Search algorithm, repetitive information, and sales on online platforms

  • Yangguang Huang*
  • , Yu Xie
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Article number102933
Number of pages22
JournalInternational Journal of Industrial Organization
Volume88
Early online date15 Feb 2023
DOIs
Publication statusPublished - May 2023

User-Defined Keywords

  • Consideration set
  • Food delivery platform
  • Online platform
  • Repetitive information
  • Search algorithm

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