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How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment
Author(s) -
Dokyun Lee,
Kartik Hosanagar
Publication year - 2019
Publication title -
information systems research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.507
H-Index - 159
eISSN - 1526-5536
pISSN - 1047-7047
DOI - 10.1287/isre.2018.0800
Subject(s) - diversity (politics) , recommender system , collaborative filtering , product (mathematics) , affect (linguistics) , product category , business , aggregate (composite) , consumption (sociology) , marketing , advertising , computer science , world wide web , psychology , social science , materials science , geometry , mathematics , communication , sociology , anthropology , composite material
Recommender systems appear all across the internet. For e-retailers, this represents an opportunity to get more and niche products before customers’ eyes. However, we find that while implementing recommender systems does increase overall sales figures, it does not generally improve the relative sales for niche items, leading to a rich-get-richer situation. We find, across a wide range of product categories, that the use of traditional collaborative filters (CFs) is associated with a decrease in sales diversity relative to a world without product recommendations. The decrease in aggregate sales diversity may not always be accompanied by a corresponding decrease in individual-level consumption diversity. In fact, it is even possible for individual consumption diversity to increase as aggregate sales diversity decreases. CFs help individuals explore new products, but similar users still end up exploring the same kinds of products, resulting in concentration bias at the aggregate level. There is one insight f...

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