Hierarchical Bayesian Method in the Study of Individual Level Behavior- In the Context of Discrete Choice Modeling with Revealed and Stated Preference Data

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9783836423533: Hierarchical Bayesian Method in the Study of Individual Level Behavior- In the Context of Discrete Choice Modeling with Revealed and Stated Preference Data

A major breakthrough in travel demand modeling in the early 1970's was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level behavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives.

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is an Assistant Professor of Marketing at theLeavey School of Business, Santa Clara University.She got her PhD from Northwestern University(Evanston, IL) and MS degree atMIT (Cambridge, MA).

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Book Description VDM Verlag Dr. Mueller E.K. 8/13/2007, 2007. Paperback or Softback. Book Condition: New. Hierarchical Bayesian Method in the Study of Individual Level Behavior- In the Context of Discrete Choice Modeling with Revealed and Stated Preference. Book. Bookseller Inventory # BBS-9783836423533

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Book Description VDM Verlag Dr. Mueller e.K., Germany, 2007. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****.A major breakthrough in travel demand modeling in the early 1970 s was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level behavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives. Bookseller Inventory # AAV9783836423533

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Book Description VDM Verlag Dr. Mueller e.K. Paperback. Book Condition: New. Paperback. 80 pages. Dimensions: 9.4in. x 6.6in. x 0.3in.A major breakthrough in travel demand modeling in the early 1970s was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level behavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9783836423533

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