Intro; Contents; Introduction; Big Data: The Oil of the New Tourism Economy; Scope and Structure of the Book; Content of the Book; 1 Composite Indicators for Measuring the Online Search Interest by a Tourist Destination; 1.1 Introduction; 1.2 Literature Review; 1.2.1 Tourism and Statistical Information; 1.2.2 Consumer Behaviour in Tourism, the Internet and Google Trends; 1.2.3 Indicators and Web Analytics Strategy; 1.3 Methodology; 1.3.1 Theoretical Framework; 1.3.2 Selection of Primary Indicators; 1.3.3 Selection of Search Terms and Geographical Locations in GT
1.3.4 Transformation, Weighting and Aggregation of Primary Indicators1.3.5 Data Collection from GT; 1.3.6 Validation and Reliability of Indicators; 1.4 Results; 1.4.1 Search Interest of Foreign Markets for Tourism in Portugal; 1.4.2 Validation and Reliability of Composite Indicators; 1.5 Discussion; 1.6 Conclusion; References; 2 Developing Smart Tourism Destinations with the Internet of Things; 2.1 Introduction; 2.2 Big Data and Smart Connectivity; 2.3 The Internet of Things for Tourism; 2.4 Summary; References
3 Big Data in Online Travel Agencies and Its Application Through Electronic Devices3.1 Introduction; 3.2 Theoretical Framework; 3.3 Methodology; 3.4 Results; 3.4.1 OTA Webpage; 3.4.2 Registration; 3.4.3 Filters; 3.4.4 Hotels Offered in the Search Results; 3.4.5 Booking Process; 3.4.6 Customer Experience; 3.5 Big Data Challenges in OTAs; 3.6 Discussion; 3.7 Conclusions; References; 4 Big Data for Measuring the Impact of Tourism Economic Development Programmes: A Process and Quality Criteria Framework for Using Big Data; 4.1 Introduction
4.2 Economic Development Agencies: Functions, Information Needs and Measurement Trends4.2.1 Functions; 4.2.2 Information Needs: Why to Measure and Why It Is not Measured; 4.2.3 Information Needs and Measurement Trends: What and How to Measure; 4.3 Traditional Versus Big Data in Measuring Economic Developmental Programmes; 4.3.1 Traditional Data; 4.3.2 Big Data: Benefits, Risks/Limitations and Requirements; 4.4 Transforming Big Data into Socio-economic Value: Processes and Criteria for Selecting Big Data; 4.4.1 Big Data Process Supporting Decision Making
4.4.2 Criteria for Selecting and Evaluating Big Data4.4.3 Proposed Framework for Selecting and Using Big Data Sources for Measuring Tourism Economic Development Programs; 4.5 Conclusions and Implications for Future Research; References; 5 Research on Big Data, VGI, and the Tourism and Hospitality Sector: Concepts, Methods, and Geographies; 5.1 Introduction; 5.2 Digital Economy, Big Data and New Challenges; 5.3 Methods; 5.4 An Overview of the Publications; 5.4.1 Type of Articles, Time-Series of Publications, Journals, and Affiliations; 5.4.2 Geographies of Scientific Production
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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.