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Models and Applications of Tourists’ Travel Behavior

Specificaties
Paperback, blz. | Engels
Elsevier Science | e druk, 2025
ISBN13: 9780443265938
Rubricering
Juridisch :
Elsevier Science e druk, 2025 9780443265938
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9780443265938
Taal:Engels
Bindwijze:Paperback

Inhoudsopgave

1. Role of Transport in Tourists&rsquo; Behavior<br>2. Literature Review on Transport and Toruists&rsquo; Travel Choices<br>3. Theoretical Approach for Modeling Tourists&rsquo; Travel Behavior<br>4. Descriptive Approach for Modeling Tourists&rsquo; Travel Behavior<br>5. Statistical Approach for Modeling for Tourists&rsquo; Travel Behavior<br>6. Choice Models Based on Stated Preference (SP) Data<br>7. Choice Models Based on Revealed Preference (RP) Data<br>8. Machine Learning and Tourism<br>9. Uncovering Patterns in Tourist Behavior through Machine Learning Methods: Naive Bayes, ANN, SVM and Random Forest

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        Models and Applications of Tourists’ Travel Behavior