Ebook Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications
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Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications
Ebook Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications
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From the Back Cover
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. It also provides a consolidated framework and roadmap summarising the major issues that both researchers and practitioners have to address for effective big data innovation.The book proposes a process-based model to identify and implement big data innovation strategies in tourism. This process framework consists of four major parts: 1) inputs required for big data innovation; 2) processes required to implement big data innovation; 3) outcomes of big data innovation; and 4) contextual factors influencing big data exploitation and advances in big data exploitation for business innovation.
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About the Author
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 Ã…bo 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.
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Product details
Hardcover: 223 pages
Publisher: Springer; 1st ed. 2019 edition (February 27, 2019)
Language: English
ISBN-10: 9811363382
ISBN-13: 978-9811363382
Product Dimensions:
6.1 x 0.6 x 9.2 inches
Shipping Weight: 1.1 pounds (View shipping rates and policies)
Average Customer Review:
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Amazon Best Sellers Rank:
#3,815,490 in Books (See Top 100 in Books)
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