Antecedents of the User Behavior for Online Businesses: A Case of Pakistan

  • Lutf Ullah Bahauddin Zakariya University, Multan Pakistan
  • Muhammad Amjad Khan University of Punjab, Lahore, Pakistan
Keywords: Perceived flow, e-loyalty, technology acceptance model, purchase intentions, online businesses


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.


Download data is not yet available.

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:

Ajzen, I., & Driver, B. L. (1992). Application of the theory of planned behavior to leisure choice. Journal of leisure research, 24(3), 207. DOI:

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:

Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: a contingency framework. Psychology and Marketing, 20(2), 123-138. DOI:

Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of management education, 24(1), 32-54. DOI:

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:

Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370. DOI:

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:

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:

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:

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:

Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15(5), 585-608. DOI:

Chen, Y.-H., & Barnes, S. (2007). Initial trust and online buyer behaviour. Industrial Management & Data Systems, 107(1), 21-36. DOI:

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:

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:

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. DOI:

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:

Evanschitzky, H., Iyer, G. R., Hesse, J., & Ahlert, D. (2004). E-satisfaction: a re-examination. Journal of retailing, 80(3), 239-247. DOI:

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:

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50. DOI:

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:

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:

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:

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:

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:

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:

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:

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:

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223. DOI:

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:

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:

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:

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:

Lin, H.-F. (2008). Antecedents of virtual community satisfaction and loyalty: an empirical test of competing theories. CyberPsychology & Behavior, 11(2), 138-144. DOI:

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:

Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of consumer research, 31(2), 324-332. DOI:

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:

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:

Oliver, R. L. (1999). Whence consumer loyalty? The Journal of Marketing, 33-44. DOI:

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:

Shih, H.-P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368. DOI:

Shin, N. (2006). Online learner’s ‘flow’experience: an empirical study. British Journal of Educational Technology, 37(5), 705-720. DOI:

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:

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176. DOI:

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:

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:

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:

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:

Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. The Journal of Marketing, 31-46. DOI:

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:

How to Cite
Ullah, L., & Khan, M. A. (2017). Antecedents of the User Behavior for Online Businesses: A Case of Pakistan. Journal of Business and Social Review in Emerging Economies, 3(2), 199-208.