Bounded Rational Choice Behaviour : Applications in Transport.

The book is an attempt to stimulate development in travel behaviour analysis and provide a basic source of reference to the transportation research community. The aim of the book is to give centre stage to some recent innovative approaches to models of bounded rationality, both under conditions of c...

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Bibliographic Details
Author / Creator: Rasouli, Soora.
Other Authors / Creators:Timmermans, Harry.
Format: eBook Electronic
Language:English
Edition:1st ed.
Imprint: Bingley : Emerald Publishing Limited, 2015.
Subjects:
Local Note:Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Online Access:Click to View
Table of Contents:
  • Front Cover
  • Bounded Rational Choice Behaviour: Applications in Transport
  • Copyright page
  • Contents
  • List of Contributors
  • Preface
  • Frontiers in Modelling Bounded Rationality in Travel Behaviour Research: Introduction to the Collection of Chapters
  • References
  • Chapter 1 Models of Bounded Rationality under Certainty
  • 1.1 Framework
  • 1.2 Non-Optimal Decision Mechanisms
  • 1.3 Considering a Subset of Influential Attributes
  • 1.4 Indifference between Small Differences in Utility or Attribute Values
  • 1.5 Considering a Subset of Choice Alternatives
  • 1.6 Applications
  • 1.7 Conclusions and Discussion
  • References
  • Chapter 2 Utility Maximisation and Regret Minimisation: A Mixture of a Generalisation
  • 2.1 Introduction
  • 2.2 Model Structures
  • 2.2.1 The Generalised RRM Model
  • 2.2.2 Mixture Model
  • 2.3 Empirical Analysis
  • 2.3.1 Data
  • 2.3.2 Results
  • 2.4 Summary and Conclusions
  • References
  • Chapter 3 Relative Utility Modelling
  • 3.1 Introduction
  • 3.2 Relative Utility Modelling
  • 3.2.1 General Formulation
  • 3.2.2 Alternative-Oriented Relative Utility
  • 3.2.3 Representing Quasi-Nested Choice Structure
  • 3.2.4 Endogenous Modelling of Choice Set Generation
  • 3.2.5 Reflecting the Non-linearity of Context Dependency
  • 3.3 Major Findings of Existing Studies
  • 3.3.1 Choices of Destinations and Stop Patterns
  • 3.3.2 Dynamic Travel Mode Choice
  • 3.3.3 Travel Information and Travel Behaviour
  • 3.3.4 Choices of Packaged Tours
  • 3.3.5 Choice Set Generation
  • 3.4 Further Improvements
  • 3.4.1 Modelling Improvements
  • 3.4.2 Model Estimation
  • 3.5 Conclusion
  • References
  • Chapter 4 The Influence of Varying Information Load on Inferred Attribute Non-Attendance
  • 4.1 Introduction
  • 4.2 Methodology
  • 4.3 Data and Model Specifications
  • 4.4 Results
  • 4.5 Discussion
  • References.
  • Chapter 5 The Heterogeneous Heuristic Modeling Framework for Inferring Decision Processes
  • 5.1 Motivation
  • 5.2 Modeling Framework
  • 5.2.1 Satisficing Decision
  • 5.2.1.1 Preference structure
  • 5.2.1.2 Deriving decision heuristics
  • 5.2.1.3 Choice of heuristics
  • 5.2.1.4 Mental effort
  • 5.2.1.5 Risk perception
  • 5.2.1.6 Expected outcome
  • 5.2.2 Extension to Comparative Decision
  • 5.3 Applications
  • 5.3.1 The Go-Home Decision
  • 5.3.1.1 Model specification
  • 5.3.1.2 Results
  • 5.3.2 The Direction Choice Decision
  • 5.3.2.1 Model specification
  • 5.3.2.2 Results
  • 5.4 Conclusion and Future Work
  • References
  • Chapter 6 Investigating Situational Differences in Individuals' Mental Representations of Activity-Travel Decisions: Progress and Empirical Illustration for the Impact of Online Alternatives
  • 6.1 Introduction
  • 6.2 Mental Representations of Complex Decision Problems
  • 6.2.1 Theory and Concepts
  • 6.2.2 Measuring Mental Representations
  • 6.3 Case Study
  • 6.3.1 Choice Task and Experimental Design
  • 6.3.2 Data Collection and Sample
  • 6.3.3 Analysis
  • 6.3.3.1 The complexity of respondents' mental representations
  • Number of recalled considerations
  • Number of attributes and number of benefits
  • Benefits per attribute
  • Number of cognitive subsets
  • Conclusions on the complexity of respondents' MRs
  • 6.3.3.2 The content of respondents' mental representations
  • Ranking of decision variables
  • The frequency of elicited attributes
  • The frequency of elicited benefits
  • The frequency of elicited cognitive subsets
  • Centrality of variables
  • 6.3.4 Conclusion
  • 6.4 Conclusions and Discussion
  • References
  • Chapter 7 Towards a Novel Classifier for the Representation of Bounded Rationality in Models of Travel Demand
  • 7.1 Introduction to Decision Theory
  • 7.2 Decision Theory in Activity-Based Models.
  • 7.2.1 Introduction
  • 7.2.2 Decision Theory in AB Models
  • 7.3 Bayesian Networks
  • 7.3.1 General Concepts
  • 7.3.2 Parameter Learning
  • 7.3.3 Entering Evidences
  • 7.3.4 Structural Learning
  • 7.4 Bayesian Network Classifiers: Problem Formulation
  • 7.5 Towards A New Integrated Classifier
  • 7.6 Data and Design of the Experiments
  • 7.6.1 Data
  • 7.6.2 Design of the Experiments
  • 7.7 Results
  • 7.7.1 Model Comparison: Accuracy Results
  • 7.7.2 Model Comparison in Terms of Model and Individual Rule Complexity
  • 7.7.3 Activity Pattern Level Analysis
  • 7.7.4 Trip Matrix Level Analysis
  • 7.8 Conclusion and Discussion of the Results
  • References
  • Chapter 8 Bounded Rationality in Dynamic Traffic Assignment
  • 8.1 Introduction
  • 8.2 Dynamic Traffic Assignment
  • 8.2.1 Problem Definition
  • 8.2.2 Example
  • 8.2.3 Travel Flow Component
  • 8.2.4 Wardrop's First Principle and its Dynamic Extensions
  • 8.3 Bounded Rationality in Traffic Assignment
  • 8.4 Boundedly Rational Dynamic User Equilibrium Route Choice Assignment
  • 8.4.1 Tolerance-Based Dynamic User Optimal Principle
  • 8.4.2 Nonlinear Complementarity Problem (NCP) Formulation
  • 8.4.3 Solution Existence and Uniqueness
  • 8.4.4 Solution Method
  • 8.5 Boundedly Rational Dynamic user Equilibrium Route and Departure Time Choice Assignment
  • 8.6 Concluding Remarks
  • Acknowledgements
  • References
  • Chapter 9 Incorporating Bounded Rationality in a Model of Endogenous Dynamics of Activity-Travel Behaviour
  • 9.1 Introduction
  • 9.2 The Model
  • 9.2.1 Activity Profiles and Universal Choice Set
  • 9.2.2 Decision-Making Process
  • 9.2.2.1 Cognitive responses
  • 9.2.2.2 Emotional responses
  • 9.2.2.3 Choice set formation
  • 9.2.2.4 Aspirations and stress
  • 9.2.2.5 Habit formation
  • 9.2.2.6 Short-term dynamics
  • Exploitation choice mode
  • Exploration choice mode
  • 9.2.2.7 Long-term dynamics.
  • Lowering aspirations
  • Becoming 'awake'
  • 9.2.3 Updating Phase
  • 9.3 Numerical Simulations
  • 9.3.1 Simulation Settings
  • 9.3.2 Basic Case Results
  • 9.3.3 Effect of Memory-Activation Parameters
  • 9.3.3.1 Effect of λ2 parameter
  • 9.3.3.2 Effect of γ parameter
  • 9.3.4 Effect of Emotion-Related Parameters
  • 9.3.4.1 Effect of α2 parameter
  • 9.3.4.2 Effect of α1 parameter
  • 9.4 Conclusions and Discussion
  • References
  • Chapter 10 Multidimensional Travel Decision-Making: Descriptive Behavioural Theory and Agent-Based Models
  • 10.1 Background
  • 10.2 Theory and Models
  • 10.2.1 Modelling Imperfect Knowledge
  • 10.2.2 Modelling Multidimensional Search
  • 10.2.3 Search Rules and Decision Rules
  • 10.2.4 Empirical Data Collection
  • 10.3 Simulation Results
  • 10.4 Discussion and Conclusion
  • References
  • Chapter 11 Prospect Theory and its Applications to the Modelling of Travel Choice
  • 11.1 Introduction
  • 11.2 Making Travel Choices under Risk: The Assumptions of Expected Utility Theory (EUT) and Prospect Theory (PT)
  • 11.3 Cumulative Prospect Theory (CPT)
  • 11.4 Numeric Example
  • 11.5 Incorporating Prospect Theory in Travel Choice Modelling - Application Areas and Evidence
  • 11.6 Prospect Theory and Behavioural Change
  • 11.7 Shortcomings and Limitations of Prospect Theory in Modelling Travel Behaviour
  • 11.8 Summary and Conclusions
  • References
  • About the Authors
  • Index.