||The Effect of Unified Theory of Acceptance and Use of Technology and Innovation Diffusion Theory on Online Shopping-Familiarity and Perceived Risk as Mediators
||Department of Business Administration
Unified Theory of Acceptance and Use of Technology
Innovation Diffusion Theory
In online shopping environment, e-retailers continuously improve their website quality and offer richer information related to products to attract more consumers; moreover, the rate of purchasing high-tech products in online stores increases year by year. This study combined Unified Theory of Acceptance and Use of Technology (UTAUT) with Innovation Diffusion Theory (IDT), including performance expectancy, effort expectancy, virtual community building and trialability, and adopted two mediators, familiarity and perceived risk, to examine online shopping behavior. In this study, a web-based survey was employed, and the respondents were drawn from Internet users. 344 valid respondents were collected. Structural equation model (SEM) and regression analysis were adopted for data analysis. Based on the results of SEM, performance expectancy and effort expectancy positively affect website familiarity; virtual community building and trialability positively influence product familiarity. However, performance expectancy, effort expectancy, virtual community building, trialability and familiarity all have no significant effects on perceived risk. Moreover, familiarity positively influence purchase intention; perceived risk negatively affects purchase intention. According to the results of regressing, website familiarity and product familiarity have mediation effects, but perceived risk has no mediation effect. In other words, website designs indirectly affect purchase intention through familiarity. In managerial implications, this study suggests managers should provide a complete community to consumers in order to enable them to share information; furthermore, managers should also build the tryout of products on the website, so that consumers can increase familiarity about websites and products, and in turn, promote purchase intention.
TABLE OF CONTENTS Ⅳ
LIST OF TABLES Ⅵ
LIST OF FIGURES Ⅶ
CHAPTER 1 INTRODUCTION 1
1.1 Research Background and Motivations 1
1.2 Research Objectives 5
1.3 Contributions of the Study 6
1.4 Research Procedures 7
CHAPTER 2 LITERATURE REVIEW 8
2.1 Definition of Theories and Research Constructs 8
2.1.1 Unified Theory of Acceptance and Use of Technology (UTAUT) and Innovation Diffusion Theory (IDT) 8
2.1.2 Performance Expectancy 11
2.1.3 Effort Expectancy 12
2.1.4 Virtual Community Building 12
2.1.5 Trialability 14
2.1.6 Familiarity 15
2.1.7 Perceived Risk 16
2.1.8 Purchase Intention 17
2.2 Hypotheses Development 18
2.2.1 Virtual Community Building and Product Familiarity 18
2.2.2 Virtual Community Building and Perceived Risk 18
2.2.3 Performance Expectancy, Website Familiarity and Perceived Risk 19
2.2.4 Effort Expectancy and Website Familiarity 20
2.2.5 Effort Expectancy and Perceived Risk 20
2.2.6 Trialability and Product Familiarity 21
2.2.7 Trialability and Perceived Risk 22
2.2.8 Familiarity and Perceived Risk 22
2.2.9 Familiarity and Purchase Intention 23
2.2.10 Perceived Risk and Purchase Intention 24
2.2.11 The Mediating Effect of Familiarity and Perceived Risk 25
2.3 Research Conceptual Framework 26
CHAPTER 3 RESEARCH DESIGN AND METHODOLOGY 29
3.1 Construct Definition and Measurement 29
3.2 Questionnaire Design 31
3.3 Sample Plan 32
3.4 Pilot Test 32
3.5 Data Analysis Procedure 37
CHAPTER 4 RESULTS OF DATA ANALYSIS 39
4.1 Characteristics of Respondents 39
4.2 Measurement Assessment 40
4.2.1 Confirmatory Factor Analysis 41
4.2.2 Model Fit Indices 44
4.2.3 Reliability and Convergent Validity Analysis 44
4.2.4 Discriminate Validity 46
4.3 ANOVA Analysis 46
4.3.1 Demographic Variables 47
4.3.2 Shopping Experience for Consumers 54
4.4 Structural Model Analysis 57
4.4.1 Model Fit Indices 58
4.4.2 Structural Coefficient Estimates 58
4.5 The Mediating Effect of Product Familiarity and Website Familiarity 62
4.6 The Mediating Effect of Perceived Risk 65
CHAPTER 5 DISCUSSION AND IMPLICATIONS 66
5.1 Discussions and Conclusions 66
5.2 Theoretical Implications 68
5.3 Managerial Implications 70
5.4 Limitations and Directions for Future Research 71
APPENDIX A 83
APPENDIX B 89
APPENDIX C 90
Agarwal, R., & Prasa, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9 (2), 204-301.
Agarwal, R., & Venkatesh, V.(2002). Assessing a firm's web presence: A heuristic evaluation procedure for the measurement of usability. Information Systems Research, 13(2), 168-186.
Ahn, T., Ryu, S., & Han, I. (2004). The impact of the online and offline features on the user acceptance of internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405–420.
Ajzen, I. (1985). From intentions to action: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Action-control: From Cognition to Behavior. Heidelberg: Springer, 11-39.
Akerlof, G. (1970). The market for ‘lemons’: Quality under uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488-500.
Amberg, M., Fischer, S., & Schröder, M. (2005). An evaluation framework for the acceptance of web-based aptitude tests. The Electronic Journal of Information Systems Evaluation, 8(3), 151-158.
Andersen, P.H. (2005). Relationship marketing and brand involvement of professionals through web-enhanced brand communities: The case of Coloplast. Industrial Marketing Management, 34(3), 39-51.
Anderson, B. (1983). Imagined Community. London: Verso.
Anderson, C.R., & Zeithaml, C.P.(1984). Stage of the product life cycle, business strategy, and business performance. Academy of Management Journal, 27 (1), 5–24.
Anderson, J.C., & Gerbing, D.W. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186-192.
Atkinson, N.L. (2007). Developing a questionnaire to measure perceived attributes of eHealth innovations. American Journal of Health Behavior, 31(6), 612-621.
Bansal, H.S., Irving, P.G., & Taylor, S.F. (2004). A three-component model of customer commitment to service providers. Journal of the Academy of Marketing Science, 32 (3), 234–250.
Baron, R.M., & Kenny, D.A (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
Bart, Y., Shankar, V., Sultan, F., & Urban, G.L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 69(4), 133-152.
Battacharya, C.B., Rao, H., & Glynn, M.A. (1995). Understanding the bond of identification: An investigation of its correlates among art museum members. Journal of Marketing, 59(4), 46-57.
Bauer, R.(1960). Consumer Behaviour as Risk Taking. In Hancock, R.F. (Ed.), Proceedings of the 43rd Conference of the American Marketing Association, American Marketing Association, Chicago, IL, 389-98.
Berthon, P., Pitt, L., & Richard, W.T. (1996). Re-surfing W3: Research perspectives on marketing communication and buyer behavior on the World Wide Web. International Journal of Advertising, 15(4), 287-301.
Bhattacherjee, A. (2002). Individual trust in online firm: Scale development and initial test. Journal of Management Information Systems, 19(1), 211–241.
Biswas, D., & Biswas, A. (2004). The diagnostic role of signals in the context of perceived risks in online shopping: Do signals matter more on the web? Journal of Interactive Marketing, 18(3), 30-45.
Brown, J., Broderick, A.J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing, 21 (3), 2-20.
Burke, R.R. (2002). Technology and the customer interface: What consumers want in the physical and virtual store. Journal of the Academy of Marketing Science, 30(4), 411-432.
Burnham, T.A., Frels, J.K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of Marketing Science, 31(2), 109–126.
Carolina, L.N., & Francisco José, M.C. (2008). Customer knowledge management and e-commerce: The role of customer perceived risk. Journal of Information Management, 28(2), 102-113.
Chau, P.Y.K., & Ho, C.K.Y. (2008). Developing consumer-based service brand equity via the internet: The role of personalization and trialability. Journal of Organizational Computing and Electronic Commerce, 18(3), 197–223.
Chau, P.Y.K., Hu, P.J., Lee, B.L.P., & Au, A.K.K. (2007). Examining customers’ trust in online vendors and their dropout decisions: An empirical study. Electronic Commerce Research and Applications, 6 (2), 171-82.
Chen, Q., Chen, H.M., & Kazman, R. (2007). Investigating antecedents of technology acceptance of initial eCRM users beyond generation X and the role of self-construal. Electronic Commerce Research, 7(3/4), 315-339.
Chen, Y.H., & Barnes, S. (2007). Initial trust and online buyer behavior. Industrial Management & Data Systems, 107(1), 21-36.
Chiu, C.K. (2009). Understanding relationship quality and online purchase intention in e-tourism: A qualitative application. Quality & Quantity, 43(4), 669-675.
Chiu, C.M., & Wang, E.T.G. (2008). Understanding Web-based learning continuance intention: The role of subjective task value. Information & Management, 45 (3), 194–201.
Cho, V. (2006). A study of the roles of trusts and risks in information-oriented online legal services using an integrated model. Information & Management, 43(4), 502-505.
Churchill, G.A. (1979). A paradigm for developing better measures of marketing constructs. Joumal of Marketing Research, 16(1), 64-73.
Compeau, D.R., & Higgins, C.A.(1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
Corritore, C.L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes: A model. International Journal of Human-Computer Studies, 58(6), 737–758.
Cowley, E., & Mitchell, A.A. (2003). The moderating effect of product knowledge on the learning and organization of product information. Journal of Consumer Research, 30(3), 443-454.
Cox, D.S., & Cox, A.D. (2002). Beyond first impressions: The effects of repeated exposure on consumer liking of visually complex and simple product designs. Journal of the Academy of Marketing Science, 30(2), 119-130.
Crespo, Á.H., del Bosque, I.R., & de los Salmones Sánchez, M.M.G. (2009). The influence of perceived risk on Internet shopping behavior: A multidimensional perspective. Journal of Risk Research, 12(2), 259–277.
Cunningham, S. (1967). The major dimensions of perceived risk. In D. Cox (Ed.), Risk Taking And Information Handling In Consumer Behavior. Cambridge, MA: Harvard University Press.
Dahan, E., & Hauser, J.R., (2002). The virtual customer. Journal of Product Innovation Management 19(5), 332–353.
Dahan, E., & Srinivasan, V. (2000). The predictive power of internet-based product concept testing using visual depiction and animation. Journal of Product Innovation Management, 17(2), 99–109.
d'Astous, A., & Gargouri, E. (2001). Consumer evaluations of brand imitations. European Journal of Marketing, 35(1/2), 153-167.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Dholakia, U.M., Bagozzi, R.P., & Pearo, L.K. (2004). A social influence model of consumer participation in network- and small-group-based virtual communities. International Journal of Research in Marketing, 21 (3), 241–263.
Dollin, B., Dillon, S., Thompson, F., & Corner, J.L. (2005). Perceived risk, internet shopping experience and online purchasing behavior: A New Zealand perspective. Journal of Global Information Management, 13(2), 66-88.
Doney, P.M., & Cannon, J.P. (1997). An examination of the nature of trust in buyer-seller relationships. Journal of Marketing, 61(2), 35-51.
E-ICP (2009). Eastern Integrated Consumer Profile. Retrieved Novenber, 2009.
Elliot, S., & Fowell, S. (2000). Expectations versus reality: A snapshot of consumer experiences with Internet retailing. International Journal of Information Management, 20(5), 323–336.
Featherman, M.S, & Pavlou, P.A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human -- Computer Studies, 59(4), 451–474.
Fornell, C., & Larcker, D.F. (1981). Evaluation structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Forsythe, S., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56(11), 867–875.
Fuller, J., & Matzler, K.(2007). Virtual product experience and customer participation—A chance for customer-centred, really new products. Technovation, 27(6/7), 378–387.
Gallaugher, J.M., & Wang, Y.M. (2002). Understanding network effects in software markets: Evidence from web server pricing. MIS Quarterly, 26(4), 303-327.
Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725-737.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and tam in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90.
Gerbing, D.W., & Anderson, J.C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment, Journal of Marketing Research, 25(2), 186-192.
Gregg, D.G, & Walczak, S. (2008). Dressing your online auction business for success: An experiment comparing two eBay businesses. MIS Quarterly, 32(3), 653-670.
Grewal, D., Munger, J., Iyer, G., & Levy, M. (2003). The influence of internet retailing factors on price expectations. Psychology & Marketing, 20(6), 477-493.
Gulati, R. (1995). Does familiarity breed trust? The implications of repeated ties for contractual choice in alliances. Academy of Management Journal, 38(1), 85-112.
Gusfieid, J. (1978). Community: A Critical Response. New York: Harper & Row.
Hagel, J. III., & Armstrong, A.G. (1997). Net Gain: Expanding Markets through Virtual Communities. Boston, MA: Harvard Business School Press.
Hair, J.F., William, C.B., Barry, J.B., Anderson, R.E., & Tatham, R.L. (2006). Multivariate Data Analysis (6th ed.). Upper Saddle River, New Jersey: Pearson Education.
Hauser, J. R., & Wernerfelt, B. (1990). An evaluation cost model of consideration sets. Journal of Consumer Research, 16(4), 393–408.
Hernandez, B., Jimenez, J., & Martı´n, M.J. (2009). Adoption v.s. acceptance of e-commerce: Two different decisions. European Journal of Marketing, 43(9/10), 1232-1245.
Hong, W., Tam, K.Y., & Yim, C.K. (2002). E-service environment: Impacts of web interface characteristics on consumers’ online shopping behavior. In R. T. Rust and P. K. Kannan (Eds.), E-Service: New Directions in Theory and Practice, NY: M. E. Sharpe, Armonk, 108-128.
Hunter, L.M., Kasouf, C.J., Celuch, K.A., & Curry, K.A. (2004). A classification of business-to-business buying decisions: Risk importance and probability as a framework for e-business benefits. Industrial Marketing Management, 33(2), 145-54.
IX (2009). InsightXplorer. Retrieved Novenber, 2009, from http://www.insightxplorer.com/index.html.
Jarvenpaa, S.L., & Tractinsky, N. (1999). Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 5(2), 1- 33.
Jarvenpaa, S.L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an Internet store. Information Technology and Management, 1(1–2), 45–71.
Jiang, Z., & Benbasat, I. (2005). Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 21(3), 111-148.
Jiang, Z., & Benbasat, I. (2007). The effects of presentation formats and task complexity on online consumers’ product understanding. MIS Quarterly, 31 (3), 475-500.
Joaquı´n A.M., Carla R.M., & Silvia S.B. (2009). Exploring individual personality factors as drivers of m-shopping acceptance. Industrial Management & Data Systems, 109(6), 739-757.
Johnson, E.J., & Russo, J.E. (1984). Product familiarity and learning new information. Journal of Consumer Research, 11(1), 542-551.
Karahanna, E., Straub, D.W., & Chervany, N.L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
Keller, K.L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22.
Kempf, D.S., & Smith, R.E. (1998). Consumer processing of product trial and influence of prior advertising: A structural modeling approach. Journal of Marketing Research, 35(3), 325-338.
Kim, D.J., Ferrin, D.L., & Rao, H.R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
Kim, J., & Forsythe, S. (2008). Sensory enabling technology acceptance model (SE-TAM): A multiple-group structural model comparison. Psychology & Marketing, 25(9), 901–922.
King, R.C., Sen, R., & Xia, M. (2004). Impact of web-based e-commerce on channel strategy in retailing. International Journal of Electronic Commerce, 8(3), 103–130.
Klein, L.R. (2003). Creating virtual product experiences: The role of telepresence. Journal of Interactive Marketing, 7(1), 41-55.
Kozinets, R.V. (2002). The field behind the screen: Using netnography for marketing research in online communities. Journal of Marketing Research, 39(1), 61-72.
Lee, K.S., & Tan, S.J. (2003). E-retailing versus physical retailing: A theoretical model and empirical test of consumer choice. Journal of Business Research, 56(11), 877-886.
Lee, Y., & Kozar, K.A. (2008). An empirical investigation of anti-spyware software adoption: A multitheoretical perspective. Information & Management, 45(2), 109-119.
Li, H., Daugherty, T., & Biocca, F. (2002). Impact of 3-D advertising on product knowledge, brand attitude, and purchase intention: The mediating role of presence. Journal of Advertising, 31(3), 43-57.
Li, H., Daugherty, T., & Biocca, F. (2003). The role of virtual experience in consumer learning. Journal of Consumer Psychology, 13(4), 395-408.
Li, H., Daugherty, T., & Biocca, F.(2001). Characteristics of virtual experience in electronic commerce: A protocol analysis. Journal of Interactive Marketing, 15(3), 13-30.
Lightner, N.J., & Eastman, C. (2002). User preference for product information in remote purchase environments. Journal of Electronic Commerce Research, 3(3), 174-185.
Lim, N. (2003). Consumers’ perceived risk: Sources versus consequences. Electronic Commerce Research and Applications, 2 (3), 216-228.
Lin, C.P., & Anol, B. (2008). Learning online social support: An investigation of network information technology based on UTAUT. Cyberpsychology & Behavior, 11(3), 268-272.
Lin, H.F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research & Applications, 6(4), 433-442.
Luhmann, N.(1979). Trust and Power. UK: Wiley, Chichester.
Mach, Q.H., Hunter, M.D., & Grewal, R.S. (2010). Neurophysiological correlates in interface design: An HCI perspective. Computers in Human Behavior, 26(3), 371-376.
MacInnis, M., & Heslop, L.A.(1990). Marketing planning in a high tech environment. Industrial Marketing Management, 19(2), 107-16.
Mael, F., & Ashforth, B.E. (1992). Alumni and their alma mater: A partial test of the reformulated model of organizational identification. Journal of Organizational Behavior, 13(2), 103-123.
Mayer, R.C., & Davis, J.H. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734.
McAlexander, J.H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of Marketing, 66(1), 38-54.
McCoy, S., Everard, A., & Loiacono, E. T. (2009). Online ads in familiar and unfamiliar sites: Effects on perceived website quality and intention to reuse. Information Systems Journal, 19(4), 437–458.
McKinney, V., Yoon, K., & Zahedi, F.(2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Research, 13(3), 296-315.
McKnight, D., Cummings, L., & Chervany, N. (1998). Initial trust formation in new organizational relationships. Academy of Management Review, 23(3), 472-490.
MIC (2009). Market Intelligence & Consulting Institute. Retrieved Novenber, 2009, from http://mic.iii.org.tw/index.asp.
Monsuwe, T.P.Y., Dellaert, B.G.C., & Ruyter, K. D. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15(1), 102-121.
Moon, J.W., & Kim, Y.G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217–230.
Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.
Nadkarni, S., & Gupta, R. (2007). A task-based model of perceived website complexity. MIS Quarterly, 31(3), 501-524.
Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78(2), 311- 329.
Nelson, P. (1974). Advertising as Information. Journal of Political Economy, 83(3), 729-754.
Oliver, R.L., & Bearden, W.O. (1985). Crossover effects in the theory of reasoned action: A moderating influence attempt. Journal of Consumer Research, 12(3), 324-340.
Palmer, J.W. (2002). Web site usability, design and performance metrics. Information Systems Research, 13(2), 151–157.
Park, J., Lennon, S. J., & Stoel, L. (2005). On-line product presentation: Effects on mood, perceived risk, and purchase intention. Psychology & Marketing, 22(9), 695-719.
Pavlou, P.A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.
Pavlou, P.A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30 (1),115–143.
Pavlou, P.A., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 37–59.
Porter, E.C. (2004). A typology of virtual communities: A multi-disciplinary foundation for future research. Journal of Computer Mediated Communication, 10(1).
Punj, Girish N., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9(4), 366-380.
Raban, D.R., & Rafaeli, S. (2007). Investigating ownership and the willingness to share information online. Computers in Human Behavior, 23(5), 2367-2382.
Rani, P., Sarkar, N., & Adams, J. (2007). Anxiety-based affective communication for implicit human–machine interaction. Advanced Engineering Informatics, 21(3), 323-334.
Rao, A.R., & Monroe, K.B. (1989). The effect of price, brand name, and store name on buyers’ perceptions of product quality: An integrative review. Journal of Marketing Research, 26(3), 351-357.
Rao, A.R., & Sieben, W. (1992). The effect of prior knowledge on price acceptability and the type of information examined. Journal of Consumer Research, 19(2), 256-270.
Rhee, C., Moon, J., & Choe, J. (2006). Web interface consistency in e-learning. Online Information Review, 30(1), 53–69.
Rheingold, H. (1993). The Virtual Community: Homesteading in the Electronic Frontier. New York: Harper Collins.
Riley, F.D., Scarpi, D., & Manaresi, A. (2009). Purchasing services online: A two-country generalization of possible influences. Journal of Services Marketing, 23(2), 93–103.
Rogers, E.M (1995). The Diffusion of Innovations. New York: Free Press.
Rogers, E.M. (1983). The Diffusion of Innovations. (3rd ed.). New York: Free Press.
Schlosser, A. E. (2003). Experiencing products in a virtual world: The role of goals and imagery in influencing attitudes versus intentions. Journal of Consumer Research, 30(2), 184–198.
Shih, H.P. (2004). An empirical study on predicting user acceptance of e-shopping on the web. Information & Management, 41(3), 351-368.
Sinioukov, T. (1999). Mastering the web by the book. BookTechi the Magazine, 2(March), 50-54.
Slyke, C.V., Shim, J.T., Johnson, R., & Jiang, J. (2006). Concern for information privacy and online consumer purchasing. Journal of the Association for Information Systems, 7(6), 415-444.
Smallman, H., St. John, M., Oonk, H., & Cowen, M. (2001). Information availability in 2D and 3D displays. IEEE Computer Graphics & Applications, 21(5), 51–57.
Sobel, M.E. (1982). Asymptotic confidence intervals for indirect effects in structural equations models. In S. Leinhart (Ed.), Sociological Methodology. San Francisco: Jossey-Bass.
Srinivasana, S.S., Andersona, R., & Ponnavolub, K. (2002). Customer loyalty in e-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78(1), 41-50.
Stone, R.N., & Gronhaug, K. (1993). Perceived risk: Further considerations for marketing discipline. European Journal of Marketing, 27(3), 39–50.
Suh, K.S., & Lee, Y.E. (2005). Effects of virtual reality on consumer learning: An empirical investigation in web-based electronic commerce. MIS Quarterly, 29(4), 673-697.
Teo, H.H., Chan, H.C., Wei, K.K., & Zhang, Z., (2003). Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities. International Journal of Human-Computer Studies, 59(5), 671–697.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization, MIS Quarterly, 15(1), 124–143.
Tsai, H.T., & Huang, H.C. (2007). Determinants of e-repurchase intentions: An integrative model of quadruple retention drivers. Information & Management, 44(3), 231-239.
Tung, F.C., Lee, M.S, Chen, C.C., & Hsu, Y.S. (2009). An extension of financial cost and TAM model with IDT for exploring users’ behavioral intentions to use the CRM information system. Social Behavior & Personality, 37(5), 621-626.
Urban, G., & Hauser, J.R. (2004).‘Listening in’ to find and explore new combinations of customer needs. Journal of Marketing, 68(2), 72–87.
Venkatesh, V., Brown, S.A., Maruping, L.M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483-502.
Venkatesh, V., Morris, M.G., & Davis, G.B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-47.
von Hippel, E., & Katz, R. (2002). Shifting innovation to users via toolkits. Management Science , 48(7), 821–833.
Wang, Y.S, Lin, H.H, & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), 157-179.
Wang, Y.S., Wu, M.C., & Wang, H.Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92–118.
Watson, N. (1997). Why we argue about virtual community: A case study of the phish. Net fan community. In S. Jones (Ed.), Virtual Culture, Thousand Oaks, CA: Sage Publications, 102-132.
Wood, S.L. (2001). Remote purchase environments: The influence of return policy leniency on two-stage decision processes. Journal of Marketing Research, 38(2), 157-169.
Wu, J.H., & Wang, S.C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42 (5), 719-29.
Wu, W.P., Chan, T.S., & Lau, H.H. (2008). Does consumers’ personal reciprocity affect future purchase intentions? Journal of Marketing Management, 24(3/4), 345-360.
Yi, M.Y., Fiedler, K.D., & Park, J. S. (2006). Understanding the role of individual innovativeness in the acceptance of it-based innovations: Comparative analyses of models and measures. Decision Sciences, 37(3), 393-426.
Yousafzai, S.Y., Pallister, J.G., & Foxall, G.R. (2005). Strategies for building and communicating trust in electronic banking: A field experiment. Psychology & Marketing, 22(2), 181-201.