國立虎尾科技大學 |

Big Data and Innovation in Tourism, Travel, and Hospitality = Managerial Approaches, Techniques, and Applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Big Data and Innovation in Tourism, Travel, and Hospitality/ edited by Marianna Sigala, Roya Rahimi, Mike Thelwall.
Reminder of title:	Managerial Approaches, Techniques, and Applications /
other author:	Sigala, Marianna.
Description:	XII, 223 p. 43 illus., 32 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-981-13-6339-9
ISBN:	9789811363399

Big Data and Innovation in Tourism, Travel, and Hospitality = Managerial Approaches, Techniques, and Applications /
Big Data and Innovation in Tourism, Travel, and HospitalityManagerial Approaches, Techniques, and Applications /[electronic resource] :edited by Marianna Sigala, Roya Rahimi, Mike Thelwall. - 1st ed. 2019. - XII, 223 p. 43 illus., 32 illus. in color.online resource.

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.

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.

ISBN: 9789811363399

Standard No.: 10.1007/978-981-13-6339-9doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: HF5548.125-5548.6

Dewey Class. No.: 658.4038

Big Data and Innovation in Tourism, Travel, and Hospitality = Managerial Approaches, Techniques, and Applications /
LDR:03578nam a22003975i 4500 001 1009308
003 DE-He213
005 20200706033824.0
007 cr nn 008mamaa
008 210106s2019 si | s |||| 0|eng d
020 $a 9789811363399 $9 978-981-13-6339-9
024 7 $a 10.1007/978-981-13-6339-9 $2 doi
035 $a 978-981-13-6339-9
050 4 $a HF5548.125-5548.6
072 7 $a KJQ $2 bicssc
072 7 $a BUS070030 $2 bisacsh
072 7 $a KJQ $2 thema
082 0 4 $a 658.4038 $2 23
245 1 0 $a Big Data and Innovation in Tourism, Travel, and Hospitality $h [electronic resource] : $b Managerial Approaches, Techniques, and Applications / $c edited by Marianna Sigala, Roya Rahimi, Mike Thelwall.
250 $a 1st ed. 2019.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a XII, 223 p. 43 illus., 32 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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.
520 $a 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.
650 0 $a Big data. $3 981821
650 0 $a Tourism. $3 558888
650 0 $a Management. $3 558618
650 1 4 $a Big Data/Analytics. $3 1106909
650 2 4 $a Tourism Management. $3 1062256
650 2 4 $a Big Data. $3 1017136
700 1 $a Sigala, Marianna. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 656866
700 1 $a Rahimi, Roya. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1303237
700 1 $a Thelwall, Mike. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1303238
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811363382
776 0 8 $i Printed edition: $z 9789811363405
776 0 8 $i Printed edition: $z 9789811363412
856 4 0 $u https://doi.org/10.1007/978-981-13-6339-9
912 $a ZDB-2-BUM
912 $a ZDB-2-SXBM
950 $a Business and Management (SpringerNature-41169)
950 $a Business and Management (R0) (SpringerNature-43719)