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E-learning technology and higher education: the impact of organizational trust

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Abstract

The aim of this paper is to analyze the impact of trust perceptions on teachers’ intention to continue using e-learning technology in higher education. Drawing on the model of organizational trust and the information systems continuance model, a new research model is developed and tested using data from a university college based on a survey of 401 university teachers. We find that teachers’ perceptions of system-based trust and trust in management exerted strong direct effects on intention to continue using an e-learning system. Additionally, system-based trust affects perceived usefulness, and thus fully mediates the influence of perceived usefulness on teachers’ intentions to use e-learning technology. Our findings clarify the relationship between trust and teachers continued use of e-learning technology and have implications, theoretical as well as practical, for trust-building structures that could improve the implementation of e-learning technologies in higher educational settings.

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References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

    Google Scholar 

  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Belanche, D., Casalò, L., Flavian, C., & Schepers, J. (2014). Trust transfer in the continued usage of public e-services. Information & Management, 51, 627–640.

    Google Scholar 

  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25, 351–370.

    Google Scholar 

  • Bhattacherjee, A., & Lin, C. -P. (2014). A unified model of IT continuance: Three complementary perspectives and crossover effects. European Journal of Information Systems, 1–10.

    Google Scholar 

  • Bøe, T., Gulbrandsen, B., & Sørebø, Ø. (2015). How to stimulate the continued use of ICT in higher education: Integrating information systems continuance theory and agency theory. Computers in Human Behavior, 50, 375–384.

    Google Scholar 

  • Bradach, J., & Eccles, R. (1989). Price, authority, and trust: from ideal types to plural forms. Annual Review of Sociology, 75, 97–118.

    Google Scholar 

  • Chai, S., & Kim, M. (2010). What makes bloggers share knowledge? An investigation on the role of trust. Journal of Information Management, 30, 408–415.

    Google Scholar 

  • Chircu, A., Davis, G., & Kaufann, R. (2000). Trust, expertise and e-commerce intermediary adoption. Proceedings of the sixth American conference on information systems, Long Beach, CA.

    Google Scholar 

  • Davis, F. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13, 319–340.

    Google Scholar 

  • Egea, J., & Gonzalez, M. (2010). Explaining physicians’ acceptance of EHCR systems: An extension of TAM with trust and risk factors. Computers in Human Behavior, 319–332.

    Google Scholar 

  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(2), 451–474.

    Google Scholar 

  • Fornell, C. D., & Lacker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Market Research, 18(Feb.), 39–50.

    Google Scholar 

  • Gefen, D. (2000). The role of familiarity and trust. Omega, 28(2), 725–737.

    Google Scholar 

  • Gefen, D., Karahanna, E., & Straub, D. (2003). Trust&TAM in online-shopping. MIS Quarterly, 27(1), 51–90.

    Google Scholar 

  • Greenberg, R. (2008). Culture and consumer trust in online businesses. Journal of Global Information Management, 76(2), 26–44.

    Google Scholar 

  • Harris, L., & Goode, M. (2004). The four levels of loyalty and the pivotal role of the trust: A study of online service dynamics. Journal of Retail, 80, 139–158.

    Google Scholar 

  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.

    Google Scholar 

  • Hernández-Ortega, B. (2011). The role of post-use trust in the acceptance of a te4chnology: Drivers and consequences. Technovation, 31, 523–538.

    Google Scholar 

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Google Scholar 

  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20, 195–204.

    Google Scholar 

  • Hung, M. C., Chang, I. C., & Hwang, H. G. (2011). Exploring academic teachers’ continuance toward the web-based learning system:The role of causal attributions. Computers & Education, 57(2), 1530–1543.

    Google Scholar 

  • Islam, N. A. (2011). Extending information system continuance theory with system quality in e-learning context. AMCIS Proceedings. AIS Electronic Library.

    Google Scholar 

  • Islam, N. A. (2012). The role of perceived system quality as educators’ motivation to continue e-learning system use. Transactions on Human-Computer Interaction, 4(2), 25–43.

    Google Scholar 

  • Kim, Y. J., Chun, J. U., & Song, J. (2009). Investigating the role of attitude in technology acceptance from an attitude strength perspective. International Journal of Information Management, 29, 67–77.

    Google Scholar 

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

    Google Scholar 

  • Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human Behavior, 25, 778–784.

    Google Scholar 

  • Laugesen, J. (2012). The role of confirmation in IS continuance theory: A comprehensive meta-analysis. International Conference on Information Systems, 1–20.

    Google Scholar 

  • Lee, J., & See, K. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 420, 50–80.

    Google Scholar 

  • Lee, M., & Turban, E. (2001). A trust model for consumer internet shopping. International journal of Electronics and Communications, 6(2), 75–91.

    Google Scholar 

  • Li, X., Hess, T. J., & Valacich, J. S. (2008). Why do we trust new technology? A study of initial trust formation with organizational information systems. Journal of Strategic Information Systems, 77(2), 39–71.

    Google Scholar 

  • Luo, X., Li, H., Zhang, J., & Shim, J. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222–234.

    Google Scholar 

  • Mayer, R., Davis, J., & Schoorman, F. (1995). An integrative model of organizational trust. Academy of Management Review, 20(2), 709–734.

    Google Scholar 

  • McKnight, D. H. (2005). Trust in information technology. In G. B. Davis (Ed.), The Blackwell encyclopedia of management (pp. 329–331). Maiden: Blackwell.

    Google Scholar 

  • McKnight, D. H., & Chervany, N. L. (2002). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International Journal of Electronics and Communications, 6(2), 35–59.

    Google Scholar 

  • McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce, an integrative typology. Information Systems Research, 73(2), 3343–3359.

    Google Scholar 

  • Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information technology continuance intention: A systematic literature review. International Journal of E-Business Research, 72(1), 58–95.

    Google Scholar 

  • Oliver, R. L. (1981). Measurement and evaluation of satisfaction process in retailer selling. Journal of Retailing, 77, 25–48.

    Google Scholar 

  • Ornes, H. (2015). Digital tilstand 2014 - Norgesuniversitetets monitor. Tromsø: Norgesuniversitetet.

    Google Scholar 

  • Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(2), 101–134.

    Google Scholar 

  • Pavlou, P., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information System Research, 75(2), 37–59.

    Google Scholar 

  • Ratnasingham, P., & Pavlou, P. (2002). Technology trust: The next value creator in B2B electronic commerce. IRMA International Conference, Seattle, WA.

    Google Scholar 

  • Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH. Retrieved from https://doi.org/www.smartpls.com

    Google Scholar 

  • Salon, J., & Karjaluoto, H. (2007). A conceptual model of trust in the online environment. Online Information Review, 31, 604–621.

    Google Scholar 

  • Shankar, V., Urban, G., & Sultan, F. (2002). Online trust: A stakeholder perspective, concepts, implications, and future directions. The Journal of Strategic Information Systems, 11(3), 325–344.

    Google Scholar 

  • Sørebø, Ø., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology. Computers & Education, 53, 1177–1187.

    Google Scholar 

  • Spreng, R. A., & Mackoy, R. D. (1996). An empirical examination of a model of perceived service quality and satisfaction. Journal of Retailing, 72(2), 201–214.

    Google Scholar 

  • Suh, B., & Han, I. (2003). The impact of customer trust and perception of security control on the acceptance of electronic commerce. International Journal of Electronics and Communications, 7(3), 135–161.

    Google Scholar 

  • Teo, T., & Liu, J. (2007). Consumer trust in e-commerce in the United States, Singapore, and China. Omega, 35, 22–38.

    Google Scholar 

  • Vatanasombut, B., Igbaria, M., Stylianou, A., & Rodgers, W. (2008). Information systems continuance intention of web-based applications customers: The case of on-line banking. Information Management, 45, 419–428.

    Google Scholar 

  • Warkentin, M., Gefen, D., Pavlou, P., & Rose, G. (2002). Encouraging citizen adoption of e-government by building trust. Electronic Markets, 72(2), 371–391.

    Google Scholar 

  • Wu, I., & Chen, J. (2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 62(2), 784–808.

    Google Scholar 

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Correspondence to Tove Bøe.

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Bøe, T. E-learning technology and higher education: the impact of organizational trust. Tert Educ Manag 24, 362–376 (2018). https://doi.org/10.1080/13583883.2018.1465991

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