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

Management Science, Vol. 55, No. 5, pp. 697-712, May 2009

49 Pages Posted: 17 Apr 2007 Last revised: 8 May 2012

Daniel M. Fleder

University of Pennsylvania - The Wharton School

Kartik Hosanagar

University of Pennsylvania - Operations & Information Management Department

Date Written: September 1, 2007

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 seeks 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 three main results. First, some well known recommenders can lead to a reduction in 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 bias toward popularity can prevent what may otherwise be better consumer-product matches. That diversity can decrease is surprising to consumers who express that recommendations have helped them discover new products. In line with this, result two shows that 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 users toward the same products.. Third, we show how basic design choices affect the outcome, and thus managers can choose recommender designs that are more consistent with their sales goals and consumers’ preferences.

Keywords: recommender systems, collaborative filtering, sales diversity, Lorenz curve, Gini coefficient, long tail, electronic commerce, path dependence, simulation, concentration, diversity

JEL Classification: M31

Suggested Citation

Fleder, Daniel M. and Hosanagar, Kartik, Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity (September 1, 2007). Management Science, Vol. 55, No. 5, pp. 697-712, May 2009. Available at SSRN: https://ssrn.com/abstract=955984 or http://dx.doi.org/10.2139/ssrn.955984

Daniel M. Fleder (Contact Author)

University of Pennsylvania - The Wharton School ( email )

Philadelphia, PA 19104
United States

Kartik Hosanagar

University of Pennsylvania - Operations & Information Management Department ( email )

Philadelphia, PA 19104
United States

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