A new version of this entry is available:
Loading...
ResearchPaper
2023
Strategic choice of price-setting algorithms
Strategic choice of price-setting algorithms
Abstract (English)
Recent experimental simulations have shown that autonomous pricing algorithms are able to learn collusive behavior and thus charge supra-competitive prices without being explicitly programmed to do so. These simulations assume, however, that both firms employ the identical price-setting algorithm based on Q-learning. Thus, the question arises whether the underlying assumption that both firms employ a Q-learning algorithm can be supported as an equilibrium in a game where firms can chose between different pricing rules. Our simulations show that when both firms use a learning algorithm, the outcome is not an equilibrium when alternative price setting rules are available. In fact, simpler price setting rules as for example meeting competition clauses yield higher payoffs compared to Q-learning algorithms.
File is subject to an embargo until
This is a new version of:
Notes
Publication license
Publication series
Hohenheim discussion papers in business, economics and social sciences; 2023,01
Published in
Faculty
Faculty of Business, Economics and Social Sciences
Institute
Institute of Economics
Examination date
Supervisor
Edition / version
Citation
Identification
DOI
ISSN
ISBN
Language
English
Publisher
Publisher place
Classification (DDC)
330 Economics