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  Hybrid Collusion: Algorithmic Pricing in Human-Computer Laboratory Markets

Normann, H.-T., & Sternberg, M. (2021). Hybrid Collusion: Algorithmic Pricing in Human-Computer Laboratory Markets.

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 Creators:
Normann, Hans-Theo1, Author              
Sternberg, Martin1, Author              
Affiliations:
1Max Planck Institute for Research on Collective Goods, Max Planck Society, ou_2173688              

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Free keywords: algorithms, collusion, human-computer interaction, laboratory experiments
 JEL: C90 - General
 JEL: L41 - Monopolization; Horizontal Anticompetitive Practices
 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.

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 Dates: 2021-05-06
 Publication Status: Published online
 Pages: -
 Publishing info: Bonn : Max Planck Institute for Research on Collective Goods, Discussion Paper 2021/11
 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: 2021/11
 Degree: -

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