Understanding determinants of information systems users’ behaviour: a comparison of two models in the context of integrated accounting and budgeting software

References

• Ajzen, I. and Fishbein, M., 1980. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Ajzen, I., 1991. The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50 (2), 179–211. doi: 10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Anderson, E. W. and Sullivan, M. W., 1993. The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12 (2), 125–143. doi: 10.1287/mksc.12.2.125
   Web of Science ®Google Scholar
• Bagozzi, R. P. and Phillips, L. W., 1982. Representing and testing organizational theories: a holistic construal. Administrative Science Quarterly, 27 (3), 459–489. doi: 10.2307/2392322
   Web of Science ®Google Scholar
• Bhattacherjee, A., 2001. Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25 (3), 351–370. doi: 10.2307/3250921
   Web of Science ®Google Scholar
• Bhattacherjee, A., Perols, J. and Sanford, C., 2008. Information technology continuance: a theoretic extension and empirical test. Journal of Computer Information Systems, 49 (1), 17–26.
   Web of Science ®Google Scholar
• Bolton, R. N., Kannan, R. K. and Bramlett, M. D., 2000. Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science, 28 (1), 95–108. doi: 10.1177/0092070300281009
   Web of Science ®Google Scholar
• Bolton, R. N., Lemon, K. N. and Verhoef, P. C., 2004. The theoretical underpinnings of customer asset management: a framework and propositions for future research. Journal of the Academy of Marketing Science, 32 (3), 271–292. doi: 10.1177/0092070304263341
   Web of Science ®Google Scholar
• Chin, W. W., Marcolin, B. L. and Newsted, P. R., 2003. A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14 (2), 189–217. doi: 10.1287/isre.14.2.189.16018
   Web of Science ®Google Scholar
• Chou, S.-W., 2010. Understanding continuance intention of knowledge creation using extended expectation-confirmation theory: an empirical study of Taiwan and China online communities. Behaviour & Information Technology, 29 (6), 557–570. doi: 10.1080/01449290903401986
   Web of Science ®Google Scholar
• Dabholkar, P. A., Shepherd, C. D. and Thorpe, D. I., 2000. A comprehensive framework for service quality: an investigation of critical conceptual and measurement issues through a longitudinal study. Journal of Retailing, 76 (2), 139–173. doi: 10.1016/S0022-4359(00)00029-4
   Web of Science ®Google Scholar
• Davis, F. D., 1986. Technology acceptance model for empirically testing new end-user information systems: theory and results. Thesis (PhD). Massachusetts Institute of Technology
   Google Scholar
• Davis, F. D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319–340. doi: 10.2307/249008
   Web of Science ®Google Scholar
• Davis, F. D., Bagozzi, R. P. and Warshaw, P. R., 1989. User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35 (8), 982–1003. doi: 10.1287/mnsc.35.8.982
   Web of Science ®Google Scholar
• Fishbein, M. and Ajzen, I., 1975. Belief, attitude, intention, and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.
   Google Scholar
• Fornell, C. and Larcker, D. F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39–50. doi: 10.2307/3151312
   Web of Science ®Google Scholar
• Henseler, J., 2010. On the convergence of the partial least squares path modeling algorithm. Computational Statistics, 25 (1), 107–120. doi: 10.1007/s00180-009-0164-x
   Web of Science ®Google Scholar
• Hong, S.-J., Thong, J. Y.L. and Tam, K. Y., 2006. Understanding continued information technology usage behavior: a comparison of three models in the context of mobile internet. Decision Support Systems, 42 (3), 1819–1834. doi: 10.1016/j.dss.2006.03.009
   Web of Science ®Google Scholar
• Hsu, M. H., Chiu, C. M. and Ju, T. L., 2004. Determinants of continued use of the WWW: an integration of two theoretical models. Industrial Management & Data System, 104 (9), 766–775. doi: 10.1108/02635570410567757
   Web of Science ®Google Scholar
• Jasperson, J., Carter, P. E. and Zmud, R. W., 2005. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29 (3), 525–557.
   Web of Science ®Google Scholar
• Jin, X.-L., Lee, M. K.O. and Cheung, C. M.K., 2010. Predicting continuance in online communities: model development and empirical test. Behaviour & Information Technology, 29 (4), 383–394. doi: 10.1080/01449290903398190
   Web of Science ®Google Scholar
• Karahanna, E., Straub, D. W. and 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. doi: 10.2307/249751
   Web of Science ®Google Scholar
• Krejcie, R. V. and Morgan, D. W., 1970. Determining sample size for research activities. Educational and Psychological Measurement, 30 (3), 607–610.
   Web of Science ®Google Scholar
• Lee, Y., Kozar, K. A. and Larsen, K. R.T., 2003. The technology acceptance model: past, present, and future. Communications of the AIS, 12 (50), 752–780.
   Google Scholar
• Legris, P., Ingham, J. and Collerette, P., 2003. Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40 (3), 191–204. doi: 10.1016/S0378-7206(01)00143-4
   Web of Science ®Google Scholar
• Limayem, M. and Cheung, C. M.K., 2011. Predicting the continued use of Internet-based learning technologies: the role of habit. Behaviour & Information Technology, 30 (1), 91–99. doi: 10.1080/0144929X.2010.490956
   Web of Science ®Google Scholar
• Lin, C. S., Wu, S. and Tsai, R. J., 2005. Integrating perceived playfulness into expectation-confirmation model for web portal context. Information & Management, 42 (5), 683–693. doi: 10.1016/j.im.2004.04.003
   Web of Science ®Google Scholar
• Lin, H.-F., 2009. Examination of cognitive absorption influencing the intention to use a virtual community. Behaviour & Information Technology, 28 (5), 421–431. doi: 10.1080/01449290701662169
   Web of Science ®Google Scholar
• Martínez-Torres, M. R., 2008. A technological acceptance of e-learning tools used in practical and laboratory teaching, according to the European higher education area. Behaviour & Information Technology, 27 (6), 495–505. doi: 10.1080/01449290600958965
   Web of Science ®Google Scholar
• Nisbet, S. L., 2006. Modelling consumer intention to use gambling technologies: an innovative approach. Behaviour & Information Technology, 25 (3), 221–231. doi: 10.1080/01449290500167840
   Web of Science ®Google Scholar
• Oliver, R. L., 1980. A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17 (4), 460–469. doi: 10.2307/3150499
   Web of Science ®Google Scholar
• Oliver, R. L., 1993. Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20 (3), 418–430. doi: 10.1086/209358
   Web of Science ®Google Scholar
• Parthasarathy, M. and Bhattacherjee, A., 1998. Understanding post-adoption behavior in the context of online services. Information Systems Research, 9 (4), 362–379. doi: 10.1287/isre.9.4.362
   Web of Science ®Google Scholar
• Patterson, P. G., Johnson, L. W. and Spreng, R. A., 1997. Modeling the determinants of customer satisfaction for business-to-business professional services. Journal of the Academy of Marketing Science, 25 (1), 4–17. doi: 10.1007/BF02894505
   Web of Science ®Google Scholar
• Premkumar, G. and Bhattacherjee, A., 2008. Explaining information technology usage: a test of competing models. Omega, 36 (1), 64–75. doi: 10.1016/j.omega.2005.12.002
   Web of Science ®Google Scholar
• Recker, J., 2010. Explaining usage of process modeling grammars: comparing three theoretical models in the study of two grammars. Information & Management, 47 (5-6), 316–324. doi: 10.1016/j.im.2010.06.006
   Web of Science ®Google Scholar
• Reichheld, F. F. and Sasser, W. E., 1990. Zero defections: quality comes to services. Harvard Business Review, 68 (5), 105–111.
   PubMed Web of Science ®Google Scholar
• Reichheld, F. F., 2001. Lead for loyalty. Harvard Business Review, 79 (7), 76–84.
   PubMed Web of Science ®Google Scholar
• Ringle, C. M., Wende, S. and Will, A., 2005. SmartPLS 2.0. Hamburg: University of Hamburg, available at http://www.smartpls.de (accessed 30 April 2009)
   Google Scholar
• Rogers, E. M., 1995. Diffusion of innovations. 4th ed. New York: Free Press.
   Google Scholar
• Seyal, A. H. and Pijpers, G. G.M., 2004. Senior government executives’ use of the internet: a Bruneian scenario. Behaviour & Information Technology, 23 (3), 197–210. doi: 10.1080/01449290410001669978
   Web of Science ®Google Scholar
• Shih, Y.-Y., 2006. The effect of computer self-efficacy on enterprise resource planning usage. Behaviour & Information Technology, 25 (5), 407–411. doi: 10.1080/01449290500168103
   Web of Science ®Google Scholar
• Spreng, R. A., MacKenzie, S. B. and Olshavsky, R. W., 1996. A reexamination of the determinants of consumer satisfaction. Journal of Marketing, 60 (3), 15–32. doi: 10.2307/1251839
   Web of Science ®Google Scholar
• Stair, R. M. and Reynolds, G. W., 2010. Principles of information systems: a managerial approach. 9th ed. Boston, Massachusetts: Course Technology Cengage Learning
   Google Scholar
• Staples, D. S., Wong, I. and Seddon, P. B., 2002. Having expectations of information systems benefits that match received benefits: does it really matter?. Information & Management, 40 (2), 115–131. doi: 10.1016/S0378-7206(01)00138-0
   Web of Science ®Google Scholar
• Susarla, A., Barua, A. and Whinston, A. B., 2003. Understanding the service component of application service provision: an empirical analysis of satisfaction with ASP services. MIS Quarterly, 27 (1), 91–123.
   Web of Science ®Google Scholar
• Swan, J. E. and Trawick, I. F., 1981. Disconfirmation of expectations and satisfaction with a retail service. Journal of Retailing, 57 (3), 49–67.
   Web of Science ®Google Scholar
• Szajna, B. and Scamell, R. W., 1993. The effects of information system user expectations on their performance and perceptions. MIS Quarterly, 17 (4), 493–516. doi: 10.2307/249589
   Web of Science ®Google Scholar
• Taylor, S. and Todd, P. A., 1995. Understanding information technology usage: a test of competing models. Information Systems Research, 6 (2), 144–176. doi: 10.1287/isre.6.2.144
   Web of Science ®Google Scholar
• Tenenhausa, M., 2005. PLS path modelling. Computational Statistics & Data Analysis, 48159–205. doi: 10.1016/j.csda.2004.03.005
   Web of Science ®Google Scholar
• Thong, J. Y.L., Hong, S.-J. and Tam, K. Y., 2006. The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human–Computer Studies, 64 (9), 799–810. doi: 10.1016/j.ijhcs.2006.05.001
   Web of Science ®Google Scholar
• Tse, D. K. and Wilton, P. C., 1988. Models of consumer satisfaction formation: an extension. Journal of Marketing Research, 25 (2), 204–212. doi: 10.2307/3172652
   Web of Science ®Google Scholar
• Wu, I.-L. and Wu, K.-W., 2005. A hybrid technology acceptance approach for exploring e-CRM adoption in organizations. Behaviour & Information Technology, 24 (4), 303–316. doi: 10.1080/0144929042000320027
   Web of Science ®Google Scholar
• Wu, J.-H., Chen, Y.-C. and Lin, L.-M., 2007. Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 23 (1), 162–174. doi: 10.1016/j.chb.2004.04.003
   Web of Science ®Google Scholar