Search algorithm, repetitive information, and sales on online platforms

Yangguang Huang and Yu Xie

International Journal of Industrial Organization, 2023, vol. 88, issue C

Abstract: A prominent feature of online sales is that buyers rely on the search tools offered by platforms to process information when searching for products. We develop a model that captures how the search algorithm affects buyers’ search processes, which further influences market equilibrium and welfare. If a platform adopts a highly unequal search algorithm, buyers are likely to obtain repetitive information about a small group of sellers, which causes buyers to consider fewer options and suppresses competition. By using data from food delivery platforms, we provide empirical evidence that markets with less equal distributions of store rankings in search results have higher average prices and more concentrated sales. We suggest that regulators should restrict search algorithms from showing repetitive information.

Keywords: Online platform; Search algorithm; Repetitive information; Consideration set; Food delivery platform (search for similar items in EconPapers)
JEL-codes: D83 L11 L13 L42 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:indorg:v:88:y:2023:i:c:s0167718723000152

DOI: 10.1016/j.ijindorg.2023.102933

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