Cambridge University Press eBooks· 2015· Book chapter
Applied Choice Analysis
- 1,546citations
- 2015year
Short summary
This book's second edition updates choice analysis methods, covering ordered choice, scaled MNL, generalized mixed logit, latent class models, group decision making, and prospect theory applications.
AI-generated from the title and abstract; the full text is not read.
Key points
- Updates choice analysis methods with new topics like ordered choice, scaled MNL, and latent class models.
- Covers group decision making, heuristics, expected utility theory, and prospect theory.
- Includes extensive case studies and Nlogit command syntax for practical application.
- Offers a blend of theory, estimation, and application for choice modeling.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. Cambridge University Press eBooks, 2015 · DOI ↗
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Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences