Random network consideration: Theory and experiment
Random network consideration: Theory and experiment
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随机网络考虑：理论与实验
DOI：
10.1016/j.jebo.2023.02.020
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发表时间：
2023
影响因子：
2.2
通讯作者：
Chadd, Ian
中科院分区：
文献类型：
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作者：
Chadd, Ian
在许多情况下，很自然地会想到有限的考虑表现出溢出效应：对特定选择的关注可能会“溢出”到基于共同特征、互补性、选择环境的特征、共同的广告活动、产品捆绑等的另一个选择。对这种形式的有限考虑产生了揭示偏好和注意力的新方法。使用一个新颖的实验室实验，我测试了先前工作中提出的确定性网络考虑模型的注意力属性，并发现了大量违反该模型的行为，甚至在个人层面上也是如此。然后，我提出了一个随机泛化，随机网络考虑，并分析了其关于考虑集形成的性质。当应用于实验室数据时，我发现与一般随机网络考虑模型有更大的一致性。这些结果表明，有限注意力理论的直观吸引力特征在实践中可能确实过于严格，这一见解应该指导未来的理论研究。
In many settings, it is natural to think of limited consideration exhibiting spillovers: attention paid to a particular alternative may “spill over” to another alternative based on shared characteristics, complementarities, features of the choice environment, shared advertising campaigns, product bundling, etc. Limited consideration of this form gives rise to new methods of revealing preferences and attention. Using a novel laboratory experiment, I test the attention properties of a deterministic Network Consideration model proposed in previous work and find a plethora of violations thereof, even at the individual level. I then propose a stochastic generalization, Random Network Consideration, and analyze its properties regarding the formation of consideration sets. When applied to the laboratory data, I find greater consistency with the general Random Network Consideration model. These results reveal that intuitively appealing features of theories of limited attention may indeed be too stringent in practice, an insight which should guide future theoretical research.