How do respondents process stated choice experiments? Attribute consideration under varying information load
通过有序异质logit模型，研究在陈述选择实验中，信息复杂度（属性数量）如何影响受访者忽略属性的程度，发现个体采用类似真实市场的应对策略，且信息量并非唯一决定因素。
Abstract The popularity of stated choice (SC) experiments has produced many design strategies in which researchers use increasingly more ‘complex’ choice settings to study choice behaviour. When the amount of information to assess increases, we wonder how an individual handles such information in making a choice. Defining the amount of information as the number of attributes associated with each choice set, we investigate how this information is processed as we vary its ‘complexity’. Four ordered heterogeneous logit models are developed, each for an SC design based on a fixed number of attributes, in which the dependent variable defines the number of attributes that are ignored. We find that the degree to which individuals ignore attributes is influenced by the dimensionality of the SC experiment, the deviation of attribute levels from an experienced reference alternative, the use of ‘adding up’ attributes where feasible, the number of choice sets evaluated, and the personal income of the respondent. The empirical evidence supports the view that individuals appear to adopt a range of ‘coping’ strategies that are consistent with how they process information in real markets, and that aligning ‘choice complexity’ with the amount of information to process is potentially misleading. Relevancy is what matters. Copyright © 2006 John Wiley & Sons, Ltd.