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Big Data and Innovation in Tourism, Travel, and Hospitality

Contributor(s): Material type: TextTextLanguage: English Publication details: Springer, 2019Description: xii, 223 p. il. col. 24 cm.ISBN:
  • 9789811363412
Subject(s): Online resources:
Contents:
Includes bibliographical references. TOC:-- Composite Indicators for Measuring the Online Search Interest by a Tourist Destination-- Developing Smart Tourism Destinations with the Internet of Things-- Big Data in Online Travel Agencies and Its Application Through Electronic Devices-- Big Data for Measuring the Impact of Tourism Economic Development Programmes: A Process and Quality Criteria Framework for Using Big Data-- Research on Big Data, VGI, and the Tourism and Hospitality Sector: Concepts, Methods, and Geographies-- Sentiment Analysis for Tourism-- Location-Based Social Network Data for Tourism Destinations-- Identifying Innovative Idea Proposals with Topic Models-A Case Study from SPA Tourism-- Customer Data and Crisis Monitoring in Flanders and Brussels-- Analyzing Airbnb Customer Experience Feedback Using Text Mining-- Big Data as a Game Changer: How Does It Shape Business Intelligence Within a Tourism and Hospitality Industry Context?-- Strengthening Relational Ties and Building Loyalty Through Relational Innovation and Technology: Evidence from Spanish Hotel Guests-- Big Data and Its Supporting Elements: Implications for Tourism and Hospitality Marketing--
Summary: 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.
Holdings
Item type Current library Call number Status Date due Barcode
Book TBS Barcelona Libre acceso G155.7 SIG (Browse shelf(Opens below)) Available B03606

Includes bibliographical references. TOC:-- Composite Indicators for Measuring the Online Search Interest by a Tourist Destination-- Developing Smart Tourism Destinations with the Internet of Things-- Big Data in Online Travel Agencies and Its Application Through Electronic Devices-- Big Data for Measuring the Impact of Tourism Economic Development Programmes: A Process and Quality Criteria Framework for Using Big Data-- Research on Big Data, VGI, and the Tourism and Hospitality Sector: Concepts, Methods, and Geographies-- Sentiment Analysis for Tourism-- Location-Based Social Network Data for Tourism Destinations-- Identifying Innovative Idea Proposals with Topic Models-A Case Study from SPA Tourism-- Customer Data and Crisis Monitoring in Flanders and Brussels-- Analyzing Airbnb Customer Experience Feedback Using Text Mining-- Big Data as a Game Changer: How Does It Shape Business Intelligence Within a Tourism and Hospitality Industry Context?-- Strengthening Relational Ties and Building Loyalty Through Relational Innovation and Technology: Evidence from Spanish Hotel Guests-- Big Data and Its Supporting Elements: Implications for Tourism and Hospitality Marketing--

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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