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IS Avoidance in Health-Care Groups: A Multilevel Investigation

Author

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  • Gerald C. Kane

    () (Carroll School of Management, Boston College, Chestnut Hill, Massachusetts 02467)

  • Giuseppe (Joe) Labianca

    () (Gatton School of Business and Economics, University of Kentucky, Lexington, Kentucky 40506)

Abstract

The information systems (IS) literature has focused considerable research on IS resistance, particularly in the health-care industry. Most of this attention has focused on the impact of IS resistance on systems' initial implementation, but little research has investigated whether and how post-adoption resistance affects performance. We focus on a particular type of post-adoption resistance, which we call IS avoidance , to identify situations in which individuals avoid working with adopted IS despite the need and opportunity to do so. We examine the effects of IS avoidance on patient care delivered by health-care groups across three levels of analysis: the individual level, the shared group level, and the configural group level. We find that IS avoidance is significantly and negatively related to patient care only at the configural group level, which suggests that patient care is not degraded by the number of doctors and/or nurses in a group avoiding a system, but rather by their locations in the group's workflow network configuration. We use qualitative data collected over 16 months at the research site to help explain these results. Implications for theory and practice are discussed.

Suggested Citation

  • Gerald C. Kane & Giuseppe (Joe) Labianca, 2011. "IS Avoidance in Health-Care Groups: A Multilevel Investigation," Information Systems Research, INFORMS, vol. 22(3), pages 504-522, September.
  • Handle: RePEc:inm:orisre:v:22:y:2011:i:3:p:504-522
    DOI: 10.1287/isre.1100.0314
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    File URL: http://dx.doi.org/10.1287/isre.1100.0314
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Meng Zhang & Guy G. Gable, 2017. "A Systematic Framework for Multilevel Theorizing in Information Systems Research," Information Systems Research, INFORMS, vol. 28(2), pages 203-224, June.
    2. Verstegen, Luuk & Houkes, Wybo & Reymen, Isabelle, 2019. "Configuring collective digital-technology usage in dynamic and complex design practices," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    3. Patrícia Lopes Costa & Ana Margarida Graça & Pedro Marques-Quinteiro & Catarina Marques Santos & António Caetano & Ana Margarida Passos, 2013. "Multilevel Research in the Field of Organizational Behavior," SAGE Open, , vol. 3(3), pages 21582440134, August.
    4. Yu-Kai Lin & Mingfeng Lin & Hsinchun Chen, 2019. "Do Electronic Health Records Affect Quality of Care? Evidence from the HITECH Act," Service Science, INFORMS, vol. 30(1), pages 306-318, March.
    5. Niam Yaraghi & Anna Ye Du & Raj Sharman & Ram D. Gopal & Ram Ramesh, 2015. "Health Information Exchange as a Multisided Platform: Adoption, Usage, and Practice Involvement in Service Co-Production," Information Systems Research, INFORMS, vol. 26(1), pages 1-18, March.
    6. Xu, Zhuo, 2019. "An empirical study of patients' privacy concerns for health informatics as a service," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 297-306.
    7. H. Colleen Stuart, 2017. "Structural Disruption, Relational Experimentation, and Performance in Professional Hockey Teams: A Network Perspective on Member Change," Organization Science, INFORMS, vol. 28(2), pages 283-300, April.

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