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Hybrid Collusion: Algorithmic Pricing in Human-Computer Laboratory Markets

Hans-Theo Normann () and Martin Sternberg ()
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Hans-Theo Normann: Heinrich Heine University, Düsseldorf
Martin Sternberg: Max Planck Institute for Research on Collective Goods, Bonn

No 2021_11, Discussion Paper Series of the Max Planck Institute for Research on Collective Goods from Max Planck Institute for Research on Collective Goods

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 threefirm 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 (search for similar items in EconPapers)
JEL-codes: C90 L41 (search for similar items in EconPapers)
Date: 2021-05-06
New Economics Papers: this item is included in nep-bec, nep-com, nep-exp, nep-law and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:mpg:wpaper:2021_11

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