Driving online shopping: Spending and behavioral differences among women in Saudi Arabia

Al-maghrabi, Talal; Dennis, Charles Article Driving online shopping: Spending and behavioral differences among women in Saudi Arabia International Journal of Business Science & Applied Management (IJBSAM) Provided in Cooperation with: International Journal of Business Science & Applied Management (IJBSAM) Suggested Citation: Al-maghrabi, Talal; Dennis, Charles (2010) : Driving online shopping: Spending and behavioral differences among women in Saudi Arabia, International Journal of Business Science & Applied Management (IJBSAM), ISSN 1753-0296, International Journal of Business Science & Applied Management, s.l., Vol. 5, Iss. 1, pp. 30-47 This Version is available at: https://hdl.handle.net/10419/190611 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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Journal of Business Science and Applied Management, Volume 5, Issue 1, 2010 Driving online shopping: Spending and behavioral differences among women in Saudi Arabia Talal Al-maghrabi Brunel Business School, Brunel University West London, UB8 3PH, United Kingdom Tel: +44 (0) 1895 267171 Email: [email protected] Charles Dennis Brunel Business School, Brunel University West London, UB8 3PH, United Kingdom Tel: +44 (0) 1895 265242 Email: [email protected] Abstract This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia. The sample consists of 650 female respondents. A structural equation model confirms model fit. Perceived enjoyment, usefulness, and subjective norms are determinants of online shopping continuance in Saudi Arabia. High and low online spenders among women in Saudi Arabia are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived site quality to perceived usefulness is not invariant between high and low e-shoppers in Saudi Arabia. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the female respondents’ intention to continue shopping online. Online strategies cannot ignore either the direct and indirect spending differences on continuance intentions, and the model can be generalized across Saudi Arabia. Keywords: internet shopping, e-shopping, technology acceptance, male and female examination, continuance online shopping, Saudi Arabia Acknowledgements: The authors thank the respondents, the editors, and the anonymous reviewers for their many helpful suggestions. Special thanks for their families for their continued support. Talal Al-maghrabi and Charles Dennis 31 1 STUDY MOTIVATION Globalization continues to drive the rapid growth of international trade, global corporations, and non-local consumption alternatives (Alden et al. 2006; Holt et al. 2004), and advances of the Internet and e-commerce have diminished trade boundaries. E-commerce and e-shopping create opportunities for businesses to reach to consumers globally and directly, and in turn, business and social science research now focuses specifically on cross-national and cross-cultural Internet marketing (Griffith et al. 2006). The Internet had changed how businesses and customers customize, distribute, and consume products. Its low cost gives both businesses and consumers a new and powerful channel for information and communication. In 1991, the Internet had less than 3 million users worldwide and no e-commerce applications; by 1999, about 250 million users appeared online, and 63 million of them engaged in online transactions, which produced a total value of $110 billion (Coppel 2000). Business-to-consumer online sales in the United States grew by 120% between 1998 and 1999 (Shop.org and Boston Consulting Group, 2000). According to a U.K. payment association, the number of consumers who shop online has increased by more than 157%, from 11 million in 2001 to more than 28 million in 2006 (cited in Alsajjan and Dennis, 2009). E-commerce transactions also are growing in the Middle East (19.5 million Internet users) and in the Gulf States. In Saudi Arabia, online transactions have increased by 100%, from $278 million in 2002 to $556 million in 2005 (Al Riyadh 2006). In 2007, Internet sales increased to more than $1.2 billion worldwide and are expected to continue to rise (World Internet Users and Population Stats 2007). An unpublished study by the Centre for Customer Driven Quality also highlights some potential savings: For one retailer, the cost of an in-store customer contact was estimated to be $10, the cost of a phone contact $5, and the cost of a Web contact $0.01 (Feinberg, et al. 2002). In the airline industry, the savings are similar. According to the International Air Transport Association, airlines currently issue approximately 300 million paper tickets per year at a cost of $10 per ticket to process (Arab News Newspaper, 2007). One e-ticket process costs only $1(Arab News Newspaper, 2007). Despite the impressive online purchasing growth rates though, compelling evidence indicates that many consumers who search different online retail sites abandon their purchases. This trend and the proliferation of business-to-consumer e-shopping activities require that online businesses understand which factors encourage consumers to complete their purchases. Acquiring new customers also can cost as much as five times more than retaining existing ones (Bhattacherjee 2001b; Crego and Schiffrin 1995; Petrissans 1999). For example, a 5% increase in customer retention in the insurance industry typically translates into an 18% reduction in operating costs (Bhattacherjee, 2001a; Crego et al, 1995). Online customer retention is particularly difficult. Modern customers demand that their needs be met immediately, perfectly, and for free, and they are empowered with more information to make decisions (Bhattacherjee 2001b; Crego and Schiffrin 1995). They also have various online and offline options from which to choose, and without a compelling reason to choose one retailer over another, they experiment or rotate purchases among multiple firms (Bhattacherjee 2001b; Crego and Schiffrin 1995). To employ the savings derived from e-businesses, companies might engage in tactics to increase switching costs and thereby retain more customers. E-retailers might recall details about the customer that reduce the customer effort demanded in future transactions; they could also learn more about the customer to tailor those future interactions to the customer’s needs (Straub and Watson 2001). Better product quality, lower prices, better services, and increased outcome value should help companies build sustainable relationships with their customers. Theoretical explanations of online shopping intentions suggest several important factors. For example, Rogers (1995) suggests that consumers reevaluate their acceptance decisions during a final confirmation stage and decide to continue or discontinue. Continuance may be an extension of acceptance behavior that covaries with acceptance (e.g., Bhattercherjee 2001a; Davis et al. 1989; Karahanna et al. 1999). We adopt the extended expectation confirmation theory (ECT; Bhattacherjee 2001b) and the technology acceptance model (TAM; Davis et al. 1989) as a theoretical basis, integrating ECT from consumer behavior literature to propose a model of e-shopping continuance intentions, similar to the way in which the TAM adapts the theory of reasoned action (TRA) from social psychology to postulate a model of technology acceptance. The TAM, as expanded by Davis and colleagues (1992) and Gefen (2003), and the ECT (Bhattacherjee 2001a; Oliver 1980) have been used widely in research in the industrialized world, but they are less commonly applied to developing countries. Moreover, the TAM stops at intention and does not investigate continuance intentions or behavior. Int. Journal of Business Science and Applied Management / Business-and-Management.org 32 As another issue in prior research, no widely acceptable definition for e-commerce exists. Coppel (2000) calls it doing business over the Internet, including both business-to-business and business-toconsumer markets. For the purpose of this research, we adopt the following definition: E-shopping, electronic shopping, online shopping, and Internet shopping are the same. All these activities include the activity of searching, buying, and selling products and services through the Internet. In recent years, the Internet has grown to include a wider range of potential commercial activities and information exchanges, such as the transaction and exchange of information between government agencies, governments and businesses, businesses and consumers, and among consumers. We focus mainly on the business-to-consumer (B2C) arena, which has been the source of most online progress and development. Previous research also finds that gender differences significantly affect new technology decisionmaking processes (Van Slyke et al. 2002; Venkatesh et al. 2000). Venkatesh and colleagues (2000) report that women tend to accept information technology when others have high opinions of it and are more influenced by ease of use. Men rely more on their evaluations of the usefulness of the technology. However, in many cultures, women represent the primary decision makers in families and households’ main shoppers. Greater e-commerce exposure and decision-making power may imply that women can attain greater satisfaction from online shopping (Alreck and Settle 2002). Finally, no previous research considers Internet shopping in Saudi Arabia or, specifically, continuance intentions for online shopping in Saudi Arabia, nor do studies address gender-based differences in shopping behavior online in Saudi Arabia. This research attempts to provide a validated conceptual model that integrates different factors, including gender, and clarifies the theoretical problems of continuance intentions in the unique context of Saudi Arabia. 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 and recommendations for further research. 2 THEORETICAL BACKGROUND The TAM (Davis 1989) represents an adaptation of the TRA, tailored to users’ acceptance of information systems. It helps explain determinants of computer acceptance and can explicate user behaviors 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; Davis 1989; Dishaw and Strong 1999; Gefen and Keil 1998; Igbaria et al. 1996; Moon and Kim 2001; Taylor and Todd 1995; Venkatesh 2000; Venkatesh and Davis 2000), but evidence regarding perceived ease of use remains inconsistent. Many studies simplify the original TAM by dropping attitude and studying just the effect of perceived usefulness and ease of use on intention to use (Gefen and Straub 2000; Leader et al. 2000; Teo et al. 1999). Updates to the TAM add antecedents of perceived usefulness and ease of use (Venkatesh and Davis 2000), such as subjective norms, experience, trust, and output quality. Ample evidence confirms that both usefulness (i.e., external motivation) and intrinsic enjoyment (i.e., internal motivation) offer direct determinants of user acceptance online (Davis et al. 1992; Leader et al. 2000; Moon and Kim 2001; Teo et al. 1999; Venkatesh 1999). Expectation confirmation theory (ECT) in turn helps predict consumer behavior before, during, and after a purchase in various contexts, 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; Swan and Trawick 1981; Tse and Wilton 1988). According to ECT, consumers define their repurchase intentions by determining whether the product or service meets their initial expectations. Their comparison of perceived usefulness versus their original expectation of usefulness influences their continuance intentions (Bhattacherjee 2001a; Oliver 1980). Their repurchase intentions depend on their satisfaction with the product or service (Anderson and Sullivan 1993; Oliver 1980). However, the 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 others’ opinions or information from mass media, whereas post-purchase expectations derive from first-hand experience, which appears more realistic (Fazio and Zanna 1981). After such first-hand experience, expectations may increase if consumers believe the product or service is useful or contains new benefits and features that were not part their initial expectation. Talal Al-maghrabi and Charles Dennis 33 Venkatesh and colleagues (2003) suggest that usage and intentions to continue usage may depend on cognitive beliefs about perceived usefulness. Gefen (2003) also indicates that perceived usefulness reinforces an online shopper’s intention to continue using a Web site, such that when a person accepts a new information system, he or she is more willing to alter practices and expend time and effort to use it (Succi and Walter 1999). However, consumers may continue using an e-commerce service if they consider it useful, even if they are dissatisfied with its prior use (Bhattacherjee 2001a). Site quality and good interface design enhance the formation of consumer trust (McKnight et al. 2002a), and if a consumer perceives a vendor’s Web site to be of high quality, he or she should trust that vendor’s competence, integrity, and benevolence (McKnight et al. 2002a). Gefen and colleagues (2003) integrate trust into the TAM in a B2C e-shopping context and find trust positively affects consumers’ intention to use a Web site. Building trust with consumers is an essential mission for eretailers, because purchasing decisions represent trust-related behaviors (Jarvenpaa et al. 2000; McKnight et al. 2002b; Urban et al. 2000). A person’s beliefs about what important others think about the behavior also should directly influence subjective norms. Therefore, if e-shopping is a socially desirable behavior, a person is more likely to e-shop (George 2002). Childers and colleagues (2001) also find that enjoyment can predict attitude towards e-shopping, just as much as usefulness can. However, usefulness was the better predictor for grocery items, whereas enjoyment offered better results for hedonic purchases. With regard to e-shopping, the hedonic enjoyment constructs in the TAM may reflect the pleasure users obtain from shopping online, which reinforces continuance intentions. 3 PROPOSED MODEL AND HYPOTHESES 3.1 Site Quality Initial trust forms quickly on the basis of available information (Meyerson et al. 1996). If consumers perceive a Web site as high quality, they trust it and will depend on that vendor (McKnight et al. 2002a). Site information quality and a good interface design enhance consumer trust (Fung and Lee, 1999). Web site quality helps predict behavior (Business Wire 1999; Carl 1995; Meltzer 1999). Perceptions of Web site quality affect trust and perceptions of usefulness. In addition, e-shoppers should perceive a Web site as more trustworthy if it appears more attractive because of its contents, layout, and colors, which represent site quality. On the basis of previous research, we therefore predict: H1a. Perceived site quality relates positively to perceived usefulness. H1b. Perceived site quality relates positively to customer trust to use online shopping. 3.2 Trust Trust refers to an expectation that others will not behave opportunistically (Gefen 2003). Trust therefore implies a belief that the vendor will provide what has been promised (Ganesan 1994). In turn, perceived usefulness should occur only for an e-vendor that can be trusted (Festinger 1975). Thus: H2. Perceived trust relates positively to perceived usefulness. 3.3 Perceived Usefulness According to Burke (1997), perceived usefulness is the primary prerequisite for mass market technology acceptance, which depends on consumers’ expectations about how technology can improve and simplify their lives (Peterson et al. 1997). A Web site is useful if it delivers services to a customer but not if the customers’ delivery expectations are not met (Barnes and Vidgen 2000). The usefulness and accuracy of the site also influence customer attitudes. Users may continue using an e-commerce service if they consider it useful, even if they may be dissatisfied with their prior use (Bhattacherjee 2001a). Consumers likely evaluate and consider product-related information prior to purchase, and perceived usefulness thus may be more important than the hedonic aspect of the shopping experience (Babin et al. 1994). In a robust TAM, perceived usefulness predicts IT use and intention to use (e.g., Adams et al. 1992; Agarwal and Prasad, 1999; Gefen and Keil 1998; Gefen and Straub 1997; Hendrickson et al. 1993; Igabria et al. 1995; Subramanian 1994), including e-commerce adoption (Gefen and Straub 2000). Therefore: H3a. Perceived usefulness relates positively to increasing customer subjective norms. Int. Journal of Business Science and Applied Management / Business-and-Management.org 34 H3b. Perceived usefulness relates positively to increasing customer enjoyment. H3c. Perceived usefulness relates positively to increasing customer continuance intentions. 3.4 Subjective Norms According to Venkatesh and colleagues (2003), social influences result from subject norms, which relate to consumers’ perceptions of the beliefs of other consumers. Shim and colleagues (2001) consider subjective norms only marginally significant on e-shopping intentions, whereas Foucault and Scheufele (2005) confirm a significant link between talking about e-shopping with friends and intention to e-shop. Enjoyment also is relevant to social norms, because involving Web sites facilitate e-friendship and enforce e-shopping as a subjective norm. Thus, H4a. Perceived subjective norms relate positively to increasing customer enjoyment. H4b. Perceived subjective norms relate positively to increasing customer continuance intentions. 3.5 Enjoyment Enjoyment in using a Web site significantly affects intentions to use (Davis et al. 1992; Igbaria et al. 1995; Teo et al. 1999; Venkatesh et al. 2002). Shopping enjoyment (Koufaris 2002), perceived entertainment value of the Web site (O’Keefe et al. 1998), and perceived visual attractiveness have positive impacts on perceived enjoyment and continuance intentions (van der Heijden 2003). Thus: H5. Perceived enjoyment relates positively to increasing customer continuance intentions. 4 METHODOLOGY To validate the conceptual model and the proposed research hypotheses, we developed an online survey, which is suitable for collecting data from large geographical areas. In addition, compared with traditional surveys, online surveys offer lower costs, faster responses, and less data entry effort. 4.1 Measures The measures of the various constructs come from previous literature, adapted to the context of online shopping if necessary. All online survey items use 1–7 Likert scales, on which 1 indicates strongly disagree and 7 is strongly agree. The site quality and trust items come from McKnight and colleagues (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 items. The continuance intention items were adapted from Yang (2004). The pilot study suggested some clarifications to the survey. Both Arabic and English language versions were available. The Arabic questionnaire employed Brislin’s (1986) back-translation method to ensure that the questionnaires have the same meaning in both languages. 5 DATA ANALYSIS Survey respondents were people who were actively engaged in Internet and online shopping in Saudi Arabia, including undergraduate and postgraduate students and professionals. As we show in Table 1, the sample consists of 650 female participants in Saudi Arabia. This somewhat surprising participation level illustrates the high rate of Internet use among women in Saudi Arabia. Most respondents are in their late 30s (2.5% younger than 18 years of age, 26.6% between 18 and 25, 42.8% are 26–35, 22% are 36–45, and 6.2% are older than 46 years). Similarly, 60% of the Saudi population is younger than 30 years of age. The vast majority (92.6%) of participants came from the three main regions in Saudi Arabia: 24.6% from the east, 27.8% from the central region, and 40.2% from the western region. The education levels indicate 1.5% of respondents earned less than a high school degree, 10.9% attended high school, 12.9% had diplomas, 52.9% had bachelor’s degrees, and 21.7% were postgraduates. Most respondents thus are well-educated. Moreover, 36% of them work in the public sector (government employee), 35.4% in the private sector, 6.5% were businesspeople, and 22.22% were students. As we show in Table 2, 52.2% of the respondents visited at least five different online sites to purchase each month, and 66.9% used the Internet for actual shopping. The western region reveals the highest percentages in most categories, such that 31.1% spend £100–£500 per year online, and 51.3% spend more than £501 per year. Furthermore, 49.7% of the respondents used the Internet in the prior six months to make flight booking or purchase airline tickets, 37.5% made hotel reservations, 35.2% purchased clothing, 58.6% bought books, and 37.8% purchased CD-DVDs or video tapes. To indicate Talal Al-maghrabi and Charles Dennis 35 why they used the Internet, as we summarize in Table 3, 82% referred to information search, 56.8% to social communication, 52.5% to banking, 64.8% to entertainment, 51% to work-related tasks, and 69% used it for study-related tasks. Table 1: Demographic Items Question Count Percentage Gender Total Female Participants 650 100 Age Less than 18 16 2.5 Between 18-25 173 26.6 Between 26-35 278 42.8 Between 36-45 143 22.0 Above 46 40 6.2 Education Level Less than high school 10 1.5 High school 71 10.9 Diploma 84 12.9 Bachelor 344 52.9 Post-graduate 141 21.7 Occupation Government employee 234 36.0 Private sector 230 35.4 Business people 42 6.5 Student 144 22.22 Income Level <SR4,000 (£1,000) 105 16.2 SR4,000-SR6,000 (£1,000-2,000) 78 12.0 SR6,001-SR8,000 (£2,001-4,000) 89 13.7 SR8,001-SR10,000 (£4,001-7,000) 77 11.8 SR10,001-SR15,000 (£7,001-10,000) 128 19.7 >SR15,001 (>£10,000) 123 18.9 Dependent on others 50 7.7 Region East region 160 24.6 West region 261 40.2 Central region 181 27.8 North region 29 4.5 South Region 19 2.9 Int. Journal of Business Science and Applied Management / Business-and-Management.org 36 Table 2: Items Purchased Online and Reasons Items purchased in the last six months Region in Saudi Arabia East West Middle Buying Books 47 71 45 16.9% 25.5% 16.2% Music CD, DVD, Videotape 34 34 28 12.2% 15.5% 10.1% Cloth 37 41 20 13.3% 14.7% 7.2% Sports equip 22 18 10 7.9% 6.5% 3.6% Travel reservation and ticketing 43 64 31 15.5% 23.0% 11.2% Hotel booking 31 50 23 11.2% 18.0% 8.3% Reason for using the Internet Info. Search 72 100 56 25.9% 36.0% 20.1% Entertainment 60 78 42 21.6% 28.1% 15.1% Social Communication 47 76 35 16.9% 27.3% 12.6% Work 39 71 32 14.0% 25.5% 11.5% Study 44 74 45 15.8% 26.6% 16.2% Purchasing 55 90 41 19.8% 32.4% 14.7% Banking 36 72 38 12.9% 25.9% 13.7% Table 3: Important Issues when Shopping Online Important issues to eshoppers Region in Saudi Arabia East West Middle Security 74 100 57 27% 36% 21% Price 75 104 56 27% 37% 20% Service, Delivery 75 97 58 27% 35% 21% Quality 75 102 60 27% 37% 22% Payment 73 100 57 26% 36% 21% Language Barrier 62 81 41 22% 29% 15% 6 ANALYSIS The Cronbach’s alphas (Table 4) are all greater than 0.7 (Bagozzi and Yi 1988). The squared multiple correlation cut-off point is 0.7, and the average variance extracted cut off-point is 0.5 or higher (Bagozzi 1994; Byrne 2001; Hair et al. 2006) (Table 5). We thus confirm the convergent reliability and discriminant validity. Talal Al-maghrabi and Charles Dennis 37 Table 4: Scale Properties and Correlations Factor Correlations Model Constructs Mean Std. Dev. Cronbach’s alpha SQ PU Trust SN Enj CIU SQ 26.92 6.38 0.927 1.000 PU 32.97 7-86 0.946 .749 1.000 Trust 21.74 5.03 0.947 .655 .695 1.000 SN 18.73 6.19 0.943 .259 .275 .395 1.000 Enj 28.39 8.61 0.931 .438 .465 .668 .536 1.000 CIU 31.48 7.98 0.961 .397 .421 .606 .533 .745 1.000 Table 5: Measurement Model Constructs/Indicators S. Factor Loading S.E C.R. AVE Squared Multiple Correlation Site Quality (SQ) 0.757 SQ 1 0.922 0.039 26.510 0.85 SQ 2 0.844 0.038 26.414 0.71 SQ 3 0.855 0.035 26.972 0.73 SQ 4 0.857 __ __ 0.74 Perceived usefulness 0.813 PU 3 0.911 0.039 37.788 0.83 PU 4 0.909 0.027 37.135 0.83 PU 5 0.914 __ __ 0.84 PU 6 0.871 0.029 33.487 0.76 Trust 0.804 Trusting Beliefs Integrity 1 0.896 0.028 35.069 0.80 Trusting Beliefs Integrity 2 0.886 0.023 42.297 0.79 Trusting Beliefs Integrity 3 0.896 0.027 35.167 0.80 Trusting Beliefs Integrity 4 0.909 __ __ 0.83 Subjective Norm 0.804 SN 3 0.731 __ __ 0.53 SN 4 0.973 0.054 25.507 0.95 SN 5 0.955 0.057 24.647 0.91 SN 6 0.908 0.055 23.875 0.82 Enjoyment 0.744 Enj 4 0.705 __ __ 0.50 Enj 5 0.94 0.055 22.934 0.88 Enj 6 0.925 0.055 22.918 0.86 Enj 8 0.858 0.052 20.672 0.74 Continuance Intention 0.864 CIU 1 0.827 0.024 35.466 0.69 CIU 2 0.928 0.017 55.752 0.86 CIU 3 0.981 __ __ 0.96 CIU 4 0.974 0.012 78.936 0.95 Int. 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