Personalization, Consumer Search and  Algorithmic Pricing

53 Pages Posted: 26 Jun 2022 Last revised: 28 Oct 2024

See all articles by Liying Qiu

Liying Qiu

Carnegie Mellon University

Yan Huang

Carnegie Mellon University - David A. Tepper School of Business

Param Vir Singh

Carnegie Mellon University - David A. Tepper School of Business

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business

Date Written: September 28, 2023

Abstract

Our study investigates the impact of product ranking systems on artificial intelligence (AI) powered pricing algorithms. Specifically, we examine the effects of "personalized" and "unpersonalized" ranking systems on algorithmic pricing outcomes and consumer welfare. Our analysis reveals that personalized ranking systems, which rank products in decreasing order of consumer's utilities, may encourage higher prices charged by pricing algorithms, especially when consumers search for products sequentially on a third-party platform. This is because personalized ranking significantly reduces the ranking-mediated price elasticity of demand and thus incentives to lower prices. Conversely, unpersonalized ranking systems  lead to significantly lower prices and greater consumer welfare. These findings suggest that even in the absence of price discrimination, personalization may not necessarily benefit consumers since pricing algorithms can undermine consumer welfare through higher prices. Thus, our study highlights the crucial role of ranking systems in shaping algorithmic pricing behaviors and consumer welfare.

Keywords: Ranking systems, Algorithmic collusion, Reinforcement learning, Pricing, Sequential search, Personalization, Marketing, Algorithmic pricing

JEL Classification: D4, L4, M2, M3

Suggested Citation

Qiu, Liying and Huang, Yan and Singh, Param Vir and Srinivasan, Kannan, Personalization, Consumer Search and  Algorithmic Pricing (September 28, 2023). Available at SSRN: https://ssrn.com/abstract=4132555

Liying Qiu

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Yan Huang

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Param Vir Singh (Contact Author)

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
412-268-3585 (Phone)

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

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