Technology renewal, user resistance, user adoption: status quo bias theory revisited

Abstract

PurposeThe article provides a conceptual replication and enrichment of the status quo bias theory in the specific context of understanding IT department user resistance and user adoption. The findings can assist technology renewals and associated change management professionals to assess and plan the adoption and active usage of human resource systems.Design/methodology/approachThe authors used survey method to gather data. All items were based on prior literature. They administrated the survey to employees of GOODTECH (name changed), information systems (IS) department members, situated in France. They obtained 103 valid responses along with usage data from the system to run their path model, in order to validate the proposed research model.FindingsThe study offers an enriched user resistance model (URM) to understand why IT-savvy employees would resist or adopt new human resource tools. Apart from providing partial validity to status quo bias theory in the French context, the enriched model uses behavioral intention to use as an intermediate variable to explain the influence of two key constructs of the original theory: switching cost and switching benefits. This research provides a better explanatory power to understand the cause of user resistance and new IT use.Research limitations/implicationsThe sample size used in the study can be considered as a limitation, although power analysis reveals that the results are significant and valid. The context of the study is also limited to one country and to a specific type of IS implementation scenario. Since the purpose of the paper was to offer contextual theory enhancement, the findings are valid for this purpose.Practical implicationsDigital project managers are offered a framework to increase technology adoption of new human resource tools and evaluate how to reduce user resistance at times of technology renewals. Self-efficacy for change and colleagues’ opinion can indirectly impact behavioral intention to use via switching cost and switching benefit perceptions and thus reducing resistance perceptions as well as increasing adoption of new IT tools in post-implementation phases.Originality/valueThe paper enriches the well-established user resistance theory in IS domain in a context of human resource post-implementation phase by studying IT-savvy end user's perceptions. The paper demonstrates the need to integrate user adoption and user resistance variables in one parsimonious framework and extends support to emerging research on dual focus perspective.