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The Contribution of Big Data to Achieving a Competitive Advantage: Proposal of a Conceptual Model Based on the VRIN Model

  • Abdelhak Ait TouilEmail author
  • Siham Jabraoui
Conference paper
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Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)

Abstract

The literature dealing with the impact of Big Data on the competitive advantage that companies can develop is based largely on the Resource-Based View as a theoretical basis for the analysis of this phenomenon. This study is based on the following observation: Resource-Based View defines the necessary conditions for resources and skills to provide a sustainable competitive advantage. Our study proposes a conceptual model based on the VRIN model (Value, Rarity, Imitability, Non-Substitution) developed by Barney in 1991, to investigate the contribution of Big Data resources and competencies to the creation of sustainable competitive advantage for firms. A future article will focus on an application of this model, through a survey whose results will shed light on its empirical validity, and thus help to better understand the paths through which Big Data could impact the competitive advantage of companies.

Keywords

Big Data Competitive advantage VRIN model 
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References

  1. 1.
    Akter, S., et al.: How to improve firm performance using big data analytics capability and business strategy alignment? Int. J. Prod. Econ. 182, 113–131 (2016).  https://doi.org/10.1016/j.ijpe.2016.08.018CrossRefGoogle Scholar
  2. 2.
    Akter, S., Wamba, S.F.: Big data analytics in E-commerce: a systematic review and agenda for future research. Electron. Mark. 26(2), 173–194 (2016).  https://doi.org/10.1007/s12525-016-0219-0CrossRefGoogle Scholar
  3. 3.
    Anwar, M., et al.: Big data capabilities and firm’s performance: a mediating role of competitive advantage. J. Inf. Knowl. Manag. 17(04), 1850045 (2018).  https://doi.org/10.1142/S0219649218500454CrossRefGoogle Scholar
  4. 4.
    Aydiner, A.S., et al.: Business analytics and firm performance: the mediating role of business process performance. J. Bus. Res. 96, 228–237 (2019).  https://doi.org/10.1016/j.jbusres.2018.11.028CrossRefGoogle Scholar
  5. 5.
    Barney, J.: Firm resources and sustained competitive advantage. J. Manag. 17(1), 99–120 (1991).  https://doi.org/10.1177/014920639101700108CrossRefGoogle Scholar
  6. 6.
    Barney, J.B.: Looking inside for competitive advantage. Acad. Manag. Exec. 9(4), 49–61 (2005)Google Scholar
  7. 7.
    Côrte-Real, N., et al.: Assessing business value of big data analytics in European firms. J. Bus. Res. 70, 379–390 (2017).  https://doi.org/10.1016/j.jbusres.2016.08.011CrossRefGoogle Scholar
  8. 8.
    Davenport, T.H., et al.: How ‘big data’ is different. MIT Sloan Manag. Rev. 5 (2012)Google Scholar
  9. 9.
    Delort, P.: Le big data. Presses Universitaires de France, Paris (2015)Google Scholar
  10. 10.
    Grant, R.M.: Toward a knowledge-based theory of the firm: knowledge-based theory of the firm. Strat. Manag. J. 17(S2), 109–122 (1996).  https://doi.org/10.1002/smj.4250171110CrossRefGoogle Scholar
  11. 11.
    Gupta, M., George, J.F.: Toward the development of a big data analytics capability. Inf. Manag. 53(8), 1049–1064 (2016).  https://doi.org/10.1016/j.im.2016.07.004CrossRefGoogle Scholar
  12. 12.
    Lavalle, S., et al.: How the smartest organizations are embedding analytics to transform information into insight and then action. Findings and recommendations from the first annual new intelligent enterprise global executive study. MIT Sloan Manag. Rev. 52(2), 20–31 (2011)Google Scholar
  13. 13.
    Marr, B., ed.: Walmart: how big data is used to drive supermarket performance. In: Big Data in Practice, pp. 5–10. Wiley, Chichester (2016).  https://doi.org/10.1002/9781119278825.ch1
  14. 14.
    McAfee, A., Brynjolfsson, E.: Big data: the management revolution (2012). https://hbr.org/2012/10/big-data-the-management-revolution
  15. 15.
    Mikalef, P., et al.: Big data analytics and firm performance: findings from a mixed-method approach. J. Bus. Res. 98, 261–276 (2019).  https://doi.org/10.1016/j.jbusres.2019.01.044CrossRefGoogle Scholar
  16. 16.
    Mikalef, P., et al.: Big data analytics capabilities: a systematic literature review and research agenda. Inf. Syst. e-Bus. Manag. 16(3), 547–578 (2018).  https://doi.org/10.1007/s10257-017-0362-yCrossRefGoogle Scholar
  17. 17.
  18. 18.
    Pace, M.: TikTok : Comment Les Médias Américains L’Utilisent Pour Séduire Les Jeunes. https://www.forbes.fr/technologie/tiktok-comment-les-medias-americains-lutilisent-pour-seduire-les-jeunes/
  19. 19.
    Peteraf, M.A.: The cornerstones of competitive advantage: a resource-based view. Strat. Manag. J. 14(3), 179–191 (1993).  https://doi.org/10.1002/smj.4250140303CrossRefGoogle Scholar
  20. 20.
    Peteraf, M.A., Barney, J.B.: Unraveling the resource-based tangle. Manag. Decis. Econ. 24(4), 309–323 (2003).  https://doi.org/10.1002/mde.1126CrossRefGoogle Scholar
  21. 21.
    Teece, D.J. et al.: Dynamic capabilities and strategic management. Strat. Manag. J. 18(7), 509–533 (1997). https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-ZCrossRefGoogle Scholar
  22. 22.
    Wamba, S.F., et al.: Big data analytics and firm performance: effects of dynamic capabilities. J. Bus. Res. 70, 356–365 (2017).  https://doi.org/10.1016/j.jbusres.2016.08.009CrossRefGoogle Scholar
  23. 23.
    Wernerfelt, B.: A resource-based view of the firm. Strat. Manag. J. 5(2), 171–180 (1984).  https://doi.org/10.1002/smj.4250050207CrossRefGoogle Scholar
  24. 24.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.ENCG CasablancaHassan Second UniversityCasablancaMorocco

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