Choice Modelling : The State-Of-the-art and the State-of-practice - Proceedings from the Inaugural International Choice Modelling Conference.

Contains a selection of the best theoretical and applied papers from the inaugural International Choice Modelling Conference. The conference was organised by the Institute for Transport Studies at the University of Leeds and held in Harrogate, North Yorkshire on 30 March to 1 April 2009.

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Bibliographic Details
Author / Creator: Hess, Stephane.
Other Authors / Creators:Daly, Andrew.
Hess, Stephane.
Daly, Andrew.
Format: eBook Electronic
Language:English
Imprint: Bingley : Emerald Publishing Limited, 2010.
Subjects:
Local Note:Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Online Access:Click to View
Table of Contents:
  • Front cover
  • Choice Modelling: The State-of-the-Art and the State-of-Practice
  • Copyright page
  • Contents
  • Biography
  • Editors
  • Guest Speakers
  • Other Authors
  • Editorial
  • Part I: Guest Speakerpapers
  • Chapter 1. Sociality, Rationality, and the Ecology of Choice
  • 1.1. Introduction
  • 1.2. How Sociality Influences Economic Behavior
  • 1.3. Modeling the Effects of Sociality
  • 1.4. Econometric Analysis of the Effects of Sociality on Choice
  • 1.5. Conclusions
  • Acknowledgment
  • References
  • Chapter 2. Planning and Action in a Model of Choice
  • 2.1. Introduction
  • 2.2. Evidence from Behavioral Research
  • 2.3. Why Represent Planning in Choice Modelsquest
  • 2.4. Modeling Framework
  • 2.5. Applications
  • 2.6. Conclusion
  • Acknowledgments
  • References
  • Chapter 3. Attribute Processing, Heuristics and Preference Construction in Choice Analysis
  • 3.1. Introduction
  • 3.2. Incorporating Attribute Processing Heuristics through Non-Linear Processing
  • 3.3. Empirical Illustration
  • 3.4. Evidence on Marginal Willingness to Pay: Value of Travel Time Savings
  • 3.5. Other Perspectives-Belief and Support Functions to Establish Judgment of Evidence Strength
  • 3.6. Conclusions
  • Acknowledgements
  • References
  • Chapter 4 The Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Formulation and Applications
  • 4.1. Introduction
  • 4.2. Functional Form of Utility Specification
  • 4.3. Stochastic Form of Utility Function
  • 4.4. Specific Model Structures
  • 4.5. The Model with an Outside Good
  • 4.6. Applications
  • 4.7. Conclusions
  • References
  • Chapter 5. Capturing Human Perception of Facial Expressions by Discrete Choice Modelling
  • 5.1. Introduction
  • 5.2. Previous Work
  • 5.3. Data Collection
  • 5.4. Discrete Choice Analysis: A Behavioural Modelling Framework
  • 5.5. Explanatory Variables
  • 5.6. Models Specification.
  • 5.7. Model Estimation
  • 5.8. Extension to Dynamic Facial Expression Recognition
  • 5.9. Conclusion and Discussion
  • References
  • Appenix 5.A. Specification Table with Estimated Parameters
  • Part II: Data Collection
  • Chapter 6. Serial Choice Conjoint Analysis for Estimating Discrete Choice Models
  • 6.1. Introduction
  • 6.2. The Multinomial Logit Model
  • 6.3. Model Estimation
  • 6.4. Experimental Design
  • 6.5. Generating Serial Efficient Designs
  • 6.6. Case Studies
  • 6.7. Summary and Discussion
  • References
  • Chapter 7. Observed Efficiency of a D-Optimal Design in an Interactive Agency Choice Experiment
  • 7.1. Introduction
  • 7.2. Optimal Designs for Multinomial Logit Models
  • 7.3. Freight Survey and its D-Efficient Design
  • 7.4. Empirical Analysis
  • 7.5. Conclusions
  • Acknowledgements
  • References
  • Chapter 8. Effects of Stated Choice Design Dimensions on Model Estimates
  • 8.1. Introduction
  • 8.2. Data
  • 8.3. Base Model
  • 8.4. Accounting for Design Dimensions
  • 8.5. Separate Models by Group
  • 8.6. Conclusions
  • Acknowledgments
  • References
  • Chapter 9. Stated Choice Experimental Designs for Scheduling Models
  • 9.1. Introduction
  • 9.2. Design Efficiency
  • 9.3. Scheduling Models and Experimental Designs
  • 9.4. Designing the SP Experiment for the Scheduling Model
  • 9.5. Comparison of Design Approaches in an Unlabeled Experiment
  • 9.6. Conclusions and Discussion
  • Acknowledgments
  • References
  • Part III: Concepts and Methodology
  • Chapter 10. Systematically Heterogeneous Covariance in Network GEV Models
  • 10.1. Introduction
  • 10.2. COVNL Model
  • 10.3. Mixed Covariance GEV
  • 10.4. Incorporating Heterogeneity Through Allocations
  • 10.5. Application
  • 10.6. Conclusions
  • References
  • Chapter 11. On Estimation of Hybrid Choice Models
  • 11.1. Introduction
  • 11.2. Hybrid Choice Modeling.
  • 11.3. HCMs: Classical Estimation
  • 11.4. Classical Estimation: Real Data Application
  • 11.5. HCM Bayesian Estimation: Analysis of a Simple Case
  • 11.6. Conclusions
  • References
  • Chapter 12. A Model of Travel Happiness and Mode Switching
  • 12.1. Introduction
  • 12.2. Happiness and Utility
  • 12.3. Data and Descriptive Findings
  • 12.4. Model Formulation
  • 12.5. Model Estimation
  • 12.6. Conclusion
  • References
  • Chapter 13. On Path Generation Algorithms for Route Choice Models
  • 13.1. Introduction
  • 13.2. Sampling of Alternatives
  • 13.3. Path Sampling
  • 13.4. Summary and Future Directions
  • 13.5. References
  • Part IV: Endogeneity and Heterogeneity
  • Chapter 14. Mode Choice Endogeneity in Value of Travel Time Estimation
  • 14.1. Introduction
  • 14.2. Model Formulation
  • 14.3. Data and Estimation
  • 14.4. Summary and Conclusions
  • Acknowledgement
  • References
  • Chapter 15. Accommodating Coefficient Outliers in Discrete Choice Modelling: A Comparison of Discrete and Continuous Mixing Approaches
  • 15.1. Introduction
  • 15.2. Methodology
  • 15.3. Simulated Data Experiments
  • 15.4. Empirical Case Study
  • 15.5. Conclusion
  • References
  • Chapter 16 . Addressing Endogeneity in Discrete Choice Models: Assessing Control-Function and Latent-Variable Methods
  • 16.1. Introduction
  • 16.2. The Problem: Endogeneity in Discrete Choice Models
  • 16.3. The Methods Under Study
  • 16.4. Combining Control-Function and Latent-Variable Methods to Correct for Endogeneity
  • 16.5. Monte Carlo Experiment
  • 16.6. Conclusion
  • Acknowledgments
  • References
  • Chapter 17. Latent Class and Mixed Logit Models with Endogenous Choice Set Formation Based on Compensatory Screening Rules
  • 17.1. Introduction
  • 17.2. The Model
  • 17.3. Data
  • 17.4. Results
  • 17.5. Conclusions
  • References
  • Part V: Transport Matters.
  • Chapter 18. Transport Welfare Benefits in the Presence of an Income Effect
  • 18.1. Introduction
  • 18. 2. Empirical Analysis
  • 18.3 The Change in Consumer Surplus and the Compensating Variation
  • 18.4. Discussion
  • 18.5. Conclusion
  • Acknowledgements
  • References
  • Chapter 19. Which Commuters Will Car Sharequest An Examination of Alternative Approaches to Identifying Market Segments
  • 19.1. Introduction
  • 19.2. Modelling Approaches
  • 19.3. Data
  • 19.4. Results
  • 19.5. Discussion
  • 19.6. Conclusions
  • Acknowledgements
  • References
  • Chapter 20. Modelling Choice in a Changing Environment: Assessing the Shock Effects of a New Transport System
  • 20.1. Introduction
  • 20.2. Data Analysis
  • 20.3. Modelling
  • 20.4. Conclusions
  • Acknowledgements
  • References
  • Chapter 21. What Do We Really Know About Travellers' Response to Unreliabilityquest
  • 21.1. Introduction
  • 21.2. Which Travel Responses Are Affected by Unreliabilityquest
  • 21.3. What Inputs Are Appropriate for Studying the Attitudes to Unreliabilityquest
  • 21.4. Which Variables can be Used to Explain the Attitudes to Unreliabilityquest
  • 21.5. What Inputs Are Needed to Estimate the Effect of Unreliability in Future Scenariosquest
  • 21.6. Conclusion
  • References
  • Appendix 21.A.1. SP Questionnaires to Investigate the Attitudes to Unreliability
  • Part VI: Beyond Transport
  • Chapter 22. Optimizing Product Portfolios Using Discrete Choice Modeling and TURF
  • 22.1. Introduction and Background
  • 22.2. Apparel Application
  • 22.3. Food Product Application
  • 22.4. Conclusions
  • References
  • Chapter 23. Preference Stability: Modeling how Consumer Preferences Shift after Receiving New Product Information
  • 23.1. Introduction
  • 23.2. Literature Review and Hypothesis Formulation
  • 23.3. Methodology
  • 23.4. Results
  • 23.5. Conclusion and Discussion
  • Acknowledgment.
  • References
  • Chapter 24. Investigating Willingness to Pay-Willingness to Accept Asymmetry in Choice Experiments
  • 24.1. Introduction
  • 24.2. Study Design
  • 24.3. Model Specification
  • 24.4. Results
  • 24.5. Conclusion
  • Acknowledgements
  • References
  • Chapter 25. Clustering Ranked Preference Data Using Sociodemographic Covariates
  • 25.1. Introduction
  • 25.2. A Mixture of Experts Model for Ranked Preference Data
  • 25.3. Model Fitting and Selection
  • 25.4. Illustrative Applications
  • 25.5. Application Results
  • 25.6. Discussion
  • Acknowledgments
  • References
  • 25.A.1. The Hamburger Preparation Quiz Data Source
  • 25.A.2. Irish Election Data Source
  • 25.A.3. Mathematical Details for the EMM Algorithm
  • Chapter 26. Continuous versus Discrete Representation of Investing Firm Heterogeneity in Modelling FDI Location Decisions
  • 26.1. Introduction
  • 26.2. The Mixed Logit and Latent Class Models
  • 26.3. The Data Set and Variable Specifications
  • 26.4. Estimation and Results
  • 26.5. Conclusions
  • Acknowledgement
  • References
  • Chapter 27. Development of Integrated Choice and Latent Variable (ICLV) Models for the Residential Relocation Decision in Island Areas
  • 27.1. Introduction
  • 27.2. State of the Art: Modeling Residential Location Choice
  • 27.3. Methodological Approach for Modeling Residential Relocation Decision in Island Areas
  • 27.4. Application for the Aegean Island Area
  • 27.5. Conclusions and Further Research
  • References.