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English
Cambridge University Press
11 June 2015
The second edition of this popular book brings students fully up to date with the latest methods and techniques in choice analysis. Comprehensive yet accessible, it offers a unique introduction to anyone interested in understanding how to model and forecast the range of choices made by individuals and groups. In addition to a complete rewrite of several chapters, new topics covered include ordered choice, scaled MNL, generalized mixed logit, latent class models, group decision making, heuristics and attribute processing strategies, expected utility theory, and prospect theoretic applications. Many additional case studies are used to illustrate the applications of choice analysis with extensive command syntax provided for all Nlogit applications and datasets available online. With its unique blend of theory, estimation, and application, this book has broad appeal to all those interested in choice modeling methods and will be a valuable resource for students as well as researchers, professionals, and consultants.
By:   , ,
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Edition:   2nd Revised edition
Dimensions:   Height: 246mm,  Width: 176mm,  Spine: 51mm
Weight:   2.370kg
ISBN:   9781107465923
ISBN 10:   1107465923
Pages:   1216
Publication Date:  
Audience:   Professional and scholarly ,  Professional and scholarly ,  Undergraduate ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

David A. Hensher is Professor of Management, and Founding Director of the Institute of Transport and Logistics Studies (ITLS) at The University of Sydney Business School. John M. Rose was previously Professor of Transport and Logistics Modelling at the Institute of Transport and Logistics Studies (ITLS) at the University of Sydney Business School and moved to The University of South Australia as co-director of the Institute for Choice in early March 2014. William H. Greene is the Robert Stansky Professor of Economics at the Stern School of Business, New York University.

Reviews for Applied Choice Analysis

Advance praise: 'This is an enormous book, covering in extraordinary detail all the topics selected by these respected authors. It represents a substantial update and renewal of the material covered in the first edition. In my opinion it should be on the shelves of anyone dealing with discrete choice models.' Juan de Dios Ortuzar Salas, Pontificia UniversiMaydad Catolica de Chile Advance praise: 'Choice modelling is a very active and rapidly evolving field, with applications across numerous disciplines. The first edition of Applied Choice Analysis accomplished the major task of making the breadth of work accessible to a wide audience, with hands on examples provided throughout. Nine years on, the field has developed further, and David A. Hensher, John M. Rose and William H. Greene have again performed a remarkable job in explaining these new methods without unnecessary jargon and complexity, helping to educate the next generation of choice modellers and striking exactly the right balance between theory and practice.' Stephane Hess, University of Leeds Advance praise: 'The new edition of this already very popular book provides substantial added value to readers. Applied choice analysis has now been extended to include all recent developments. More intuition and further clarifications have been added. The examples provided cover thoroughly the range of case study applications. This book will work perfectly as a step-by-step introduction for the neophite as well as a core reference for the practitioner. The authors have managed to strike the right balance between practicality and accuracy, without subtracting much of the econometric details.' Riccardo Scarpa, Gibson Chair for MayFood, Rural and Environmental Economics, Queens University Belfast Advance praise: 'I cannot imagine a better introduction to choice modeling. The authors manage to bring a vivid, storytelling voice to this complex topic, with language that has personality and rhythm. The various interrelated concepts and procedures that constitute choice modeling come across as simple and straightforward. An amazing feat. The ins-and-outs of a computer code are also taught along with the statistical methods. This integration of computer language within the text is unusual and highly valuable, giving readers all the steps that are needed to implement the methods on their own data.' Kenneth Train, Adjunct Professor, University of California, Berkeley


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