This book provides a general framework for the construction of statistically efficient choice designs. It reviews previous strategies researchers have used to generate reasonable choice designs, develops criteria for efficiency when one has prior information about the model parameters, specifies general search algorithms for generating efficient choice designs, and finally, uses this knowledge to develop and test individual-level choice models. The book is of interest to researchers and practitioners in marketing science, economics, and statistics.

The chapter starts with a positioning of this dissertation in the marketing discipline. It then provides a comparison of the two most popular methods for studying consumer preferences/choices, namely conjoint analysis and discrete choice experiments. Chapter 1 continues with a description of the context of discrete choice experiments. Subsequently, the research problems and the objectives ofthis dissertation are discussed. The chapter concludes with an outline of the organization of this dissertation. 1. 1 Positioning of the Dissertation During this century, increasing globalization and technological progress has forced companies to undergo rapid and dramatic changes-for some a threat, for others it offers new opportunities. Companies have to survive in a Darwinian marketplace where the principle of natural selection applies. Marketplace success goes to those companies that are able to produce marketable value, Le. , products and services that others are willing to purchase (Kotler 1997). Every company must be engaged in new-product development to create the new products customers want because competitors will do their best to supply them. Besides offering competitive advantages, new products usually lead to sales growth and stability. As household incomes increase and consumers become more selective, fmns need to know how consumers respond to different features and appeals. Successful products and services begin with a thorough understanding of consumer needs and wants. Stated otherwise, companies need to know about consumer preferences to manufacture tailor-made products, consumers are willing to buy.

Inhalt

1. Introduction.- 2. Review of Linear Design and Discrete Choice Models.- 3. Designs for Discrete Choice Models.- 4. Using Priors in Choice Designs.- 5. Individual Choice Models.- 6. Conclusion.- Appendix A: Derivation of Probability-Centered Estimation Error.- Appendix B: Example Screens of Self-Explicated Task.- Appendix C: Example Screen of Conjoint Task.- Appendix D: Example Screen of Choice Task.- Appendix E: Holdout Choice Sets.- Appendix F: Experimental Conjoint Design.- Appendix G: Experimental Choice Designs and Partworth Values.- References.