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The Innovation of Refereeing in Football Through AI

Author

Listed:
  • Cedric Gottschalk

    (FOM University of Applied Science, Essen, Germany)

  • Stefan Tewes

    (FOM University of Applied Science, Essen, Germany)

  • Benjamin Niestroj

    (FOM University of Applied Science, Essen, Germany)

Abstract

Digital transformation owns megatrend character. Especially technologies of artificial intelligence (AI) will help organizations to solve problems in the future. Therefore, the relationship between humans and technology will become increasingly intertwined. The use of AI in football refereeing is whitely unexplored. Wrong referee decisions lead to negative economic and psychological consequences and are therefore problematic. Accordingly, by the advances in AI, there is an increasing demand for the application of this technology to improve the precision of referee decisions. This paper applies a set of qualitative research methods to assess the potentials and limits of the use of AI for the support of referee decisions. Generally, judgements that have to do with positions are relatively easy to solve with the help of technology. However, referee decisions, which require a high degree of understanding for the situation, are considered difficult to implement. Hence, this paper identifies potentials for AI application in referee decisions, which are either black-or-white and outlines the limits in referee decisions, which give space for interpretation.

Suggested Citation

  • Cedric Gottschalk & Stefan Tewes & Benjamin Niestroj, 2020. "The Innovation of Refereeing in Football Through AI," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 6(2), pages 35-54, June.
    • Handle: RePEc:mgs:ijoied:v:6:y:2020:i:2:p:35-54
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    References listed on IDEAS

    as
    1. Pettersson-Lidbom, Per & Priks, Mikael, 2010. "Behavior under social pressure: Empty Italian stadiums and referee bias," Economics Letters, Elsevier, vol. 108(2), pages 212-214, August.
    2. Christian Deutscher & Eugen Dimant & Brad R. Humphreys, 2017. "Match Fixing and Sports Betting in Football: Empirical Evidence from the German Bundesliga," Working Papers 17-01, Department of Economics, West Virginia University.
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    Cited by:

    1. Cedric Gottschalk & Stefan Tewes & Benjamin Niestroj & Clemens Jäger & Jochen Drees & Alexander Ernst, 2022. "Innovation in Elite Refereeing Through AI Technological Support for DOGSO Decisions," International Journal of Operations Management, Inovatus Services Ltd., vol. 2(3), pages 7-15, April.

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    More about this item

    Keywords

    Artificial intelligence; Digital transformation; Referee decision; Decision making; Trends; Football; Future;
    All these keywords.

    JEL classification:

    • M00 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General - - - General

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