Advertisement

Big Data in Online Travel Agencies and Its Application Through Electronic Devices

  • Josep Ma EspinetEmail author
Chapter

Abstract

The aim of this chapter is to shed light on the present and future of big data in OTAs with regard to the particular electronic device where the website or app is displayed. Use of big data is strategic for OTAs as it could allow these companies to gain a competitive advantage and reduce their costs. The results from the empirical research carried out specifically for this chapter reveal that OTAs use big data extensively throughout the entire customer experience. Nevertheless, untapped potential remains which could be exploited to derive further competitive advantage. The main differences created by using different electronic devices is the quantity of information displayed due to the reduced size of the screens. Smartphones can provide OTAs another important difference through the use of GPS and highly accurate tracking technologies that enable these companies to obtain accurate information about what their customers do during a stay in a destination, so that these companies can offer a more customized service. Finally, OTAs should consider big data as a mindset which affects the whole company and its organizational structure, and not only as information and its associated technology.

Keywords

OTAs Electronic devices Big data Customer experience Smartphones 

Notes

Acknowledgements

I would like to thank Laura Rafel, Àlex Espinet and Gethyn Rees for their help in this chapter.

References

  1. Anderson CK (2011) Search, OTAs, and online booking: an expanded analysis of the billboard effect. Cornell Hospitality Report 11(8):4–10Google Scholar
  2. Ayscue EP, Boley BB, Mertzlufft CE (2016) Mobile technology & resident attitude research. Tour Manage 52:559–562CrossRefGoogle Scholar
  3. Bai B, Law R, Wen I (2008) The impact of website quality on customer satisfaction and purchase intentions: evidence from Chinese online visitors. Int J Hospitality Manage 27(3):391–402CrossRefGoogle Scholar
  4. Baldwin H (2015) When Big Data projects go wrong. Forbes. Retrieved the 20 Jan 2018 from http://www.forbes.com/sites/howardbaldwin/2015/01/22/when-big-data-projects-go-wrong/#4b11e3a26231
  5. Banerjee S, Chua AY (2016) In search of patterns among travellers’ hotel ratings in TripAdvisor. Tour Manage 53:125–131CrossRefGoogle Scholar
  6. Cheng M, Edwards D (2015) Social media in tourism: a visual analytic approach. Curr Issues Tour 18(11):1080–1087CrossRefGoogle Scholar
  7. Côrte-Real N, Oliveira T, Ruivo P (2017) Assessing business value of Big Data Analytics in European firms. J Bus Res 70:379–390CrossRefGoogle Scholar
  8. Ditrendia (2017) Informe Mobile en España y en el Mundo 2017. Retrieved 25 Jan 2017 from http://www.amic.media/media/files/file_352_1289.pdf
  9. Erevelles S, Fukawa N, Swayne L (2016) Big Data consumer analytics and the transformation of marketing. J Bus Res 69:897–904CrossRefGoogle Scholar
  10. Espinet JM, Espinet A (2017) Calidad y Satisfacción de los clientes del sector turístico a través de los dispositivos electrónicos: presente y futuro. Proceedings of International Marketing Trends Conference 2017 Madrid, 26–28 January, ed. Jean-Claude Andreani and Umberto Collesei, Paris-Venice Marketing Trends AssociationGoogle Scholar
  11. Espinet JM, Espinet A, Filimon N (2017) Marketing through smartphones: the role of customer satisfaction and prices. In: 22nd International conference on corporate and marketing communications. challenges of marketing communications in a globalized world. 4–5, May 2017. ISBN: 978-84-946082-09Google Scholar
  12. Gandomi A, Haider M (2015) Beyond the hype: big data concepts, methods, and analytics. Int J Inf Manage 35(2):137–144CrossRefGoogle Scholar
  13. Guo Y, Barnes SJ, Jia Q (2017) Mining meaning from online ratings and reviews: tourist satisfaction analysis using latent dirichlet al location. Tour Manage 59:467–483CrossRefGoogle Scholar
  14. Hardy A, Hyslop S, Booth K, Robards B, Aryal J, Gretzel U et al (2017) Tracking tourists’ travel with smartphone-based GPS technology: a methodological discussion. Inf Technol Tour 17(3):255–274CrossRefGoogle Scholar
  15. Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU (2015) The rise of “big data” on cloud computing: review and open research issues. Inf Syst 47:98–115CrossRefGoogle Scholar
  16. Kambatla K, Kollias G, Kumar V, Grama A (2014) Trends in big data analytics. J Parallel Distrib Comput 74(7):2561–2573CrossRefGoogle Scholar
  17. Khan N et al (2014) Big Data: survey, technologies, opportunities, and challenges. Sci World J 2014:18Google Scholar
  18. Kim HH, Law R (2015) Smartphones in tourism and hospitality marketing: a literature review. J Travel Tour Mark 32(6):692–711CrossRefGoogle Scholar
  19. Li J, Xu L, Tang L, Wang S, Li L (2018) Big data in tourism research: a literature review. Tour Manage 68:301–323CrossRefGoogle Scholar
  20. Liu Y, Teichert T, Rossi M, Li H, Hu F (2017) Big Data for big insights: investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tour Manage 59:554–563CrossRefGoogle Scholar
  21. Mantelero A (2017) Regulation Big Data. the guidelines of the Council of Europe in the context of the European data protection framework. Comput Law Secur Rev 584–602CrossRefGoogle Scholar
  22. Mariani M, Borghi M (2018) Effects of the Booking.com rating system: bringing hotel class into the picture. Tour Manage 66:47–52CrossRefGoogle Scholar
  23. Mariani M, Di Felice M, Mura M (2016) Facebook as a destination marketing tool: evidence from Italian regional Destination Management Organizations. Tour Manage 54:321–343CrossRefGoogle Scholar
  24. Marine-Roig E, Clavé SA (2015) Tourism analytics with massive user generated content: a case study of Barcelona. J Destination Mark Manage 4(3):162–172CrossRefGoogle Scholar
  25. Miah SJ, Vu HQ, Gammack J, McGrath M (2017) A big data analytics method for tourist behaviour analysis. Inf Manage 54(6):771–785CrossRefGoogle Scholar
  26. Murphy HC, Chen MM, Cossutta M (2016) An investigation of multiple devices and information sources used in the hotel booking process. Tour Manage 52:44–51CrossRefGoogle Scholar
  27. Nikolopoulos K, Petropoulos F (2017) Forecasting for Big Data: does suboptimality matter? Computers and Operations Research, onlineGoogle Scholar
  28. Oracle (2013) Big Data for the enterprise. OracleWhite Paper 1–16. Retrieved 20 Jan 2018 from http://www.oracle.com/us/products/database/big-data-for-enterprise-519135.pdf
  29. Plaza B (2011) Google Analytics for measuring website performance. Tour Manage 32(3):477–481CrossRefGoogle Scholar
  30. Raguseo E (2018) Big Data technologies: an empirical investigation on their adoption, benefits and risks for companies. Int J Inf Manage 28:187–195CrossRefGoogle Scholar
  31. Raun J, Ahas R, Tiru M (2016) Measuring tourism destinations using mobile tracking data. Tour Manage 57:202–212CrossRefGoogle Scholar
  32. Sivarajah U, Kamal M, Irani Z, Weerakkody V (2017) Critical analysis of Big Data challenges and analytical methods. J Bus Res 70:263–286CrossRefGoogle Scholar
  33. Smith R, Deitz G, Royne MB, Hansen JD, Grünhagen M, Witte C (2013) Cross-cultural examination of online shopping behavior: a comparison of Norway, Germany, and the United States. J Bus Res 66(3):328–335CrossRefGoogle Scholar
  34. Steppe R (2017) Online price discrimination and personal data: a General Data Protection Regulation perspective. Comput Law Secur Rev 33:768–785CrossRefGoogle Scholar
  35. Stieglitz S, Mirbabaie M, Ross B, Neuberger C (2018) Social media analytics—challenges in topic discovery, data collection, and data preparation. Int J Inf Manage 39:156–168CrossRefGoogle Scholar
  36. Stringam BB, Gerdes J Jr (2010) An analysis of word-of-mouse ratings and guest comments of online hotel distribution sites. J Hospitality Mark Manage 19(7):773–796CrossRefGoogle Scholar
  37. Ur Rehman MH, Chang V, Batool A, Wah TY (2016) Big Data reduction framework for value creation in sustainable enterprises. Int J Inf Manage 36(6):917–928CrossRefGoogle Scholar
  38. Verma R, Stock D, McCarthy L (2012) Customer preferences for online, social media, and mobile innovations in the hospitality industry. Cornell Hospitality Q 53(3):183–186CrossRefGoogle Scholar
  39. Xiang Z, Schwartz Z, Gerdes JH Jr, Uysal M (2015) What can Big Data and text analytics tell us about hotel guest experience and satisfaction? Int J Hospitality Manage 44:120–130CrossRefGoogle Scholar
  40. Xiang Z, Du Q, Ma Y, Fan W (2017) A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour Manage 58:51–65CrossRefGoogle Scholar
  41. Yaqoob I, Hashem I, Gani A, Mokhtar S, Ahmed E, Anuar N, Vasilakos AV (2016) Big Data: from beginning to future. Int J Inf Manage 36:1231–1247CrossRefGoogle Scholar
  42. Yovcheva Z, Buhalis D, Gatzidis C (2012) Smartphone augmented reality applications for tourism. e-Review Tour Res (eRTR) 10(2):2012Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Universitat de GironaGironaSpain
  2. 2.Universitat de MediterraniBarcelonaSpain

Personalised recommendations