AI 中文总结
该研究扩展了Luce多项logit模型，刻画了广告影响消费者选择的机制，推导了广告设计规则，并提出可分离广告注意力与偏好效应的通用框架。
AI 中文摘要
我们通过扩展Luce（1959）模型（即多项logit模型），研究广告产品（如Top Picks、推荐、Featured）如何影响数字平台和零售界面上的消费者选择。消费者要么关注广告商品，要么考虑全部可选商品，随后根据Luce/logit规则在考虑的选项中进行选择。我们对该模型进行了刻画，证明其基础原始参数可从选择数据中唯一识别。我们还研究了一个对管理至关重要的广告设计问题，即平台或零售商选择广告子集以最大化预期利润，并推导了可实施的设计规则。随后我们引入了一个更丰富的框架，其中广告可同时影响注意力和偏好；对于这个更通用的模型，我们提供了刻画方法，并展示了如何利用选择数据将注意力效应与偏好效应区分开。
英文摘要
We study how advertised products (e.g., Top Picks, Recommended, Featured) affect consumer choice on digital platforms and retail interfaces by extending the Luce (1959) (or multinomial logit) model. A consumer either focuses on the advertised items or considers the full menu, then chooses among the considered alternatives according to the Luce/logit rule. We characterize this model and show that its underlying primitives are uniquely identified from choice data. We also study a managerially important advertisement-design problem, in which a platform or retailer chooses the advertised subset to maximize expected profit, and we derive implementable design rules. We then introduce a richer framework in which advertising can influence both attention and preference. For this more general model, we provide a characterization and show how choice data can be used to separate the attention effect from the preference effect.
