Stated Choice Methods : Analysis and Applications.

By: Louviere, Jordan JContributor(s): Hensher, David A | Swait, Joffre D | Adamowicz, WiktorMaterial type: TextTextPublisher: Cambridge : Cambridge University Press, 2000Copyright date: ©2000Description: 1 online resource (418 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9780511151613Subject(s): Consumer behavior -- Mathematical models | Decision making -- Mathematical modelsGenre/Form: Electronic books.Additional physical formats: Print version:: Stated Choice Methods : Analysis and ApplicationsDDC classification: 658.8/342 LOC classification: HF5415.32 -- .L687 2000ebOnline resources: Click to View
Contents:
Intro -- Contents -- Figures -- Tables -- Acknowledgements -- 1 Choosing as a way of life -- 1.1 Introduction -- 1.2 Decision making and choice behaviour -- 1.3 Conceptual framework -- 1.4 The world of choice is complex: the challenge ahead -- Appendix A1 Choosing a residential telecommunications bundle -- 2 Introduction to stated preference models and methods -- 2.1 Introduction -- 2.2 Preference data come in many forms -- 2.3 Preference data consistent with RUT -- 3 Choosing a choice model -- 3.1 Introduction -- 3.2 Setting out the underlying behavioural decision framework -- 3.3 Random utility maximisation -- 3.4 The basic choice model - a particular model formulation -- 3.5 Statistical estimation procedure -- 3.6 Model outputs -- 3.7 Behavioural outputs of choice models -- 3.8 A simple illustration of the basic model -- 3.9 Linking to the later chapters -- Appendix A3 Maximum likelihood estimation technique -- Appendix B3 Linear probability and generalised least squares models -- 4 Experimental design -- 4.1 Introduction -- 4.2 Factorial designs -- 4.3 Fractional factorial designs -- 4.4 Practical considerations in fractional designs -- 4.5 Design strategies for simple SP experiments -- 5 Design of choice experiments -- 5.1 Introduction -- 5.2 Multiple choice experiments -- 5.3 General design principles for choice experiments -- 5.4 Availability designs for labelled alternatives -- Appendix A5 Some popular choice designs -- 6 Relaxing the IID assumption - introducing variants of the MNL model -- 6.1 Setting the context for behaviourally more plausible models -- 6.2 Deriving the mean and variance of the extreme value type 1 distribution -- 6.3 Introduction to the nested logit model -- 6.4 Empirical illustration -- 6.5 The nested logit model - empirical examples -- 6.6 Tests of overall model performance for nested models.
6.7 Conclusions and linkages between the MNL/NL models and more complex models -- Appendix A6 Detailed characterisation of the nested logit model -- Appendix B6 Advanced discrete choice methods -- 7 Complex non-IID multiple choice designs -- 7.1 Introduction -- 7.2 Designs for alternatives with non-constant error variances -- 7.3 Designs for portfolio, bundle or menu choices -- 7.4 Summary -- 8 Combining sources of preference data -- 8.1 Appreciating the opportunity -- 8.2 Characteristics of RP and SP data -- 8.3 The mechanics of data enrichment -- 8.4 Is it always possible to combine preference data sources? -- 8.5 A general preference data generation process -- 8.6 Summary -- 9 Implementing SP choice behaviour projects -- 9.1 Introduction -- 9.2 Components of the choice process -- 9.3 The steps in an SP choice study -- 9.4 Summary -- 10 Marketing case studies -- 10.1 Introduction -- 10.2 Case study 1: preference heterogeneity vs. variance heteroscedasticity -- 10.3 Case study 2: choice set generation analysis -- 10.4 Summary -- 11 Transportation case studies -- 11.1 Introduction -- 11.2 Case study 1: introducing a new alternative: high speed rail and the random effects HEV model in an SPĐRP context -- 11.3 Case study 2: high speed rail and random effects HEV in a switching context -- 11.4 Case study 3: valuation of travel time savings and urban route choice with tolled options in an SP context -- 11.5 Case study 4: establishing a fare elasticity regime for urban passenger transport -- 11.6 Conclusions to chapter -- 12 Environmental valuation case studies -- 12.1 Introduction -- 12.2 Environmental valuation: theory and practice -- 12.3 Case study 1: use values - recreational hunting site choices -- 12.4 Case study 2: passive use values -- 12.5 The passive use value controversy: can SP help? -- 12.6 Conclusions.
13 Cross validity and external validity of SP models -- 13.1 Introduction -- 13.2 A brief review of preference model comparisons -- 13.3 Preference regularities -- 13.4 Procedures for testing preference regularity -- 13.5 Empirical case studies and results -- 13.6 Summary and conclusions -- References -- Index.
Summary: A multidisciplinary graduate and practitioner guide, first published in 2000, which offers the theory and application of stated choice methods.
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Intro -- Contents -- Figures -- Tables -- Acknowledgements -- 1 Choosing as a way of life -- 1.1 Introduction -- 1.2 Decision making and choice behaviour -- 1.3 Conceptual framework -- 1.4 The world of choice is complex: the challenge ahead -- Appendix A1 Choosing a residential telecommunications bundle -- 2 Introduction to stated preference models and methods -- 2.1 Introduction -- 2.2 Preference data come in many forms -- 2.3 Preference data consistent with RUT -- 3 Choosing a choice model -- 3.1 Introduction -- 3.2 Setting out the underlying behavioural decision framework -- 3.3 Random utility maximisation -- 3.4 The basic choice model - a particular model formulation -- 3.5 Statistical estimation procedure -- 3.6 Model outputs -- 3.7 Behavioural outputs of choice models -- 3.8 A simple illustration of the basic model -- 3.9 Linking to the later chapters -- Appendix A3 Maximum likelihood estimation technique -- Appendix B3 Linear probability and generalised least squares models -- 4 Experimental design -- 4.1 Introduction -- 4.2 Factorial designs -- 4.3 Fractional factorial designs -- 4.4 Practical considerations in fractional designs -- 4.5 Design strategies for simple SP experiments -- 5 Design of choice experiments -- 5.1 Introduction -- 5.2 Multiple choice experiments -- 5.3 General design principles for choice experiments -- 5.4 Availability designs for labelled alternatives -- Appendix A5 Some popular choice designs -- 6 Relaxing the IID assumption - introducing variants of the MNL model -- 6.1 Setting the context for behaviourally more plausible models -- 6.2 Deriving the mean and variance of the extreme value type 1 distribution -- 6.3 Introduction to the nested logit model -- 6.4 Empirical illustration -- 6.5 The nested logit model - empirical examples -- 6.6 Tests of overall model performance for nested models.

6.7 Conclusions and linkages between the MNL/NL models and more complex models -- Appendix A6 Detailed characterisation of the nested logit model -- Appendix B6 Advanced discrete choice methods -- 7 Complex non-IID multiple choice designs -- 7.1 Introduction -- 7.2 Designs for alternatives with non-constant error variances -- 7.3 Designs for portfolio, bundle or menu choices -- 7.4 Summary -- 8 Combining sources of preference data -- 8.1 Appreciating the opportunity -- 8.2 Characteristics of RP and SP data -- 8.3 The mechanics of data enrichment -- 8.4 Is it always possible to combine preference data sources? -- 8.5 A general preference data generation process -- 8.6 Summary -- 9 Implementing SP choice behaviour projects -- 9.1 Introduction -- 9.2 Components of the choice process -- 9.3 The steps in an SP choice study -- 9.4 Summary -- 10 Marketing case studies -- 10.1 Introduction -- 10.2 Case study 1: preference heterogeneity vs. variance heteroscedasticity -- 10.3 Case study 2: choice set generation analysis -- 10.4 Summary -- 11 Transportation case studies -- 11.1 Introduction -- 11.2 Case study 1: introducing a new alternative: high speed rail and the random effects HEV model in an SPĐRP context -- 11.3 Case study 2: high speed rail and random effects HEV in a switching context -- 11.4 Case study 3: valuation of travel time savings and urban route choice with tolled options in an SP context -- 11.5 Case study 4: establishing a fare elasticity regime for urban passenger transport -- 11.6 Conclusions to chapter -- 12 Environmental valuation case studies -- 12.1 Introduction -- 12.2 Environmental valuation: theory and practice -- 12.3 Case study 1: use values - recreational hunting site choices -- 12.4 Case study 2: passive use values -- 12.5 The passive use value controversy: can SP help? -- 12.6 Conclusions.

13 Cross validity and external validity of SP models -- 13.1 Introduction -- 13.2 A brief review of preference model comparisons -- 13.3 Preference regularities -- 13.4 Procedures for testing preference regularity -- 13.5 Empirical case studies and results -- 13.6 Summary and conclusions -- References -- Index.

A multidisciplinary graduate and practitioner guide, first published in 2000, which offers the theory and application of stated choice methods.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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