Users often face bundle promotions when purchasing, where they have to select between two options: buy the single item at full price, or buy the bundle at a discount. In this scenario, users' preferences are usually influenced by the projection bias, that is, users often believe that their future preferences are similar to their current preferences, causing them to make irrational and short-sighted decisions. It is of great significance to analyze the effect of the projection bias on users' preferences, and this study may help understand users' decision-making process and provide bundling and pricing strategies for sellers. Prior works typically use a linear bias model for qualitative analysis, and they cannot quantitatively calculate users' nonlinear and personalized bias. In this work, we propose Pobe, a projection bias-embedded preference model to accurately predict users' choices. The proposed Pobe introduces the prospect theory to analyze users' irrational decisions, and utilizes the weight function to handle users' nonlinear and personalized bias. Based on the proposed Pobe, we also study the impact of items' correlations or discount prices on users' choices, and provide four bundling strategies. Experimental results show that the proposed method can achieve better performance than prior works, especially when only small data is available.

本文提出了一种局限偏见（projection bias）嵌入的偏好模型Pobe，用于在捆绑促销中准确预测用户的选择，分析用户的非线性和个性化偏见以及物品之间的相关性或折扣价格对用户选择的影响，并提出了四种捆绑策略。

基于前景理论的跨期选择中的投影偏差建模