Consumer Choice Models with Endogenous Network Effects

• 成果类型: Article
• 署名作者: Wang, Ruxian; Wang, Zizhuo
• 署名单位: Johns Hopkins University; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2016.2520
• 发表日期: 2017
• 页码: 3944-3960
• 关键词: revenue management and consumer choice; Network externality; Marketing; Assortment Planning; expectation-maximization

摘要

Network externality arises when the utility of a product depends not only on its attributes but also on the number of consumers who purchase the same product. In this paper, we study consumer choice models that endogenize such network externality. We first characterize the choice probabilities under such models and conduct studies on comparative statics. Then we investigate the assortment optimization problem under such choice models. Although the problem is generally NP-hard, we show that a new class of assortments, called quasi-revenue-ordered assortments, which consist of a revenue-ordered assortment plus at most one additional item, are optimal under mild conditions. We also propose an iterative estimation method to calibrate such choice models, for both uncensored and censored data cases. An empirical study on a mobile game data set shows that our proposed model can provide better fits for the data, increase the prediction accuracy for consumer choices, and potentially increase revenue.