Using attribute importance rankings within discrete choice experiments: an application to valuing bread attributes

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 a§ected by the mode of survey delivery. We conclude that the ranking data is a complementary source of information about respondent utility functions within hypothetical DCEs

Information customization and food choice

In this paper we employ a hypothetical discrete choice experiment (DCE) to examine how much consumers are willing to pay to use technology to customize their food shopping. We conjecture that customized information provision can aid in the composition of a healthier shop. Our results reveal that consumers are prepared to pay relatively more for individual specic information as opposed to generic nutritional information that is typically provided on food labels. In arriving at these results we have examined various model specications including those that make use of ex-post de-brieng questions on attribute nonattendance and attribute ranking information and those that consider the time taken to complete the survey. Our main results are robust to the various model specications we examine