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Acknowledgments; Contents; List of Contributors; Analytics in Tourism Design; 1 Introduction; 2 Foundations of Big Data Analytics; 3 Analytics in Tourism Design: Needs and Opportunities; 4 Directions for Research; References; Part I: Travel Demand Analytics; Predicting Tourist Demand Using Big Data; 1 Introduction; 2 What Is Tourism Big Data?; 3 Advantages of Using Big Data in Tourism; 4 Characteristics of Tourism Big Data; 5 Benefits of Big Data to Tourism Businesses; 5.1 Consumer Behavior; 5.2 Feedback Mechanisms; 6 How to Use Big Data in Tourism Forecasting
6.1 Capturing Big Data for Tourism Forecasting7 Selecting and Shrinking Big Data; 8 A Framework for Predicting Tourism Demand Using Big Data; 9 Conclusions; References; Travel Demand Modeling with Behavioral Data; 1 Introduction; 2 Empirical Results; 2.1 Heterogeneity in Tourists; 2.2 Choice Set; 2.3 Information Hierarchy; 3 Research Avenues; 4 Conclusions; References; Part II: Analytics in Everyday Life and Travel; Measuring Human Senses and the Touristic Experience: Methods and Applications; 1 Introduction; 2 Senses and Tourism Research; 3 Psychophysiological Foundations of Senses
4 Senses and Related Research4.1 Vision; 4.2 Hearing; 4.3 Smell; 4.4 Taste; 4.5 Touch; 4.6 Other Somatosensory Modalities: Movement, Temperature, and Pain; 5 Capturing Travelerś Senses: Challenges and Possible Solutions; 6 Conclusions; References; The Quantified Traveler: Implications for Smart Tourism Development; 1 Introduction; 2 Emergence of the Quantified Traveler and Wearable Technologies; 2.1 The Quantified Traveler and Context-Awareness; 2.2 The Quantified Traveler and Ordinary Life; 3 The Quantified Traveler and Smart Tourism Development; 4 Conclusion; References
Part III: Tourism GeoanalyticsGeospatial Analytics for Park and Protected Land Visitor Reservation Data; 1 Introduction; 2 Working with PPL Reservation Data Sets; 2.1 Lessons from Private Sector Tourism; 2.2 Preprocessing and Enriching PPL Reservation Data; 2.2.1 Enrichment from Visitor Origin Geography; 2.2.2 Enrichment of PPL Destinations Attributes; 2.3 Data Reduction and Geographic Data Mining; 2.4 Utilizing Information Generated from Geographic Data Mining; 2.5 Geovisualization for Pattern Interpretation of PPL Demand Populations
2.6 Geovisualization for Pattern Interpretation of PPL Destinations3 U.S. Federally Managed PPL Reservation Data Set Example; 4 Geovisualizations for U.S. Federally Managed PPLs; 5 The Past, Present and Future of U.S. Federally Managed PPL Reservation Data; 6 Conclusions; References; GIS Monitoring of Traveler Flows Based on Big Data; 1 Introduction; 2 Literature Review; 3 Tourist Flow Analysis; 4 GIS Analysis of Tourist Flows; 5 Methodology; 6 Data Description; 7 Results; 8 Conclusions; References; Part IV: Web and Social Media Analytics: Concepts and Methods
6.1 Capturing Big Data for Tourism Forecasting7 Selecting and Shrinking Big Data; 8 A Framework for Predicting Tourism Demand Using Big Data; 9 Conclusions; References; Travel Demand Modeling with Behavioral Data; 1 Introduction; 2 Empirical Results; 2.1 Heterogeneity in Tourists; 2.2 Choice Set; 2.3 Information Hierarchy; 3 Research Avenues; 4 Conclusions; References; Part II: Analytics in Everyday Life and Travel; Measuring Human Senses and the Touristic Experience: Methods and Applications; 1 Introduction; 2 Senses and Tourism Research; 3 Psychophysiological Foundations of Senses
4 Senses and Related Research4.1 Vision; 4.2 Hearing; 4.3 Smell; 4.4 Taste; 4.5 Touch; 4.6 Other Somatosensory Modalities: Movement, Temperature, and Pain; 5 Capturing Travelerś Senses: Challenges and Possible Solutions; 6 Conclusions; References; The Quantified Traveler: Implications for Smart Tourism Development; 1 Introduction; 2 Emergence of the Quantified Traveler and Wearable Technologies; 2.1 The Quantified Traveler and Context-Awareness; 2.2 The Quantified Traveler and Ordinary Life; 3 The Quantified Traveler and Smart Tourism Development; 4 Conclusion; References
Part III: Tourism GeoanalyticsGeospatial Analytics for Park and Protected Land Visitor Reservation Data; 1 Introduction; 2 Working with PPL Reservation Data Sets; 2.1 Lessons from Private Sector Tourism; 2.2 Preprocessing and Enriching PPL Reservation Data; 2.2.1 Enrichment from Visitor Origin Geography; 2.2.2 Enrichment of PPL Destinations Attributes; 2.3 Data Reduction and Geographic Data Mining; 2.4 Utilizing Information Generated from Geographic Data Mining; 2.5 Geovisualization for Pattern Interpretation of PPL Demand Populations
2.6 Geovisualization for Pattern Interpretation of PPL Destinations3 U.S. Federally Managed PPL Reservation Data Set Example; 4 Geovisualizations for U.S. Federally Managed PPLs; 5 The Past, Present and Future of U.S. Federally Managed PPL Reservation Data; 6 Conclusions; References; GIS Monitoring of Traveler Flows Based on Big Data; 1 Introduction; 2 Literature Review; 3 Tourist Flow Analysis; 4 GIS Analysis of Tourist Flows; 5 Methodology; 6 Data Description; 7 Results; 8 Conclusions; References; Part IV: Web and Social Media Analytics: Concepts and Methods