Synopses & Reviews
Understanding and predicting the behavior of decision makers when choosing among discrete goods has been one of the most fruitful areas of applied research over the past thirty years. An understanding of individual consumer behavior can lead to significant changes in product or service design, pricing strategy, distribution channel and communication strategy selection, as well as public welfare analysis. This book is a reference work dealing with the study and prediction of consumer choice behavior, concentrating on stated preference (SP) methods. It shows how SP methods can be implemented, from experimental design to econometric modeling. The book also presents an update of econometric approaches to choice modeling.
Review
"It can be recommended not only as an excellent reference book, but also as an excellent textbook." Mathematical Reviews
Synopsis
This guide to analysing consumer choice behaviour concentrates on stated preference (SP) methods--placing decision makers in controlled experiments that yield hypothetical choices--rather than revealed preferences (RP)--actual choices in the market. The authors show how SP methods can be implemented, from experimental design to econometric modelling of choice, and combined with RP data to get the best from each type. The book also presents an update of econometric approaches to choice modelling. Central to welfare economics, econometrics, decision sciences, marketing, transport planning, environmental evaluation, geography, statistics.
Description
Includes bibliographical references (p. 382-398) and index.
Table of Contents
1. Choosing as a way of life; Appendix A1. Choosing a residential telecommunications bundle; 2. Introduction to stated preference models and methods; 3. Choosing a choice model; Appendix A3. Maximum likelihood estimation technique; Appendix B3. Linear probability and generalised least squares models; 4. Experimental design; 5. Design of choice experiments; Appendix A5. 6. Relaxing the IID assumption-introducing variants of the MNL model; Appendix A6. Detailed characterisation of the nested logit model; Appendix B6. Advanced discrete choice methods; 7. Complex, non-IID multiple choice designs; 8. Combining sources of preference data; 9. Implementing SP choice behaviour projects; 10. Marketing case studies; 11. Transportation case studies; 12. Environmental valuation case studies; 13. Cross and external validity of SP models.