Innovation in Elite Refereeing Through AI Technological Support for DOGSO Decisions

Cedric Gottschalk, Stefan Tewes, Benjamin Niestroj, Clemens Jäger, Jochen Drees and Alexander Ernst
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Cedric Gottschalk: FOM University of Applied Science, Herkulesstraße 32, 45127 Essen, Germany
Stefan Tewes: FOM University of Applied Science, Herkulesstraße 32, 45127 Essen, Germany
Benjamin Niestroj: FOM University of Applied Science, Herkulesstraße 32, 45127 Essen, Germany
Clemens Jäger: FOM University of Applied Science, Herkulesstraße 32, 45127 Essen, Germany
Jochen Drees: DFB Deutscher Fußball-Bund, Otto-Fleck-Schneise 6, 60528 Frankfurt am Main
Alexander Ernst: DFB Deutscher Fußball-Bund, Otto-Fleck-Schneise 6, 60528 Frankfurt am Main

International Journal of Operations Management, 2022, vol. 2, issue 3, 7-15

Abstract: Digitalization is driving social and economic change – in soccer, too. Artificial intelligence will increasingly solve problems and further intertwine the relationship between people and technology. Largely unexplored – but at the same time significant due to economic, psychological and sporting problems – are digital innovations in refereeing. Gottschalk et al. (2020) showed the potential for artificial intelligence and digitalization in refereeing. In a next step the researchers worked with the refereeing department of the German Football Association (DFB) to gain further insights for digitization in elite refereeing. As a result potential was identified for DOGSO decisions. The researchers conducted various interview rounds with elite referees of the German Football Association to identify all factors of human assessment influencing DOGSO decisions. The objective was to define a criteria system which can be evaluated by technology. As a result, more than 40 factors determining DOGSO decisions have been identified.

Keywords: Artificial intelligence; Digital transformation; Referee decision; Football; Decision-making; Trend Research (search for similar items in EconPapers)
JEL-codes: M00 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:mgs:iojome:v:2:y:2022:i:3:p:7-15

DOI: 10.18775/ijom.2757-0509.2020.23.4001

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