Analyzing key determinants of online repurchase intentions

Asia Pacific Journal of Marketing and Logistics Emerald Article: Analyzing key determinants of online repurchase intentions Chai Har Lee, Uchenna Cyril Eze, Nelson Oly Ndubisi Article information: To cite this document: Chai Har Lee, Uchenna Cyril Eze, Nelson Oly Ndubisi, (2011),"Analyzing key determinants of online repurchase intentions", Asia Pacific Journal of Marketing and Logistics, Vol. 23 Iss: 2 pp. 200 - 221 Permanent link to this document: http://dx.doi.org/10.1108/13555851111120498 Downloaded on: 23-04-2012 References: This document contains references to 46 other documents To copy this document: permissions@emeraldinsight.com This document has been downloaded 3113 times. Access to this document was granted through an Emerald subscription provided by FERDOWSI UNIVERSITY OF MASHHAD For Authors: If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service. Information about how to choose which publication to write for and submission guidelines are available for all. Additional help for authors is available for Emerald subscribers. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com With over forty years' experience, Emerald Group Publishing is a leading independent publisher of global research with impact in business, society, public policy and education. In total, Emerald publishes over 275 journals and more than 130 book series, as well as an extensive range of online products and services. Emerald is both COUNTER 3 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. *Related content and download information correct at time of download. The current issue and full text archive of this journal is available at www.emeraldinsight.com/1355-5855.htm APJML 23,2 Analyzing key determinants of online repurchase intentions Chai Har Lee Multimedia University, Bukit Beruang, Malaysia 200 Uchenna Cyril Eze Received December 2009 Revised September 2010 Accepted October 2010 School of Business, Monash University, Bandar Sunway, Malaysia, and Nelson Oly Ndubisi Griffith Business School, Griffith University, Gold Coast, Australia Abstract Purpose – The rapid changing internet environment has created a competitive business landscape, which provides opportunities and challenges for a variety of businesses. One of these opportunities includes conducting businesses online. Online transaction systems enable users to buy and make payment for products and services using the internet platform. The purpose of this paper is to examine the factors that may affect consumers’ intentions to repurchase products and services online. Design/methodology/approach – The research framework is grounded in extended technology acceptance model (TAM). The authors used survey questionnaire to collect 102 valid responses from participants in Malaysia who must have made, at least, one previous online purchase. The snowball approach was used to select the participants, to ensure that participants had previously purchased online. Findings – Data collected were analysed using regression model to determine the significance of the relationship between the dependent and independent variables. The emerging results provide significant evidence in support of the eight hypotheses proposed. Research limitations/implications – One of the limitations of this research is the relatively small sample size. Future research may use larger responses, as well as applying other relevant information system (IS) models/theories. Nonetheless, the paper provides a synthesis of extant literature relevant to the subject area, which is critical in addressing theoretical development in online-related purchase research. In addition, the empirical results corroborate some of the existing literature, as well as contribute to the advancement of the frontier of knowledge in the field. Practical implications – This paper provides useful information for managing online businesses, especially in developing key responses to consumers’ needs and in building critical capabilities to enhance competitive position in the online marketplace. Originality/value – This is one of the few studies on online repurchase intentions in Malaysia that uses data from Malaysian consumers as well as an extended IS model. The extension of the well-established TAM model by integrating additional variables provides researchers with a fuller model, and more theoretical options in developing frameworks, which are relevant to the specific context of the study – Malaysia. Keywords Electronic commerce, Consumer behaviour, Internet marketing, Malaysia Paper type Research paper Asia Pacific Journal of Marketing and Logistics Vol. 23 No. 2, 2011 pp. 200-221 q Emerald Group Publishing Limited 1355-5855 DOI 10.1108/13555851111120498 Introduction The emergence of the internet has created opportunities for firms to stay competitive by providing customers with a convenient, faster and cheaper way to make purchases. Purchasing via the internet is one of the most rapidly growing forms of shopping (Grunert and Ramus, 2005). In principle, the internet can be used to facilitate purchase transactions among all kinds of actors: among consumers, among businesses, between businesses and consumers (Grunert and Ramus, 2005). Moreover, being a global medium, the internet removes the many barriers to communication with consumers and employees created by geography, time zones and location, enabling a “frictionless” business environment (Yu, 2006). Yu (2006) pointed out that it helps to simplify business operations, because it allows companies to handle transactions electronically, thereby reducing their dependence on agents and distributors. This process of disintermediation enables the organization to deal directly with customers, eliminate or reduce middleman/agent’s cost and ultimately reduce the final cost paid by customers. It also permits the organization to improve feedback system and customer services by monitoring visits to their web site (Yu, 2006). Firms have realised that it is easier and less expensive to venture into global market or internationalize their activities via the internet. So, having an online store is no longer an option for businesses, it is rather a necessity in this new digital economy, especially for firms that intend to expand regionally. As in the traditional physical stores, a critical measure of success factor for online stores is customers’ repurchase behaviour. While new or first time customers are important to the firm, they are more expensive to serve than existing or loyal customers are (Rosenberg and Czepiel, 1983). Thus, it is important to determine the key drivers of online repurchase behaviour of Malaysia’s internet shoppers. Development of online shopping Electronic retailing over the internet or online shopping first started in 1994 (Chua et al., 2006). This new concept of retailing has captured the interest of many retailers and merchants because of the recognition that online shopping will is considered as an alternative channel alongside traditional offline retail channels such as physical retail stores (Chua et al., 2006). The world wide web (WWW) has enabled numerous firms to transform the challenges of the past into the opportunities of the future, not merely in the context of marketing but more importantly as an efficient medium to nurture customer relationships (Kim et al., 2009). Merchants tend to establish online storefronts as an online retailing method when the product brand names and reputations are well established and widely known among consumers (Chua et al., 2006). A good example is The Dell Online Store that sells personal computers (The Economist, 1997) to consumers everywhere. Owing to cultural, economic, societal and political factors, e-commerce development will not be identical across countries (Yu, 2006). Internet retailing is one of the fastest growing sectors in the UK, and is having significant effects on traditional retail provision (Gunawan et al., 2008). According to Interactive Media Retail Group, internet sales have continued to rise from £14.5 billion in 2004 to around £26 billion, in 2006, which represents 10 per cent of total retail sales in the UK (Gunawan et al., 2008). The actual number of internet shoppers has also grown; in 2006, approximately 26 million, over half of UK adults, bought goods via the internet (Gunawan et al., 2008). In the case of China, the development of e-commerce faces several difficulties (Yu, 2006). Internet penetration among households in China lags far behind developed countries because the access price is out of reach for many. The cost of access is much higher than it is in the USA. A report by the China Internet Information Center (2004) shows that the internet reached only about 7 per cent of the population in the middle of 2004. A study by International Data Corporation Asia-Pacific, indicates that the future forecast for online shopping in Malaysia looks bright and promising (Chua et al., 2006). Online repurchase intentions 201 APJML 23,2 202 Despite the statistics and success stories of many online merchants elsewhere, many local firms, especially the smaller companies are apprehensive about online business. Local companies appear to be lagging and tend to be afraid to venture into online retailing. This is plausibly because internet commerce is still relatively new and there are no hard and fast rules to follow, with no tried and tested business model to imitate (Chua et al., 2006). It is important for Malaysian firms to have a good understanding of the marketplace for their products and their target customers before engaging in online retailing (Chua et al., 2006). With a good understanding of their target customers, online retailers and entrepreneurs may be able to develop more effective and targeted online retail operations that meet the requirements and expectations of their online shopping customers (Chua et al., 2006). Table I shows the total population of Malaysia and total number of internet users from 2005 to 2008. The figure shows 47 per cent in year 2005, 50 per cent in year 2006, 53 per cent in year 2007 and 54 per cent in year 2008. The increasing rate of internet diffusion indicates a growing opportunity for online businesses and for conducting commercial transactions electronically. The internet generally helps to overcome the challenges posed by distance and/or geographical boundaries to trade. As a result, firms can target more customers with the help of the internet which has dramatically reduced the constraints posed by distance between marketers and markets. In Malaysia, however, despite the phenomenal growth in online retailing, a clear understanding of the facilitators of online purchase intention of customers is still lacking due largely to little research done within the Malaysia context. It is important for researchers and practitioners especially those who run/manage online businesses to be aware of the factors that encourage customers to repurchase from an online store. Therefore, this paper aims to examine the key determinants of online repurchase behaviour of Malaysian consumers. The expanded technology acceptance model (TAM) was adopted as the underlying model and integrates perceived value, firm reputation, privacy, trust, reliability and functionality in juxtaposition with the two most important TAM constructs – perceived usefulness and perceived ease of use. These eight determinants were measured and examined to understand their influences on consumers’ online repurchase intentions in Malaysia. Conceptual framework and hypothesis development Figure 1 shows the research framework for this paper and illustrates eight independent variables namely perceived value, perceived ease of use, perceived usefulness, firm reputation, privacy, trust, reliability and functionality. We generated eight hypotheses based on this framework to test the influence of each independent variable on online repurchase intention. The TAM developed by Davis (1989) underpins the development of this framework. The extended TAM model which integrates eight constructs altogether Table I. Total population and total number of internet users in Malaysia from year 2005 to 2008 Total population Total no. of internet user Year 2005 Year 2006 Year 2007 Year 2008 26,127,700 12,465,300 26,640,200 13,474,800 27,173,600 14,792,700 27,728,700 15,074,000 Sources: Total population – Department of Statistics, Malaysia; total number of internet user – Worldbank, World Development Indicators Online repurchase intentions Perceived value Perceived ease of use Perceived usefulness Firm’s reputation Online repurchase intentions 203 Privacy Trust Reliability Functionality was adopted in this study to help understand the role of user process and outcome orientations, firm reputation and customer confidence, as well as customer value in online repurchase decisions. The next section discusses the hypotheses development. Customers repurchase behaviour or intention is beneficial to the online business. In some studies, repurchase intentions have been closely linked to customer loyalty (Jiang and Rosenbllom, 2005). Both academics and practitioners recognize the importance of loyal customers. They usually spend more, buy more frequently, have more motivation to search for information, are more resistant to competitors’ promotions, and are more likely to spread positive word of mouth (Jiang and Rosenbllom, 2005). Jiang and Rosenbllom (2005) found, for example, that increasing customer retention rates by 5 per cent, increased profits by 25-95 per cent. They also argue that customer loyalty is even more important in online channels, because acquiring customers on the internet can be very expensive. In this study, we argue for the facilitating role of perceived value, perceived ease of use, perceived usefulness, reputation, privacy, trust, reliability and functionality in repurchase intentions of online customers. Perceived value Perceived value is the essential result of marketing activities and is a first-order element in relationship marketing (Moliner et al., 2007). Research indicates that perceived value has a direct and encounter-specific relationship with satisfaction (Hume, 2008). Thus, consumers may cognitively integrate their perceptions of what they get (benefits) and what they had to give up (sacrifices) in order to receive a certain service (Ha and Janda, 2008). In addition, Hume (2008) also suggests that perceived value is the most important indicator of repurchase intention. If a purchase offered a high level of value, this would improve the customer’s level of return and repurchase in future. In the context of retailing, Guenzi et al. (2009) found that merchandise value perceptions mediate the impact of store environmental cues and store choice criteria (e.g. merchandise quality) on store patronage intentions. Similarly, Guenzi et al. (2009) found evidence that perceived value affects loyalty intentions. Based on the preceding discussion, we develop Hypothesis 1: H1. Perceived value will have a positive influence on customer online repurchase intentions. Figure 1. Conceptual framework of key determinants of online repurchase intentions in Malaysia APJML 23,2 204 Perceived ease of use and perceived usefulness are key constructs in the TAM (Davis, 1989) and have been researched in a number of contexts and among different users. In Malaysia, Ndubisi et al. (2005) examined the role of the two constructs in information systems (ISs) adoption by entrepreneurs and found to be instrumental. Perceived ease of use in the context of this research refers to the extent to which a consumer believes that online shopping will be free of effort (Chiu et al., 2009). The WWW is a medium that allows users arbitrary connections in an open environment; within this environment, users have computer skills ranging from novice to expert (Pearson et al., 2007). With all the available web sites and the diverse set of user skills, what motivates users to choose one site over another may lie in their ease of use perceptions. If a user finds a site difficult to use, cannot find the desired product on a business-to-consumer (B2C) web site, or is not clear on what a site offers, the user will typically leave that site (Pearson et al., 2007). Web site design quality is crucial for online stores (Lee and Lin, 2005) and has strong impact on user perception of ease of use. Web site design describes the appeal that user interface design presents to customers (Lee and Lin, 2005). A recent empirical study found that web site design factors are strong predictors of customer quality judgments, satisfaction and loyalty for internet retailers (Lee and Lin, 2005). According to Kim et al. (2009), online features that are customer centered have an impact on online shoppers’ positive attitude toward the internet. Kim et al. (2007, 2009) found that retail web sites with more customer-centered web attributes had higher annual web sales and higher market shares than those retail web sites with fewer customer-centered web attributes. In addition, Kim et al. (2007, 2009) indicate that the buying environment characteristics of retail web sites impact the financial performance of e-retailers, and many e-retailers under-perform in offering web service attributes that can accommodate individual customers’ needs and facilitate online shopping. Thus, when consumers perceive web site to be ease to use, it would affect their intentions to repurchase in future. Hence, the following hypothesis: H2. Perceived ease of use will have a positive influence on customer online repurchase intentions. Perceived usefulness is defined as the extent to which a consumer believes that online shopping will enhance his or her transaction performance (Chiu et al., 2009). According to Chiu et al. (2009), an individual is more likely to undertake continued usage when such usage is perceived to be useful. Customers who have accomplished the shopping task of product acquisition in an efficient manner will be more likely to exhibit stronger repurchase intentions (Chiu et al., 2009). Prior research shows that perceived usefulness has a significant effect on customer loyalty intention (Chiu et al., 2009). Perceived usefulness has also shown to be an important determinant of ISs adoption in general (Ndubisi et al., 2005; Davis, 1989). Hence, the following hypothesis: H3. Perceived usefulness will have a positive influence on customer online repurchase intentions. Firm reputation According to Hess (2008), firm reputation can be defined as customers’ perceptions on how well a firm takes care of customers and is genuinely concerned about their welfare. In addition, Hess (2008) revealed that excellent reputations provide firms with a “buffering effect”, insulating them from some of the negative consequences of failures. He argued that firm reputation moderated the relationship between failure severity and satisfaction, lowered attributions of controllability and stability, and led to higher repurchase intentions following service failures. Attributions of controllability and stability were related only to repurchase intentions; satisfaction did not fully mediate these relationships. Given these previous research findings, it is likely that a good firm reputation will also lead to greater online repurchase intentions. This analysis leads to the next hypothesis: H4. Firm reputation will have a positive influence on customer online repurchase intentions. Privacy Privacy refers to the degree to which the online shopping web site is safe and protects the customers’ information (Chiu et al., 2009). New technologies’ growing capacity for information processing, plus its complexity, have made privacy an increasingly important issue (Flavián and Guinalı́u, 2006). Consequently, consumer distrust is increasing regarding how their personal data are being gathered and processed (Flavián and Guinalı́u, 2006). In Malaysia, many buyers appear to be afraid to purchase products and services online or to provide personal information online due to fears of lack of privacy and possibility that online retailers will misuse their personal information. For example, it has been shown that consumers will hesitate to shop online if they do not feel assured that their credit card information is secured and protected from potential hackers (Collier and Bienstock, 2006). Prior research on online shopping context indicates that consumers’ perceptions of privacy have a significant and positive effect on their trust in the online vendor (Chiu et al., 2009). The quantitative importance of this issue is shown by Udo (2001), who points out that the protection of privacy is the greatest concern of internet purchasers (Flavián and Guinalı́u, 2006). As such, if customers are not sure of protection of privacy, they will be unwilling to repurchase online, but if privacy is assured, they will be more willing to repurchase online as shown in Hypothesis 5: H5. Privacy will have a positive influence on customer online repurchase intentions. Trust Customer’s trust plays a fundamental role in maintaining long-term relationships with the retailer. According to Chiu et al. (2009), 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 opportunistically against the trustor, even given the opportunity (Chiu et al., 2009; Ndubisi, 2011). Competence is the belief in the trustee’s ability to fulfill its obligations as expected by the trustor (Chiu et al., 2009). Integrity is the belief that the trustee will be honest and will honour its commitments (Chiu et al., 2009; Ndubisi, 2011). Customer’s trust implies that the good intentions of the firm are not questioned by the consumer, that the promises made do not generate uncertainties in the purchaser, and that the communication between the parties is honest. Customer’s uncertainty can imply the potential for service failure and negative outcomes therefore, trust becomes vital to long-lasting relationships (Eisingerich and Bell, 2007). Lack of trust reduces the chances of buyers to engage in online shopping because they are unwilling to deal with a vendor whom they do not trust. Online repurchase intentions 205 APJML 23,2 Indeed, prior research indicates that trust plays a pivotal role in driving customer repurchase intentions (Chiu et al., 2009). The analysis leads to Hypothesis 6: H6. Trust will have a positive influence on customer online repurchase intentions. 206 Reliability Goode and Harris (2007) define perceived online reliability as the extent to which the site consistently responds and functions as expected (without broken links, broken pages or dead end links). According to Kim et al. (2009), service reliability is one of the major e-service quality dimensions leading to overall customer satisfaction. In another study, Ndubisi (2011) showed that service reliability leads to customer orientation and satisfaction, and indirectly to loyalty which is mediated by satisfaction. It has been argued that to attract new customers and to retain existing customers, the perceived reliability of web sites is of pivotal importance (Goode and Harris, 2007). Goode and Harris (2007) found that where existing customers find evidence of unreliable service or online performance (for example, broken links, failed java script, scripting errors and missing graphics), such shoppers will often leave the site, frustrated with the online provision. Thus, commentators argue that where consumers’ perceive a site to be reliable, actual and intended loyalty increases (Goode and Harris, 2007). Hence, Hypothesis 7 states as follows: H7. Reliability will have a positive influence on customer online repurchase intentions. Functionality Functionality deals with the extent to which a web site provides sufficient information about the products/services being promoted (Law and Bai, 2008). In this study, functionality of the web site can be defined as providing a time efficient and effective delivery mechanism for online information (Yates, 2005). A web site is perhaps the only way an online store communicates with its customers (Chang and Chen, 2008). The greatest difficulty that consumers may face when using an organization’s web site is actually locating the information they require or the transaction they wish to undertake. The more difficult it is to do this, the less chance of consumers making a purchase or considering future purchases via the web site. Thus, web site quality serves as the store atmosphere and accordingly is a trustworthiness cue, especially at the beginning of transactions (Chang and Chen, 2008). Therefore, customer will have more confidence to repurchase from the online store if its web site is very functional (Table II). Hence, the following hypothesis: H8. Functionality will have a positive influence on customer online repurchase intentions. Methodology The information and data for this research project were gathered from various sources: primary and secondary data sources. The primary data are derived from survey questionnaire. Survey questionnaires were used to obtain responses from participants. We employed snowballing sampling method to select the participants for this research. This was to ensure that the participants have used the internet to purchase a product or service. Since, we were interested in participants’ willingness and ability to repurchase products/services online, it was considered reasonable to collect data from Variable names Description Sources Perceived value The essential result of marketing activities and is a first-order element in relationship marketing Perceived ease The extent to which a consumer believes that online shopping will be free of effort of use The extent to which a consumer believes that Perceived online shopping will enhance his or her usefulness transaction performance Customers’ perceptions of how well a firm Firm take care of customers and are genuinely reputation concerned about their welfare Privacy The degree to which the online shopping web site is safe and protects the customers’ information Trust A set of specific beliefs dealing primarily with the benevolence, competence and integrity of another party Reliability The extent to which the site consistently responds and functions as expected (without broken links, broken pages or dead-end links) Functionality The extent to which a web site provides sufficient information about the products/ services being promoted Moliner et al. (2007) and Oh (2003) Online repurchase intentions Chiu et al. (2009) and Davis (1989) Chiu et al. (2009) and Davis (1989) 207 Brown et al. (2005) and Hess (2008) Román (2007) and Chiu et al. (2009) Pavlou and Fygenson (2006) and Chiu et al. (2009) Swaminathan et al. (1999) and Goode and Harris (2007) Chung and Law (2003) and Law and Bai (2008) those who have prior experience in buying products or services online in line with the key informant technique (Ndubisi, 2011). The key informant method was used and only customers with online shopping experience were requested to respond to the questions. Key informants are viewed as appropriate respondents if appropriate selection procedures are used (John and Reve, 1982). Thus, using guidelines on selecting key respondents from previous research (Campbell, 1955), key informants were screened and chosen on the basis of their knowledge of the research issues, their experience with online shopping, and willingness to respond. The snowball approach used in this study enabled us to achieve this objective and the wider research objective and is a sampling method widely used in internet-based research. Questionnaire design The questionnaire for this research is divided into two parts – Sections A and B. Section A of the questionnaire contains questions on the demographic profile such as respondents’ age, gender, occupation, education level and monthly income. Section B of the questionnaire solicits responses on the key constructs of the research framework namely, perceived value, perceived ease of use, perceived usefulness, firm reputation, privacy, trust, reliability and functionality. The measurement items were adapted from previous studies and revalidated for this study. Perceived value was measured with items adapted from Moliner et al. (2007) and Oh (2003). Measures of perceived usefulness and ease of use were adapted from Chiu et al. (2009) and Davis (1989). Firm’s reputation was measured with items adapted from Brown et al. (2005) and Hess (2008). Measures for privacy were adapted from Román (2007) and Chiu et al. (2009). Trust was measured with items Table II. Summary table of variables definition and sources APJML 23,2 208 adapted from Pavlou and Fygenson (2006). The measures for reliability were adapted from Swaminathan et al. (1999) and Goode and Harris (2007) whereas functionality items were adapted from Chung and Law (2003) and Law and Bai (2008). Appendix 2 shows the full list of the items. The measurement for the conceptual variables was based on a seven-point Likert scale with scale anchors from “1” – strongly disagree to “7” – strongly agree. Previous researchers have also used similar measurement in their studies. Lin and Sun (2009) and Wang et al. (2009) are some of the most recent studies which have found the seven-point Likert scales to be effective measures. Content validity The issue of content validity was tackled from the beginning of the study during the development of measurement items and instrument as recommended by Sonquist and Dunkelburg (1997). In the literature review, measurement scales were identified and modified to suit the research purpose of the study and the local context (Gu et al., 2008). This was supplemented with interviews with a few managers. Additionally, the questionnaire was pilot tested in the field and modifications were made. Using pilot survey to measure the face validity and reliability of a survey questionnaire is best practice and common among researchers (Babbie, 1990; Sekaran, 2003; Law and Bai, 2008; Ndubisi, 2011). Pilot study was conducted using a group of 30 consumers, who have had experiences in purchasing products and services through the internet. The suggestions, comments and critiques from these participants were evaluated and incorporated into the survey before generating the final survey questionnaire. Finally, the revised and complete questionnaires were sent to participants, who have purchased products or services online, at least, once, for completion. Data analysis We used inferential statistics to make deductions based on the results and the significance. Descriptive analytical tools such as mean and standard deviation were used to summarize the respondents’ feedback. For reliability and validity measurement of the variables, factor analysis and reliability tests were conducted before subjecting the data to inferential analysis. The eight variables were tested for their relationship with online repurchase intentions using correlations and regression analysis. SPSS was used for the analysis. Results and findings A total of 124 completed questionnares were retruned, and 22 of this were invalid due to incomplete reseponses, which results to 102 usable responses. Table III illustrates the demographic profile of the 102 respondents who participated in this research. It is shown that female resondents have a higher percentage (55.9 per cent) compared to male respondents. There are more respondents (60.8 per cent) who are single than respondents who are married. Also, majority of the respondents are from the age group of 20-30 years (48.0 per cent). In terms of ethnicity, most of the respondents are Chinese (47.8 per cent). Majority of the respondents have bachelor degree, earning monthtly income ranging from RM2,000 to RM4,000. Besides, that, 67.6 per cent of total respodents have a habit of purchasing items or services online once a year. In addition, majority of the respondents (27.5 per cent) have purchased materials online two to three times in the past five years. About 36 per cent of the respondents spend more than Items Gender Categories Male Female Marital status Married Single Age ,20 20-30 31-40 41-50 .50 Race Malay Chinese India Education level O level A level Diploma/higher diploma Degree Post graduate Monthly income , RM2,000 RM2,000-RM4,000 RM4,001-RM6,000 RM6,001-RM8,000 RM8,001-RM10,000 . RM10,000 Job status Employed Self-employed Retiree Homemaker Student Frequency of online purchases? Once a week Once a month Once a year How many times purchased materials ,2 times online in the past five years 2-3 times 4-6 times 7-9 times .10 times Time spent on a web site when purchasing ,5 minutes a product/service (minutes) 5-15 minutes 16-30 minutes 31-45 minutes .45 minutes Number of online shops patronized ,2 shops 2-3 shops 4-5 shops 6-7 shops 8-9 shops 10 and more shops Frequency % Cumulative (%) 45 57 40 62 8 49 27 10 8 25 59 18 8 8 44.1 55.9 39.2 60.8 7.8 48 26.5 9.8 7.8 24.5 57.8 17.6 7.8 7.8 44.1 100 39.2 100 7.8 55.9 82.4 92.2 100 24.5 82.4 100 7.8 15.7 16 43 27 19 44 21 8 7 3 72 11 6 4 9 5 28 69 20 28 25 7 22 1 7 28 29 37 25 40 21 6 3 7 15.7 42.2 26.5 18.6 43.1 20.6 7.8 6.9 2.9 70.6 10.8 5.9 3.9 8.8 4.9 27.5 67.6 19.6 27.5 24.5 6.9 21.6 1 6.9 27.5 28.4 36.3 24.5 39.2 20.6 5.9 2.9 6.9 31.4 73.5 100 18.6 61.8 82.4 90.2 97.1 100 70.6 81.4 87.3 91.2 100 4.9 32.4 100 19.6 47.1 71.6 78.4 100 1 7.8 35.3 63.7 100 24.5 63.7 84.3 90.2 93.1 100 (continued) Online repurchase intentions 209 Table III. Demographic profile APJML 23,2 210 Items Categories Online items purchased for? Oneself Friends Family members Excellent Good Average Bad Online repurchase experience Table III. Frequency % Cumulative (%) 66 17 19 31 50 20 1 64.7 16.7 18.6 30.4 49 19.6 1 64.7 81.4 100 30.4 79.4 99 100 45 minutes on a web site when they wish to purchase product/service online and most of them have experience with two to three online shops to purchase product/service. Most of the respondents (64.7 per cent) make online purchases for themselves. Lastly, majority of respondents (49.0 per cent) had a good experience during their online repurchase activities. Table IV presents the mean values, standard deviations and the number of items for each variable. For the independent variables, trust yielded the highest mean (5.67), followed by privacy (5.64), functionality (5.60), firm reputation (5.54), perceived usefulness (5.52), perceived value (5.49), reliability (5.47) and lastly perceived ease of use (5.46). Since all variables yielded mean value more than 5, one can conclude that the respondents perceptions on these variables are mostly favourable. Table IV also shows the Cronbach’s alpha values for the independent and dependent variables in this research. The result indicates that Cronbach’s alpha value range from 0.711 to 0.830. According to Nunnally (1978), the value for Cronbach’s alpha of 0.7 or higher is considered acceptable. Thus, the data on these variables are reliable and consistent with research standards. Appendix 1 shows the rotated components matrix indicating that the factor loadings of the variables meet the require treshhold of not less than 0.5 points. This means that the results met the convergent and discriminant validities. Normal P-P plot of regression standardized residual provide a visual examination of the assumptions of normality between the predicted dependent variable scores and the errors of prediction. The primary benefit is that the assumptions can be viewed and analysed in one glance; therefore, any violation can be determined quickly and easily. A 458 diagonal line represents the normal probability line. The dots represent the Table IV. Mean and reliability of variables ID Variable name PV PE PU FR PR TR RE FU ORI Perceived value Perceived ease of use Perceived usefulness Firm’s reputation Privacy Trust Reliability Functionality Online repurchase intentions Mean (n ¼ 102) SD Number of items Cronbach’s alpha 5.49 5.46 5.52 5.54 5.64 5.67 5.47 5.60 5.61 0.993 0.905 0.963 0.924 0.926 0.903 1.009 0.950 0.893 9 7 7 8 7 7 7 8 8 0.781 0.711 0.741 0.796 0.830 0.809 0.781 0.748 0.817 actual residual, if the residuals are normally distributed the values should fall on the diagonal line of identity. Figure 2 shows the normal P-P plot of regression standardized residual of this research. The data collected could be considered as normally distributed for a sample n ¼ 102 derived from the normal population. Table V reveals the correlation matrix of the conceptual variables. A two-tail test at 0.05 significance level indicates that there are positive relationships among dependent variable and the independent variables. From Table VI, R ¼ 0.954 and R 2-value ¼ 0.909. This means that 90.9 per cent of the variation in Y can be explained by all eight predictors (or accounted for by) the variation in X. The results in Table VII show the eight independent variables predict 91 per cent of the variation in online repurchase intention. This is a considerable amount of variance. The results also show the detials of the estimated coefficients, where b (constant) is 20.559, bPV is 0.130, bPE is 0.125, bPU is 0.165, bFR is 0.141, bPR is 0.147, bTR is 0.169, bRE is 0.101 and bFU is 0.131. The result shows that all eight variables are significant at 0.05 significance level (,0.05). This indicates that there is linear relationship between the dependent variable (online repurchase intentions) and the predictor variables (perceived value, perceived ease of use, perceived usefulness, firm reputation, privacy, trust, reliability and functionality). Online repurchase intentions 211 Dependent variable: online repurchase intentions Expected cum prob 1.0 0.8 0.6 0.4 0.2 Figure 2. Normal P-P plot of regression standardized residual 0.0 0.0 PV PE PU FR PR TR RE FU ORI 0.2 0.4 0.6 0.8 Observed cum prob 1.0 PV PE PU FR PR TR RE FU ORI 1.000 0.586 * 0.680 * 0.665 * 0.543 * 0.601 * 0.607 * 0.564 * 0.742 * 1.000 0.660 * 0.764 * 0.545 * 0.703 * 0.699 * 0.634 * 0.784 * 1.000 0.769 * 0.620 * 0.735 * 0.734 * 0.696 * 0.844 * 1.000 0.583 * 0.798 * 0.746 * 0.726 * 0.858 * 1.000 0.543 * 0.565 * 0.616 * 0.721 * 1.000 0.729 * 0.720 * 0.835 * 1.000 0.702 * 0.812 * 1.000 0.801 * 1.000 Note: Correlation is significant at the *0.05 level Table V. Pearson correlation coefficient matrix APJML 23,2 212 Discussion and conclusion Existing research has dealt extensively with the factors affecting customers’ offline repurchase behaviour. Relatively, the amount of research that have considered online repurchase behaviour is small, as such this paper adds value by contributing to the relatively sparse literature in the area by integrating different models from past studies. The results from this study indicate that the all the factors identified in the study infleunce the intention to repurchase online. The outcome of this research not only corroborates some of the findings of prior studies, but is also an advance over many as the integrated model explains a greater amount of variance in repurchase intention than any previous model. As such, the integrated model is more helpful in understanding customers online repurchase behaiour. Contextually, this document represents some form of contribution to the literature on the subject in Malaysia. While there has been a recent increase in research on Malaysia, the quantum and quality is still a far cry relative to the amount of work done in many of its Asian counterparts. Besides its contribution to research in Malaysia, practitioners can avail the knowledge and information unveiled in this study, especially in strategy decision. Clearly, as the coefficients suggest, some factors emerged with stronger impact compared to others, online retailers are therefore able to make informed decision on which factors to pay greater emphasis. Online businesses could use the findings to enhance their service offerings by deploying more information and knowledge management systems with stronger capabilities. By extension, the study is also relevant to other Asian online marketers. Albeit the present study’s empirical sample was generated from Malaysia, a largely Muslim (over 60 per cent), the country is “truly Asian” (Malays 50 per cent, Chinese 24 per cent, Indigenous 11 per cent and Indian 11 per cent (US Central Intelligence Agency, 2008). Model 1 Table VI. Multiple regression analysis (R and R 2) R R2 Adjusted R 2 SE of the estimate Durbin-Watson 0.954a 0.909 0.902 0.18619 2.004 Notes: Predictors: (constant), PV, PE, PU, FR, PR, RE, FU; dependent variable – ORI; let Y – online repurchase intentions (ORI); X – perceived value (PV), perceived ease of use (PE), perceived usefulness (PU), firm reputation (FR), privacy (PR), trust (TR), reliability (RE) and functionality (FU) Unstandardized coefficients b SE Model 1 Table VII. Regression coefficients Constant PV PE PU FR PR TR RE FU 20.559 0.130 0.125 0.165 0.141 0.147 0.169 0.101 0.131 0.213 0.045 0.056 0.057 0.066 0.039 0.056 0.049 0.054 t Sig. 22.619 2.914 2.234 2.906 2.153 3.775 3.022 2.068 2.414 0.010 0.004 0.028 0.005 0.034 0.000 0.003 0.041 0.018 Collinearity statistics Tolerance VIF 0.470 0.363 0.291 0.226 0.527 0.288 0.325 0.355 2.127 2.754 3.439 4.422 1.899 3.476 3.077 2.820 This suggests that the outcome may be relevant to a number of Asian consumers and marketers. Malaysia is commonly dubbed “truly Asian” because it is a potpourri of Asian cultures, and a representative Asian values, as such the applicability of the findings of this study to other Asian economies is high. Online retailers should strive to build good reputation and trust which will enable customers to continue to buy from them. Privacy is another important driver. Businesses should continue to focus on improving their goodwill by maintaining good business ethics, which will help in building trust and confidence among customers. Besides, ensuring privacy of information provided by customers, building trust and good reputation, added value and usefulness of this mode should be enhanced and communicated to customers. The greater the value and/or usefulness perceptions of customers, the greater their likelihood of returning, therefore, online retailers should clearly demonstrate these benefits in their benefits proposal to the public. Outcomes are not the only important elements. While outcome orientation of the respondents are clearly demonstrated in this study, the respondents are also process oriented. It is crucial for the respective online firms in Malaysia to recognise the importance of managing consumer expectations and be able to provide functional, reliable and easy-to-use systems that enable enjoyable online purchase experiences. As the study shows, customers will be happy to repurchase products and services from an online store that offers an excellent functional store front that is free of hickups and other constraints that could frustrate potential customers. Online businesses must understand what a great online shopping experience is for Malaysians and Asians by extension, and then provide them. Unlike most past Western-based studies where outcome and process orientations of customers were insturmantal in their online repurchase behaviours, our Malaysian data show that ethical and relational variables namely privacy, reputation and trust are very important factors to pay close attention. To achieve business success in the marketplace, online businesses in Malaysia would need to invest resources and time to understand their customers and their buying motives. Based on this research, the online firms should capitalise on the ethical, outcome, and process orientations of customers, and through that develop applicable marketing strategies to retain their customers, which would enhance repurchase activities in the future. A good customer relationship management will enable a firm to provide excellent service quality to satisfy customers’ needs. This can enhance customer satisfaction, and help to reduce customers swtiching behaviours. It is therefore possible for online firms to improve their competitiveness by effectively managing and delivering services to customers that guarranttee highest level of ethical standards, efficient processes and beneficial outcomes. Relevant government agencies could find the outcomes of this paper useful, particularly with respect to developing internet infrastructure in Malaysia. There is the need to enhance competition among internet service providers in Malaysia. With greater competition, customers would have greater options and better services at competitive prices. It is necessary at this point to mention some of the weaknesses of this paper and to draw some future research directions. First, we consider the number of usable responses in this research small. Whereas, the research objectives were fully met, future research should strive for higher reponse rate. This will increase the representativeness of the sample and consequently the generaliszability of the findings. In addition, future research may also consider the responses from businesses. This will enable a stronger and a more balanced perspective on the research issues. Online repurchase intentions 213 APJML 23,2 214 References Babbie, E. (1990), Survey Research Methods, 2nd ed., Wadsworth, Belmont, CA. Brown, T., Barry, T., Dacin, P. and Gunst, R. (2005), “Spreading the word: investigating antecedents of consumers’ positive word-of-mouth intentions and behaviors in a retailing context”, Journal of the Academy of Marketing Science, Vol. 33 No. 2, pp. 123-38. Campbell, D. (1955), “The informant in quantitative research”, American Journal of Sociological, Vol. 60, January, pp. 110-33. Chang, H.H. and Chen, S.W. (2008), “The impact of online store environment cues on purchase intention, trust and perceived risk as a mediator”, Online Information Review, Vol. 32 No. 6, pp. 818-41. China Internet Information Center (2004), 14th Statistical Survey on the Internet Development in China, CNNIC, Beijing. Chiu, C.M., Chang, C.C., Cheng, H.L. and Fang, Y.H. (2009), “Determinants of customer repurchase intention in online shopping”, Online Information Review, Vol. 33 No. 4, pp. 761-84. Chua, A.P.H., Khatibi, A. and Ismail, H.B. (2006), “E-Commerce: a study on online shopping in Malaysia”, J. Soc. Sci., Vol. 13 No. 3, pp. 231-42. Chung, T. and Law, R. (2003), “Developing a performance indicator for hotel websites”, International Journal of Hospitality Management, Vol. 22 No. 1, pp. 119-25. Collier, J.E. and Bienstock, C.C. (2006), “Measuring service quality in e-retailing”, Journal of Service Research, Vol. 8 No. 3, pp. 260-75. Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13 No. 3, pp. 319-40. (The) Economist (1997), “The once and future mall”, The Economist, Vol. 1, November, pp. 76-8. Eisingerich, A.B. and Bell, S.J. (2007), “Maintaining customers relationships in high credence services”, Journal of Services Marketing, Vol. 21 No. 4, pp. 253-62. Flaviaán, C. and Guinalı́u, M. (2006), “Consumer trust, perceived security and privacy policy: three basic elements of loyalty to a web site”, Industrial Management & Data Systems, Vol. 106 No. 5, pp. 601-20. Goode, M.M.H. and Harris, L.C. (2007), “Online behavioural intentions: an empirical investigation of antecedents and moderators”, European Journal of Marketing, Vol. 41 Nos 5/6, pp. 512-36. Grunert, K.G. and Ramus, K. (2005), “Consumers’ willingness to buy food through the internet”, British Food Journal, Vol. 107 No. 6, pp. 381-403. Guenzi, P., Johnson, M.D. and Castaldo, S. (2009), “A comprehensive model of customer trust in two retail stores”, Journal of Service Management, Vol. 20 No. 3, pp. 290-316. Gunawan, G., Ellis-Chadwick, F. and King, M. (2008), “An empirical study of the uptake of performance measurement by internet retailers”, Internet Research, Vol. 18 No. 4, pp. 361-81. Gu, F.F., Hung, K. and Tse, D.K. (2008), “When does Guanxi matter? Issues of capitalization and its dark sides”, Journal of Marketing, Vol. 72, July, pp. 12-28. Ha, H.Y. and Janda, S. (2008), “An empirical test of a proposed customer satisfaction model in e-services”, Journal of Services Marketing, Vol. 22 No. 5, pp. 399-408. Hess, R.L. (2008), “The impact of firm reputation and failure severity on customers’ responses to service failures”, Journal of Services Marketing, Vol. 22 No. 5, pp. 385-98. Hume, M. (2008), “Understanding core and peripheral service quality in customer repurchase of the performing arts”, Managing Service Quality, Vol. 18 No. 4, pp. 349-69. Jiang, P. and Rosenbllom, B. (2005), “Customer intention to return online: price perception, attribute-level performance, and satisfaction unfolding over time”, European Journal of Marketing, Vol. 39 Nos 1/2, pp. 150-74. John, G. and Reve, T. (1982), “The reliability and validity of key informant data from dyadic relationships in marketing channels”, Journal of Marketing Research, Vol. 19, November, pp. 517-24. Kim, J.H., Kim, M. and Kandampully, J. (2007), “The impact of buying environment characteristics of retail web sites”, Service Industries Journal, Vol. 27 No. 7, pp. 865-80. Kim, J.H., Kim, M. and Kandampully, J. (2009), “Buying environment characteristics in the context of e-service”, European Journal of Marketing, Vol. 43 Nos 9/10, pp. 1188-204. Law, R. and Bai, B. (2008), “How do the preferences of online buyers and browsers differ on the design and content of travel websites?”, International Journal of Contemporary Hospitality Management, Vol. 20 No. 4, pp. 388-400. Lee, G.G. and Lin, H.F. (2005), “Customer perceptions of e-service quality in online shopping”, International Journal of Retail & Distribution Management, Vol. 33 No. 2, pp. 161-76. Lin, G.T.R. and Sun, C.C. (2009), “Factors influencing satisfaction and loyalty in online shopping: an integrated model”, Online Information Review, Vol. 33 No. 3, pp. 458-75. Moliner, M.A., Sánchez, J., Rodrı́guez, R.M. and Callarisa, L. (2007), “Perceived relationship quality and post-purchase perceived value: an integrative framework”, European Journal of Marketing, Vol. 41 Nos 11/12, pp. 1392-422. Ndubisi, N.O. (2011), “Conflict handling, trust and commitment in outsourcing relationship: a Chinese and Indian study”, Industrial Marketing Management, Vol. 40 No. 1, pp. 109-17. Ndubisi, N.O. (2011), “Mindfulness, reliability, pre-emptive conflict handling, customer orientation and outcomes in Malaysia’s healthcare sector”, Journal of Business Research (in press). Ndubisi, N.O., Gupta, O.K. and Ndubisi, G.C. (2005), “The Moguls’ model of computing: integrating the moderating impact of users’ persona into the technology acceptance model”, Journal of Global Information Technology Management, Vol. 8 No. 1, pp. 27-47. Nunnally, J.C. (1978), Psychometric Theory, 2nd ed., McGraw-Hill, New York, NY. Oh, H. (2003), “Price fairness and its asymmetric effects on overall price, quality, and value judgments: the case of a upscale hotel”, Tourism Management, Vol. 24, pp. 241-9. Pavlou, P.A. and Fygenson, M. (2006), “Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior”, MIS Quarterly, Vol. 30 No. 1, pp. 115-43. Pearson, J.M., Pearson, A. and Green, D. (2007), “Determining the importance of key criteria in web usability”, Management Research News, Vol. 30 No. 11, pp. 816-28. Román, S. (2007), “The ethics of online retailing: a scale development and validation from the consumers’ perspective”, Journal of Business Ethics, Vol. 72 No. 2, pp. 131-48. Rosenberg, L. and Czepiel, J. (1983), “A marketing approach for consumer retention”, Journal of Consumer Marketing, Vol. 1 No. 1, pp. 45-51. Sekaran, U. (2003), Research Methods for Business: A Skill Building Approach, 4th ed., Willey, Hoboken, NJ. Sonquist, J.A. and Dunkelburg, W.C. (1997), Survey and Opinion Research: Procedures for Processing and Analysis, Prentice-Hall, Englewood Cliffs, NJ. Online repurchase intentions 215 APJML 23,2 216 Swaminathan, V., Lepkowska-White, E. and Rao, B.P. (1999), “Browsers or buyers in cyberspace? An investigation of factors influencing electronic exchange”, Journal of Computer Mediated Communication, Vol. 5 No. 2, pp. 1-21. Udo, G. (2001), “Privacy and security concerns as major barriers for e-commerce: a survey study”, Information Management & Computer Security, Vol. 9 No. 4, pp. 165-74. US Central Intelligence Agency (2008), The World Factbook, available at: www.cia.gov/cia/ publications/factbook/index.html Wang, C.C., Chen, C.A. and Jiang, J.C. (2009), “The impact of knowledge and trust on e-consumers’ online shopping activities: an empirical study”, Journal of Computers, Vol. 4 No. 1, pp. 11-18. Yates, R. (2005), “Web site accessibility and usability: towards more functional sites for all”, Campus-Wide Information Systems, Vol. 22 No. 4, pp. 180-8. Yu, J. (2006), “Marketing to Chinese consumers on the internet”, Marketing Intelligence & Planning, Vol. 24 No. 4, pp. 380-92. Corresponding author Uchenna Cyril Eze can be contacted at: uc_chinwe@hotmail.com To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints PV1 PV2 PV3 PV4 PV5 PV6 PV7 PV8 PV9 PE1 PE2 PE3 PE4 PE5 PE6 PE7 PU1 PU2 PU3 PU4 PU5 PU6 PU7 FR1 FR2 FR3 FR4 FR5 FR6 FR7 FR8 2 3 4 5 6 7 8 0.792 0.750 0.828 0.713 0.560 0.886 0.730 0.690 0.909 Appendix 1 Component 1 0.887 0.876 0.777 0.670 0.766 0.798 0.838 0.853 0.875 0.786 0.747 0.863 0.662 0.750 0.752 0.797 0.743 0.562 0.838 0.513 0.798 0.428 (continued) Online repurchase intentions 217 Table AI. Rotated component matrix APJML 23,2 218 Table AI. Component 1 PR1 PR2 PR3 PR4 PR5 PR6 PR7 TR1 TR2 TR3 TR4 TR5 TR6 TR7 RE1 RE2 RE3 RE4 RE5 RE6 RE7 FU1 FU2 FU3 FU4 FU5 FU6 FU7 FU8 2 3 4 5 6 7 8 0.653 0.865 0.783 0.689 0.842 0.769 0.825 0.846 0.766 0.634 0.588 0.729 0.803 0.608 0.858 0.843 0.730 0.541 0.771 0.796 0.782 0.640 0.852 0.798 0.681 0.548 0.723 0.765 0.715 Items Perceived value PV1 PV2 PV3 PV4 PV5 PV6 PV7 PV8 Perceived ease of use PV9 PE1 PE2 PE3 PE4 Perceived usefulness PE5 PE6 PE7 PU1 Source (s) – – – – I will be attracted to repurchase a product online, if I experience tangible values Moliner et al. (2007) and Oh (2003) Online shopping makes it easier for me to purchase at anytime and anywhere I will repurchase online provided the web site offers good value for money Perceive value for time used online will attract me to repurchase a product/service online – Greater value-added services provided on the web site would attract me to shop online – I will repurchase online if the online store provides a promise to refund, or an exchange policy – Online store that provides a transparent pricing policy would be an additional value to attract me to revisit – Buying products/services online will enhance my shopping effectiveness and productivity (e.g. make purchase decisions or find product information within the shortest period) – online retailers always offer the best selling price to customers – online shopping makes it easier for me to make products comparison among few Chiu et al. (2009) and Davis (1989) retailers – purchasing products and services online is easy to learn and use – online store should provide a web site that is flexible to interact with – online shopping web site provides various payment channels that make my shopping online easy – purchasing online does not require a lot of mental effort – new service of the web site should be well explained – I do not get frustrated when I shop online – I always repurchase online based on my need for the product or service Davis (1989) and Chiu et al. (2009) Appendix 2 Construct PU2 – I will repurchase online if it provides more benefit than cost to me PU3 – adequate information about the product or service from the web site is necessary for me to be attracted to shop online PU4 – I will purchase products or services online if it enhances my life style PU5 – I find online shopping more convenient compared with offline shopping PU6 – I will repurchase online when I realize it is very useful and workable (continued) Online repurchase intentions 219 Table AII. The list of items and sources Items Source (s) PU7 – I find online shopping useful to manage my time (saves time) FR1 – I will like to repurchase online, if the firm has a good image Brown et al. (2005) and Hess (2008) FR2 FR3 FR4 FR5 FR6 Privacy Trust APJML 23,2 Firm’s reputation 220 Table AII. Construct – I compare firms’ images before my repurchase decision – I will repurchase products or services, if the firm’s image meets my expectation – I will repurchase products/services online, if the firms provide a dependable web site – I will like to repurchase products or services from web sites that are popular – I will repurchase products/services online, if my friends recommend the web sites to me FR7 – I will repurchase products/services online, if the firm has partners and suppliers that have strong brand name in the market FR8 – I will repurchase online from web site that offers quality products or services PR1 – web sites that will not share my online shopping behaviour, will attract me to Román (2007) and Chiu et al. (2009) repurchase PR2 – I will review customers’ feedback or comments on privacy issue before any repurchase decision PR3 – I will read the privacy policy before any repurchase decision to ensure no amendments made without notifications PR4 – I will only repurchase from a web site that keeps my entire personal information private PR5 – keeping customers’ information confidential is an important consideration during my repurchase decision PR6 – I will repurchase products and services online, if the firm assures that my financial details will not be accessible by a third party PR7 – authorized username and password are important TR1 – a trustable web site will ensure product shown in web site is reliable Pavlou and Fygenson (2006) and Chiu et al. (2009) TR2 – an online store that appears believable will attract me to repurchase products/services more often TR3 – I will repurchase products and services from the web site, if the purchase terms and conditions are clear TR4 – I will repurchase from the online store, if the technical infrastructure of the web site is dependable (continued) Construct Reliability Functionality Items Source (s) TR5 – A web site that offers secure personal data can be trusted TR6 – transaction securities enhance the level of trust towards the web site TR7 – product attributes and specifications that are delivered as promised are persuasive to me RE1 – web sites without broken links/broken pages reflect that the web sites are Swaminathan et al. (1999) and dependable Goode and Harris (2007) RE2 – I will repurchase from same web site rather than making new purchase from other web site if the web site is genuine RE3 – I will repurchase products/services online, if the web site does not breakdown frequently RE4 – I will always evaluate the quality of the web site before any repurchase decision RE5 – I expect web sites that are capable to process large number of transactions are to be dependable RE6 – I will repurchase products/services online, if the firm maintains accurate product and service information on the web sites RE7 – well-recommended online store tend to be trustable FU1 – I will ensure that the web site functions effectively before any repurchase decision Chung and Law (2003) and Law and Bai (2008) FU2 – I will repurchase from a web site that provides related links that makes my shopping experience more fun and less frustrating FU3 – I will repurchase from web sites that is well organized FU4 – I will be attracted to repurchase from web sites that update the online shopping site continuously with latest information FU5 – I will be attracted to online shopping sites that can provide live support through the web site FU6 – I will repurchase products/services online, if it is easy to make changes even after I submit online transaction FU7 – I will be favourable to revisit the online shop, if the web site is user friendly FU8 – simple web sites with great functionality will attract me to revisit Online repurchase intentions 221 Table AII.