Perceived service quality, value, and customer satisfaction have long been regarded as among the most important research topics in services marketing literature (Cronin, Brady, & Hult, 2000). Service marketers are continually trying to develop efficient service strategies in order to deliver high quality service and satisfy customers. Internet marketing is one of the increasingly important electronic marketing tools for enhancing customer attraction, delivering services, and executing transactions (Sohn & Tadisina, 2008; Song & Zinkhan, 2008). Although the number of Internet users has grown rapidly with technological innovation (Gounaris, Dimitriadis, & Stathakopoulos, 2005), e-service marketers are still in the initial stages of designing efficient website features that will enhance customers’ perception of service quality and value in online service transactions (Collier & Bienstock, 2006). Service designers need to be committed to improving e-service quality, website interactivity, and e-service recovery issues, all with the goal of fulfilling consumers’ expectations. Delivering quality e-services by establishing customer value and satisfying customers’ needs has been shown to be an important strategy for marketers who are trying to differentiate their service offerings (Ozment & Morash, 1994). Promoting customer loyalty and retention have also been shown to be important (Imrie, Durden, & Cadogan, 2000). We inferred that in order to be successful, e-service marketers must focus on e-customer relationship management, tipping the balance of power in favor of consumers by means of interactive features. Venkatesh and Davis (2000) argue that perceived usefulness is a theoretical extension of the technology acceptance model (TAM) in terms of cognitive instrumental processes.

In this study we explored customers’ perceptions of e-service quality and its relationship with online service satisfaction when using airline service websites. We also investigated the moderating role of technology acceptance, including customer perceptions of both trust and usefulness, in terms of the key elements of the service offered and customers’ perception of service satisfaction.

Literature Review

E-Service Quality, Perceived Service Value, and Service Satisfaction

E-service quality in relation to websites is defined as the extent to which a website facilitates efficient and effective shopping, purchasing, and delivery of products and services (Zeithaml, Parasuraman, & Malhotra, 2002). Customers’ assessments of website quality and e-service quality include their experience of interacting with the website as well as postinteraction service aspects, that encompass core service quality (e.g., efficiency, fulfillment, system availability, privacy) and e-recovery service quality (e.g., responsiveness, compensation, contact; Parasuraman & Grewal, 2000). Website design, reliability, and privacy/security have also been identified as elements of service quality in shopping sites (Keating, Rugimbana, & Quazi, 2003). Ongoing attempts to understand the dynamics of service in an online shopping context have indicated service quality is related to satisfaction and website patronage.

Perceived service value is the consumer’s overall assessment of the utility of a product based on perceptions of what is received and what is given (Zeithaml, 1988). As service quality improves, the probability of customer satisfaction increases. In turn, perceptions of better service value in service exchanges provided by service organizations leads to increased customer satisfaction (Arasli, Mehtap-Smadi, & Turan Katircioglu, 2005; Lovelock & Wirtz, 2007), and positive evaluations of these service exchanges (Cronin et al., 2000).

Customer satisfaction refers to the degree to which customers are satisfied and pleased with their shopping experience (Szymanski & Hise, 2000). Previous researchers have suggested that customer satisfaction can be significantly predicted by the perceived quality of convenience, product information, security, and reliability or fulfillment (Szymanski & Hise, 2000; Zeithaml et al., 2002). Service satisfaction results from perceptions of quality or value. Customers will decide whether they are receiving fair treatment based on their own service experiences and expectations (Oliver, 1999). In order to satisfy its customers, a service firm needs to fulfill three customer expectations; product quality, service quality, and price value.

In a service management context, customer satisfaction is the consequence of the customer’s perception of value received from the transaction or relationship with the service providers (Lam, Shankar, Erramilli, & Murthy, 2004). Consumers’ perceptions of good service are closely related to their awareness of the exceptional value they have received from a service exchange with a service provider, and customer satisfaction reflects the customer’s overall feeling derived from that value. Therefore, we proposed the following three hypotheses:
H1: The level of a customer’s perception of e-service quality will positively affect his/her perceived service value.
H2: The level of a customer’s perception of e-service quality will positively affect his/her perceived service satisfaction.
H3: The level of a customer’s perception of service value will positively affect his/her perceived service satisfaction.

Moderating Roles of Perceived Trust in the Relationships Among E-Service Quality, Perceived Service Value, and Service Satisfaction

Morgan and Hunt (1994) define trust as existing when one party has confidence in the exchange partner’s reliability and integrity. Perceived trust refers to the expectations held by the customer that the service provider is dependable and can be relied on to deliver on his or her promises (Sirdeshmukh, Singh, & Sabol, 2002). Perceived trust also refers to a customer’s belief that an organization’s underlying technological infrastructure and control mechanisms are capable of supporting transactions (Cao, Zhang, & Seydel, 2005). From an e-service perspective, perceived trust can be defined as being the concept that exists when one party has confidence in the other partner’s reliability and integrity (Morgan & Hunt, 1994; Ranaweera & Prabhu, 2003). Perceived trust has been conceptualized as a dimension of the technology acceptance model (TAM), and it has also been found to have a considerable influence on a user’s willingness to engage in online exchanges of money and service expectations in terms of useful information supplied to customers (Hoffman, Novak, & Peralta, 1999). In other words, from a service quality perspective, trust could also be regarded as trust in the service itself (Parasuraman, Zeithaml, & Berry, 1988). This view is consistent with that of previous researchers of e-service marketing channels who have demonstrated that rather than benefits service organizations often give priority to satisfaction because this is rated highly by customers in long-term relational exchanges with service firms (Gwinner, Gremler, & Bitner, 1998; Morgan & Hunt, 1994).

In the model of the e-loyalty development process proposed by Kim, Jin, and Swinney (2009), it is stated that e-trust has a strong moderating impact on the relationship between e-quality – including fulfillment/reliability, responsiveness, and security/privacy – and e-service satisfaction. Chiou and Droge (2006) also found that perceived trust had a moderating effect on the relationship between e-service quality – including facility and interactive service quality – and e-service satisfaction. Chen (2009) concluded that the effect of e-service value on e-service satisfaction was greater among those who trust the service more, and Hsu (2009) also found perceived trust to be a strong, positive moderator of the relationship between e-service value and e-service satisfaction. It is logical that the more customers feel safe and confident in using service transactions based upon high quality service experiences, the greater will be their satisfaction. Therefore, we proposed the following two hypotheses:
H4: A customer’s perception of trust will positively moderate the relationship between e-service quality and customer service satisfaction in service transactions.
H5: A customer’s perception of trust will positively moderate the relationship between perceived service value and customer service satisfaction in service transactions.

Moderating Role of Perceived Usefulness in the Relationships Among E-Service Quality, Perceived Service Value, and Service Satisfaction

Perceived usefulness originates from the technology acceptance model (TAM). Perceived usefulness is defined as the degree to which a person believes that using a particular system will enhance his or her job performance in TAM (Davis, Bagozzi, & Warshaw, 1989). Researchers have successfully applied this concept of perceived usefulness to online customers’ evaluations of how well they understand information on websites in terms of perceived service quality, degree of satisfaction, and shopping online (Koufaris, 2002). Perceived usefulness refers to perceptions of service quality, consumer satisfaction, and a high level of perceived usefulness leads to increased intention by the consumer to purchase (Cao, Zhang, & Seydel, 2005; Hampton-Sosa, 2004; Kim & Lee, 2008; Koufaris, 2002). Perceived usefulness moderates the relationship between service quality beliefs and continuance intention (Naidoo & Leonard, 2007). Perceived usefulness is strongly associated with customers’ cognitive function in terms of enhancing job effectiveness (Davis, 1989) and refers to customers’ perception of how well they understand information on websites in terms of the degree of perceived service quality and satisfaction. Perceptions of good service quality, high consumer satisfaction, and a high degree of usefulness with regard to a service performed by a service organization, leads to increased intention by the consumer to purchase (Cao et al., 2005; Koufaris & Hampton-Sosa, 2004).

Shih (2008) demonstrated that the perception of usefulness strongly and positively influences the relationship between e-service quality and e-service satisfaction. Wu (2008) also found that the relationship between e-service value and e-service satisfaction was positively influenced by perceived usefulness. It is logical that perceived usefulness plays an important role in determining, or indirectly facilitating, service quality and satisfaction with online service adoption intention (Guriting & Ndubisi, 2006). In other words, high quality service performance of an e-service design, and the provision of service transactions in ways which are easy to use and provide the intended service effectively and efficiently, leads to increased customer satisfaction. Thus, we proposed the following two hypotheses:
H6: Customer perception of usefulness will positively moderate the relationship between e-service quality and customer service satisfaction in service transactions.
H7: Customer perception of usefulness will positively moderate the relationship between perceived service value and customer service satisfaction in service transactions.

Method

Research Model

Many researchers have studied e-service quality and online shopping intention using the technology acceptance model (Davis, 1989; Davis et al., 1989; Venkatesh & Davis, 2000). For example, Cao et al. (2005) investigated the direct influence of service quality on perceived ease of use and perceived usefulness by observing student behavior when buying books over the Internet. However, in this study we went one step further by investigating whether or not customer perceptions of both usefulness and trust really do play key roles as moderators that affect the influence of e-service quality and perceived service value on service satisfaction. We conducted our investigation by means of an empirical survey posted on e-tourism payment websites. The conceptual model is shown in Figure 1.

Instruments

In order to test the conceptual model empirically, we used a 22-item questionnaire developed by Parasuraman et al. (2005). Efficiency, system availability, fulfillment, and privacy are the four dimensions of e-service quality explored in the questionnaire. We also used a dimension of four items of perceived service value also derived from Parasuraman et al. (2005). We also used questionnaire items of perceived trust (eight items) and perceived usefulness (six items) from Cao et al. (2005), and service satisfaction (five items) from Janda, Trocchia, and Gwinner (2002). The resulting questionnaire we used in our study had 45 items and was designed in both English and Chinese with responses to be given on 5-point Likert scales. Hypotheses 1 to 3 were tested using structural equation modeling (SEM) and a competing model was used for hypotheses 4 to 7.

Data Collection and Sample Design

We used the critical incident technique (CIT), developed by Flanagan (1954), for data collection. The CIT has been confirmed as an appropriate method of identifying the underlying sources of customer service experiences in service encounters (Bitner, Booms, & Tetreault, 1990; Van Doorn & Verhoef, 2008). In the service marketing context, the CIT has been used to identify the sources of satisfactory and unsatisfactory service experiences from the customer’s point of view (Bitner et al., 1990). In this study, we used the CIT to collect data from respondents regarding their perceptions of e-service quality, service value, trust, usefulness, and service satisfaction in a specific previous service encounter when using airline online service. A convenience sampling selection process was used, and 30 airline websites were selected from the Top 200 Service Firms List provided by Taiwan’s Commonwealth magazine (2008).

From the beginning of January to the end of April 2009, we selected international travelers who had previously performed online service transactions with the selected airline agencies, and invited them to evaluate the 45 questionnaire items at Taiwan, Taiyuan, and Kaohsiung International Airports. We delivered questionnaires by hand to 715 international travelers; 236 were satisfactorily completed, returned, and used for further analysis, representing a response rate of 33%.

Results and Discussion

Factor Analysis and Reliability Tests

The results of factor analysis and reliability tests for five constructs of e-service quality, perceived service value, service satisfaction, perceived trust, and perceived usefulness are presented in Tables 1 and 2. As can be seen in Tables 1 and 2, after deleting several items based on the factor loadings, for item to total correlation and Cronbach’s alpha, the remaining items all fulfilled the criteria. Therefore, for simplification, the summated factor scores (the average of all items in a single score) were used for further empirical validation.

Validation Tests

Discriminant and convergent validity were measured in terms of average variance extracted (AVE). As shown in Tables 3 and 4, the AVE values for all of the study’s constructs were well above the threshold for acceptability, and the square root of the AVE value in the diagonal for each construct was larger than the correlation coefficients in the corresponding rows and columns. Consequently, both discriminant and convergent validity were deemed acceptable in this study.

The proposed structural equation model is shown in Figure 2. To further evaluate the moderating effects of perceived trust and perceived usefulness, we compared the first model (original) and the competing model by dividing them into two groups. By using AMOS version 5.0 to test the moderating variables, it was found that all paths were unconstrained between the two groups. According to Algesheimer, Dholakia, and Herrmann (2005), the difference in the chi-square (χ²) values between the two models (original and competing models) provides a test for the equality of the path of the two groups. Additionally, the t value should be greater than 1.96 (absolute value).

The original model showed that GFI = .911, AGFI = .903, chi-square = 56.496, p < .001. In the competing model (Model 1), after introducing the moderating role of perceived trust on perceptions of e-service quality and service value on service satisfaction, the results showed GFI = .923, AGFI = .915, χ² = 71.846, p < .001. Furthermore, in the second competing model (Model 2), with the moderating effect of perceived usefulness on perceptions of e-service quality and service value on service satisfaction, the results were GFI = .903, AGFI = .897, χ² = 67.727, p < .001. When comparing the results shown in Table 5, for χ² of the original model, competing model 1 and competing model 2, and t value from these results we concluded that the moderating effects of customer perceptions of both trust and usefulness are significant. Thus, Hypotheses 4, 5, 6, and 7 all received support.

By using the 236 samples to analyze the data, the full model showed (see Figure 2) that the model is stable for the overall model fit assessment of path direct relationships. In addition, the results shown in Figure 2 also support Hypotheses 1, 2, and 3.

Conclusion

In this study we investigated customers’ perceptions of quality of e-service experiences and service satisfaction by applying a technology acceptance perspective (i.e., customer perceived trust and usefulness) to predict consumer behavior when purchasing airline tickets online from e-traveling service companies. It was evident from the results in our study that perceived trust and perceived usefulness not only play a key role in predicting customers’ attitudes toward online shopping and purchasing intention, but also in the moderating role of the perceptions of international travelers of e-service quality and service satisfaction for consumers who have used e-traveling services.

We also intended that in this study we would contribute to the current understanding of online shopping behavior. In terms of upgrading e-service quality, consumers’ perceptions of value, and customers’ service satisfaction, e-service agencies should pay more attention to developing and improving the design of their websites, should increase their service quality by providing accurate service, strengthen the security of online transactions, and help customers to resolve time-related problems such as long waiting and response times (Chang & Wang, 2008). These developments and improvements would lead to an increase in consumer trust in and loyalty to that particular service, and improve trust of and benefits for customers (i.e., good services, service image).

In summary, we found that the TAM can be used and tested in terms of the general perceptions of consumers who have used online shopping. Based upon this finding, the TAM is an important tool for e-service marketers who are trying to develop high quality e-service strategies to attract consumers and satisfy their needs. Although perceived trust is not the main concept in the TAM, our findings in this empirical test have meaningful implications for e-service marketing websites in terms of the increased use that can be achieved through enhancing customers’ trust and perceptions of usefulness. Therefore, our conceptual model has been confirmed to be useful, and can be adopted for similar research in the future. By contrast, according to the telepresence theory (Steuer, 1992) positive consumer perception of previous service experiences in online shopping have been found to be associated more with the extent to which a person feels the needs to engage in a mediated environment. Future empirical research could be conducted to investigate shopping intentions by applying the telepresence theory to predict customer behavior when purchasing products online.

References

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Arasli, H., Mehtap-Smadi, S., & Turan Katircioglu, S. (2005). Customer service quality in the Greek Cypriot banking industry. Managing Service Quality, 15(1), 41-56.

Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: Diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1), 71-84.

Cao, M., Zhang, Q., & Seydel, J. (2005). B2C e-commerce web site quality: An empirical examination. Industrial Management and Data System, 105(5), 645-661.

Chang, H. H., & Wang, H. W. (2008). The relationships among e-service quality, value, satisfaction, and loyalty in online shopping. European Advances in Consumer Research, 8(1), 10-14.

Chen, C. T. (2009). A study of the influence of perceived risk and trust on taxpayers’ behavioral intention to use e-taxation. Master’s thesis, National Kaohsiung First University of Science and Technology, Taiwan.

Chiou, J. S., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: Direct and indirect effects in a satisfaction-loyalty framework. Journal of the Academy of Marketing Science, 34(4), 613-627.

Collier, J. E., & Bienstock, C. C. (2006). Measuring service quality in e-retailing. Journal of Service Research, 8(3), 260-275.

Cronin, J. J., Jr., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193-218.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 54(4), 327-358.

Gounaris, S., Dimitriadis, S., & Stathakopoulos, V. (2005). Antecedents of perceived quality in the context of Internet retail stores. Journal of Marketing Management, 21(7/8), 669-700.

Guriting, P., & Ndubisi, N. O. (2006). Borneo online banking: Evaluating customer perceptions and behavioral intention. Management Research News, 29(1/2), 6-15.

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Hsu, H. M. (2009). Application of the TAM in the channel of online shopping in Taiwan. Master’s thesis, National Central University, Taiwan, ROC.

Imrie, B. C., Durden, G., & Cadogan, J. W. (2000). Towards a conceptualization of service quality in the global market arena. Advances in International Marketing, 10(1), 143-162.

Janda, S., Trocchia, P. J., & Gwinner, K. P. (2002). Consumer perceptions of Internet retail service quality. International Journal of Service Industry Management, 13(5), 412-431.

Keating, B., Rugimbana, R., & Quazi, A. (2003). Differentiating between service quality and relationship quality in cyberspace. Managing Service Quality, 13(3), 217-232.

Kim, J., Jin, B., & Swinney, J. L. (2009). The role of retail quality, e-satisfaction and e-trust in online loyalty development process, Journal of Retailing and Consumer Services, 16(4), 239-247.

Kim, J., & Lee, H. H. (2008). Consumer product search and purchase behavior using various retail channels: The role of perceived usefulness. International Journal of Consumer Studies, 32, 619-627.

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Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information and Management, 41(3), 377-397.

Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: An illustration from a business to business service context. Journal of the Academy of Marketing Science, 32(3), 293-311.

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Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(7), 20-38.

Naidoo, R., & Leonard, A. (2007). Perceived usefulness, service quality, and loyalty incentives: Effects on electronic service continuance. South African Journal of Business Management, 38(3), 39-48.

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Ozment, J., & Morash, E. A. (1994). The augmented service offering for perceived and actual service quality. Journal of Academy of Marketing Science, 4(22), 352-363.

Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-value-loyalty chain: A research agenda. Journal of Academy of Marketing Science, 28(1), 168-174.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-29.

Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.

Ranaweera, C., & Prabhu, J. (2003). The influence of satisfaction, trust and switching barriers on customer retention in a continuous purchasing setting. International Journal of Service Industry Management, 14(4), 374-395.

Shih, S. T. (2008). A study of consumer perceived usefulness for Internet banking: A TAM perspective. Master’s thesis, Chung Yuan Christian University, Taiwan, ROC.

Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37.

Sohn, C., & Tadisina, S. K. (2008). Development of an e-service quality measure for internet-based financial institutions. Total Quality Management & Business Excellence, 19(9), 903-918.

Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived website interactivity. Journal of Marketing, 72, 99-113.

Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73-93.

Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76(3), 309-322.

Top 200 service firms. (2008). Commonwealth, 396(5), 114-118.

Van Doorn, J., & Verhoef, P. C. (2008). Critical incidents and the impact of satisfaction on customer share. Journal of Marketing, 72, 123-142.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

Wu, Y. H. (2008). An empirical study of perceived usefulness and TAM: An example of online shopping. Journal of Information Management, 15(1), 123-152.

Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A mean-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.

Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002). Service quality delivery through websites: A critical review of extant knowledge. Journal of the Academy of Marketing Science, 30(4), 362-375.

Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from European car clubs. Journal of Marketing, 69(3), 19-34.

Arasli, H., Mehtap-Smadi, S., & Turan Katircioglu, S. (2005). Customer service quality in the Greek Cypriot banking industry. Managing Service Quality, 15(1), 41-56.

Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: Diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1), 71-84.

Cao, M., Zhang, Q., & Seydel, J. (2005). B2C e-commerce web site quality: An empirical examination. Industrial Management and Data System, 105(5), 645-661.

Chang, H. H., & Wang, H. W. (2008). The relationships among e-service quality, value, satisfaction, and loyalty in online shopping. European Advances in Consumer Research, 8(1), 10-14.

Chen, C. T. (2009). A study of the influence of perceived risk and trust on taxpayers’ behavioral intention to use e-taxation. Master’s thesis, National Kaohsiung First University of Science and Technology, Taiwan.

Chiou, J. S., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: Direct and indirect effects in a satisfaction-loyalty framework. Journal of the Academy of Marketing Science, 34(4), 613-627.

Collier, J. E., & Bienstock, C. C. (2006). Measuring service quality in e-retailing. Journal of Service Research, 8(3), 260-275.

Cronin, J. J., Jr., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193-218.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 54(4), 327-358.

Gounaris, S., Dimitriadis, S., & Stathakopoulos, V. (2005). Antecedents of perceived quality in the context of Internet retail stores. Journal of Marketing Management, 21(7/8), 669-700.

Guriting, P., & Ndubisi, N. O. (2006). Borneo online banking: Evaluating customer perceptions and behavioral intention. Management Research News, 29(1/2), 6-15.

Gwinner, K. P., Gremler, D. D., & Bitner, M. J. (1998). Relational benefits in services industries: The customer’s perspective. Journal of the Academy of Marketing Science, 26(2), 101-114.

Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80-85.

Hsu, H. M. (2009). Application of the TAM in the channel of online shopping in Taiwan. Master’s thesis, National Central University, Taiwan, ROC.

Imrie, B. C., Durden, G., & Cadogan, J. W. (2000). Towards a conceptualization of service quality in the global market arena. Advances in International Marketing, 10(1), 143-162.

Janda, S., Trocchia, P. J., & Gwinner, K. P. (2002). Consumer perceptions of Internet retail service quality. International Journal of Service Industry Management, 13(5), 412-431.

Keating, B., Rugimbana, R., & Quazi, A. (2003). Differentiating between service quality and relationship quality in cyberspace. Managing Service Quality, 13(3), 217-232.

Kim, J., Jin, B., & Swinney, J. L. (2009). The role of retail quality, e-satisfaction and e-trust in online loyalty development process, Journal of Retailing and Consumer Services, 16(4), 239-247.

Kim, J., & Lee, H. H. (2008). Consumer product search and purchase behavior using various retail channels: The role of perceived usefulness. International Journal of Consumer Studies, 32, 619-627.

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 205-223.

Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information and Management, 41(3), 377-397.

Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: An illustration from a business to business service context. Journal of the Academy of Marketing Science, 32(3), 293-311.

Lovelock, C., & Wirtz, J. (2007). Services marketing: People, technology, strategy (6th ed.). New Jersey: Prentice-Hall.

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(7), 20-38.

Naidoo, R., & Leonard, A. (2007). Perceived usefulness, service quality, and loyalty incentives: Effects on electronic service continuance. South African Journal of Business Management, 38(3), 39-48.

Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4), 33-44.

Ozment, J., & Morash, E. A. (1994). The augmented service offering for perceived and actual service quality. Journal of Academy of Marketing Science, 4(22), 352-363.

Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-value-loyalty chain: A research agenda. Journal of Academy of Marketing Science, 28(1), 168-174.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-29.

Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.

Ranaweera, C., & Prabhu, J. (2003). The influence of satisfaction, trust and switching barriers on customer retention in a continuous purchasing setting. International Journal of Service Industry Management, 14(4), 374-395.

Shih, S. T. (2008). A study of consumer perceived usefulness for Internet banking: A TAM perspective. Master’s thesis, Chung Yuan Christian University, Taiwan, ROC.

Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37.

Sohn, C., & Tadisina, S. K. (2008). Development of an e-service quality measure for internet-based financial institutions. Total Quality Management & Business Excellence, 19(9), 903-918.

Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived website interactivity. Journal of Marketing, 72, 99-113.

Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73-93.

Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76(3), 309-322.

Top 200 service firms. (2008). Commonwealth, 396(5), 114-118.

Van Doorn, J., & Verhoef, P. C. (2008). Critical incidents and the impact of satisfaction on customer share. Journal of Marketing, 72, 123-142.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

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Appreciation is due to anonymous reviewers.

Shu-Fang Luo, Department of Business Administration, Tainan University of Technology, No. 529 Jhongjheng Road, YongKang City, Tainan County, 71002, Taiwan, ROC. Email: [email protected] or [email protected]