Foundations of Stated Preferences Elicitation provides the reader with stated preference data collection methods, discrete choice models, and statistical analysis tools that can be used to forecast demand and assess welfare impacts for new or modified products or services in real markets, and summarize the conditions under which the reliability of these methods has been demonstrated or can be tested. One focus is the collection of preference and related data from consumer responses in hypothetical choice experiments, particularly conjoint analysis methods that have proven useful in market research. Another is the economic theory and statistical analysis of choice behavior, revealed or stated, and an economic framework for forecasting market demand and measuring consumer welfare. The treatment is informed by and benefits from experiments on perceptions and decision-making behavior in cognitive science and behavioral economics, and includes methods that can accommodate features of consumer choice that impact forecast reliability such as anchoring, adaptation to the status quo, and sensitivity to context. However, the authors’ emphasis is on forecasting tools developed from traditional economic consumer theory and does not touch on the implications of behavioral consumer theory for demand forecasting.
Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis| Moshe Ben-Akiva (Author), Daniel McFadden (Author), Kenneth Train (Author)| Now Publishers Inc
Table of Contents
Chapter 1. Some History of Stated Preference Elicitation
Chapter 2. Choice-Based Conjoint (CBC) Analysis
Chapter 3. Choice Behavior
Chapter 4. Choice Model Estimation and Forecasting with CBC Data
Chapter 5. Maximum Simulated Likelihood (MSL) Analysis of CBC Data
Chapter 6. Hierarchical Bayes Estimation
Chapter 7. An Empirical CBC Study Using MSL and HB Methods
Chapter 8. An Application with Inter and Intra-consumer Heterogeneity
Chapter 9. Policy Analysis
Chapter 10. Conclusions
Appendix
Acknowledgements
References
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