Models and Applications of Tourists’ Travel Behavior offers an exhaustive overview of various approaches to modeling tourists’ travel behavior, aiding readers in selecting the most suitable theoretical approach based on the available data. The book bridges traditional travel behavior theories and tourist studies, introducing specific tourist contexts in travel demand modeling. It transcends theoretical understanding, providing practical insights for choosing the right model and data source. It covers theoretical, descriptive, and statistical approaches to modeling, discussing choice models based on both Stated Preference Data and Revealed Preference Data.
The book starts by exploring the role of transport in tourist travel behavior and employs a comprehensive literature review to establish a foundational understanding. The concluding chapters delve into machine learning methods, emphasizing the modeling of transport in tourism, including mode choice, waiting time, and delay modeling. This resource is beneficial for educators, students, and researchers alike, providing a solid foundation for future model development.
1. Models and Applications of Tourists’ Travel Behavior - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. i 5. Copyright - p. iv 6. Dedication - p. v 7. Contributors - p. xi 8. About the authors - p. xiii 9. Preface - p. xv 10. Acknowledgments - p. xix 11. Chapter 1 Role of transport in tourists’ behavior - p. 1 12. Chapter 2 Transportation choice in tourism and travel: A bibliometrics literature review - p. 21 13. Chapter 3 Theoretical approach for modeling tourists' travel behavior - p. 47 14. Chapter 4 Descriptive approach for modeling tourists’ travel behavior - p. 59 15. Chapter 5 Statistical approach for modeling for tourists' travel behavior - p. 91 16. Chapter 6 Modeling tourist decision-making through discrete choice analysis: Theoretical approaches - p. 125 17. Chapter 7 Discrete choice models: Practical examples - p. 151 18. Chapter 8 Machine learning and tourism: Uncovering patterns in tourist behavior through machine learning methods - p. 167 19. Index - p. 197
Models and Applications of Tourists’ Travel Behavior offers an exhaustive overview of various approaches to modeling tourists’ travel behavior, aiding readers in selecting the most suitable theoretical approach based on the available data. The book bridges traditional travel behavior theories and tourist studies, introducing specific tourist contexts in travel demand modeling. It transcends theoretical understanding, providing practical insights for choosing the right model and data source. It covers theoretical, descriptive, and statistical approaches to modeling, discussing choice models based on both Stated Preference Data and Revealed Preference Data.
The book starts by exploring the role of transport in tourist travel behavior and employs a comprehensive literature review to establish a foundational understanding. The concluding chapters delve into machine learning methods, emphasizing the modeling of transport in tourism, including mode choice, waiting time, and delay modeling. This resource is beneficial for educators, students, and researchers alike, providing a solid foundation for future model development.
1. Models and Applications of Tourists’ Travel Behavior - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. i 5. Copyright - p. iv 6. Dedication - p. v 7. Contributors - p. xi 8. About the authors - p. xiii 9. Preface - p. xv 10. Acknowledgments - p. xix 11. Chapter 1 Role of transport in tourists’ behavior - p. 1 12. Chapter 2 Transportation choice in tourism and travel: A bibliometrics literature review - p. 21 13. Chapter 3 Theoretical approach for modeling tourists' travel behavior - p. 47 14. Chapter 4 Descriptive approach for modeling tourists’ travel behavior - p. 59 15. Chapter 5 Statistical approach for modeling for tourists' travel behavior - p. 91 16. Chapter 6 Modeling tourist decision-making through discrete choice analysis: Theoretical approaches - p. 125 17. Chapter 7 Discrete choice models: Practical examples - p. 151 18. Chapter 8 Machine learning and tourism: Uncovering patterns in tourist behavior through machine learning methods - p. 167 19. Index - p. 197
