Antecedents of the User Behavior for Online Businesses: A Case of Pakistan
Purpose: This study tries to investigate the antecedents of user behavior like purchase intentions and e-loyalty in the context of Pakistan. More specifically, it studies the relationship between perceived flow, perceived usefulness, perceived ease of use and the user behavior constructs which this study considers are e-loyalty and purchase intentions.
Design/Methodology/Approach: Primary Data is obtained through survey from 466 respondents and was analyzed through PLS-SEM approach.
Findings: Findings suggest that perceived flow and technological acceptance model constructs which are perceived ease of use and perceived usefulness have significant positive impact on the e-loyalty and purchase intentions in the developing economy like Pakistan.
Implications/Originality/Value: This study is a contribution to the literature acknowledging the importance of flow and technology acceptance model constructs as antecedents of user behavior for online businesses in the context of developing country like Pakistan. This study guides practitioners for designing such a website that make a user feel 'flow' situation while surfing their website. If they are able to make their visitors feel flow, they are more likely to generate purchase intention and develop e-loyalty for the e-vendor.
Article Analytics Summary
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS quarterly, 227-247. DOI: https://doi.org/10.2307/249577
Ajzen, I., & Driver, B. L. (1992). Application of the theory of planned behavior to leisure choice. Journal of leisure research, 24(3), 207. DOI: https://doi.org/10.1080/00222216.1992.11969889
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour.
Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing science, 12(2), 125-143. DOI: https://doi.org/10.1287/mksc.12.2.125
Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: a contingency framework. Psychology and Marketing, 20(2), 123-138. DOI: https://doi.org/10.1002/mar.10063
Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of management education, 24(1), 32-54. DOI: https://doi.org/10.1177/105256290002400104
Bai, B., Law, R., & Wen, I. (2008). The impact of website quality on customer satisfaction and purchase intentions: Evidence from Chinese online visitors. International Journal of Hospitality Management, 27(3), 391-402. DOI: https://doi.org/10.1016/j.ijhm.2007.10.008
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370. DOI: https://doi.org/10.2307/3250921
Boulding, W., Kalra, A., Staelin, R., & Zeithaml, V. A. (1993). A dynamic process model of service quality: from expectations to behavioral intentions. Journal of marketing research, 30(1), 7. DOI: https://doi.org/10.2307/3172510
Buttle, F., & Bok, B. (1996). Hotel marketing strategy and the theory of reasoned action. International Journal of Contemporary Hospitality Management, 8(3), 5-10. DOI: https://doi.org/10.1108/09596119610115943
Chang, H. H., Wang, Y.-H., & Yang, W.-Y. (2009). The impact of e-service quality, customer satisfaction and loyalty on e-marketing: Moderating effect of perceived value. Total Quality Management, 20(4), 423-443. DOI: https://doi.org/10.1080/14783360902781923
Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995-1001. DOI: https://doi.org/10.1016/j.chb.2012.01.001
Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15(5), 585-608. DOI: https://doi.org/10.1016/S0747-5632(99)00038-2
Chen, Y.-H., & Barnes, S. (2007). Initial trust and online buyer behaviour. Industrial Management & Data Systems, 107(1), 21-36. DOI: https://doi.org/10.1108/02635570710719034
Chiu, C.-M., Lin, H.-Y., Sun, S.-Y., & Hsu, M.-H. (2009). Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory. Behaviour & Information Technology, 28(4), 347-360. DOI: https://doi.org/10.1080/01449290801892492
Cyr, D., Bonanni, C., Bowes, J., & Ilsever, J. (2005). Beyond trust: Web site design preferences across cultures. Journal of Global Information Management (JGIM), 13(4), 25-54. DOI: https://doi.org/10.4018/jgim.2005100102
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. DOI: https://doi.org/10.2307/249008
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. DOI: https://doi.org/10.1287/mnsc.35.8.982
Evanschitzky, H., Iyer, G. R., Hesse, J., & Ahlert, D. (2004). E-satisfaction: a re-examination. Journal of retailing, 80(3), 239-247. DOI: https://doi.org/10.1016/j.jretai.2004.08.002
Fisk, R. P., Patricio, L., Lin, J.-S. C., & Chang, H.-C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424-444. DOI: https://doi.org/10.1108/09604521111146289
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50. DOI: https://doi.org/10.1177/002224378101800104
Gopalakrishna, P., & Mummalaneni, V. (1993). Influencing satisfaction for dental services. Marketing Health Services, 13(1), 16.
Gremler, D. D. (1995). The effect of satisfaction, switching costs, and interpersonal bonds on service loyalty. Arizona State University Tempe, AZ.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6): Pearson Prentice Hall Upper Saddle River, NJ.
Heskett, J., Sasser, W. E., & Schlesinger, L. A. (1997). The Service Profit Chain: How Leading Companies Link Profit and Growth to Loyalty, Satisfaction, and Value (Цепочка создания прибыли в сфере услуг: как ведущие компании связывают прибыль и рост с лояльностью, удовлетворением и ценностью).
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: conceptual foundations. The Journal of Marketing, 50-68. DOI: https://doi.org/10.1177/002224299606000304
Hsu, C.-L., Chang, K.-C., & Chen, M.-C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and e-Business Management, 10(4), 549-570. DOI: https://doi.org/10.1007/s10257-011-0181-5
Hsu, C.-L., & Lu, H.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868. DOI: https://doi.org/10.1016/j.im.2003.08.014
Hsu, C.-L., Wu, C.-C., & Chen, M.-C. (2013). An empirical analysis of the antecedents of e-satisfaction and e-loyalty: focusing on the role of flow and its antecedents. Information Systems and e-Business Management, 11(2), 287-311. DOI: https://doi.org/10.1007/s10257-012-0194-8
Hsu, M.-H., Yen, C.-H., Chiu, C.-M., & Chang, C.-M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 64(9), 889-904. DOI: https://doi.org/10.1016/j.ijhcs.2006.04.004
Ju Rebecca Yen, H., & Gwinner, K. P. (2003). Internet retail customer loyalty: the mediating role of relational benefits. International Journal of Service Industry Management, 14(5), 483-500. DOI: https://doi.org/10.1108/09564230310500183
Kabadayi, S., & Gupta, R. (2005). Website loyalty: an empirical investigation of its antecedents. International Journal of Internet Marketing and Advertising, 2(4), 321-345. DOI: https://doi.org/10.1504/IJIMA.2005.008105
Kim, D. J. (2012). An investigation of the effect of online consumer trust on expectation, satisfaction, and post-expectation. Information Systems and e-Business Management, 10(2), 219-240. DOI: https://doi.org/10.1007/s10257-010-0136-2
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223. DOI: https://doi.org/10.1287/isre.188.8.131.52
Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110. DOI: https://doi.org/10.1016/j.chb.2008.07.007
Lee, H., Choi, S. Y., & Kang, Y. S. (2009). Formation of e-satisfaction and repurchase intention: Moderating roles of computer self-efficacy and computer anxiety. Expert Systems with Applications, 36(4), 7848-7859. DOI: https://doi.org/10.1016/j.eswa.2008.11.005
Lee, M.-C., & Tsai, T.-R. (2010). What drives people to continue to play online games? An extension of technology model and theory of planned behavior. Intl. Journal of Human–Computer Interaction, 26(6), 601-620. DOI: https://doi.org/10.1080/10447311003781318
Lin, C.-P., & Ding, C. G. (2005). Opening the black box: assessing the mediating mechanism of relationship quality and the moderating effects of prior experience in ISP service. International Journal of Service Industry Management, 16(1), 55-80. DOI: https://doi.org/10.1108/09564230510587159
Lin, H.-F. (2008). Antecedents of virtual community satisfaction and loyalty: an empirical test of competing theories. CyberPsychology & Behavior, 11(2), 138-144. DOI: https://doi.org/10.1089/cpb.2007.0003
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39. DOI: https://doi.org/10.1016/j.chb.2008.06.002
Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of consumer research, 31(2), 324-332. DOI: https://doi.org/10.1086/422111
Novak, T. P., Hoffman, D. L., & Yung, Y.-F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing science, 19(1), 22-42. DOI: https://doi.org/10.1287/mksc.184.108.40.20684
Nunnally, J. (1978). Psychometric theory. Mc Graw-Hill Publ Co. New York.
O'Cass, A., & Carlson, J. (2010). Examining the effects of website-induced flow in professional sporting team websites. Internet Research, 20(2), 115-134. DOI: https://doi.org/10.1108/10662241011032209
Oliver, R. L. (1999). Whence consumer loyalty? The Journal of Marketing, 33-44. DOI: https://doi.org/10.2307/1252099
Schefter, P., & Reichheld, F. (2000). E-loyalty: your secret weapon on the Web. Harvard Business Review, 78(4), 105-113.
Shankar, V., Smith, A. K., & Rangaswamy, A. (2003). Customer satisfaction and loyalty in online and offline environments. International journal of research in marketing, 20(2), 153-175. DOI: https://doi.org/10.1016/S0167-8116(03)00016-8
Shih, H.-P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368. DOI: https://doi.org/10.1016/S0378-7206(03)00079-X
Shin, N. (2006). Online learner’s ‘flow’experience: an empirical study. British Journal of Educational Technology, 37(5), 705-720. DOI: https://doi.org/10.1111/j.1467-8535.2006.00641.x
Srinivasan, S. S., Anderson, R., & Ponnavolu, K. (2002). Customer loyalty in e-commerce: an exploration of its antecedents and consequences. Journal of retailing, 78(1), 41-50. DOI: https://doi.org/10.1016/S0022-4359(01)00065-3
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176. DOI: https://doi.org/10.1287/isre.6.2.144
Tsai, H. T., Huang, H. C., Jaw, Y. L., & Chen, W. K. (2006). Why on‐line customers remain with a particular e‐retailer: An integrative model and empirical evidence. Psychology & Marketing, 23(5), 447-464. DOI: https://doi.org/10.1002/mar.20121
Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 9(4), 411-426. DOI: https://doi.org/10.1016/0747-5632(93)90032-N
Westbrook, R. A. (1981). Sources of consumer satisfaction with retail outlets. Journal of retailing, 57(3), 68-85.
Wu, J.-J., & Chang, Y.-S. (2005). Towards understanding members' interactivity, trust, and flow in online travel community. Industrial Management & Data Systems, 105(7), 937-954. DOI: https://doi.org/10.1108/02635570510616120
Zeithaml, V. A. (2000). Service quality, profitability, and the economic worth of customers: what we know and what we need to learn. Journal of the academy of marketing science, 28(1), 67-85. DOI: https://doi.org/10.1177/0092070300281007
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. The Journal of Marketing, 31-46. DOI: https://doi.org/10.1177/002224299606000203
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883-889. DOI: https://doi.org/10.1016/j.chb.2010.11.013
CSRC Publishing and JBSEE adhere to Creative Commons Attribution-Non Commercial 4.0 International License. The authors submitting and publishing in JBSEE agree to the copyright policy under creative common license 4.0 (Attribution-Non Commercial 4.0 International). Under this license, the authors published in JBSEE retain the copyright including publishing rights of their scholarly work and agree to let others remix, tweak, and build upon their work non-commercially. All other authors using the content of SBSEE are required to cite author(s) and publisher in their work. CSRC Publishing and JBSEE follow an Open Access Policy for copyright and licensing.