Handbook of Choice Modelling


Handbook of Choice Modelling

Second Edition

2nd edition

9781800375628 Edward Elgar Publishing
Edited by Stephane Hess, Professor of Choice Modelling and Andrew Daly, Professor Emeritus, University of Leeds, UK
Publication Date: 2024 ISBN: 978 1 80037 562 8 Extent: 796 pp
This thoroughly revised second edition Handbook provides an authoritative and in-depth overview of choice modelling, covering essential topics range from data collection through model specification and estimation to analysis and use of results. It aptly emphasises the broad relevance of choice modelling when applied to a multitude of fields, including but not limited to transport, marketing, health and environmental economics.

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This thoroughly revised second edition Handbook provides an authoritative and in-depth overview of choice modelling, a key technique used across disciplines as diverse as transport, marketing, health and environmental economics.

Composed of contributions from influential senior researchers, this erudite Handbook covers all the significant steps of choice modelling analysis, including underlying economic and psychological theory, data collection and sampling, model specification and estimation, and interpretation and use of results. New chapters examining topics including endogeneity in discrete choice models, machine learning, and novel data sources such as virtual reality provide a fresh outlook on this fundamental empirical methodology.

This second edition of the Handbook of Choice Modelling will be an important read for academics and students across disciplines that have an interest in behavioural modelling. It will also benefit practitioners seeking to understand the theoretical underpinning of their work.
Critical Acclaim
‘The best is now even better: the Handbook of Choice Modelling, which has been the go-to source for years, has now been updated to cover the most important new topics in the field. It’s an excellent collection - useful to anyone working at any level with choice models.’
– Kenneth Train, University of California, Berkeley, US

‘Ten years after the first edition, this second edition maintains the jewels of the past and adds new contributions on topics that have witnessed significant research progress. Additions include virtual reality, machine learning, dynamic choice models, and endogeneity. This book should not be missed by any serious choice modeller.’
– Riccardo Scarpa, Durham University, UK

‘Decision-making underpins daily life, from the simple to the complex. Neurophysiologists, psychologists and economists have all spent decades studying decision-making from very different perspectives. Theoretical advances in the different fields have complementary strengths, creating the need for an integrated approach. This book represents a milestone in bringing together different theoretical perspectives on decision-making, setting the foundations for exciting new multi-disciplinary approaches.’
– Scott Brown, The University of Newcastle, Australia
Contributors include: Maya Abou Zeid, Kay Axhausen, Camila Balbontin, Moshe Ben-Akiva, Chandra Bhat, Michel Bierlaire, Michiel Bliemer, David Bunch, Jerome Busemeyer, Caspar Chorus, Andrew Daly, André de Palma, Alex Erath, Mogens Fosgerau, Emma Frejinger, Konstadinos Goulias, William Greene, C. Angelo Guevara, Glenn Harrison, David Hensher, Stephane Hess, Tim Hillel, Jared Hotaling, Anders Karlström, Rico Krueger, Peter Lenk, Robin Lindsey, Tony Marley, Panos Mavros, Daniel McFadden, Aupal Mondal, Ram Pendyala, Francisco Camara Pereira, Nathalie Picard, Abdul Pinjari, Joerg Rieskamp, Filipe Rodrigues, John Rose, Shobhit Saxena, Sander van Cranenburgh, Michael van Eggermond, Akshay Vij, Joan Walker

1 Introduction to the Handbook of Choice Modelling 1
Stephane Hess and Andrew Daly
2 The new science of pleasure: consumer choice behavior and the measurement
of well-being 6
Daniel McFadden
3 Psychological research and theories of preferential choice 49
Jared M. Hotaling, Jerome R. Busemeyer and Jörg Rieskamp
4 Model building, inference and interpretation: developing discrete choice
models in the age of machine learning 74
Filipe Rodrigues, Rico Krueger and Francisco Camara Pereira
5 Choice context 117
Konstadinos G. Goulias and Ram M. Pendyala
6 Self-tracing and reporting: state-of-the-art in the capture of revealed
behaviour 147
Kay W. Axhausen
7 Designing and conducting stated choice experiments 172
Michiel C. J. Bliemer and John M. Rose
8 Best-worst scaling: theory and methods 206
A. A. J. Marley
9 Real choices and hypothetical choices 246
Glenn W. Harrison
10 Virtual reality and choice modelling: existing applications and future research
directions 276
Michael A. B. van Eggermond, Panos Mavros and Alex Erath
11 Nonparametric approaches to describing heterogeneity 308
Mogens Fosgerau
12 Attribute processing as a behavioural strategy in stated preference choice
making 319
David A. Hensher and Camila Balbontin
13 Alternative decision rules in (travel) choice models: A review and critical
discussion 339
Caspar G. Chorus and Sander van Cranenburgh
14 Latent class structures: taste heterogeneity and beyond 372
Stephane Hess
15 Models for ordered choices 393
William Greene
16 Activity and transportation decisions within households 426
André de Palma, Nathalie Picard and Robin Lindsey
17 Multiple discrete-continuous choice models: a reflective analysis and a
prospective view 452
Abdul R. Pinjari, Chandra Bhat, Shobhit Saxena and Aupal Mondal
18 Hybrid choice models 489
Maya Abou-Zeid and Moshe Ben-Akiva
19 Hybrid choice models: the identification problem 522
Akshay Vij and Joan L. Walker
20 Dynamic choice models 568
Michel Bierlaire, Emma Frejinger and Tim Hillel
21 Numerical methods for optimization-based model estimation and inference 594
David S. Bunch
22 Bayesian estimation of random utility models 630
Peter Lenk
23 Endogeneity in discrete choice models 668
C. Angelo Guevara
24 Sampling and discrete choice 693
Michel Bierlaire and Rico Krueger
25 Appraisal 720
Anders Karlström
26 Forecasting choice 746
Andrew Daly
Index 766
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