TY - GEN
T1 - Coopetition Against an Amazon
AU - Gradwohl, Ronen
AU - Tennenholtz, Moshe
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - This paper studies cooperative data-sharing between competitors vying to predict a consumer’s tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon—a company with more, better data. We show that simple schemes—threshold rules that probabilistically induce either full data-sharing between competitors, or the full transfer of data from one competitor to another—are either optimal or approximately optimal, depending on properties of the information structure. We also provide conditions under which firms share more data when they face stronger outside competition, and describe situations in which this conclusion is reversed.
AB - This paper studies cooperative data-sharing between competitors vying to predict a consumer’s tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon—a company with more, better data. We show that simple schemes—threshold rules that probabilistically induce either full data-sharing between competitors, or the full transfer of data from one competitor to another—are either optimal or approximately optimal, depending on properties of the information structure. We also provide conditions under which firms share more data when they face stronger outside competition, and describe situations in which this conclusion is reversed.
UR - http://www.scopus.com/inward/record.url?scp=85138836303&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-15714-1_20
DO - 10.1007/978-3-031-15714-1_20
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AN - SCOPUS:85138836303
SN - 9783031157134
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 347
EP - 365
BT - Algorithmic Game Theory - 15th International Symposium, SAGT 2022, Proceedings
A2 - Kanellopoulos, Panagiotis
A2 - Kyropoulou, Maria
A2 - Voudouris, Alexandros
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Symposium on Algorithmic Game Theory, SAGT 2022
Y2 - 12 September 2022 through 15 September 2022
ER -