Models and Applications of Tourists’ Travel Behavior provides an overview of all possible approaches to modeling tourists’ travel behavior, helping readers decide which theoretical approach should be chosen depending on the available type of data. It focuses on the connection between traditional travel behavior theories and tourist studies and introduces specific tourist contexts in travel demand modelling. It goes beyond the theoretical background of tourist travel behavior modeling and offers a practical understanding for choosing the right model and sourcing the right data.

The book begins with the role of transport in tourist’ travel behavior, then employs a literature review to establish the necessary background on the topic. It then goes on to describe theoretical approaches, descriptive approaches, and statistical approaches for modelling. It discusses choice models based on both Stated Preference Data and Revealed Preference Data. It concludes with chapters on machine learning methods. This book uniquely focuses on modeling transport with regard to tourism, including mode choice, modelling waiting time, modelling delay, and more.

A variety of readers will find this book a valuable resource: Educators can use it as a basis for courses on the quantification of tourists’ travel behavior; students will learn how to deal with modeling tourists’ travel choices; and researchers will benefit from a good starting point from where new models can be developed.

• Includes the latest advances in methodologies, including 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