A Survey : Application of Big Data in the Travel and Tourism Industry

  • Putri Previa Yanti Institut Teknologi Bandung
Keywords: big data, travel industry, tourism, survey

Abstract

The development of information technology has increased the travel and tourism industry. The travel and tourism data are available in many sources such as telephone, social media, sensor system on the internet of things, and others. The application of big data has great potential in the development of the travel and tourism industry. Big data can take advantage of new things in making the right decisions and seeing opportunities in doing better business. This paper provides a survey that discusses big data in the travel and tourism industry. Big data is used to ticket price and demand prediction. In addition, big data is also used to build a tourism plans and recommender system with the personalized and adaptive method. Combination of using the internet of things and big data can help the industry to price their product. The result of this study is some of the implementation of big data in the travel and tourism industry. We conclude that big data can be used to explore new things in making the right decisions, seeing opportunities more observant, and doing business more efficiently

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References

J. A. Abdella, N. Zaki, K. Shuaib, dan F. Khan, “Airline Ticket Price and Demand Prediction: A survey,†J. King Saud Univ. - Comput. Inf. Sci., no. xxxx, 2019.

J. Liu, B. Liu, Y. Liu, H. Chen, L. Feng, H. Xiong, dan Y. Huang, “Personalized Air Travel Prediction,†ACM Trans. Intell. Syst. Technol., vol. 9, no. 3, hal. 1–26, 2018.

X. Zhang dan W. T. Yue, “Transformative value of the Internet of Things and pricing decisions,†Electron. Commer. Res. Appl., vol. 34, no. January, 2019.

M. B. Dezfouli, M. H. N. Shahraki, dan H. Zamani, “A Novel Tour Planning Model using Big Data,†in 2018 International Conference on Artificial Intelligence and Data Processing (IDAP), 2018, hal. 1–6.

H. Song dan H. Liu, “Predicting Tourist Demand Using Big Data,†in Analytics in Smart Tourism Design: Concepts and Methods, Springer International Publishing, 2017, hal. 13–29.

O. Boulaalam, B. Aghoutane, D. El Ouadghiri, A. Moumen, dan M. L. Cheikh Malinine, “Proposal of a Big data System Based on the Recommendation and Profiling Techniques for an Intelligent Management of Moroccan Tourism,†in Procedia Computer Science, 2018, vol. 134, no. 2017, hal. 346–351.

O. Etzioni, C. A. Knoblock, M. Rey, dan A. Yates, “To Buy or Not to Buy : Mining Airfare Data to Minimize Ticket Purchase Price Categories and Subject Descriptors,†in 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003, hal. 119–128.

J. A. Abdella, N. Zaki, dan K. Shuaib, “Automatic Detection of Airline Ticket Price and Demand : A review,†in 2018 International Conference on Innovations in Information Technology (IIT), 2018, hal. 169–174.

W. Groves dan M. L. Gini, “An agent for optimizing airline ticket purchasing.,†in Proceedings of the International Conference on Autonomous Agents and Multi-agent Systems, 2013, no. May 2013, hal. 1341–1342.

W. Groves dan M. Gini, “On Optimizing Airline Ticket Purchase Timing,†ACM Trans. Intell. Syst. Technol., vol. 7, no. 1, hal. 1–28, 2015.

T. Wohlfarth, S. Clémencon, F. Roueff, dan X. Casellato, “A data-mining approach to travel price forecasting,†in Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011, 2011, vol. 1, no. M, hal. 84–89.

Y. Chen, J. Cao, S. Feng, dan Y. Tan, “An ensemble learning based approach for building airfare forecast service,†in Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015, 2015, hal. 964–969.

T. Liu, J. Cao, Y. Tan, dan Q. Xiao, “ACER: An adaptive context-aware ensemble regression model for airfare price prediction,†in Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017, 2017, hal. 312–317.

T. Janssen, “A Linear Quantile Mixed Regression Model for Prediction of Airline Ticket Prices,†Radboud University, 2014.

H. Yuan, W. Xu, dan C. Yang, “A user behavior-based ticket sales prediction using data mining tools: An empirical study in an OTA company,†in 11th International Conference on Service Systems and Service Management, ICSSSM 2014 - Proceeding, 2014, hal. 1–6.

D. Liu, “A Model of Optimal Consumer Search and Price Discrimination in the Airline Industry,†2015, hal. 1–31.

S. L. Puller dan L. M. Taylor, “Price discrimination by day-of-week of purchase: Evidence from the U.S. airline industry,†J. Econ. Behav. Organ., vol. 84, no. 3, hal. 801–812, 2012.

A. Alaei dan S. Becken, “Sentiment Analysis in Tourism : Capitalizing on Big Data,†J. Travel Res., no. December, 2017.

S. J. Miah, H. Q. Vu, J. Gammack, dan M. McGrath, “A Big Data Analytics Method for Tourist Behaviour Analysis,†Inf. Manag., vol. 54, no. 6, hal. 771–785, 2017.

Published
2020-07-31
How to Cite
Yanti, P. P. (2020). A Survey : Application of Big Data in the Travel and Tourism Industry. ITEJ (Information Technology Engineering Journals), 5(1), 1 - 13. https://doi.org/10.24235/itej.v5i1.38
Section
Articles