Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis

By Moshe E. Ben-Akiva, Daniel McFadden, Kenneth Train. Foundations and Trends® in Econometrics, 2019

203 citations recorded by the source corpus.

Stated preference elicitation methods collect data on consumers by "just asking" about tastes, perceptions, valuations, attitudes, motivations, life satisfactions, and/or intended choices. Choice-Based Conjoint (CBC) analysis asks subjects to make choices from hypothetical menus in experiments that are designed to mimic market experiences. Stated preference methods are controversial in economics, particularly for valuation of non-market goods, but CBC analysis is accepted and used widely in marketing and policy analysis. The promise of stated preference experiments is that they can provide deeper and broader data on the structure of consumer preferences than is obtainable from revealed market observations, with experimental control of the choice environment that circumvents the feedback found in real market equilibria. The risk is that they give pictures of consumers that do not predict real market behavior. It is important for both economists and non-economists to learn about the performance of stated preference elicitations and the conditions under which they can contribute to understanding consumer behavior and forecasting market demand. This monograph re-examines the discrete choice methods and stated preference elicitation procedures that are commonly used in CBC, and provides a guide to techniques for CBC data collection, model specification, estimation, and policy analysis. The aim is to clarify the domain of applicability and delineate the circumstances under which stated preference elicitations can provide reliable information on preferences.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/e1f340401abff7fc8d709d525e23a4eae583836a

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Citations in the corpus

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software (2017, methodology): “[55] covers this estimation approach in detail with illustrative examples.”
Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods (2021, background): “…of stated preference (SP) (Thurstone, 1931), has sparked debate as to whether consumer experiments should go anywhere beyond the mere testing of axioms of economic choice and whether SP data collected outside of real-world markets can be utilised for demand estimation (Ben-Akiva et al., 2019).”