Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287295 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of the Academy of Marketing Science [ISSN:] 1552-7824 [Volume:] 49 [Issue:] 3 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 482-500
Publisher: 
Springer US, New York, NY
Abstract: 
Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method's use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.
Subjects: 
Adoption
Electric vehicles
Complementary mobility services
Discrete choice experiment
Dual response
Sample-based longitudinal study
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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