Consumer Choice Models with Endogenous Network Effects
研究了产品效用受购买人数影响的消费者选择模型，提出了准收益排序产品组合的最优性条件，并给出了模型校准方法，在手机游戏数据中提升了预测准确率和收益。
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. This paper was accepted by Noah Gans, stochastic models and simulation.