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The implications on willingness to pay of respondents ignoring specific attributes

机译:忽略特定属性的受访者对支付意愿的影响

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Individuals processing the information in a stated choice experiment are typically assumed to evaluate each and every attribute offered within and between alternatives, and to choose their most preferred alternative. However, it has always been thought that some attributes are ignored in this process for many reasons, including a coping strategy to handle one's perception of the complexity of the choice task. Nonetheless, analysts typically proceed to estimate discrete choice models as if all attributes have influenced the outcome to some degree. The cognitive processes used to evaluate trade-offs are complex with boundaries often placed on the task to assist the respondent. These boundaries can include prioritising attributes and ignoring specific attributes. In this paper we investigate the implications of bounding the information processing task by attribute elimination through ignoring one or more attributes. Using a sample of car commuters in Sydney we estimate mixed logit models that assume all attributes are candidate contributors, and models that assume certain attributes are ignored, the latter based on supplementary information provided by respondents. We compare the value of travel time savings under the alternative attribute processing regimes. Assuming that all attributes are not ignored and duly processed, leads to estimates of parameters which produce significantly different willingness to pay (WTP) to that obtained when the exclusion rule is invoked.
机译:通常假定在指定的选择实验中处理信息的个人评估替代方案之内和之间提供的每个属性,并选择他们最喜欢的替代方案。但是,人们一直认为,由于许多原因,在此过程中某些属性被忽略了,包括一种应对策略,以处理人们对选择任务的复杂性的感知。尽管如此,分析人员通常会继续估计离散选择模型,好像所有属性都在某种程度上影响了结果。用于评估权衡的认知过程非常复杂,通常会在任务上设置边界以协助受访者。这些边界可以包括设置属性优先级和忽略特定属性。在本文中,我们研究了通过忽略一个或多个属性来通过属性消除来限制信息处理任务的含义。通过使用悉尼的一个汽车通勤者样本,我们估计假设所有属性都是候选贡献者的混合logit模型,而忽略某些属性的模型,后者基于受访者提供的补充信息。我们比较了在替代属性处理机制下节省的旅行时间价值。假设没有忽略所有属性并进行了适当处理,则会导致对参数的估计,这些参数产生的支付意愿与调用排除规则时产生的支付意愿截然不同。

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