Hybrid Collusion: Algorithmic Pricing in Human-Computer Laboratory Markets

54 Pages Posted: 10 May 2021 Last revised: 10 Aug 2021

See all articles by Hans-Theo Normann

Hans-Theo Normann

Heinrich Heine University Dusseldorf - Department of Economics; Max Planck Institute for Research on Collective Goods

Martin Sternberg

MPI for Research on Collective Goods, Bonn

Date Written: May 6, 2021

Abstract

We investigate collusive pricing in laboratory markets when human players interact with an algorithm. We compare the degree of (tacit) collusion when exclusively humans interact to the case of one firm in the market delegating its decisions to an algorithm. We further vary whether participants know about the presence of the algorithm. We find that three-firm markets involving an algorithmic player are significantly more collusive than human-only markets. Firms employing an algorithm earn significantly less profit than their rivals. For four-firm markets, we find no significant differences. (Un)certainty about the actual presence of an algorithm does not significantly affect collusion.

Keywords: algorithms, collusion, human-computer interaction, laboratory experiments

JEL Classification: C90, L41

Suggested Citation

Normann, Hans-Theo and Sternberg, Martin, Hybrid Collusion: Algorithmic Pricing in Human-Computer Laboratory Markets (May 6, 2021). MPI Collective Goods Discussion Paper, No. 2021/11, Available at SSRN: https://ssrn.com/abstract=3840789 or http://dx.doi.org/10.2139/ssrn.3840789

Hans-Theo Normann

Heinrich Heine University Dusseldorf - Department of Economics ( email )

Duesseldorf
Germany

Max Planck Institute for Research on Collective Goods ( email )

Kurt-Schumacher-Str. 10
D-53113 Bonn, 53113
Germany

Martin Sternberg (Contact Author)

MPI for Research on Collective Goods, Bonn ( email )

Kurt-Schumacher-Str. 10
D-53113 Bonn, 53113
Germany

HOME PAGE: http://www.coll.mpg.de/56658/martin-sternberg

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