Interactions of automated pricing algorithms

Abstract

The advent of electronic commerce enables retailers to set prices via automated algorithms.This paper employs the method of experimental economics to examine human behavior in environments where multiple automated pricing algorithms are available for use.The results of the experiments reported here indicate that individuals prefer using automated pricing algorithms to setting prices manually.However, neither a pricebeating nor a price-matching automated rule is dominant in terms of the frequency of usage.We find that the composite distribution of prices is a mean-and median-preserving spread for the gametheoretic distribution and for the previously reported distribution of manually set prices.Our primary finding is that individuals encounter difficulty in coordinating to achieve tacitly collusive outcomes.However, as indicated by one market, multiple algorithms do not necessarily preclude tacit collusion.

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