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Big Data and Innovation in Tourism, Travel, and Hospitality

Managerial Approaches, Techniques, and Applications
BuchGebunden
223 Seiten
Englisch
Springererschienen am08.03.20191st ed. 2019
This book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism.mehr
Verfügbare Formate
BuchGebunden
EUR171,19
BuchKartoniert, Paperback
EUR171,19
E-BookPDF1 - PDF WatermarkE-Book
EUR160,49

Produkt

KlappentextThis book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism.
Details
ISBN/GTIN978-981-13-6338-2
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2019
Erscheinungsdatum08.03.2019
Auflage1st ed. 2019
Seiten223 Seiten
SpracheEnglisch
Gewicht504 g
IllustrationenXII, 223 p. 43 illus., 32 illus. in color.
Artikel-Nr.46118955
Rubriken
GenreWirtschaft

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1. Big Data: the Oil of the New Tourism Economy.- Chapter 2. Composite Indicators for Measuring the Online Search Interest by a Tourist Destination.- Chapter 3. Developing Smart Tourism Destinations with the Internet of Things.- Chapter 4. Big Data in Online Travel Agencies and its Application Through Electronic Devices.- Chapter 5. Big Data for Measuring the Impact of Tourism Economic Development Programme: a Process and Quality Criteria Framework for Using Big Data.- Chapter 6. Research on Big Data, VGI, and the Tourism and Hospitality Sector: Concepts, Methods, and Geographies.- Chapter 7. Sentiment Analysis for Tourism.- Chapter 8. Location-Based Social Network Data for Tourism Destinations.- Chapter 9. Identifying Innovative Idea Proposals with Topic Models - A Case Study from SPA Tourism.- Chapter 10. Customer Data and Crisis Monitoring in Flanders and Brussels.- Chapter 11. Analyzing Airbnb Customer Experience Feedback Using Text Mining.- Chapter 12. Big Data as a Game Changer: How does it Shape Business Intelligence within a Tourism and Hospitality Industry Context?.- Chapter 13. Strengthening Relational Ties and Building Loyalty Through Relational Innovation and Technology: Evidence from Spanish Hotel Guests.- Chapter 14. Big Data and its Supporting Elements: Implications for Tourism and Hospitality Marketing.mehr
Kritik
"This book, 'Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications' constitutes valuable reading for academic researchers, educators, students, and professionals who are interested in data analytics and its possibility for innovation. ... If you are interested in AI, machine learning, deep learning, and smartness, it is more necessary to read this book as fundamental knowledge. I hope you can benefit from this book as much as I have." (Hsuan Hsu, Information Technology & Tourism, Vol. 24 (2), 2022)mehr

Schlagworte

Autor

Marianna Sigala is Professor in Tourism at the University of South Australia Business School, Adelaide, Australia. She is a widely published authority in the area of service operations management and information and communication technology (ICT) applications in tourism and hospitality. She also has an interest in e-learning models and pedagogies.

Roya Rahimi is Reader in Marketing and Leisure Management at the University of Wolverhampton. Her research interests are in CRM, organisational culture, human resource management, gender equality, and tourism higher education.

Mike Thelwall is Professor of Information Science and leader of the Statistical Cybermetrics Research Group at the University of Wolverhampton. He is also Docent in the Department of Information Studies at Åbo Akademi University, and a research associate at the Oxford Internet Institute. His current research field includes identifying and analysing web phenomena using quantitative-led research methods, including altmetrics and sentiment analysis, and has pioneered an information science approach to link analysis. He has developed a wide range of tools for gathering and analysing web data, including hyperlink analysis, sentiment analysis and content analysis for Twitter, YouTube, MySpace, blogs, and the web in general.