Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity

Daniel Fleder (dfleder@wharton.upenn.edu) and Kartik Hosanagar (kartikh@wharton.upenn.edu)
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Daniel Fleder: The Wharton School, University of Pennsylvania, http://assets.wharton.upenn.edu/~dfleder
Kartik Hosanagar: The Wharton School, University of Pennsylvania

No 07-10, Working Papers from NET Institute

Abstract: This paper examines the effect of recommender systems on the diversity of sales. Two anecdotal views exist about such effects. Some believe recommenders help consumers discover new products and thus increase sales diversity. Others believe recommenders only reinforce the popularity of already popular products. This paper is a first attempt to reconcile these seemingly incompatible views. We explore the question in two ways. First, modeling recommender systems analytically allows us to explore their path dependent effects. Second, turning to simulation, we increase the realism of our results by combining choice models with actual implementations of recommender systems. We arrive at four main results. One, some common recommenders lead to a net reduction in average sales diversity. Because common recommenders (e.g., collaborative filters) recommend products based on sales and ratings, they cannot recommend products with limited historical data, even if they would be rated favorably. In turn, these recommenders can create a rich-get-richer effect for popular products and vice-versa for unpopular ones. This finding is often surprising to consumers who express that recommendations have helped them discover new products. In line with this, result two shows it is possible for individual-level diversity to increase but aggregate diversity to decrease; recommenders can push each person to new products, but they often push us toward the same new products. Result three finds that recommenders intensify the effects of chance events on market outcomes. At the product level, recommenders can ‘create hits' out of products with early, high sales due to chance alone. At the market level, in individual sample paths it is possible to observe more diversity, even though on average diversity often decreases. Four, we show how basic design choices affect the outcome. Thus, managers can choose recommender designs that are more consistent with their sales or product assortment strategies.

Keywords: recommender systems; collaborative filtering; long tail; path dependence; concentration; diversity (search for similar items in EconPapers)
JEL-codes: D83 M31 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2007-09, Revised 2007-09
References: Add references at CitEc
Citations: View citations in EconPapers (4)

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