An Economic Analysis of Product Recommendation in the Presence of Quality and Taste-Match Heterogeneity

• 成果类型: Article
• 署名作者: Shi, Zhan (Michael); Raghu, T. S.
• 署名单位: Arizona State University; Arizona State University-Tempe
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2019.0893
• 发表日期: 2020
• 页码: 399-411
• 关键词: search costs; INFORMATION; COMPETITION; governance; systems

摘要

This paper investigates the strategy for product recommendation. Specifically, we analyze a platform-based market where consumers search and purchase products that potentially differ in quality. In addition, consumers have idiosyncratic tastes for a product, and the extent of this heterogeneity may vary from one product to another. In other words, there may be products with low taste dispersion (products for which there is less heterogeneity among consumers), as well as products with high taste dispersion. Our modeling framework elucidates how platform recommendation influences the market-level equilibrium outcomes, thereby informing the optimal recommendation strategy. We find that the quality and taste-dispersion dimensions can interact to affect the overall effectiveness of product-recommendation strategies. Conditioning on taste dispersion, recommending high-quality products increases both producer profits and consumer surplus. Conditioning on quality, recommending high-taste-dispersion products may, however, increase or decrease producer profits, depending on the joint effect of profit margin and purchase probability. The direction of change in consumer surplus is also uncertain-recommending a high-taste-dispersion product is more likely to increase (decrease) consumer surplus if the quality is low (high). Importantly, we show that when the platform cannot discern product types, recommendation strategies based on observed price or sales signals cannot guarantee the optimal outcome in the general case.