A Stage Model for Uncovering Inertia in Big Data Analytics Adoption

Patrick Mikalef, John Krogstie, Rogier van de Wetering, Ilias Pappas

Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review


Big data and analytics have been credited with being a revolution that will radically transform the way firms do business. Nevertheless, the process of adopting and diffusing big data analytics, as well as actions taken in response to generated insight, require organizational transformation. Yet, as with any form of organizational transformation, there are multiple inhibiting factors that threaten successful change. The purpose of this study is to examine the inertial forces that can hamper the value of big data analytics throughout this process. We draw on a multiple case study approach of 27 firms to examine this question. Building on a stage model of adoption, our findings suggest that inertia is present in different forms, including economic, political, socio-cognitive, negative psychology, and socio- technical. The ways in which firms attempt to mitigate these forces of inertia is elaborated on, and best practices are presented. We conclude the paper by discussing the implications that these findings have for both research and practice.
Original languageEnglish
Title of host publicationProceedings of the Pacific Asia Conference on Information Systems (PACIS) 2018
Subtitle of host publicationOpportunities and Challenges for the Digitized Society: Are We Ready?
EditorsMotonari Tanabu, Dai Senoo
Place of PublicationYokohama, Japan
Number of pages14
ISBN (Electronic)9784902590838
Publication statusPublished - 2018
EventPacific Asia Conference on Information Systems - Yokohama, Japan
Duration: 26 Jun 201826 Jun 2018


ConferencePacific Asia Conference on Information Systems
Abbreviated titlePACIS 2018
Internet address


  • Big data analytics
  • Deployment
  • IT-enabled transformation
  • Inertia
  • Organizational transformation


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