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Disruption and Legitimacy: Big Data in Society

Author

Listed:
  • Carlos Ferreira

    (Coventry University)

  • Alessandro Merendino

    (Coventry University)

  • Maureen Meadows

    (Coventry University)

Abstract

The growing availability of data and the emergence of business analytics ecosystems offer possibilities for companies developing innovative business models. However, the disruptive impact of these business models on society is not always judged favourably. This paper explores the growing tensions in the relationship between disruptive Big Data companies and society through the lens of legitimacy – a judgement about the fit and propriety of an entity, such as a company, to society. The study is based on four instrumental cases where Big Data organisations were faced with challenges to their legitimacy. The findings elaborate how digital transformations require companies to understand and manage how much to disrupt and how much to conform to social norms and values. Big Data businesses face a dynamic and paradoxical tension between the potential costs and benefits of their disruptive business models. The topic of legitimacy management is also addressed, drawing out implications for practice.

Suggested Citation

  • Carlos Ferreira & Alessandro Merendino & Maureen Meadows, 2023. "Disruption and Legitimacy: Big Data in Society," Information Systems Frontiers, Springer, vol. 25(3), pages 1081-1100, June.
  • Handle: RePEc:spr:infosf:v:25:y:2023:i:3:d:10.1007_s10796-021-10155-3
    DOI: 10.1007/s10796-021-10155-3
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    1. Amir Hassan Zadeh & Hamed M. Zolbanin & Ramesh Sharda & Dursun Delen, 2019. "Social Media for Nowcasting Flu Activity: Spatio-Temporal Big Data Analysis," Information Systems Frontiers, Springer, vol. 21(4), pages 743-760, August.
    2. Kilkki, Kalevi & Mäntylä, Martti & Karhu, Kimmo & Hämmäinen, Heikki & Ailisto, Heikki, 2018. "A disruption framework," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 275-284.
    3. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    4. Geissinger, Andrea & Laurell, Christofer & Sandström, Christian, 2020. "Digital Disruption beyond Uber and Airbnb—Tracking the long tail of the sharing economy," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    5. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    6. Stahl, Bernd Carsten & McBride, Neil & Wakunuma, Kutoma & Flick, Catherine, 2014. "The empathic care robot: A prototype of responsible research and innovation," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 74-85.
    7. Daniel Guttentag, 2015. "Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector," Current Issues in Tourism, Taylor & Francis Journals, vol. 18(12), pages 1192-1217, December.
    8. Shih-Chia Huang & Suzanne McIntosh & Stanislav Sobolevsky & Patrick C. K. Hung, 2017. "Big Data Analytics and Business Intelligence in Industry," Information Systems Frontiers, Springer, vol. 19(6), pages 1229-1232, December.
    9. Juho Hamari & Mimmi Sjöklint & Antti Ukkonen, 2016. "The sharing economy: Why people participate in collaborative consumption," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2047-2059, September.
    10. Karim Ben Slimane & Cédric Diridollou & Karim Hamadache, 2020. "The legitimation strategies of early stage disruptive innovation," Post-Print hal-02892879, HAL.
    11. Jiyoung Hwang, 2019. "Managing the innovation legitimacy of the sharing economy," International Journal of Quality Innovation, Springer, vol. 5(1), pages 1-21, December.
    12. Ashish Gupta & Amit Deokar & Lakshmi Iyer & Ramesh Sharda & Dave Schrader, 2018. "Big Data & Analytics for Societal Impact: Recent Research and Trends," Information Systems Frontiers, Springer, vol. 20(2), pages 185-194, April.
    13. Opresnik, David & Taisch, Marco, 2015. "The value of Big Data in servitization," International Journal of Production Economics, Elsevier, vol. 165(C), pages 174-184.
    14. Ben-Slimane, Karim & Diridollou, Cédric & Hamadache, Karim, 2020. "The legitimation strategies of early stage disruptive innovation," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    15. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," MPRA Paper 85625, University Library of Munich, Germany.
    16. Patrick Haack & Michael D. Pfarrer & Andreas Georg Scherer, 2014. "Legitimacy-as-Feeling: How Affect Leads to Vertical Legitimacy Spillovers in Transnational Governance," Journal of Management Studies, Wiley Blackwell, vol. 51(4), pages 634-666, June.
    17. Noel Brown & Craig Deegan, 1998. "The public disclosure of environmental performance information—a dual test of media agenda setting theory and legitimacy theory," Accounting and Business Research, Taylor & Francis Journals, vol. 29(1), pages 21-41.
    18. van den Broek, Tijs & van Veenstra, Anne Fleur, 2018. "Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 330-338.
    19. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 167-174.
    20. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    21. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    22. Braganza, Ashley & Brooks, Laurence & Nepelski, Daniel & Ali, Maged & Moro, Russ, 2017. "Resource management in big data initiatives: Processes and dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 328-337.
    23. Merendino, Alessandro & Dibb, Sally & Meadows, Maureen & Quinn, Lee & Wilson, David & Simkin, Lyndon & Canhoto, Ana, 2018. "Big data, big decisions: The impact of big data on board level decision-making," Journal of Business Research, Elsevier, vol. 93(C), pages 67-78.
    24. Pratyush Bharati & Abhijit Chaudhury, 2019. "Assimilation of Big Data Innovation: Investigating the Roles of IT, Social Media, and Relational Capital," Information Systems Frontiers, Springer, vol. 21(6), pages 1357-1368, December.
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    Keywords

    Big data; Legitimacy; Disruption;
    All these keywords.

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