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.

• Includes the latest advances in methodologies, such as machine learning algorithms, mixed methods, and how to leverage big data to complement traditional regression models
• Compares the pros and cons of each method to help with choosing the appropriate model for each scenario
• Covers all modes of transportation while uniquely focusing on the tourist context in the modeling process