Search Algorithm and Sales on Online Platforms: Evidence from Food Delivery Platforms

Yangguang Huang ()
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Yangguang Huang: Department of Economics, The Hong Kong University of Science and Technology

No 202101, HKUST CEP Working Papers Series from HKUST Center for Economic Policy

Abstract: One 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 process, which influences the market equilibrium and welfare. The development of online platforms can reduce buyers' search costs and promote competition among sellers, but a platform may design a search algorithm that is too "selective" from the social welfare perspective, which causes consumers to consider fewer options and suppresses competition. By using data from food delivery platforms, we provide empirical evidence that search algorithms deeply affect restaurant revenues. Markets with more chain restaurants with established brands tend to have more concentrated sales. This is partly caused by search algorithms being biased towards large restaurant chains.

Keywords: online platform; search algorithm; consideration set; food-delivery platform (search for similar items in EconPapers)
JEL-codes: D83 L11 L13 L42 (search for similar items in EconPapers)
Date: 2021-01
New Economics Papers: this item is included in nep-cmp, nep-com and nep-pay
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