Using Attribute Importance Rankings Within Discrete Choice Experiments: An Application to Valuing Bread Attributes
提出一种新的贝叶斯计量模型，将受访者对属性重要性的排序信息纳入离散选择实验，发现排序数据有助于解释选择行为，且调查方式（在线或邮寄）对结果无显著影响。
Abstract We present a new Bayesian econometric specification for a hypothetical Discrete Choice Experiment (DCE) incorporating respondent ranking information about attribute importance. Our results indicate that a DCE debriefing question that asks respondents to rank the importance of attributes helps to explain the resulting choices. We also examine how mode of survey delivery (online and mail) impacts model performance, finding that results are not substantively affected by the mode of survey delivery. We conclude that the ranking data are a complementary source of information about respondent utility functions within hypothetical DCEs.