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  Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory Markets

Normann, H.-T., & Sternberg, M. (2021). Human-Algorithm Interaction: Algorithmic Pricing in Hybrid 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: This paper investigates pricing in laboratory markets when human players interact with an algorithm. We compare the degree of competition when exclusively humans interact to the case of one firm delegating its decisions to an algorithm, an n-player generalization of tit-for-tat. We further vary whether participants know about the presence of the algorithm. When one of three firms in a market is an algorithm, we observe significantly higher prices compared to human-only markets. Firms employing an algorithm earn significantly less profit than their rivals. (Un)certainty about the actual presence of an algorithm does not significantly affect collusion, although humans seem to perceive algorithms as more disruptive.

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 Dates: 2022-04-142021-05-06
 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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