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Physicians' resistance toward healthcare information technology: a theoretical model and empirical test

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  • Anol Bhattacherjee
  • Neset Hikmet

Abstract

This paper presents a theoretical model of physician resistance of healthcare information technology (HIT) usage by integrating the technology acceptance and resistance to change literatures, using a dual-factor model of technology usage. This model elaborates the interdependent and asymmetric effects of inhibiting usage perceptions, such as resistance, on HIT usage intentions relative to enabling perceptions, such as perceived usefulness and perceived ease of use. It also proposes perceived threat as a predictor of resistance, perceived compatibility as predicting perceived usefulness, and related knowledge as predicting perceived ease of use. The resulting model is empirically supported using a field survey of a computerized physician order entry system among 129 practicing physicians at a large acute-care hospital. Our study illustrates the importance of incorporating user resistance in technology usage studies in general and HIT usage studies in particular, grounds resistance research within extant theories of technology usage, and provides a preliminary model of resistance that can serve as the starting point for future research in this relatively unexplored yet potentially fertile area of research.

Suggested Citation

  • Anol Bhattacherjee & Neset Hikmet, 2007. "Physicians' resistance toward healthcare information technology: a theoretical model and empirical test," European Journal of Information Systems, Taylor & Francis Journals, vol. 16(6), pages 725-737, December.
    • Handle: RePEc:taf:tjisxx:v:16:y:2007:i:6:p:725-737
    DOI: 10.1057/palgrave.ejis.3000717
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    Cited by:

    1. Hung-Pin Shih & Wuqiang Liu, 2023. "Beyond the trade-offs on Facebook: the underlying mechanisms of privacy choices," Information Systems and e-Business Management, Springer, vol. 21(2), pages 353-387, June.
    2. Mario Saba & Peter Bou Saba & Antoine Harfouche, 2018. "Hidden facets of IT projects are revealed only after deployment," Post-Print hal-04263515, HAL.
    3. Na, Eunkyung & Jung, Yoonhyuk & Kim, Seongcheol, 2023. "How do care service managers and workers perceive care robot adoption in elderly care facilities?," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    4. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    5. Huigang Liang & Yajiong Xue, 2022. "Save Face or Save Life: Physicians’ Dilemma in Using Clinical Decision Support Systems," Information Systems Research, INFORMS, vol. 33(2), pages 737-758, June.

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