Big Data Analytics for the Prediction of Tourist Preferences Worldwide
By
N. Padmaja;
N. Padmaja
SRI Padmavati Mahila Visvavidyalayam, India
Search for other works by this author on:
Rajalakshmi Subramaniam;
Rajalakshmi Subramaniam
Talaash Research Consultants, India
Search for other works by this author on:
Sanjay Mohapatra
Sanjay Mohapatra
Batoi Systems Pvt Ltd, India
Search for other works by this author on:
N. Padmaja
SRI Padmavati Mahila Visvavidyalayam, India
Rajalakshmi Subramaniam
Talaash Research Consultants, India
Sanjay Mohapatra
Batoi Systems Pvt Ltd, India
Emerald Publishing Limited
ISBN electronic:
978-1-83549-338-0
ISBN print:
978-1-83549-339-7
Publication date:
2024
Chapter Contents
Book Chapter
References
Copyright © 2024 N. Padmaja, Rajalakshmi Subramaniam and Sanjay Mohapatra. Published under exclusive licence by Emerald Publishing Limited
2024
N. Padmaja, Rajalakshmi Subramaniam and Sanjay Mohapatra
-
Published:2024
Citation
2024. "References", Big Data Analytics for the Prediction of Tourist Preferences Worldwide, N. Padmaja, Rajalakshmi Subramaniam, Sanjay Mohapatra
Download citation file:
Open figure viewer
Copyright © 2024 N. Padmaja, Rajalakshmi Subramaniam and Sanjay Mohapatra. Published under exclusive licence by Emerald Publishing Limited
2024
N. Padmaja, Rajalakshmi Subramaniam and Sanjay Mohapatra
References
Abbasi et al., 2016
Abbasi
, A.
, Sarker
, S.
, & Chiang
, R. H. L.
(2016
). Big data research in information systems toward an inclusive research agenda
. Journal of the Association for Information Systems
, 17
(2
), 1
–32
.Aguilar et al., 2020
Aguilar
, J.
, Salazar
, C.
, Velasco
, H.
, Monsalve-Pulido
, J.
, & Montoya
, E.
(2020
). Comparison and evaluation of different methods for the feature extraction from educational contents
. Computation
, 8
(30
), 1
–20
.Alaei et al., 2019
Alaei
, A.
, Becken
, S.
, & Stantic
, B.
(2019
). Sentiment analysis in tourism capitalizing on big data
. Journal of Travel Research
, 1
–17
.Alcántara-Pilar et al., 2017
Alcántara-Pilar
, J. M.
, del Barrio-García
, S.
, Crespo-Almendros
, E.
, & Porcu
, L.
(2017
). Toward an understanding of online information processing in e-tourism does national culture matter?
Journal of Travel & Tourism Marketing
, 34
(8
), 1128
–1142
.Ardito et al., 2019
Ardito
, L.
, Cerchione
, R.
, Vecchio
, P. D.
, & Raguseo
, E.
(2019
). Big data in smart tourism challenges, issues and opportunities
. Current Issues in Tourism
, 22
(15
), 1805
–1809
.Arsalan, 2019
Arsalan
. (2019
). Opportunities and challenges of big data in hospitality and tourism management
. Academic Master
.Baggio, 2016
Baggio
, R.
(2016
). Big data, business intelligence and tourism: A brief analysis of the literature
. https//www.iby.it/turismo/papers/baggio_BigDataSurvey.pdf. Accessed on January 3, 2019
.Bello-Orgaza, 2015
Bello-Orgaza
, J. J. C.
(2015
). Social big data: Recent achievements and new challenges
. Information Fusion
.Bernabeu, 2016
Bernabeu
, M. A. C.
(2016
). Big Data and Smart tourism destinations challenges and opportunities from an industry perspective
. In School of Hospitality and Tourism Management Conference
, UK
.Bernabeu et al., 2016
Bernabeu
, C.
, Lopez
, M.
, Norberto
, J.
, Sanchez
, G.
, Baidal
, D. I.
, & Antoni
, J.
(2016
). Big Data and smart tourism destinations challenges and opportunities from an industry perspective
. Researchgate Publications
.Blei et al., 2003
Blei
, D. M.
, Ng
, A. Y.
, & Jordan
, M. I.
(2003
). Latent Dirichlet allocation
. Journal of Machine Learning Research
, 3
, 993
–1022
.Brida and Schubert, 2008
Brida
, J.
, & Schubert
, S.
(2008
). The economic effects of advertising on tourism demand
. Economics Bulletin
, 6
(45
), 1
–16
.Brown et al., 2011
Brown
, B.
, Chui
, M.
, & Manyika
, J.
(2011
). Are you ready for the era of “Big Data”
. McKinsey Quarterly
, 4
, 24
–35
.Bucur, 2015
Bucur
, C.
(2015
). Using opinion mining techniques in tourism
. Procedia Economics and Finance
, 23
, 1666
–1673
.Camilleri, 2019
Camilleri
, M. A.
(2019
). The use of data driven technologies in tourism marketing
. In V.
Ratten
, J.
Alvarez-Garcia
, & M.
De l Cruz Del Rio-Rama
(Eds.), Entrepreneurship, innovation and inequality exploring territorial dynamics and development
(
(1st ed.)
). Routledge
.Çeltek and Ilhan, 2020
Çeltek
, E.
, & Ilhan
, I.
(2020
). Big data, artificial intelligence, and their implications in the tourism industry
. In Handbook of research on smart technology applications in the tourism industry
(pp. 115
–130
). IGI Global
.Chahal and Gulia, 2016
Chahal
, H.
, & Gulia
, P.
(2016
). Big data analytics
. Research Journal of Computer and Information Technology Sciences
, 4
(2
), 1
–4
.Chen, 2017
Chen
, G. H.
(2017
). Big data drive tourism enterprises integration innovation
. In ITM Web of Conferences
(pp. 1
–3
).Chen et al., 2014
Chen
, M.
, Mao
, S.
, & Liu
, Y.
(2014
). Big data: A survey
. Mobile Networks and Applications
, 19
(2
), 171
–209
.Dai and Xiang, 2016
Dai
, Z.
, & Xiang
, C.
(2016
). Research on intelligent tourism application based on big data
. In 7th International Conference on Education, Management, Information and Computer Science (ICEMC 2017)
. Atlantis Press
.Datascience101, 2015
Datascience101
. (2015
). NIST defines Big Data and Data Science
. WordPress.com
.Demunter, 2017
Demunter
, C.
(2017
). Tourism statistics: Early adopters of big data?
https//ec.europa.eu/eurostat/documents/3888793/8234206/KS-TC-17-004-EN-N.pdf. Accessed on January 29, 2020
.EMC Education Services, 2016
EMC Education Services
. (2016
). Data science and big data analytics: Disovering, analyzing, visualizing and presenting data
. http//index-of.co.uk/Big-Data-Technologies/Data%20Science%20and%20 Big%20 Data%20Analytics.pdf. Accessed on May 4, 2020
.Fuchs et al.,
Fuchs, M., Höpken, W., & Lexhagen, M. (Eds.)
. (2012
). Big data and business intelligence in the travel and tourism industry (pp. 127–131). Mid Sweden University.Guanglu et al., 2015
Guanglu
, L.
, Xiangye
, S.
, Hong
, L.
, & Hongzhi
, L.
(2015
). Path analysis on big data in promoting intelligent tourism implementation
. In International Conference on Management Science, Education Technology, Arts, Social Science and Economics
.Guilarte and Quintans, 2019
Guilarte
, Y. P.
, & Quintans
, D. B.
(2019
). Using big data to measure tourist sustainability: Myth or reality?
Sustainability Journal
, 11
(5641
), 1
–19
.Gupta et al., 2017
Gupta
, K.
, Gauba
, T.
, & Jain
, S.
(2017
). Big data in hospitality industry: A survey
. International Research Journal of Engineering and Technology
, 4
(11
), 476
–479
.Habegger et al., 2014
Habegger
, B.
, Hasan
, O.
, Brunie
, L.
, Bennani
, N.
, Kosch
, H.
, & Damiani
, E.
(2014
). Personalization vs. privacy in big data analysis
. International Journal of Behavioral Development
, 25
–35
.Hammer et al., 2017
Hammer
, C.
, Kostroch
, M. D. C.
, & Quiros
, M. G.
(2017
). Big data potential, challenges and statistical implications
. International Monetary Fund
.Haynes and Egan, 2016,
Haynes
, N.
, & Egan
, D.
(2016, April
). Towards an understanding of how Big Data is changing revenue management in hotels
. University of Surrey Conference
.Hemlata and Gulia, 2016
Hemlata
, & Gulia
, P.
(2016
). Big data analytics
. Research Journal of Computer and Information Technology Sciences
, 4
(2
), 1
–4
.Hopken and Fuchs, 2016
Hopken
, W.
, & Fuchs
, M.
(2016
). Introduction: Special issue on business intelligence and big data in the travel and tourism domain
. Information Technology & Tourism
, 16
(1
), 1
–4
.Hu et al., 2017
Hu
, Y. H.
, Chen
, Y. L.
, & Chou
, H. L.
(2017
). Opinion mining from online hotel reviews – A text summarization approach
. Information Processing & Management
, 53
(2
), 436
–444
.Inanc–Demir and Kozak, 2019
Inanc–Demir
, M.
, & Kozak
, M.
(2019
). Big data and its supporting elements implications for tourism and hospitality marketing
. In M.
Sigala
, R.
Rahimi
, & M.
Thelwall
(Eds.), Big data and innovation in tourism, travel, and hospitality
. Springer
.Jha, 2018
Jwa, 2016
Jwa
, J. W.
(2016
). Pedestrian network models for mobile smart tour guide services
. International Journal of Internet, Broadcasting and Communication
, 8
(1
), 27
–32
.Kachniewska, 2019
Kachniewska
, M.
(2019
). Big Data Analysis as the tool for predictive intelligence and experience personalization in tourism
(pp. 39
–50
). https://cor.sgh.waw.pl/bitstream/handle/20.500.12182/779/Kachniewska_Magdalena_Big_Data_Analysis_as_the_tool_for_predictive_intelligence_and_experience_personalization_in_tourism.pdf?sequence=2&isAllowed=y. Accessed on December 27, 2019
.Kapukaranov and Nakov, 2015
Kapukaranov
, B.
, & Nakov
, P.
(2015
). Fine-grained sentiment analysis for movie reviews in Bulgarian
. In Proceedings of the International Conference Recent Advances in Natural Language Processing
(pp. 266
–274
).Kavitha et al., 2017
Kavitha
, S.
, Sathyavathi
, S.
, Prabhakaran
, S.
, & Swathi
, S.
(2017
). Opinion mining on tourism
. IJIRST – International Journal for Innovative Research in Science & Technology
, 3
(8
), 128
–131
.Latif, 2019
Latif
, D. V.
(2019
). Big data analysis in determining tourist package prices
. Journal of Advanced Research in Dynamical and Computer Science
, 11
(2
), 1319
–1325
.Law et al., 2014
Law
, R.
, Buhalis
, D.
, & Cobanoglu
, C.
(2014
). Progress on information and communication technologies in hospitality and tourism
. International Journal of Contemporary Hospitality Management
, 26
(5
), 727
–750
.Leung et al., 2013
Leung
, R.
, Rong
, J.
, Li
, G.
, & Law
, R.
(2013
). Personality differences and hotel web design study using targeted positive and negative association rule mining
. Journal of Hospitality Marketing & Management
, 22
(7
), 701
–727
.Liebowitz, 2013
Lingyun et al., 2012
Lingyun
, Z.
, Nao
, Z.
, & Min
, L.
(2012
). On the basic concept of smarter tourism and its theoretical system [J]
. Tourism Tribune
, 27
(5
), 66
–73
.Luo et al., 2016
Luo
, C.
, Sang
, C.
, & Ling
, L.
(2016
). Quantitative analysis of tourism economic contribution degree based on big data information and time series
. Model
, 9
(9
), 305
–316
.Ly, 2019
Ly
, B.
(2019
). Utilization of big data in tourism industries
. Research Journal of Economics & Business Studies
, 3
, 1
–9
.Mankar and Ingle, 2015
Mankar
, S. A.
, & Ingle
, M.
(2015
). Implicit sentiment identification using aspect based opinion mining
. International Journal on Recent and Innovation Trends in Computing and Communication
, 3
(2015
), 2184
–2188
.Maria, 2018
Maria
, K.
(2018
). Big data in tourism
. Master Thesis
. Hellenic University
. https://pdfs.semanticscholar.org/9562/40bd5f88f54a6facb7fa12527c8a46a5165f.pdf. Accessed on December 27, 2019
.Mariani et al., 2019
Mariani
, M. M.
, Baggio
, R.
, Fuchs
, M.
, & Höpken
, W.
(2019
). Business intelligence and big data in hospitality and tourism: A systematic literature review
. https//pdfs.semanticscholar.org/1f00/3999f952f67cd2bcb75fa417c568cf08faab.pdf. Accessed on January 4, 2019
.Mayer-Schönberger and Cukier, 2013
Mayer-Schönberger
, V.
, & Cukier
, K.
(2013
). Big data: A revolution that will transform how we live, work, and think
. Houghton Mifflin Harcourt
.Miah et al., 2017
Miah
, S. J.
, Vu
, H. Q.
, Gammack
, J.
, & McGrath
, M.
(2017
). A big data analytics method for tourist behaviour analysis
. Information & Management
, 54
(6
), 771
–785
.Mikolov et al., 2013
Mikolov
, T.
, Chen
, K.
, Corrado
, G.
, & Dean
, J.
(2013
). Efficient estimation of word representations in vector space
. Mirończuk and Protasiewicz, 2018
Mirończuk
, M. M.
, & Protasiewicz
, J.
(2018
). A recent overview of the state-of-the-art elements of text classification
. Expert Systems with Applications
, 106
, 36
–54
.Mohan, 2016
Mohan
, A.
(2016
). Big data analytics recent achievements and new challenges
. International Journal of Computer Applications Technology and Research
, 5
(7
), 460
–464
.Nichols, 2013
O'Flannagan, 2014
O'Flannagan
, D.
(2014
). The future of personalized marketing in travel
. Boxever Skift Report
.Oussous et al., 2016
Oussous
, A.
, Benjelloun
, F. Z.
, Lahcen
, A. A.
, & Belfkih
, S.
(2016
). Big Data technologies: A survey
. Journal of King Saud University – Computer and Information Sciences
, 30
, 431
–438
.Palomo, 2016
Palomo
, J.
(2016
). The use of new data analysis techniques in tourism: A bibliometric analysis in data mining, big data and structural equations models
. http//agrilife.org/ertr/files/2016/12/RN90.pdf. Accessed on January 2, 2019
.Pan and Yang, 2016
Pan
, B.
, & Yang
, Y.
(2016
). Monitoring and forecasting tourist activities with big data
. In M.
Uysal
, Z.
Schwartz
, & E.
Sirakaya-Turk
(Eds.), Management science in hospitality and tourism
(pp. 43
–62
).Parashar and Sharma,
Parashar
, P.
, & Sharma
, S.
(2016
).Opinion mining of tourism review using hybrid technique of support vector machine and animal migration optimization
. International Journal of Innovations in Engineering and Technology
, 7
(1
), 718
–731
.Patel and Bhosale, 2018
Patel
, P. C.
, & Bhosale
, A.
(2018
). Big data analytics
. Open Access Journal of Science
, 2
(5
), 326
–335
.Pham et al., 2017
Pham
, T. N.
, Nguyen
, V. Q.
, Tran
, V. H.
, Nguyen
, T. T.
, & Ha
, Q. T.
(2017
). A semi-supervised multi-label classification framework with feature reduction and enrichment
. Journal of Information and Telecommunication
, 1 4
, 305
–318
.Qiu et al., 2014
Qiu
, Z.
, Wu
, B.
, Wang
, B.
, Shi
, C.
, & Yu
, L.
(2014
). Collapsed Gibbs sampling for latent Dirichlet allocation on spark
. Journal of Machine Learning Research
, 36
, 17
–28
.Rajput, 2019
Rajput
, R.
(2019
). How big data triggered travel industry success? Meeting information need of travel industry
. ThriveGlobal
.Ramzan et al., 2019
Ramzan
, B.
, Bajwa
, I. S.
, Jamil
, N.
, Amin
, R. U.
, Ramzan
, S.
, Mirza
, F.
, & Sarwar
, N.
(2019
). An intelligent data analysis for recommendation system using machine learning
. Scientific Programming
. Ransbotham and Kiron, 2018
Ransbotham
, S.
, & Kiron
, D.
(2018
). Using analytics to improve customer engagement
. MIT Sloan Management Review
.Riahi and Riahi, 2018
Riahi
, Y.
, & Riahi
, S.
(2018
). Big data and big data analytics concepts, types and technologies
. International Journal of Religious Education
, 5
(9
), 524
–528
.Robertson, 2004
Robertson
, S.
(2004
). Understanding inverse document frequency on theoretical arguments for idf
. Journal of Documentation
, 60
, 503
–520
.Salas-Olmedo et al., 2018
Salas-Olmedo
, M. H.
, Moya-Gómez
, B.
, García-Palomares
, J. C.
, & Gutiérrez
, J.
(2018
). Tourists' digital footprint in cities: Comparing Big Data sources
. Tourism Management
, 66
, 13
–25
.Satish and &Yusof, 2017
Satish
, L.
, & Yusof
, N.
(2017
). A review big data analytics for enhanced customer experiences with crowd sourcing
. Procedia Computer Science
, 116
, 274
–283
.Saunders, 2017
Saunders
, A. A.
(2017
). Transforming the travel industry with Big Data Analytics
. https//www.digitaldoughnut.com/articles/2017/February/how-big-data-analytics-is-transforming-the-travel. Accessed on December 29, 2019
.Shafiee and Ghatari, 2016
Shafiee
, S.
, & Ghatari
, A. R.
(2016
). Big data in tourism industry
. In 10th International Conference on E-commerce in Developing Countries with focus on e-Tourism (ECDC)
. IEEE Publisher
.Sheoran, 2017
Sheoran
, S. K.
(2017
). Big data: A big boon for tourism sector
. International Journal of Research in Advanced Engineering and Technology
, 3
(1
), 10
–13
.Siblini et al., 2019
Siblini
, W.
, Kuntz
, P.
, & Meyer
, F.
(2019
). A review on dimensionality reduction for multi-label classification
. In IEEE Transactions on Knowledge and Data Engineering
. Institute of Electrical and Electronics Engineers
.Sigala and Rahimi, 2017
Sigala
, M.
, & Rahimi
, R.
(2017
). Big data in hospitality and tourism
. Emerald Publishing Limited
.Sobolevsky et al., 2014
Sobolevsky
, S.
, Sitko
, I.
, Tachet des Combes
, R.
, Hawelka
, B.
, Murillo Arias
, J.
, & Ratti
, C.
(2014
). Money on the move big data of bank card transactions as the ne proxy for human mobility patterns and regional delineation. The case of residents and foreign visitors in Spain
. Paper presented at the
IEEE International Congress on Big Data (BigData Congress), 2014
.Song and Han, 2017
Song
, H.
, & Han
, L.
(2017
). Predicting tourist demand using big data
. https//www.researchgate.net/publication/309092870_Predicting_Tourist_Demand_Using_Big_Data/citation/download. Accessed on December 27, 2019
.Song and Li, 2008
Song
, H.
, & Li
, G.
(2008
). Tourism demand modelling and forecasting A review of recent research
. Tourism Management
, 29
, 203
–220
.Stienmetz and Fesenmaier, 2013
Stienmetz
, J. L.
, & Fesenmaier
, D. R.
(2013
). Traveling the network a proposal for destination performance metrics
. International Journal of Tourism Sciences
, 13
(2
), 57
–75
.Thomas and Davenport, 2013
Thomas
, H.
, & Davenport
, J. D.
(2013
). Big data in big companies
. International Institute for Analytics
.Tian et al., 2016
Tian
, X.
, He
, W.
, Tao
, R.
, & Akula
, V.
(2016
). Mining online hotel reviews a case study from hotels in China
. In 22nd Americas Conference on Information Systems
(pp. 1
–7
). San Diego
.Upadhyaya and Kynclova, 2019
Upadhyaya
, S.
, & Kynclova
, P.
(2019
). Big Data – Its relevance and impact on industrial statistics
. Working Paper 11
. United Nations Industrial Development Organization
, Vienna
.Van de Cruys, 2011
Van de Cruys
, T.
(2011
). Two multivariate generalizations of pointwise mutual information
. In Proceedings of the Workshop on Distributional Semantics and Compositionality
(pp. 16
–20
). Association for Computational Linguistics
.Vecchio et al., 2018
Vecchio
, P. D.
, Mele
, G.
, Ndou
, V.
, & Secundo
, G.
(2018
). Open innovation and social big data for sustainability evidence from the tourism industry
. Sustainability
, 10
(3215
), 1
–15
.Verhoef et al., 2016
Verhoef
, P. C.
, Kooge
, E.
, & Walk
, N.
(2016
). Creating value with big data analytics making smarter marketing decisions
. Routledge
.Wang et al., 2018
Wang
, H.
, Gao
, S.
, Tang
, O.
, & Yin
, P.
(2018
). Identifying competitors through comparative relation mining of online reviews in the restaurant industry
. International Journal of Hospitality Management
, 71
, 19
–32
.Wang et al., 2018
Wang
, J.
, Li
, S.
, Jiang
, M.
, Wu
, H.
, & Zhou
, G.
(2018
). Cross-media user profiling with joint textual and social user embedding
. In Proceedings of the 27th International Conference on Computational Linguistics
(pp. 1410
–1420
). 21–25 August 2018
, Santa Fe, NM, USA
.Wang et al., 2017
Wang
, J.
, Li
, S.
, & Zhou
, G.
(2017
). Joint learning on relevant user attributes in micro-blog
. In Proceedings of the 26th International Joint Conference on Artificial Intelligence
(pp. 4130
–4136
). 21–25 August 2017
, Melbourne, Australia
.Wang et al., 2016
Wang
, H.
, Xu
, Z.
, Fujita
, H.
, & Liu
, S.
(2016
). Towards felicitous decision making an overview on challenges and trends of big data
. Information Science
, 367
, 747
–765
.Watson, 2014
Watson
, H. J.
(2014
), Tutorial: Big data analytics: Concepts, technologies, and applications
, Communications of the Association for Information Systems
, 34
, 124
–168
.Wu et al., 2016
Wu
, F.
, Huang
, Y.
, Song
, Y.
, & Liu
, S.
(2016
). Towards building a high-quality microblog-specific Chinese sentiment lexicon
. Decision Support Systems
, 87
, 39
–49
.Xiang, 2016
Xiang
, Z.
(2016
). Analytics for tourism management needs and directions for research
. Springer.Yang and Stienmetz, 2018
Yang
, Y.
, & Stienmetz
, J. L.
(2018
). Big data and tourism planning
. Information Technology & Tourism
, 20
, 189
–190
.Yaw, 2015
Yaw
, K. C.
(2015
). Sentiment analysis of hotel service system
. http//eprints.utar.edu.my/1839/1/IB-2015-13ACB00854-1.pdf. Accessed on October 10, 2020
.Zerba, 2018
Zerba
, F.
(2018
). Big data tools and tourism market intelligence
. In 15th Global Forum on Tourism Statistics Cusco
. Peru
.Zheng, 2014
Zheng
, Q.
(2014
). Online public opinion needs tourism online reputation evaluation mechanisms
. As Cited in Guanglu, L, Xiangye, S., Hong, L., Hongzhi, L. (2015). Path Analysis on Big Data in Promoting Intelligent Tourism Implementation. International Conference on Management Science, Education Technology, Arts, Social Science and Economics
.
This content is only available via PDF.
Related Topics
Email alerts
Related Articles
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
