[论文解读] Pairwise Beats All-at-Once: Behavioral Gains from Sequential Choice Presentation

Dipankar Das|arXiv (Cornell University)|Jan 20, 2026

Decision-Making and Behavioral Economics被引用 0

一句话总结

论文提出顺序理性假设，展示在注意力受限下，选项的顺序成对呈现比一次性显示更能提高实现效用最大化的选择，与一次性展示形成对比。

ABSTRACT

This paper presents the Sequential Rationality Hypothesis, which argues that consumers are better able to make utility-maximizing decisions when products appear in sequential pairwise comparisons rather than in simultaneous multi-option displays. Although this involves higher cognitive costs than the all-at-once format, the current digital market, with its diverse products listed by review ratings, pricing, and paid products, often creates inconsistent choices. The present work shows that preparing the list sequentially supports more rational choice, as the consumer tries to minimize cognitive costs and may otherwise make an irrational decision. If the decision remains the same on both offers, then that is a consistent preference. The platform uses this approach by reducing cognitive costs while still providing the list in an all-at-once format rather than sequentially. To show how sequential exposure reduces cognitive overload and prevents context-dependent errors, we develop a bounded attention model and extend the monotonic attention rule of the random attention model to theorize the sequential rational hypothesis. Using a theoretical design with common consumer goods, we test these hypotheses. This theoretical model helps policymakers in digital market laws, behavioral economics, marketing, and digital platform design consider how choice architectures may improve consumer choices and encourage rational decision-making.

研究动机与目标

• 在数字选择环境中激发有界理性与注意力约束。
• 引入顺序理性假设，作为通过顺序成对呈现改进理性决策的机制。
• 为在认知约束下的顺序二元比较建立基于RAM的理论模型。
• 推导公理与理论结果，展示何时顺序暴露优于同时呈现。
• 讨论减少认知负担、改善决策质量的政策与平台设计含义。

提出的方法

• 在随机注意模型RAM的基础上加入单调注意力与认知成本考量。
• 将CSEQ定义为递归二元比较选择规则。
• 形成带单调性的潜在注意力集T：μ(T|S) ≤ μ(T|S∖{a}) 对于 a ∈ S∖T。
• 在单调注意力下给出经修正的选择规则：π(x|S) = ∑T⊆S 1{x=max≻T} · μ(T|S)。
• 提出序贯选择过程CSEQ并利用二叉树结构将其与同时RAM进行比较。
• 提供用于有界注意下的序列理性的一致性公理（二元一致性、序列传递性、注意单调性、认知简洁性）。

Figure 1 : Sequential Binary Comparisons under the SRH Model. Note: $\mu(\{A,C\})=0.4$ represents the probability of choosing $A$ over $C$ in a binary setting.

实验结果

研究问题

• RQ1 在有界注意下，序列成对曝露是否相较一次性曝露更高概率地选择真正的效用最大化选项？
• RQ2 如何扩展RAM以形式化建模有界注意下的序列二元比较并界定数字市场中的认知成本？
• RQ3 哪些公理表征有界注意下的序列理性，它们如何导出可检验的预测？
• RQ4 在降低认知负担、提高决策质量的推荐流设计中，政策与平台设计含义为何？

主要发现

• 在有界注意下，序列化的二元比较相较于同时呈现更大概率选择效用最大化选项。
• 一个递归的CSEQ模型形成二叉决策树，能够捕捉路径依赖并降低认知负担。
• 单调注意与认知成本的定义支撑理论结果，并解释在有界注意下正则性减弱。
• 该模型提供了可证伪的预测，以及序列与同时暴露格式之间的福利比较。