Stated Choice Methods : Analysis and Applications

Understanding and predicting the behaviour of decision makers when choosing among discrete goods has been one of the most fruitful areas of applied research over the last thirty years. An understanding of individual consumer behaviour 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 graduate and practitioner guide, first published in 2000, deals with the study and prediction of consumer choice behaviour, concentrating 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. It shows how SP methods can be implemented, from experimental design to econometric modelling, and suggests how to combine RP and SP data to get the best from each type. The book also presents an update of econometric approaches to choice modelling. Contents......Page 5 Figures......Page 9 Tables......Page 11 Acknowledgements......Page 15 1.1 Introduction......Page 17 1.2 Decision making and choice behaviour......Page 18 1.3 Conceptual framework......Page 24 1.4 The world of choice is complex: the challenge ahead......Page 26 Appendix A1 Choosing a residential telecommunications bundle......Page 35 2.2 Preference data come in many forms......Page 36 2.3 Preference data consistent with RUT......Page 41 3.1 Introduction......Page 50 3.2 Setting out the underlying behavioural decision framework......Page 51 3.3 Random utility maximisation......Page 53 3.4 The basic choice model - a particular model formulation......Page 60 3.5 Statistical estimation procedure......Page 63 3.6 Model outputs......Page 67 3.7 Behavioural outputs of choice models......Page 73 3.8 A simple illustration of the basic model......Page 78 3.9 Linking to the later chapters......Page 81 Appendix A3 Maximum likelihood estimation technique......Page 82 Appendix B3 Linear probability and generalised least squares models......Page 88 4.1 Introduction......Page 99 4.2 Factorial designs......Page 100 4.3 Fractional factorial designs......Page 105 4.4 Practical considerations in fractional designs......Page 110 4.5 Design strategies for simple SP experiments......Page 112 5.1 Introduction......Page 127 5.2 Multiple choice experiments......Page 128 5.3 General design principles for choice experiments......Page 135 5.4 Availability designs for labelled alternatives......Page 142 Appendix A5 Some popular choice designs......Page 147 6.1 Setting the context for behaviourally more plausible models......Page 154 6.2 Deriving the mean and variance of the extreme value type 1 distribution......Page 158 6.3 Introduction to the nested logit model......Page 160 6.4 Empirical illustration......Page 170 6.5 The nested logit model - empirical examples......Page 178 6.6 Tests of overall model performance for nested models......Page 192 6.7 Conclusions and linkages between the MNL/NL models and more complex models......Page 198 Appendix A6 Detailed characterisation of the nested logit model......Page 199 Appendix B6 Advanced discrete choice methods......Page 205 7.1 Introduction......Page 229 7.2 Designs for alternatives with non-constant error variances......Page 230 7.3 Designs for portfolio, bundle or menu choices......Page 231 7.4 Summary......Page 242 8.1 Appreciating the opportunity......Page 243 8.2 Characteristics of RP and SP data......Page 244 8.3 The mechanics of data enrichment......Page 249 8.4 Is it always possible to combine preference data sources?......Page 259 8.5 A general preference data generation process......Page 264 8.6 Summary......Page 267 9.2 Components of the choice process......Page 268 9.3 The steps in an SP choice study......Page 271 9.4 Summary......Page 298 10.2 Case study 1: preference heterogeneity vs. variance heteroscedasticity......Page 299 10.3 Case study 2: choice set generation analysis......Page 308 10.4 Summary......Page 313 11.1 Introduction......Page 314 11.2 Case study 1: introducing a new alternative: high speed rail and the random effects HEV model in an SPÐRP context......Page 315 11.3 Case study 2: high speed rail and random effects HEV in a switching context......Page 317 11.4 Case study 3: valuation of travel time savings and urban route choice with tolled options in an SP context......Page 322 11.5 Case study 4: establishing a fare elasticity regime for urban passenger transport......Page 331 11.6 Conclusions to chapter......Page 344 12.2 Environmental valuation: theory and practice......Page 345 12.3 Case study 1: use values - recreational hunting site choices......Page 347 12.4 Case study 2: passive use values......Page 359 12.5 The passive use value controversy: can SP help?......Page 366 12.6 Conclusions......Page 368 13.1 Introduction......Page 370 13.2 A brief review of preference model comparisons......Page 372 13.3 Preference regularities......Page 373 13.4 Procedures for testing preference regularity......Page 379 13.5 Empirical case studies and results......Page 385 13.6 Summary and conclusions......Page 395 References......Page 398 Index......Page 415 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 -- placing decision makers in controlled experiments that evaluate hypothetical choices rather than actual choices in the market. It shows how SP methods can be implemented, from experimental design to econometric modeling, and suggests how to combine RP and SP data to get the best from each type. The book also presents an update of econometric approaches to choice modeling.--Back cover

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.

This graduate and practitioner guide to analysing consumer choice behaviour concentrates on stated preference (SP) methods. The authors show how these methods can be implemented, from experimental design to econometric modelling, and also combined with revealed preference (RP) data. The book also presents an update of econometric approaches to choice modelling This is a reference work dealing with the study and prediction of consumer choice behaviour, concentrating on stated preference methods - placing decision makers in controlled experiments that yield hypothetical choices Understanding the behavioural responses of individuals to the actions of business and government will always be of interest to a wide spectrum of society.