Modeling the Choice of Choice Set in Discrete-Choice Random-Utility Models
Modeling the Choice of Choice Set in Discrete-Choice Random-Utility Models
复制标题
对离散选择随机效用模型中的选择集选择进行建模
DOI：
10.1068/a231237
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发表时间：
1991
期刊：
影响因子：
--
通讯作者：
J. Horowitz
中科院分区：
文献类型：
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作者：
J. Horowitz
在传统的随机效用模型中，例如多项Logit模型，假设决策者的选择集与他或她的偏好无关，条件是模型的解释变量。然而，在许多情况下，决策者选择选择集，从而使独立性假设变得不可信。例如，如果有关替代方案的信息成本很高，个人可能会选择只详细了解其中的一小部分。本文研究具有内生选择集的离散选择的建模问题。假设昂贵的信息迫使决策者只获得她或他所选择的一小部分备选方案的详细知识。在这一背景下，为选择集的生成和为内生选择集的选择条件而开发了模型。
In conventional random-utility models, such as the multinomial logit model, it is assumed that a decisionmaker's choice set is independent of his or her preferences conditional on the explanatory variables of the models. However, there are many situations in which the decisionmaker chooses the choice set, thereby making the independence assumption implausible. For example, if information about alternatives is costly, an individual may choose to learn in detail about only a small group of them. This paper is concerned with the modeling of discrete choice with endogenous choice sets. It is assumed that costly information forces the decisionmaker to acquire detailed knowledge of only a small group of alternatives that she or he selects. Models are developed for choice-set generation in this context and for choice conditional on endogenous choice sets.