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Management of Big data: An empirical investigation of the Too-Much-of-a-Good-Thing effect in medium and large firms

Author

Listed:
  • Claudio Vitari

    (AMU - Aix Marseille Université, CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon)

  • Elisabetta Raguseo

    (Polito - Politecnico di Torino = Polytechnic of Turin)

  • Federico Pigni

    (EESC-GEM Grenoble Ecole de Management)

Abstract

Firms adopt Big data solutions, but a body of evidence suggests that Big data in some cases may create more problems than benefits. We hypothesize that the problem may not be Big data in itself but rather too much of it. These kinds of effects echo the Too-Much-of-a-Good-Thing (TMGT) effect in the field of management. This theory also seems meaningful and applicable in management information systems. We contribute to assessments of the TMGT effect related to Big data by providing an answer to the following question: When does the extension of Big data lead to value erosion? We collected data from a sample of medium and large firms and established a set of regression models to test the relationship between Big data and value creation, considering firm size as a moderator. The data confirm the existence of both an inverted U-shaped curve and firm size moderation. These results extend the applicability of the TMGT effect theory and are useful for firms exploring investments in Big data.

Suggested Citation

  • Claudio Vitari & Elisabetta Raguseo & Federico Pigni, 2022. "Management of Big data: An empirical investigation of the Too-Much-of-a-Good-Thing effect in medium and large firms," Post-Print hal-03876785, HAL.
    • Handle: RePEc:hal:journl:hal-03876785
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-03876785
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    Keywords

    Too-Much-of-a-Good-Thing effect; inverted U-shaped curve; Big data; business value; medium and large firms;
    All these keywords.

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