongly indicates that

many consumers who search different e-retail sites abandon their purchase intentions. Helping online businesses

understand which factors encourage consumers to remain loyal a shopping website is critical because acquiring

new customers may cost five times more than retaining existing ones (Crego and Schiffrin 1995; Petrissans

1999).

Increasingly, commercial websites seek to provide useful product information in order to attract potential e-

shoppers (Totty 2001). Keeney (1999) pointed out that measuring only actual purchases may be too narrow

scope when assessing e-shopping activity, contending that gathering product information is an essential aspect

of e-shopping activity. This two-fold definition has since been applied in e-shopping studies (e.g. Chen et al.

2002). We employ a similar definition in order to develop a more holistic view of e-shopping continuance

intention.

E-shopping in this study is a combination of both product information search and purchasing activities. For

the purpose of this research, we address e-shopping, online shopping, and internet shopping, terms which are

frequently used interchangeably. We propose a comprehensive definition which includes all the activities of

searching, buying, and selling products and services online. This study focuses mainly on the business-to-

consumer (B2C) arena, which has been the source of most online progress and development. The author

generalizes the two-fold definition, and rather than evaluating shopping at a particular site (as in Chen et al.

2002), respondents were asked to generalize all e-shopping activities.

Previous research found that gender and age differences significantly affect new technology decision-

making processes (Van Slyke et al. 2002; Venkatesh et al. 2000; Spero and Stone 2004). Furthermore, younger

people are more likely than older adults to use the internet (Williamson, 2006). However, type of usage varies

by age, with younger internet users are more likely to engage in communication and creative activities, but less

likely to purchase online than older users (Rainie and Horrigan, 2005). Additionally, youth populations are

motivated by status and peer pressure (Spero and Stone 2004). On the other hand, men rely more on their

evaluations of the usefulness of the technology. As the Internet is one of the main environments for young

people to play, work, learn and communicate (Alreck and Settle 2002; Spero and Stone 2004), greater e-

commerce exposure and decision-making power may imply that males and females can attain greater

satisfaction from e-shopping. Saudi Arabia has a population of 25 million, highly skewed in terms of age

distribution, with 60% under the age of 30 (Middle East Statistics 2007). This age profile is relevant to our

topic, as in countries that are further advanced in Internet shopping; much of the growth has been driven by

young people.

In summary, researchers are confronted with a multitude of models, and find that they can “pick and

choose” constructs, or choose a “favoured” model, largely ignoring the contributions from alternative models

(Venkatesh et al. 2003). Theoretical explanations of e-shopping intentions consider several factors. Rogers‟

theory of innovation (1995) suggests that consumers re-evaluate acceptance decisions during a final

confirmation stage and then decide to continue or discontinue. The decision to continue may be an extension of

acceptance behaviour that co-varies with acceptance (e.g. Bhattercherjee 2001a; Davis et al. 1989; Karahanna et

al. 1999). The technology acceptance model (TAM), as expanded by Davis et al. (1992) and Gefen (2003), and

the expectation confirmation theory (ECT) (Oliver 1980; Bhattacherjee 2001a) have been widely used in

research in the industrialized world, but they are less commonly applied to developing countries. Given the

complementary nature of TAM and ECT, our research aims to propose a model of e-shopping continuance

intentions (Figure 1). This adapts different constructs from the modified TAM and ECT, and considers variance

of continuance intentions in the context of e-shopping.

The remainder of this article proceeds as follows. We offer a review of existing literature, and then detail

our proposed model, hypotheses, and methodology. After describing the structural equation model and analysis,

we provide our results. We conclude with some limitations, conclusions contribution, and recommendations for

further research. Finally, we present managerial implications.

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

2 THEORETICAL BACKGROUND

The TAM (Davis 1989) represents an adaptation of the theory of reasoned action (TRA), tailored to users‟

acceptance of information systems. It helps explain determinants of computer acceptance and can explicate user

behaviours across a broad range of computing technologies and populations; it also is parsimonious and

theoretically justified (Davis et al. 1989). The major determinants are perceived usefulness and ease of use.

Perceived usefulness significantly influences attitude formation (Agarwal and Prasad 1999; Dishaw and Strong

1999; Gefen and Keil 1998; Igbaria et al. 1996; Moon and Kim 2001; Taylor and Todd 1995; Venkatesh and

Davis 2000), but evidence regarding perceived ease of use remains inconsistent. Furthermore, other researchers

(e.g., Bhattachergee 2001a; Ma and Liu 2004; van der Heijden et al. 2003) indicate that the effect of ease of use

on acceptance is subject to a certain threshold. That is, with more experience, the impact of ease of use on

intention declines. Since our research focuses on continuance intentions, we assume all participants already have

e-shopping experience, which implies that other factors may be more important than ease of use.

Expectation confirmation theory (ECT) in turn helps predict consumer behaviour before, during, and after a

purchase, in terms of both product and service repurchases (Anderson and Sullivan 1993; Dabholkar et al. 2000;

Oliver 1980, 1993; Patterson et al. 1997; Spreng et al. 1996). According to ECT, consumers define their

repurchase intentions by determining whether the product or service meets their initial expectations. Shoppers‟

comparisons of perceived usefulness versus their original expectation of usefulness influence their continuance

intentions (Oliver 1980; Bhattacherjee 2001a). If use meets the initial expectation and leaves the consumer

satisfied, the consumer experiences positive intentions to repurchase (Oliver 1980; Anderson and Sullivan

1993).

However, ECT ignores potential changes in initial expectations following the consumption experience and

the effect of these expectation changes on subsequent cognitive processes (Bhattacherjee 2001a). Pre-purchase

expectations typically are based on media or others‟ opinions, whereas post-purchase expectations derive from

usage experience, which appears more realistic (Fazio and Zanna 1981). Following such experience,

expectations may increase if consumers believe the product or service is useful or contains new benefits that

were not part their initial expectation. Therefore, the research model focuses only on post-acceptance variables

and the model assumes e-shopping retailers target users and improves their loyalty to the site. Hence, the post-

expectation in the original ECT is represented by perceived usefulness.

Venkatesh and others (2003) suggest that usage and continuance intentions may depend on cognitive

beliefs about perceived usefulness. Gefen (2003) also indicates that perceived usefulness reinforces online-

shoppers‟ continuance intention, such that when a person accepts a new information system, he or she is more

willing to modify practices and expend time and effort to use it (Succi and Walter 1999). However, consumers

who are dissatisfied with prior use may continue using an e-commerce service if they consider it useful

(Bhattacherjee 2001a).

The dominant influence of perceived usefulness has led Bhattacherjee (2001) to include usefulness in his

revised ECT. Furthermore, in a recent study by Premkumar and Bhattacherjee (2008), perceived usefulness is

found to be the strongest predictor of intention in TAM, and continues to be the strongest predictor of

continuance intention (over satisfaction) when TAM is combined with ECT, whereas satisfaction was dominant

in ECT (Premkumar and Bhattacherjee 2008). The relative dominance of usefulness explains its role as critical

driver in continuance decisions (Premkumar and Bhattacherjee 2008).

Site quality and good interface design enhance the formation of consumer trust, and if a consumer

perceives a vendor‟s website to be of high quality, he or she should trust the vendor‟s competence, integrity, and

benevolence (McKnight et al. 2002a). Gefen and others (2003) integrate trust into the TAM in a B2C e-

shopping context and find that trust positively affects consumers‟ intention to use a website. Building trust with

consumers is an essential mission for e-retailers, because purchasing decisions represent trust-related behaviours

(Jarvenpaa et al. 2000; McKnight et al. 2002b; Urban et al. 2000).

Subjective norm can be thought of as composed of two components: societal norm and social influence

(Pavlou and Chai 2002). Societal norm refers to the process of adherence to the larger societal fashion, i.e., a

large circle of influence. Collectivism, however, refers to the extent to which individuals are integrated into

groups, forming their judgments based on group norms (Hofstede and Bond 1988). Other studies replicate

Hofstede‟s cultural dimension of collectivism, finding that it places greater relative importance on the group's

needs and norms than individualism (Triandis 1989). Social influence refers to the extent to which people accept

a hierarchical system with an unequal power distribution (Pavlou and Chai 2002), and here is seen to reflect

adherence to opinions from family, friends, and peers, i.e., a smaller circle of influence.

Additionally, other studies suggest that individuals place more trust in people similar to themselves and

assess trustworthiness on second-hand information (Zucker 1986; Morgan and Hunt 1994; McKnight,

Cummings, and Chervany 1998). In highly collectivistic cultures, such as the Arab World, individuals‟ actions

are typically influenced by the expectations of people around them. Therefore, if e-shopping is a socially

desirable behaviour, a person is more likely to e-shop (George 2002).

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

Since thousands of e-retailers provide similar services, retention of existing users is difficult and important.

Attracting and retaining users by providing an enjoyable website has gained researchers‟ attention. Enjoyment is

significantly associated with total web use, especially for entertainment purposes (Atkinson and Kydd 1997).

Moon and Kim (2001) extend TAM, in a parallel with Lin et al. (2005), who extend ECT for a WWW context,

indicating that enjoyment and playfulness were an intrinsic motivation factor in acceptance and continuance

intention. Furthermore, Childers et al (2001) also find that enjoyment can predict attitude towards e-shopping,

just as much as can usefulness. Therefore, we integrated the perceived enjoyment construct into our research

model in an attempt to enhance understanding of individuals‟ e-shopping continuance or revisit intention.

3 PROPOSED MODEL AND HYPOTHESES

Site Quality

E-shopping web site quality refers to “overall consumer perceptions of the excellence and effectiveness of

an e-tailer's product and/or service offering through its virtual store” (Ha and Stoel, 2009). In the online context,

website quality is unique and unanimously seen as vital factor during the initial online purchase stage (Yoon,

2002; Koufaris and Hampton-Sosa, 2004). For the first-time buyer with no previous experience with the seller,

the initial trust, from the consumers' perspective, is formed quickly by indirect experience on the basis of

available information such as reputation, recommendation, effective communication, and information quality of

the seller website (Meyerson et al., 1996; Kim et al., 2003). Website quality has been found as a trust-building

lever in the e-purchase context for the first-time consumers (McKnight et al., 2002). Wirtz and Lihotzky (2003)

argue that online experiences differ from those found in traditional (physical) shopping, suggesting that

consumer evaluation of the quality of online shopping may differ in achieving initial trust, which make it more

complicated.

Additionally, shopping online include a number of experiences such as information search, web site

browsing/navigation, ordering, payment, customer service interactions, delivery, post-purchase problem

resolution, and satisfaction with one's purchases (Ha and Stoel, 2009). Website quality helps predict behaviour

(Business Wire, 1999; Carl 1995; Meltzer, 1999); if the vendor‟s website is perceived to be of high quality, the

consumer is more likely to depend on the vendor (McKnight et al., 2002). Furthermore, an e-vendors‟ site with

user-friendly search and navigation functions provide users with a better sense of control over their online

shopping experience which in turn may translate into positive feelings about the competence of the vendor.

Thus, a well-designed and organized web interface can stimulate initial consumer interest to further explore a

site (Menon and Kahn, 2002) and reduce customers‟ cost and the time required when searching for product

information. Similarly, if a customer perceives a vendor‟s website to be of high quality, he/she will be more

likely to generate a favorable attitude towards it, demonstrate behavioral control over it (Pavlou and Fygenson,

2006; Jahng, Jain and Ramamurthy, 2007), which in turn, translates into an easier experience for consumers to

release the product or service value and feature. On the basis of this research, we therefore predict:

H1.a Perceived Site Quality is positively related to Perceived Usefulness.

H1.b. Perceived Site Quality is positively related to Customer Trust in using e-shopping.

Trust

In general, trust is viewed as a set of specific beliefs dealing primarily with the benevolence, competence

and integrity of another party. Benevolence is the belief that the trustee will not act against the trustor, even

given the opportunity. Competence is the belief in the trustee‟s ability to fulfil the obligations expected by the

trustor. Integrity is the belief that the trustee will be honest and will honour its commitments (McKnight et al.

2002a). Also, trust refers to an expectation that others will not behave opportunistically and/or take advantage of

a situation (Gefen 2003). If the e-vendor cannot be trusted to behave in accordance with the consumers‟

expectations, then there is no reason why consumers should expect to gain any utility or benefit from using the

interface (Pavlou 2003; Gefen 2004; Chiu 2009). A lack of trust will, therefore, prevent buyers from engaging in

e-shopping (Hoffman et al. 1999). When consumers initially trust their online retailers, and have a perception

that e-shopping is beneficial, they will eventually accept that e-shopping is useful (Gefen et al. 2003). In turn,

perceived usefulness should occur only for an e-vendor that can be trusted (Festinger 1975). Indeed, prior

research shows that trust plays a pivotal role in driving perceived usefulness (Gefen et al. 2003; Pavlou 2003)

Thus:

H2. Perceived Trust is positively related to customer perceived Usefulness.

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

Perceived Usefulness

Perceived usefulness is defined as the extent to which a consumer believes that e-shopping will enhance his

or her transaction performance (Chiu 2009). According to Burke (1997), perceived usefulness is the primary

prerequisite for mass market technology acceptance. This depends on consumers‟ expectations of how

technology can improve their lives (Peterson et al. 1997). A website is useful if it delivers services to a

customer, but not if the customers‟ delivery expectations are not met (Barnes and Vidgen 2000). The importance

of perceived usefulness as a key motivating factor derives from the TRA and TAM models, which propose that

perceived usefulness affects user acceptance due to reinforcement values of outcomes (Adams, Nelson and Todd

1992; Davis et al. 1989). In a robust TAM, perceived usefulness predicts IT use and intention to use (e.g.,

Agarwal and Prasad 1999; Gefen and Keil 1998; Gefen and Straub 1997; Igabria et al. 1995), as well as e-

commerce adoption (Gefen and Straub 2000) and exhibits a stronger and more consistent relationship with

usage than did other variables reported in the literature (Davis et al. 1989). Furthermore, Davis et al. (1989)

indicates that individuals shape behavioural intentions towards e-shopping, based largely on a cognitive

evaluation of how it will improve their shopping performance. According to Bhattacherjee (2001), and Babin

and Babin (2001), an individual is more likely to undertake continued or repurchase intentions when such usage

is perceived to be beneficial.

Consumers are likely to evaluate and consider product-related information prior to purchase, and perceived

usefulness may, therefore, be more important than the enjoyment (hedonic aspect) of the shopping experience

(Babin et al. 1994). Additionally, Davis et al. (1992) identified a positive relationship between perceived

usefulness and enjoyment (Chung and Tan 2004). We also posit that a useful online product could make people

more likely to experience greater enjoyment at e-store that establishes high quality in terms of marketing and

information related attributes (Ha and Stoel, 2009) use and recommend it to their peers. Although it does not

affect the importance of friends, perceived usefulness is likely to encourage peers to spread recommendations by

word-of-mouth, thereby increasing continuance intentions. Therefore:

H3a. Perceived Usefulness is positively related to increasing customer Enjoyment.

H3b. Perceived Usefulness is positively related to increasing customer Continuance Intention.

Social Pressure

According to Ajzen, (1985) and George (2004), subjective norms to refer to the person's perception of the

social pressures that are put on him or her to perform the behaviour in question. Social pressure can affect the

attitudes and behaviour of individuals in varying degrees in different societies depending on the culture.

Furthermore, social influences result from subjective norms (social pressure), which relate to individual

consumers‟ perceptions about the beliefs of other consumers (Venkatesh et al. 2003). Shim and colleagues

(2001) find subjective norms to be only marginally significant for e-shopping intentions, whereas Foucault et al.

(2005) find a significant link between talking about e-shopping with friends and intention to e-shop.

Researchers such as Hofstede (1994) and Adler (1995), maintain that the individualism-collectivism

dimension is an important means of understanding the motives of human action and behaviour (Ali, 1988). This

perspective refers to the need to either satisfy personal aspirations or attend to group needs. In highly

collectivistic cultures, such as the Arab World, an individual‟s actions are typically influenced by the

expectations of people around him or her.

Therefore, in terms of the underlying motivation to accept technology or e-shopping, individuals from a

collectivistic culture may use e-shopping less because of the potential usefulness or enjoyment, more because of

the perceived social pressure from their family and friends. These individuals will conform to the accepted

social norm by using the technology to perform e-shopping because of their belief that they will be perceived to

be technologically sophisticated by those whom they consider important for their future well-being. Taking that

into consideration, social norms also is relevant to enjoyment, because involving consumers in the web sites

facilitate e-friendship and enforce e-shopping, which produce similar result of greater enjoyable experience.

Thus:

H4a. Perceived Social Norm is positively related to increasing customer Enjoyment and

H4b. Perceived Social Norm is positively related to increasing customer Continuance Intention.

Enjoyment

Perceived enjoyment refers to the extent to which the activity of using an e-commerce website is enjoyable

in its own right, beyond the instrumental value (Davis et al. 1992). It is also the extent to which e-shopping is

perceived to be personally enjoyable and fun (Chiu 2009). According to self-determination theory, customers

are self-determining and intrinsically motivated in e-shopping when they are interested in it or enjoy doing it

(Chiu 2009). Because Internet shopping is usually voluntary, and searching and buying are impulsive

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

behaviours, it seems likely that shoppers‟ intentions become stronger if they perceive higher enjoyment from the

website (Atkinson and Kydd 1997; Li and Zhang 2005).

Empirical research indicates that the general characteristics of enjoyment and fun relate positively to

creativity and an exploratory type of behaviour during interaction with computers (Webster 1992). Research

indicates that individuals who experience pleasure and joy from using a computer, and perceive any activity

involving use of e-shopping as inherently enjoyable apart from any anticipated improvement in performance, are

likely to use it more extensively than others (Davis 1992; Malone 1981; Webster 1989). Davis et al. (1989)

found that while perceived usefulness emerged as the major determinant of computer acceptance in the

workplace, enjoyment and fun had a significant effect beyond perceived usefulness.

Enjoyment in using a website significantly affects intentions to use (Davis et al. 1992; Igbaria et al. 1995;

Teo et al. 1999; Venkatesh et al. 2002). Furthermore, Hirschman and Holbrook (1982) suggested that positive

consumption, related to emotions in a hedonic context, is likely to lead to very high levels of commitment and

repurchase intention. Davis et al.‟s (1989) findings support the idea that enjoyment has a significant impact on

customer behaviour on the web, such as increasing customer intention to return (Koufaris et al. 2001; Koufaris

2002; Bart et al. 2005; Cyr et al. 2006; Chiu 2009). Thus:

H5. Perceived Enjoyment is positively related to increasing customer Continuance Intention.

4 METHODOLOGY

The methodology used in this research is useful in indicating the potential generalisability of the study

findings‟ across different cultures and contexts. This research is theory oriented and is concerned with assessing

the correspondence between relationships discernible across cases and a broad theoretically based interpretation

of social phenomenon. According to Ragin (1987) and Creswell (2003), investigators who use such approach

focus their interest on testing hypothesis and propositions derived from theory to determine whether the

predictive generalization of the theory hold. This is achieved by conducting a comprehensive analysis that

includes Exploratory Factor Analysis (EFA), Structural Equation Modelling (SEM) and invariance analysis for

the data collected for the purpose of examining research model generalisability.

The population of interest in this study is Internet users in Saudi Arabia over 18 years old who have

previous experience of online shopping. An online survey is used to validate the conceptual model and the

proposed research hypotheses. Since Saudi Arabia is a big country with multiple traditions and subcultures, the

developed online survey is suitable for targeting online shoppers and collecting data from large geographical

areas. Compared with traditional surveys, online surveys offer lower costs, faster responses, and less data entry

effort.

Student samples were added to the research because online customers commonly are younger and more

highly educated than conventional customers, making a student sample more representative of the online

customer population (Al-Diri, Hobbs, and Qahwaji, 2006; Williamson, 2006). Furthermore, adding a student

sample may represent the future e-shopping patterns of the population at large. Student samples were extracted

from seven universities and colleges, including the five regions of Saudi Arabia.

However, since this research cannot cover such a massive population, a sample was used for the data

collection process. One conventional sampling approach is to randomly distribute surveys to members of the

general population, since such a sample is frequently a good representation of the population at large.

Additionally, the researcher makes attempt to insure that this sample is an accurate representation of some larger

group or population by covering the main five regions in Saudi Arabia.

Measures

The measures of the various constructs come from previous literature, adapted to the context of e-shopping.

Marketing models often include relationships among sets of constructs. The constructs used in this study are

latent, each represented by a number of indicators. A structural equation model (SEM) is developed in order to

investigate the relationships between the constructs, which are either formative or reflective in nature. However,

since this research uses SEM with (using SPSS AMOS 5.0 software) AMOS software can handle only reflective

scales (Bagozzi 1982; Bagozzi and Fornell 1982; Fornell and Bookstein 1982). In a reflective scale, all observed

indicators are viewed as being caused by some underlying common dimension or construct (Bagozzi 1982. All

online survey items used 1–7 Likert scales, on which 1 indicates strongly disagree and 7 strongly agree. The site

quality and trust items come from McKnight and others (2002a, 2002b). The perceived usefulness items derive

from Gefen (2003). Perceived enjoyment is a measure from Childers (2001). Shih and Fang (2004) provide the

subjective norm (social pressure) items. The continuance intention items were adapted from Yang and Peterson

(2004). Appendix A lists the measurement scales.

A pilot study was carried out in Saudi Arabia to evaluate the effectiveness of the research instrument. The

pilot study suggested some clarifications to the survey instruments. Questionnaires were developed initially in

English and then translated into Arabic. To avoid any bias, the back-translation method, Brislin‟s (1986),

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

ensures they have the same meaning. The Arabic and English versions were validated and proofread for final

approval of the content, wording, and clarity of the questions by native speakers.

Data analysis

Survey respondents were people who were actively engaged in Internet use and e-shopping in Saudi

Arabia. The sample consists of 465 participants, 68.6% (319) of whom are women and 31.4% (146) of whom

are men (Table 1). The domination of women participants in this research is surprising especially both genders

have the same accessibility and freedom to participate in the survey. Despite the fact that women comprise

68.6% of the participants in this research, women in Islamic countries are facing several social and cultural

obstacles preventing them from engaging in work (Al-maghrabi, 2010). Thus, the revolution in information and

communication technology and the nature of the research, online shopping have broadened the work of

members of the community particularly that carried out by women, at administrative, social and economic

levels. These should be as an indicator for the domination of women participation in the research and reflect the

importance of using the internet and online shopping to Muslim women, which may outweigh the importance

level for women living in non-Muslim societies. Furthermore, linking the domination of women participants to

recent surveys, such as the Pew Internet conducted in 2002 and Sky News conducted in 2002, which indicated

that women are now dominant in e-shopping (cited in Cha 2009). In the same context and according to

comScore, focusing on expenditures online, women accounted for 58% of e-shopping, whereas men were

responsible for 42% between April 2004 and March 2005 (Maguire 2006). Furthermore, most respondents are in

the younger age groups, with 74.8% younger than 35 and 25.1% 35 years or older. This age range broadly

reflects the profile of the young Saudi population. The vast majority (92.3%) of respondents came from the three

main regions in Saudi Arabia: 25.2% from the eastern region, 26.5% from the central region, and 40.6% from

the western region.

Younger people have the intention to spend more than older people in Saudi Arabia, as indicated in Table

1. As we demonstrate in Table 2, 208 (59.8%) and 149 (42.8%) of the respondents younger than 35 years old

used the Internet in the previous six months to book flights, purchase airline tickets and make hotel reservations,

compared to 86 (73.5%) and 69 (59.0%) respondents in the other group of 35 years and older; 102 (29.3%) have

purchased fashion products, compared to 18 (15.4%) for 35 and older. Security, quality, payment, and language

barrier are considered as an issue when conducting e-shopping in Saudi Arabia, as reported in Table 3.

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

Table 1: Sample Demographics

Question

younger than 35

35 and older

Gender

Male

114 (32.8%)

32 (27.4%)

Female

234 (67.2%)

85 (72.6%)

Age

Less than 18

16 (4.6%)

Between 18-25

130 (37.4%)

Between 26-35

202 (58%)

Between 36-45

88 (75.2%)

Above 46

29 (24.8%)

Education Level

Less than high school

8 (2.3%)

1 (0.9%)

High school

49 (14.1%)

8 (6.8%)

Diploma

43 (12.4%)

12 (10.3%)

Bachelor

191 (54.9%)

50 (42.7%)

Post-graduate

57 (16.4%)

46 (39.3%)

Internet Spending

None

49 (14.1%)

9 (7.7%)

SR100-1,000 (£100-500)

115 (33.0%)

48 (41.0%)

SR1,001-5,000 (£501-1,000)

111 (31.9%)

32 (27.4%)

>SR5,001 (£>1,001)

73 (21.0%)

28 (23.9%)

Income Level

<SR4,000 (£1,000)

87 (25.0%)

5 (4.3%)

SR4,000-SR6,000 (£1,000-2,000)

56 (16.1%)

13 (11.1%)

SR6,001-SR8,000 (£2,001-4,000)

46 (13.2%)

12 (10.3%)

SR8,001-SR10,000 (£4,001-7,000)

33 (9.5%)

9 (7.7%)

SR10,001-SR15,000 (£7,001-10,000)

42 (12.1%)

27 (23.1%)

>SR15,001 (>£10,000)

21 (6.0%)

49 (41.9%)

Dependent on others

63 (18.1%)

2 (1.7%)

Region

East region

100 (28.7%)

17 (14.5%)

West region

122 (35.1%)

67 (57.3%)

Central region

93 (26.7%)

30 (25.6%)

North region

20 (5.7%)

1 (0.9%)

South region

13 (3.7%)

2 (1.7%)

Table 2: Items purchased online and reason for using the Internet

Items purchased in the last six months

younger than 35

Percentage (%)

35 and older

Percentage (%)

Books

197

56.6%

55.6%

Music CD, DVD, Videotape

157

45.1%

30.8%

Fashion

102

29.3%

15.4%

Sports equip

19.3%

15.4%

Travel reservation and ticketing

208

59.8%

73.5%

Hotel booking

149

42.8%

59.0%

Reason for using the Internet

Information search

320

92%

112

95.7%

Entertainment

256

73.6

63.2%

Social communication

245

70.4%

65.8%

Work

194

55.7%

78.6%

Study

60.9%

50.4%

Purchasing

284

81.6%

82.9%

Banking

231

66.4%

76.9%

Types of companies trusted

Local companies

12.1%

10.3%

International companies

143

41.1%

46.2%

Trust them both the same

163

46.8%

43.6%

** Respondent can select more than one option.

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

Table 3: Important issues when shopping online

Important issues to e-shoppers

younger than 35

Percentage (%)

35 and older

Percentage (%)

Security

275

79%

100

85.5%

Price

204

58.6%

62.4%

Service, delivery

222

63.8%

66.7%

Quality

252

72.4%

69.2%

Payment

220

63.2%

66.7%

Language barrier

157

45.1%

47.9%

** Respondents can select more than one option.

The scale reliability and validity were assessed, as well as an examination of the convergent and

discriminant validity of the research instruments. The criterion for the minimum loading of 0.70 required for the

inclusion of an item within a scale was applied (Fornell and Bookstein 1982). Fornell and Larcker's (1981)

criterion for average variance extracted (AVE) of 0.50 or more was applied. The researcher also consider the

guidelines recommended by Hair et al. (2006) in determining the relative importance and significance of the

factor loading of each item, (i.e., loadings greater than 0.30 are considered significant; loadings greater than

0.40 are considered important; and loadings 0.50 or greater are considered to be very significant). Finally, the

criteria suggested by Nunnally (1978) were applied to determine the adequacy of the reliability coefficients

obtained for each measure.

Discriminant validity, which assesses whether individual indicators can adequately distinguish between

different constructs, is assured if the square root of AVE for each construct is greater than the correlation

between the measures of potentially overlapping constructs (Fornell and Larcker 1981).

The internal consistency reliabilities, Cronbach‟s alphas, (Table 4) are all greater than 0.7, exceeding the

recommended values in Bagozzi and Yi‟s (1988) guidelines. The correlation matrix in Table 4 indicates that the

square root of the AVE of each construct is higher than the corresponding correlation values for that variable,

thereby assuring discriminant validity (Fornell and Larcker 1981). Consistent with the recommendation of

Bagozzi (1994), Byrne (2001), and Hair et al. (2006), the squared multiple correlation exceeded the cut-off point

of 0.7, and the average variance extracted exceeded the cut off-point of 0.5 (Table 5). We thus confirm the

convergent reliability and discriminant validity.

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

Table 4: Convergent and Discriminant Validity and Scale Correlations

Factor Correlations

Model

Constructs

Cronbach’s alpha

Trust

Enj

CIU

0.926

0.871

0.949

0.698

0.904

Trust

0.949

0.000

0.902

0.947

0.684

0.672

0.000

0.905

Enj

0.935

0.379

0.372

0.360

0.555

0.869

CIU

0.961

0.365

0.359

0.379

0.534

0.688

0.934

Diagonal elements represent square root of the AVE value

Table 5: Measurement Model

Constructs/Indicators

S. Factor

S.E

C.R.

AVE

Squared Multiple

Correlation

Site Quality (SQ)

0.758

SQ 1

0.918

0.043

24.143

0.84

SQ 2

0.850

0.042

23.400

0.72

SQ 3

0.841

0.041

22.731

0.71

SQ 4

0.872

0.76

Perceived Usefulness

0.817

PU 3

0.906

0.031

31.931

0.82

PU 4

0.892

0.030

32.097

0.80

PU 5

0.937

0.88

PU 6

0.880

0.031

30.848

0.77

Trust

0.814

Trusting Beliefs Integrity 1

0.903

0.032

31.167

0.82

Trusting Beliefs Integrity 2

0.897

0.025

38.232

0.80

Trusting Beliefs Integrity 3

0.889

0.030

30.023

0.79

Trusting Beliefs Integrity 4

0.919

0.85

Social Pressure

0.819

SP 3

0.757

0.57

SP 4

0.976

0.057

23.251

0.95

SP 5

0.966

0.057

22.815

0.93

SP 6

0.904

0.059

21.415

0.82

Enjoyment

0.756

Enj 4

0.704

0.79

Enj 5

0.931

0.066

19.223

0.87

Enj 6

0.935

0.067

19.479

0.88

Enj 8

0.887

0.066

18.058

0.50

Continuance Intention

0.872

CIU 1

0.872

0.026

34.199

0.76

CIU 2

0.938

0.020

47.621

0.88

CIU 3

0.975

0.95

CIU 4

0.946

0.020

50.386

0.90

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

5 STRUCTURAL EQUATION MODEL

As the first step in testing the proposed model, we estimate the goodness-of-fit indices (Figure 1). Bentler

and Bonnett (1980) suggest the Chi-square/Degrees-of-freedom (CMIN/DF) ratio as an appropriate measure of

model fit, which should not exceed 5 (Bentler 1989).

SEM with AMOS 5.0 software determines additional goodness-of-fit indices, including Critical Ratio

(CR), Chi-square (CMIN), Degrees-of-Freedom (df), Chi-square/Degrees-of-freedom (CMIN/DF), Root mean

square residual (RMR), Root mean square error of approximate (RMSEA), Goodness-of-fit (GFI), and

Comparative fit index (CFI). In general, GFI and CFI greater than 0.90 indicate good model fit (Bentler 1989).

As illustrated in Table 6, all hypotheses are statistically significant and supported, with critical ratios ranging

from 17.261 to 4.594, which are greater than 1.96 and thus indicate acceptable results (Hair et al. 2006; Holmes-

Smith 2000). The goodness-of-fit indices of the proposed model of continuance intentions fit the data

reasonably well, as confirmed by the chi-square CMIN=656.880, df=236, CMIN/DF=2.783, RMR=0.176,

GFI=0.897, CFI=0.966, and RMSEA=0.062 (Table 7).

Table 6: Regression Weights

Hypotheses

Paths

Standardized

Regression

Weights

(B)

Standard

Error

S.E.

Critical Ratio

C.R.

P Value

Hypotheses

Findings

H1 a

Trust

<---

0.698

0.042

15.778

***

Supported

H1 b

<---

0.420

0.052

7.859

***

Supported

<---

Trust

0.379

0.055

7.077

***

Supported

H4 a

Enj

<---

0.360

0.039

7.781

***

Supported

H3 a

Enj

<---

0.555

0.041

10.979

***

Supported

H4 b

CIU

<---

0.216

0.046

5.250

***

Supported

CIU

<---

Enj

0.455

0.067

8.963

***

Supported

H3 b

CIU

<---

0.282

0.051

6.037

***

Supported

Table 7: Goodness-of-fit indices

Confirmatory Factor Analysis CFA

(Goodness-of-fit measure)

Acceptable Values

Value

Chi-Square CMIN

656.880

Degree of freedom

236

CMIN/DF

Chi square/ df ≤5 (Bentler and Bonnett, 1989)

2.783

P value

p≤0.05 (Hair et al., 2006)

0.000

Root mean square residual (RMR)

No established thresholds (the smaller the better)

(Hair et al., 2006)

0.176

Goodness-of-fit (GFI)

≥ 0.90 (the higher the better) (Hair et al., 2006)

0.897

Comparative fit index (CFI)

≥ 0.90 (Hair et al., 2006)

0.966

Root mean square error of approximate

(RMSEA)

< 0.08 (Hair et al., 2006)

0.062

Normal fit index (NFI)

≥ 0.90 (Hair et al., 2006)

0.943

Incremental fit index (IFI)

≥ 0.90 (Hair et al., 2006)

0.960

Relative fit index (RFI)

≥ 0.90 (Hair et al., 2006)

0.933

Next, we examine the regression weights (path significance) of each relationship in our research model and

the variance explained (R2 value) by each path. The AMOS software reports the standardized regression

weights and critical ratio for each path (Table 5). The hypothesized associations are strongly significant at p =

***. Perceived enjoyment is the strongest predictor of continuance intention (B = 0.455), followed by perceived

usefulness (B = 0.282), and then social pressure (B = 0.216). The model explains 55% of the variance in

continuance intentions (Figure 1).

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

Figure 1: Internet Continuance Intention shopping model in Saudi Arabia

6 INVARIANCE ANALYSIS

As has been demonstrated in Table 1, due to a higher-than-average percentage of young consumers (35

years old and younger in this research), it is considered important to conduct age invariance analysis. Online

customers commonly are younger and more highly educated than conventional customers, making a young

consumer more representative of the online customer population (OECD 1998). Additionally, users who range

in age from their teens through their 30s are particularly attractive targets for sellers of goods and services and

are also more likely to purchase products or services online than are older consumers (Akhter 2003; He and

Mykytyn 2007).

When comparing cultures or groups, research participants may not recognize the same meaning and

understanding of survey items. Scholars have emphasized the importance of minimizing possible research biases

when comparing cultures or groups (Yi et al. 2008). To minimize bias, we assessed the measurement invariance

(equivalence) across the groups to consider the constructs‟ factorial invariance (Cheung et al. 1999).

Invariance analysis indicates whether any differences occur between the two age groups; young and old.

The factorial analysis reveals whether young and old conceptualize the model constructs the same way. If we

find an age effect on the measurement invariance of the construct and the score of the group analysis is

significant, the construct measurement differs for the two groups, and they cannot be compared directly.

Therefore, the factorial invariance (metric equivalence) for both age groups were assessed (Hair et al., 2006).

The CMIN=1206.661, df=468, CMIN/DF=2.578, RMR=0.123, GFI=0.906, CFI=0.971, and RMSEA=0.041,

indicate satisfactory goodness-of-fit indices across the groups (Table 8).

Table 8: Goodness-of-fit indices (Younger than 35 – 35 and Older)

Confirmatory Factor Analysis CFA

(Goodness-of-fit measure)

Acceptable Values

Value

Chi-Square CMIN

1206.661

Degree of freedom

468

CMIN/DF

Chi square/ df ≤5 (Bentler and Bonnett, 1989)

2.578

P value

p≤0.05 (Hair et al., 2006)

0.000

Root mean square residual (RMR)

No established thresholds (the smaller the better)

(Hair et al., 2006)

0.123

Goodness-of-fit (GFI)

> 0.90 (the higher the better) (Hair et al., 2006)

0.906

Comparative fit index (CFI)

> 0.90 (Hair et al., 2006)

0.971

Root mean square error of approximate

(RMSEA)

< 0.08 (Hair et al., 2006)

0.041

Normal fit index (NFI)

≥ 0.90 (Hair et al., 2006)

0.916

Site Quality

Social Pressure

Enjoyment

Enj

Perceived

usefulness

Trust

Continuance

Intention

CIU

χ²= 656.880

df=236

χ²/df= 2.783

CFI=0.966

RMSEA=0.062

0.38

0.42

=0.49

= 0.54

=0.44

0.55

0.28

0.36

0.54

0.22

0.70

=0.55

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

Confirmatory Factor Analysis CFA

(Goodness-of-fit measure)

Acceptable Values

Value

Incremental fit index (IFI)

≥ 0.90 (Hair et al., 2006)

0.949

Relative fit index (RFI)

≥ 0.90 (Hair et al., 2006)

0.907

Assuming the unconstrained model is correct, compared with constraining all factorial paths, the results

across groups indicate changes in df (Δdf) = 18, chi-square (Δχ²) = 31.677, and p = 0.115, which is greater than

Byrne‟s (2001) 0.05 cut-off. Tests of measurement invariance in which we freely estimate the other loadings

appear in Table 9. According to the results, changes in the chi-square and df are insignificant (p = 0.115).

Therefore, the goodness-of-fit indices are comparable across age groups, supporting the invariance of the

unconstrained and constrained models. We thereby establish metric equivalence and can proceed in our analysis

to regression paths.

Table 9: Invariance analysis (Younger than 35 – 35 and Older)

Model

Δdf

Δχ²

Measurement weights

31.677

.115

Structural weights

13.244

.369

The coefficient (regression paths) invariance analysis determines if young and old respondents have the

same relationships with the same variables in the research model. The findings in Table 9 suggest coefficient

invariance among age groups across the research model with all regression paths constrained (Δχ² = 13.244, Δdf

= 9, p = 0. 369). Even though the structural weight in Table 9 shows invariance among the groups, the author

realised the need to minimize the possibility of research biases in the two age groups (younger than 35 years old

and 35 and older) analysis among constructs relationship (path) that may arise from the data strength and

weakness when applied to every constructs‟ path. Therefore, the author decided to test each factorial path

separately, while the rest of the paths are freely estimated across the two age groups to look for any non-

invariance path.

The findings in Table 10 indicate that young and old age group are non-invariant in certain relational paths.

Therefore, in this case testing the individual path has demonstrated to be a more rigorous test for non-invariance.

Differences in their intention in the context of e-shopping continuance can be observed in the different

coefficients in the social pressure  enjoyment link. Specifically, in the comparisons of the young with old (Δχ²

= 5.609, p = 0.018), the influence of social pressure is greater for the younger sample than for the older sample.

Table 10: Structural Factorial of theoretical construct (structure Invariant – Regression) for the age

sample (Younger than 35 – 35 and Older)

Hypo-

theses

Paths

Younger than 35

Sample

35 and older Sample

Invariance

C.R.

value

C.R.

P Value

Δ DF

Δχ²

P Value

H4 a

Enj

<---

0.186

7.039

***

0.322

5.694

***

5.609

0.018

Age was found to have latent mean non-invariance for the research constructs (Table 11). This difference

between younger than 35 and 35 and older, in the context on continuance Internet shopping, resulted from the

differences of the latent mean of trust, enjoyment, and continuance intention. The standardized latent mean of

trust, enjoyment, and continuance intention in the younger than 35 sample is estimated to be: trust = 0.278;

enjoyment = 0.401; continuance intention = 0.217, with a standard error (SE) of: trust = 0.097; enjoyment =

0.095; continuance intention = 0.097, and CR (t-value) of: trust = 2.875; enjoyment = 4.209; continuance

intention = 2.237. The result is significant (p>0.05, trust, p=0.004; enjoyment p=***; continuance intention

p=0.025). Thus, trust is 0.278 more (higher) among the younger sample than it is among older sample. The same

applies for enjoyment with 0.401 and continuance intention with 0.217, higher among the younger sample than

it is among the older sample.

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

Table 11: Means: (Younger than 35 - Default model) - for the age sample (Younger than 35 – 35 and

Older)

Latent mean

S.E.

C.R.

P Value

0.096

0.092

1.037

0.300

Trust

0.278

0.097

2.875

0.004

Enj

0.401

0.095

4.209

***

CIU

0.217

0.097

2.237

0.025

0.070

0.091

.769

0.442

0.149

0.091

1.644

0.100

7 DIRECT AND INDIRECT EFFECT ANALYSIS

SEM distinguishes between direct, indirect, and total effects (Jöreskog and Sörbom, 2001). The direct

effect is the relationship linking two constructs with a single arrow between them (Hair et al., 2006). On the

other hand, the indirect effect is a sequence of relationships with at least one mediating constructs involved

(Hair et al., 2006). The sum of the indirect and direct relationships between the constructs will constitute the

total effect (Hair et al., 2006).

Both the indirect effect and the total effects can facilitate understanding of important questions and

relationships that are not addressed when investigating the direct effect alone (Kline, 1998). The direct and

indirect effects (Hair et al. 2006) in Table 12 reveal that the greatest total influences of direct and indirect

(mediated) effects on continuance intentions come from enjoyment (0.749 for the 35 years and older, and 0.705

for younger than 35 years). The next greatest influences derive from site quality (0.624 for the 35 years and

older, and 0.620 for younger than 35 years). Additionally, social pressure has the second highest direct influence

on continuance intention (0.215 for younger than 35 years and 0.212 for 35 years and older). Therefore, site

quality, trust, perceived usefulness, enjoyment, and social pressure all play significant direct and indirect roles

for continuance intentions regarding e-shopping for both age groups.

Table 12: Direct and Indirect influences on CIU

Construct

CIU (Younger than 35)

CIU (35 and older)

Direct

Indirect

Total

Direct

Indirect

Total

--------

0.620

--------

0.624

TRUST

--------

0.318

--------

0.269

0.211

0.215

0.426

0.263

0.244

0.506

0.215

0.131

0.346

0.212

0.241

0.453

ENJ

0.147

--------

0.141

0.749

--------

0.749

= 0.55

8 DISCUSSION

This research provides an integrated conceptual model that clarifies the theoretical problems of continuance

e-shopping intentions and age behavioural differences in Saudi Arabia. All hypotheses are confirmed,

demonstrating that perceived enjoyment, perceived usefulness, and social pressure are the main determinants of

continuance intentions, explaining 55% of continuance e-shopping intentions. However, enjoyment is most

influential (see Table 6; SRW = 0.455, C.R. = 8.963), followed by perceived usefulness (SRW = 0.282, C.R. =

6.037), and then social pressure (SRW = 0.216, C.R. = 5.250). These findings are consistent with previous

research (e.g., Bhattacherjee 2001a; Childers 2001; Davis et al. 1989; George 2002; Shih and Fang 2004; Teo et

al. 1999; Venkatesh et al. 2003). Enjoyment, perceived usefulness, and social pressure have positive influences

(direct or indirect) on consumers‟ continuance e-shopping intentions.

The measurement weights of the younger and older groups are consistent and similar. However, the social

pressure  enjoyment path is non-invariant between the age groups. That is, younger people are more

influenced by evaluations of the opinions of others (young RW = 0.186, C.R. = 7.039; old RW = 0.322, C.R. =

5.694; Δχ²=5.609, p=0.018). This may reflect the general tendency of more mature people to rely on their own

experience; thus young people are more influenced by peer groups (Spero and Stone 2004).

Site quality and trust are strong antecedents of perceived usefulness (site quality SRW = 0.420, C.R. =

7.859; trust SRW = 0.379, C.R. = 7.077). Both site quality (0.620) and trust (0.318) have large indirect effects

on continuance intentions (Table 12). These findings are consistent with the collectivist culture of Saudi Arabia,

where people tend to trust only those within their in-group (Yamagishi and Yamagishi 1994).

The latent means of trust, enjoyment and continuance intention are higher among the younger population

(trust p=0.004; enjoyment p<0.001; continuance intention to use p=0.025). Thus, trust is 0.278 higher among the

younger sample than the older sample. The same goes for enjoyment with 0.401 and continuance intention to

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

use with 0.217; both higher among the younger sample than among older sample, and consistent with the

expected greater readiness of younger people to embrace technological innovations.

9 RESEARCH LIMITATIONS

Typical of most survey research, this study suffers some limitations. First, the novelty associated with

using an online survey indicates that empirical data may lead to novelty effect bias. Second, the online survey

was posted, with permission, on Saudi universities‟ online forums. However, the survey may suffer a non-

response bias, but there is no systematic way to determine the response rate in an online survey. Although the

survey attracted a large sample of participants (928 in the first two months) and covers all three main

commercial geographical regions in Saudi Arabia, it may still suffer from the biases that are inherent to survey

studies. Conversely, this survey can claim to be more realistic than typical laboratory experiments, as it

addresses real consumers and real shopping issues, outweighing the disadvantages of the method.

The adoption of e-shopping and online revisit intention might also be influenced by the product or service

itself (Klein 2003). Since this study has not focused specifically on any particular products or e-retailers, it is not

known to what extent our research results may be extended to specific products or services. Without referring to

the nature of the product, participants in this research have used their Internet shopping preferences to answer

the questionnaires. Certain products or services on a website may be relatively simple, low-touch products that

require relatively less trust, have some unique features (e.g., web-based, graphics-rich, interactive interface),

purpose (e.g., learning new concepts), or more complex high-touch products for which trust issues are expected

to be more dominant. Such related differences may alter some of the path effects reported in our study.

Therefore, future research needs to assess the generalisability of the model for the purchase of relatively simple

low-touch or for more complex high-touch products, including applicability to other related online industries,

such as financial services and airlines industries.

Furthermore, Girard, Korgaonka, and Silverblatt (2003) find that e-shopping preferences depend on

product types. Men are more likely to shop online for utilitarian experience goods (e.g., cell phones, computers),

whereas women shop online for hedonic experience goods, such as perfume and clothing. Our study focuses on

consumers who had previously purchased from an e-vendor's website, without any preferences for any particular

industry. The results may differ from those of consumers who have never purchased from a site other than a

preferred one. Thus, the generalisability of results to potential consumers of an e-vendor that have never visited

or have never purchased from the e-vendor's website is not immediately obvious and, therefore, warrants further

investigation.

10 CONCLUSIONS, CONTRIBUTION AND AREAS FOR FURTHER RESEARCH

This study was motivated by prior research indicating that many consumers who search different online

retail sites abandon their purchase intentions. In order to study the important, little-researched area of

continuance e-shopping, we adapted the TAM and ECT. By integrating these and deriving our own model, we

have contributed to an understanding of the factors that encourage consumers to continue their e-shopping

intention. A key conclusion from this study is the importance of both the direct and indirect effects of age

differences in Saudi Arabia, which should be considered when developing any website and marketing strategy

for e-retailing.

The latent mean findings reveal that younger consumers have higher continuance intention. Akhter (2003)

suggests that younger people are more likely than older consumers to purchase using the Internet. These

contributions are in line with previous research that young people are more likely than older adults to use the

Internet, which represent one of the main environments for young people to play, learn, communicate, and share

experiences (Alreck and Settle 2002; Spero and Stone 2004; Williamson, 2006; Rainie and Horrigan, 2005).

Additionally, previous researchers demonstrated that consumers who experience pleasure and joy from using e-

shopping are likely to use it more extensively than others (Davis 1992; Malone 1981; Webster 1989). Therefore,

managers should work to increase the level of trust, enjoyment, and continuance intention among older

consumers.

From a theoretical standpoint, these research results contribute to existing literature in several ways. First,

we enhance e-shopping literature by providing insights into the factors that seem to affect e-shopping

continuance intentions. We also posit that enjoyment, social pressure, and perceived usefulness have direct and

indirect effects on continuance intention. The greater positive indirect effects of site quality and trust suggest

that e-retailers should increase the positive perceptions of trust and site quality to make their e-shopping

environment more useful and enjoyable. For example, if a new customer is more likely to judge a website by its

appeal, reflecting its quality and trustworthiness rather than its usability, then e-retailers need to increase the

appeal of their sites. Furthermore, e-retailers should emphasise their trustworthiness by, for example, marketing

their robust security and policies measures, adding a Frequently Asked Questions section and including

statements such as “secure servers” (Gehrke and Turban 1999).

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

Continuance intention to use a technology such as e-shopping is not only determined by social pressure, but

also by users‟ needs to build relationships with others inside the online social communities (Schau and Gilly

2003). According to Wilska (2003 p.459), the customer‟s relation to technology would impact consumers‟

lifestyles. To have a significant effect on e-shopping continuance intentions, any e-shopping environment should

encourage a shopping experience that is useful and enjoyable. Customers‟ involvements in the product design

process are likely to be perceived as more enjoyable. For example, Nike online shoppers (www.nike.com) can

customize shoes, colours, styles, and even select a name or message. Another example involves e-retailers that

provide online customer services through modern communication tools, such as real time chat or Twitter (see

Zappos, www.zappos.com). Similarly, communication on useful offers, as is done with social networking sites

such as Osoyou (www.osoyou.com), is likely to be perceived as a useful way of sharing with friends and

relatives.

Second, the results support previous research that perceived usefulness reflects the utilitarian aspects of e-

shopping, whereas perceived enjoyment reflects its hedonic aspects. In our study, enjoyment has the strongest

effect on e-shopping continuance intentions, confirming that enjoyment in an e-shopping environment is

important and the effect is direct. For instance, if an individual „„feels good‟‟ about an online activity, the

individual is more likely to engage in it and shape intention to revisit e-shopping. Nevertheless, combining the

direct and indirect effects indicates that perceived usefulness has a stronger total effect on e-shopping

continuance intentions, supporting previous findings. Usefulness is an important criterion for consumers when

they select online stores and can increase their satisfaction. Consumers may continue using a useful e-commerce

service, even if they are dissatisfied with it (Bhattacherjee 2001a).

Third, few prior studies use SEM as their methodological approach in Saudi Arabia, and even fewer apply

invariance analysis to verify age behavioural differences. This study addresses this knowledge gap for a unique

culture.

Users in our study have different experiences based on whether they trust local or international e-retailers,

and other related issues when shopping online. 41.1% for young users and 46.2% for old users trust international

e-retailers, compared to 11.1% for young users and 10.3% for old users for the local retailers. Though not

discussed in this research, the type of e-retailer (local or international), the mode of payment, online security,

and language barriers may constrain the research model constructs on continuance e-shopping intention. Since

prior research in the context of e-shopping in Saudi Arabia has not distinguished between these constraints,

further research is recommended to explore such distinction.

11 RESEARCH MODEL GENERALIZABILITY

Hofstede (1984) argues with reference to several contexts that the popular theories are culture-bound. The

theoretical basis of this study is the extended TAM, which is derived from the TRA model, and the extended

ECT. Both extended TAM and ECT have adapted other constructs to measure continuance intention (Agarwal

and Prasad 1999; Dishaw and Strong 1999; Gefen and Keil 1998; Moon and Kim 2001; Venkatesh and Davis

2000; Premkumar and Bhattacherjee 2008; Lin, Wu and Tsai 2005).

The research model in this study confirms that online shopping involves hedonic as well as utilitarian

value. Additionally, social pressure and social influence, play an important role in Saudi Arabia. As expected

based on current IS literature, perceived usefulness (utilitarian) and perceived enjoyment (hedonic) value are

influential indicators of intention and revisit intention (Davis et al., 1992; Van der Heijden, 2004; Lin, Wu and

Tsai, 2005; Donovan and Rossiter 1982; Al-maghrabi, Dennis, and Halliday, 2011). Shim et al. (2001) consider

social pressure only marginally significant for e-shopping intentions, whereas Foucault et al. (2005) confirm a

significant link between talking about e-shopping with friends and intention to e-shop. However, TAM omits

subjective norms, primarily because Davis claimed that they are not significant in explaining behavioural

intentions (Davis et al., 1989). The similarity and distinction in the findings between this research and literatures

could be attributed to cultures, which suggest that information technology and management practices should be

modified for different cultural contexts.

The Arab World culture, including Saudi Arabia, is dominated by high collectivism, i.e., an individual‟s

beliefs depend on the social norms of the group (Kluckhorn and Strodtbeck, 1961). Additionally, other studies

suggest that individuals place more trust in people similar to themselves and assess trustworthiness based on

second-hand information and on stereotypes (McKnigh et al., 1998; Morgan and Hunt, 1994; Zucker, 1986). In

a similar vein, recent studies in the marketing literature have also confirmed the importance and dynamics of

social pressure on consumer behaviour. For instance, Takada and Jain (1991) have found that the diffusion of

consumer goods in South Korea and Taiwan is directly influenced by social value.

Prior research indicates that consumers in all shopping channels shop for both utilitarian and hedonic

outcomes (Childers et al., 2001), which is also consistent with previous research that social influence plays an

important role in collectivist cultures (Foucault et al. 2005; Anandarajan, 2002). The author of this research

suggests that the research model and the results of this study could be generalized into other contexts in general,

Arab countries in particular, and Gulf Cooperation Council countries (GCC) in specific. This is because Arab

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

countries are classified by Hofstede (1984) as collectivist culture. The generalization of the research model to

the Gulf Cooperation Council countries is more likely to be applicable because of having parallels with Saudi

Arabia in sharing similar values, tribes, relatively young population, and rapid economic growth rates (Nations

Online, 2008).

Additionally, the growth of disposable family income in and distribution of the spending within families in

GCC countries are similar. Shopping is done by good value of the economic potential available, on the

experience of each person, on the social scale of the individual and on the peer groups and sub-groups that

individual mixed in, specially that most of the GCC countries have been ranked in the top 30 in the 2010

Kearney Global Retail Development Index for retail attractiveness (Kearney GRDI, 2010).

However, the author in this research suggests that the external validity (generalisability) of TAM and ECT

in other cultures is questionable. The author recommends that the research model should be further tested in

other cultural contexts to show the potential generalisability, particularly cultures that may have similarities with

Saudi Arabia.

12 MANAGERIAL IMPLICATIONS

This study provides managers with useful and important information to encourage shoppers to complete

their online purchases, and we suggest that this should feed into website planning and marketing strategies.

Managers and site developers should focus on the quality and informative content, which reflect usefulness and

enjoyment. Managers also should not underestimate the power of the technology and the Internet, especially in a

young population Continuance shopping is important, because customers who fail to return reduce the firm‟s

customer base and its revenues, and may well require substantial expenditure to attract them back from

competitors. Managers cannot ignore either direct (perceived usefulness, enjoyment, social pressure) or indirect

(site quality, trust) influences on continuance intention. The findings indicate that both young and old

respondents have concerns about trusting local e-shopping sites. Managers are advised to enhance website

security, content and design quality, and add a dual language feature, in order to retain consumers and build long

term, trusting relationships.

Online retailers can build positive word of mouth to enhance the perceptions of friends and family

members of current customers regarding the website‟s usefulness, site quality, interactivity, and enjoyment, thus

increasing perceptions of the firm‟s trustworthiness. The research findings confirm that young people spend

more time and money in e-shopping, and trust Internet shopping more than do older people. Therefore,

managers should communicate the product benefits and values, and rely on young people to spread positive

word of mouth and recommend the product. Peer pressure would engage and encourage consumers to enjoy

shopping online, leading to more intention to e-shop. Use should be made of social networks such as Facebook,

Twitter, and many more, to enhance the perceptions of family, friends, potential and actual customers of their

websites‟ usefulness and trustworthiness. This is more important among young consumers as they are making

the online world their environment, developing personal relationships, playing, learning, and spreading

experiences.

Based on the current research findings, understanding the utilitarian and hedonic roles of e-shopping would

enable marketing managers to increase the scope of e-shopping. For example, interactive activities such as an

inside look at an airplane in a 360˚ view, selecting your travel seat using virtual model technology, or trying-on

clothing can provide enjoyment in addition to facilitating product evaluation. Sophisticated technologies used in

e-shopping can provide e-retailers with many techniques that will increase e-shopping usefulness and

enjoyment, resulting in the continuity of loyal e-shoppers. Amazon‟s technique („users who bought this item

were interested in this item as well‟) is probably the most famous example using customer profiles. Thus, given

the current research findings, e-retailers should ensure that they are providing sufficient hedonic value to online

shoppers before attempting to focus on other aspects of their website development.

APPENDIX A

Questionnaire (Measurement indicators)

Perceived Usefulness (Strongly disagree . . .Strongly agree)

Adapted from (Gefen et al., 2003).

 The website I use for my online shopping is useful for searching and purchasing.

 The website I use for my online shopping improves my performance in searching and purchasing.

 The website I use for my online shopping enables me to search and purchase faster.

 The website I use for my online shopping enhances my effectiveness in searching and purchasing.

 The website I use for my online shopping makes it easier to search for and purchase.

 The website I use for my online shopping increases my productivity in searching and purchasing.

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

Trust (Strongly disagree . . .Strongly agree)

Adapted from (McKnight et al., 2002b).

Trusting Beliefs (Benevolence)

 I believe that the website I use for my online shopping would act in my best interest.

 If I required help, the website I use for my online shopping would do its best to help me.

 The website I use for my online shopping is interested in my well-being, not just its own.

Integrity

 The website I use for my online shopping is truthful in its dealings with me.

 I would characterize the website I use for my online shopping as honest.

 The website I use for my online shopping would keep its commitments.

 The website I use for my online shopping is sincere and genuine.

Competence

 The website I use for my online shopping is competent and effective in providing online business.

 The website I use for my online shopping performs its role of giving shopping advice very well.

 Overall, the website I use for my online shopping is a capable and proficient Internet shopping

provider.

 In general, the website I use for my online shopping is very knowledgeable about its service.

Trusting Intentions (Willingness to Depend)

 When an important shopping issue or problem arises, I would feel comfortable depending on the

information provided by the website I use for my online shopping.

 I can always rely on the website I use for my online shopping in a tough shopping situation.

 I feel that I could count on the website I use for my online shopping to help with a crucial

shopping problem.

 If I had a challenging shopping problem, I would want to use the website I use for my online

shopping again.

Perceived Enjoyment (Strongly disagree . . .Strongly agree)

Adapted from (Childers et al., 2001).

 Shopping online in this website would be fun for its own sake.

 Shopping online in this website would make me feel good.

 Shopping online in this website would be boring.

 Shopping online in this website would involve me in the shopping process.

 Shopping online in this website would be exciting.

 Shopping online in this website would be enjoyable.

 Shopping online in this website would be uncomfortable.

 Shopping online in this website would be interesting.

Perceived Site Quality (Strongly disagree . . .Strongly agree)

Adapted from (McKnight et al., 2002b).

 Overall, this website worked very well technically.

 Visually, this website resembled other sites I think highly of.

 This website was simple to navigate.

 On this website, it was easy to find the information I wanted.

 This website clearly showed how I can contact or communicate with online shopping customer

service.

Social Pressure (Strongly disagree . . .Strongly agree)

Adapted from (Shine and Fang, 2004).

 Most people who are important to me would think that using the website to shop online is a wise

idea.

 Most people who are important to me would think that using the website to shop online is a good

idea.

 Most people who are important to me would think I should use the website to shop online.

 My family who are important to me would think that using the website to shop online is a wise

idea.

 My family who are important to me would think that using the website to shop online is a good

idea.

Talal Al-maghrabi, Charles Dennis, Sue Vaux Halliday and Abeer BinAli

 My family who are important to me would think I should use the website to shop online.

Continuance Intention (Strongly disagree . . .Strongly agree)

Adapted from (Yang and Peterson, 2004).

 I say positive things about the website I use for my online shopping to other people.

 I would recommend the website I use for my online shopping to those who seek my advice about

such matters.

 I would encourage friends and relatives to use the website I use for my online shopping.

 I would post positive messages about the website I use for my online shopping on some Internet

message board.

 I intend to continue to do business with the present website.

 I intend to do more business with the present website.

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