AcknowledgementsMany individuals have contributed intellectually to this book. The literature on discrete choice analysis, combining sources of preference data and experimental design, is vast, with a history spanning at least sixty years. This book is a contribution to that literature, inspired by a need at the end of the twentieth century for a single source accessible to both practitioners and researchers who need some assistance in`travelling' through the essential components of the extant literature in order to undertake an appropriate systematic study of consumer choice behaviour.To Daniel McFadden, Norman Anderson and Moshe Ben-Akiva we owe a special debt for their contribution to the literature and for their inspiration to all authors. Wiktor Adamowicz and graduate students and sta in the Faculty of Economics and Business at the University of Sydney read earlier versions of the book and guided us in revisions. The in¯uence of a number of other colleagues has been substantial in our appreciation of the topic. We especially thank

Almost without exception, everything human beings undertake involves a choice. In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals with the purpose of gaining a better understanding both of how choices are made and of forecasting future choice responses. In this primer the authors provide an unintimidating introduction to the main techniques of choice analysis and include detail on themes such as data collection and preparation, model estimation and interpretation and the design of choice experiments. A companion website to the book provides practice data sets and software to estimate the main discrete choice models such as multinomial logit, nested logit and mixed logit. This primer will be an invaluable resource to students as well as of immense value to consultants and professionals, researchers and anyone else interested in choice analysis and modelling.

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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.

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