TY  - GEN
T1  - Price discrimination with inequity-averse consumers : a reinforcement learning approach
A1  - Buchali,Katrin
Y1  - 2021/06/23
N2  - With the advent of big data, unique opportunities arise for data collection and
analysis and thus for personalized pricing. We simulate a self-learning algorithm
setting personalized prices based on additional information about consumer sensi-
tivities in order to analyze market outcomes for consumers who have a preference
for fair, equitable outcomes. For this purpose, we compare a situation that does
not consider fairness to a situation in which we allow for inequity-averse consumers.
We show that the algorithm learns to charge different, revenue-maximizing prices
and simultaneously increase fairness in terms of a more homogeneous distribution
of prices.
KW  - Preisdiskriminierung
KW  - Algorithmus
CY  - Hohenheim
PB  - Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim
AD  - Garbenstr. 15, 70593 Stuttgart
UR  - http://opus.uni-hohenheim.de/volltexte/2021/1905
ER  -