Biased Recommender Systems And Supplier Competition

35 Pages Posted: 6 Jan 2023 Last revised: 14 Apr 2023

See all articles by Amelia Fletcher

Amelia Fletcher

Centre for Competition Policy and Norwich Business School, UEA

Peter L. Ormosi

Norwich Business School; University of East Anglia (UEA) - Centre for Competition Policy; Compass Lexecon

Rahul Savani

Dept. of Computer Science, University of Liverpool

Jacopo Castellini

Independent

Date Written: March 27, 2023

Abstract

Recommender systems are prevalent across digital platforms. They use machine learning techniques to help consumers make choices by predicting their preferred items. If RS had perfect information about consumer preferences and item attributes, they could recommend the most suitable item for each consumer. However, in practice, recommender systems have incomplete information, and their prediction models can exhibit systemic biases. Our stylised model shows such biases can dampen competition between the suppliers selling through digital platform, arising from the fact that biased recommendations are less closely linked to true preferences. Three specific types of bias are examined and are shown to have subtly different effects. Competition remains stronger where suppliers can compete to gain the benefit of the bias, a form of competition for the market. The worst market outcomes can be avoided if consumers can reject unsuitable recommendations, since this helps to restore the competitive constraint on suppliers. However, a model extension shows that these results no longer necessarily hold with endogenous vertical quality. Importantly, in choosing its recommender system, the platform’s preferences are not typically aligned with those of consumers.

Keywords: digital platforms, online marketplaces, recommender systems, algorithmic bias

Suggested Citation

Fletcher, Amelia and Ormosi, Peter L. and Ormosi, Peter L. and Savani, Rahul and Castellini, Jacopo, Biased Recommender Systems And Supplier Competition (March 27, 2023). Available at SSRN: https://ssrn.com/abstract=4319311 or http://dx.doi.org/10.2139/ssrn.4319311

Amelia Fletcher (Contact Author)

Centre for Competition Policy and Norwich Business School, UEA ( email )

Norwich
United Kingdom

HOME PAGE: http://https://people.uea.ac.uk/amelia_fletcher

Peter L. Ormosi

Norwich Business School ( email )

Norwich
NR4 7TJ
United Kingdom

University of East Anglia (UEA) - Centre for Competition Policy ( email )

UEA
Norwich Research Park
Norwich, Norfolk NR47TJ
United Kingdom

Compass Lexecon ( email )

United States

Rahul Savani

Dept. of Computer Science, University of Liverpool ( email )

Department of Computer Science
Brownlow Hill
Liverpool, L69 3BX
Great Britain

Jacopo Castellini

Independent

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