Analytics in Smart Tourism Design (inbunden)
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Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
307
Utgivningsdatum
2016-10-24
Upplaga
1st ed. 2017
Förlag
Springer International Publishing AG
Medarbetare
Xiang, Zheng (ed.), Fesenmaier, Daniel R. (ed.)
Illustratör/Fotograf
Bibliographie 10 schwarz-weiße und 13 farbige Abbildungen
Illustrationer
38 Tables, color; 40 Illustrations, color; 18 Illustrations, black and white; XVI, 307 p. 58 illus.,
Dimensioner
234 x 156 x 19 mm
Vikt
631 g
Antal komponenter
1
Komponenter
1 Hardback
ISBN
9783319442624
Analytics in Smart Tourism Design (inbunden)

Analytics in Smart Tourism Design

Concepts and Methods

Inbunden Engelska, 2016-10-24
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This book presents cutting edge research on the development of analytics in travel and tourism. It introduces new conceptual frameworks and measurement tools, as well as applications and case studies for destination marketing and management. It is divided into five parts: Part one on travel demand analytics focuses on conceptualizing and implementing travel demand modeling using big data. It illustrates new ways to identify, generate and utilize large quantities of data in tourism demand forecasting and modeling. Part two focuses on analytics in travel and everyday life, presenting recent developments in wearable computers and physiological measurement devices, and the implications for our understanding of on-the-go travelers and tourism design. Part three embraces tourism geoanalytics, correlating social media and geo-based data with tourism statistics. Part four discusses web-based and social media analytics and presents the latest developments in utilizing user-generated content on the Internet to understand a number of managerial problems. The final part is a collection of case studies using web-based and social media analytics, with examples from the Sochi Olympics on Twitter, leveraging online reviews in the hotel industry, and evaluating destination communications and market intelligence with online hotel reviews. The chapters in this section collectively describe a range of different approaches to understanding market dynamics in tourism and hospitality.
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Recensioner i media

"This book provides an update on recent development of analytics in tourism design in terms of theoretical frames, technology development, design principles and case studies. The editors and authors have demonstrated the idea of building a smart tourism system involving parties including the consumer, the business, and the destination as a whole. The book constitutes a very useful reading for academic researchers, graduate students and professionals who are interested in apply data analytics to the design of tourism systems." (Gang Li, Information Technology & Tourism, Vol. 17, 2017)

Övrig information

Zheng Xiang is Associate Professor in the Department of Hospitality and Tourism Management at Virginia Polytechnic Institute and State University. His research interests include travel information search, social media marketing, and business analytics for the tourism and hospitality industries. He is a recipient of Emerging Scholar of Distinction award by the International Academy for the Study of Tourism and board member of International Federation for IT and Travel & Tourism (IFITT). He is currently Director of Research and Awards for IFITT. Daniel R. Fesenmaier is Professor and Director of the National Laboratory for Tourism & eCommerce, Eric Friedheim Tourism Institute, Department of Tourism, Recreation and Sport Management, University of Florida. He is author, co-author and co-editor of several books focusing on information technology and tourism marketing including "Tourism Information Technology". He teaches and conducts research focusing on the role of information technology in travel decisions, advertising evaluation, and the design of tourism places.

Innehållsförteckning

Introduction.- Part I: Travel Demand Analytics.- Part II: Analytics in Every Day Life and Travel.- Part III: Tourism Geoanalytics.- Part IV: Web and Social Media Analytics: Concepts and Methods.- Part V: Case Studies in Web and Social Media Analytics.- Closing Remarks.