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Discrete Choice Modelling and Air Travel Demand: Theory and Applications

Autor Laurie A. Garrow
en Limba Engleză Hardback – 28 iun 2010
In recent years, airline practitioners and academics have started to explore new ways to model airline passenger demand using discrete choice methods. This book provides an introduction to discrete choice models and uses extensive examples to illustrate how these models have been used in the airline industry. These examples span network planning, revenue management, and pricing applications. Numerous examples of fundamental logit modeling concepts are covered in the text, including probability calculations, value of time calculations, elasticity calculations, nested and non-nested likelihood ratio tests, etc. The core chapters of the book are written at a level appropriate for airline practitioners and graduate students with operations research or travel demand modeling backgrounds. Given the majority of discrete choice modeling advancements in transportation evolved from urban travel demand studies, the introduction first orients readers from different backgrounds by highlighting major distinctions between aviation and urban travel demand studies. This is followed by an in-depth treatment of two of the most common discrete choice models, namely the multinomial and nested logit models. More advanced discrete choice models are covered, including mixed logit models and generalized extreme value models that belong to the generalized nested logit class and/or the network generalized extreme value class. An emphasis is placed on highlighting open research questions associated with these models that will be of particular interest to operations research students. Practical modeling issues related to data and estimation software are also addressed, and an extensive modeling exercise focused on the interpretation and application of statistical tests used to guide the selection of a preferred model specification is included; the modeling exercise uses itinerary choice data from a major airline. The text concludes with a discussion of on-going customer modeling research in aviation. Discrete Choice Modelling and Air Travel Demand is enriched by a comprehensive set of technical appendices that will be of particular interest to advanced students of discrete choice modeling theory. The appendices also include detailed proofs of the multinomial and nested logit models and derivations of measures used to represent competition among alternatives, namely correlation, direct-elasticities, and cross-elasticities.
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Specificații

ISBN-13: 9780754670513
ISBN-10: 0754670511
Pagini: 306
Dimensiuni: 156 x 234 x 24 mm
Greutate: 0.73 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Locul publicării:Oxford, United Kingdom

Recenzii

'Laurie Garrow has written the book we’ve been needing and waiting for. Discrete Choice Modelling and Air Travel Demand: Theory and Application will be required reading for practitioners and modelers throughout the air transportation industry. Not only does Laurie provide the background for sound demand modeling, she establishes the foundation for modeling advances in scheduling, pricing, revenue management and distribution.' Barry Smith, Georgia Institute of Technology, USA 'Garrow is one of those rare individuals with expertise in discrete choice analysis and knowledge of the airline industry, giving her a pilot's seat view into passenger demand modeling. The book should be required reading for anyone seriously interested in quantifying what drives passengers to do what they do--a topic that remains one of the great challenges facing airlines to this day.' E. Andrew Boyd, Former Chief Scientist, PROS, USA 'Dr. Garrow's book contains a solid exposition of the theory of logit models with examples relevant to aviation practitioners. It is mainly designed for graduate students and sophisticated aviation analysts who have a good understanding of the features and limitations of logit models.' Journal of Airport Management, Vol 5 No 1, 2010

Notă biografică

Laurie A. Garrow, Ph.D., is an assistant professor in the School of Civil and Environmental Engineering at the Georgia Institute of Technology. Her research addresses the development and application of advanced models of travel demand based on discrete choice methods. Prior to joining the faculty, she worked for four years at United Airlines in their revenue management research and development group. Her dissertation won first prize in the 2004 Aviation Applications Section of the Institute for Operations Research and the Management Sciences (INFORMS) and honorable mention in the 2004 Eric Pas dissertation competition sponsored by the International Association of Travel Behavior Research (IATBR). She is the 2009 recipient of the Council of University Transportation Centers-American Road and Transportation Builders Association (CUTC-ARTBA) New Faculty Member Award, one of the most prestigious awards given to an untenured faculty member in transportation that recognizes research and teaching contributions. She is also the recipient of a CAREER award that was jointly funded in 2009 by two programs at the National Science Foundation - the Decision, Risk and Management Sciences Program and the Service Enterprise Systems Program.

Cuprins

1: Introduction; 2: Binary Logit and Multinomial Logit Models; 3: Nested Logit Model; 4: Structured Extensions of MNL and NL Discrete Choice Models; 5: Network GEV Models; 6: Mixed Logit; 7: MNL, NL, and OGEV Models of Itinerary Choice; 8: Conclusions and Directions for Future Research

Descriere

In recent years, airline practitioners and academics have started to explore new ways to model airline passenger demand using discrete choice methods. This book provides an introduction to discrete choice models and uses extensive examples to illustrate how these models have been used in the airline industry. These examples span network planning, revenue management, and pricing applications. Numerous examples of fundamental logit modeling concepts are covered in the text, including probability calculations, value of time calculations, elasticity calculations, nested and non-nested likelihood ratio tests, etc.