Advertisement

Big Data Enabled Organizational Transformation: The Effect of Inertia in Adoption and Diffusion

  • Patrick Mikalef
  • Rogier van de Wetering
  • John Krogstie
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 320)

Abstract

Big data and analytics have been credited with being a revolution that will radically transform the way firms operate and conduct business. Nevertheless, the process of adopting and diffusing big data analytics, as well as actions taken in response to generated insight, necessitate organizational transformation. Nevertheless, 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. 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.

Keywords

Big data analytics Organizational transformation Inertia Deployment IT-enabled transformation 

Notes

Acknowledgments

Open image in new window This project has received funding from the European Union’s Horizon 2020 research and innovation programme, under the Marie Sklodowska-Curie grant agreement No. 704110.

References

  1. 1.
    Gupta, M., George, J.F.: Toward the development of a big data analytics capability. Inf. Manag. 53, 1049–1064 (2016)CrossRefGoogle Scholar
  2. 2.
    Prescott, M.: Big data and competitive advantage at Nielsen. Manag. Decis. 52, 573–601 (2014)CrossRefGoogle Scholar
  3. 3.
    Sydow, J., Schreyögg, G., Koch, J.: Organizational path dependence: opening the black box. Acad. Manag. Rev. 34, 689–709 (2009)Google Scholar
  4. 4.
    Vidgen, R., Shaw, S., Grant, D.B.: Management challenges in creating value from business analytics. Eur. J. Oper. Res. 261, 626–639 (2017)CrossRefGoogle Scholar
  5. 5.
    McAfee, A., Brynjolfsson, E., Davenport, T.H.: Big data: the management revolution. Harvard Bus. Rev. 90, 60–68 (2012)Google Scholar
  6. 6.
    Wamba, S.F., Gunasekaran, A., Akter, S., Ren, S.J.-f., Dubey, R., Childe, S.J.: Big data analytics and firm performance: effects of dynamic capabilities. J. Bus. Res. 70, 356–365 (2017)CrossRefGoogle Scholar
  7. 7.
    Mikalef, P., Pappas, I.O., Giannakos, M.N., Krogstie, J., Lekakos, G.: Big data and strategy: a research framework. In: MCIS, p. 50 (2016)Google Scholar
  8. 8.
    Brown, B., Chui, M., Manyika, J.: Are you ready for the era of ‘big data’. McKinsey Q. 4, 24–35 (2011)Google Scholar
  9. 9.
    Mikalef, P., Pappas, I.O., Krogstie, J., Giannakos, M.: Big data analytics capabilities: a systematic literature review and research agenda. Inf. Syst. e-Bus. Manage., 1–32 (2017)Google Scholar
  10. 10.
    Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)Google Scholar
  11. 11.
    Wang, G., Gunasekaran, A., Ngai, E.W., Papadopoulos, T.: Big data analytics in logistics and supply chain management: certain investigations for research and applications. Int. J. Prod. Econ. 176, 98–110 (2016)CrossRefGoogle Scholar
  12. 12.
    Constantiou, I.D., Kallinikos, J.: New games, new rules: big data and the changing context of strategy. J. Inf. Technol. 30, 44–57 (2015)CrossRefGoogle Scholar
  13. 13.
    Liu, Y.: Big data and predictive business analytics. J. Bus. Forecasting 33, 40 (2014)Google Scholar
  14. 14.
    Ransbotham, S., Kiron, D.: Analytics as a source of business innovation. MIT Sloan Manag. Rev. (2017)Google Scholar
  15. 15.
    Janssen, M., van der Voort, H., Wahyudi, A.: Factors influencing big data decision-making quality. J. Bus. Res. 70, 338–345 (2017)CrossRefGoogle Scholar
  16. 16.
    Mikalef, P., Pateli, A.: Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: findings from PLS-SEM and fsQCA. J. Bus. Res. 70, 1–16 (2017)CrossRefGoogle Scholar
  17. 17.
    Karahanna, E., Straub, D.W., Chervany, N.L.: Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q. 23(2), 183–213 (1999)CrossRefGoogle Scholar
  18. 18.
    Besson, P., Rowe, F.: Strategizing information systems-enabled organizational transformation: a transdisciplinary review and new directions. J. Strateg. Inf. Syst. 21, 103–124 (2012)CrossRefGoogle Scholar
  19. 19.
    Haag, S.: Organizational inertia as barrier to firms’ IT adoption–multidimensional scale development and validation (2014)Google Scholar
  20. 20.
    Polites, G.L., Karahanna, E.: Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Q. 36(1), 21–42 (2012)Google Scholar
  21. 21.
    Kelly, D., Amburgey, T.L.: Organizational inertia and momentum: a dynamic model of strategic change. Acad. Manag. J. 34, 591–612 (1991)Google Scholar
  22. 22.
    Hannan, M.T., Freeman, J.: Structural inertia and organizational change. Am. Sociol. Rev. 49, 149–164 (1984)CrossRefGoogle Scholar
  23. 23.
    Stieglitz, N., Knudsen, T., Becker, M.C.: Adaptation and inertia in dynamic environments. Strateg. Manag. J. 37, 1854–1864 (2016)CrossRefGoogle Scholar
  24. 24.
    Barnett, W.P., Pontikes, E.G.: The Red Queen, success bias, and organizational inertia. Manag. Sci. 54, 1237–1251 (2008)CrossRefGoogle Scholar
  25. 25.
    Kim, H.-W., Kankanhalli, A.: Investigating user resistance to information systems implementation: a status quo bias perspective. MIS Q. 33(3), 567–582 (2009)CrossRefGoogle Scholar
  26. 26.
    Lyytinen, K., Newman, M.: Explaining information systems change: a punctuated socio-technical change model. Eur. J. Inf. Syst. 17, 589–613 (2008)CrossRefGoogle Scholar
  27. 27.
    Rowe, F., Besson, P., Hemon, A.: Socio-technical inertia, dynamic capabilities and environmental uncertainty: senior management view and implications for organizational transformation (2017)Google Scholar
  28. 28.
    Mikalef, P., Framnes, V.A., Danielsen, F., Krogstie, J., Olsen, D.H.: Big data analytics capability: antecedents and business value. In: Pacific Asia Conference on Information Systems (2017)Google Scholar
  29. 29.
    Mikalef, P., Krogstie, J., van de Wetering, R., Pappas, I., Giannakos, M.: Information Governance in the big data era: aligning organizational capabilities. In: Proceedings of the 51st Hawaii International Conference on System Sciences (2018)Google Scholar
  30. 30.
    Benbasat, I., Goldstein, D.K., Mead, M.: The case research strategy in studies of information systems. MIS Q. 11, 369–386 (1987)CrossRefGoogle Scholar
  31. 31.
    Battistella, C., De Toni, A.F., De Zan, G., Pessot, E.: Cultivating business model agility through focused capabilities: a multiple case study. J. Bus. Res. 73, 65–82 (2017)CrossRefGoogle Scholar
  32. 32.
    Gregor, S.: The nature of theory in information systems. MIS Q. 30, 611–642 (2006)CrossRefGoogle Scholar
  33. 33.
    Yin, R.K.: Case Study Research and Applications: Design and Methods. Sage Publications (2017)Google Scholar
  34. 34.
    Boudreau, M.-C., Gefen, D., Straub, D.W.: Validation in information systems research: a state-of-the-art assessment. MIS Q. 25(1), 1–16 (2001)CrossRefGoogle Scholar
  35. 35.
    Myers, M.D., Newman, M.: The qualitative interview in IS research: examining the craft. Inf. Organ. 17, 2–26 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Patrick Mikalef
    • 1
  • Rogier van de Wetering
    • 2
  • John Krogstie
    • 1
  1. 1.Department of Computer ScienceNorwegian University of Science and TechnologyTrondheimNorway
  2. 2.Faculty of Management Science and TechnologyOpen University of the NetherlandsHeerlenThe Netherlands

Personalised recommendations