Abstract
Big data plays a catalytic role in the determination of consumers’ preferences while achieving meaningful results together by obtaining the right data. Artificial intelligence systems, particularly those powered by machine technology, can achieve significant results through the rapid elimination of large data sets. This leads to determining structural changes both in consumer behaviour models and marketing strategies. With preliminary information about consumers, intelligent system mechanisms, i.e. artificial intelligence and Internet of Things (IoT), have increased the speed of information processing and the analysis of larger volumes of information and have also targeted reaching the right consumer segments, affecting their decision-making preferences before the event. As a result, these types of automations may enable tourism and hospitality businesses to benefit from marketing activities with the help of different algorithmic solutions. Thus, this chapter aims to debate how big data, artificial intelligence and IoT are likely to reshape the traditional structure of tourism and hospitality marketing in the future and introduces new approaches as the key elements in maintaining competitiveness in a new era.
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- 1.
‘Internet of Things’ connected devices almost triple to over 38 billion units by 2020. https://www.juniperresearch.com/press/press-releases/iot-connected-devices-to-triple-to-38-bn-by-2020. Accessed on 3 March 2018.
- 2.
Defining the future of travel through intelligence. A discussion paper from Amadeus, 2016, Amadeus IT Group.
- 3.
Barcelona IoT, big data projects help manage tourists at popular attractions. https://internetofbusiness.com/barcelona-iot-big-data-tourist/. Accessed on 19 February 2018.
- 4.
‘Internet of Things connected devices almost triple to over 38 billion units by 2020. https://www.juniperresearch.com/press/press-releases/iot-connected-devices-to-triple-to-38-bn-by-2020. Accessed on 3 March 2018.
- 5.
Tourism and The Internet of Things—IoT. https://medium.com/3baysover-tourism-networking/tourism-and-the-internet-of-things-iot-e41b125e7ddd. Accessed on 19 February 2018.
References
Ahas R, Aasa A, Roose A, Mark U, Silm S (2008) Evaluating passive mobile positioning data for tourism surveys: an Estonian case study. Tour Manag 29(3):469–486
Davenport TH (2013) At the Big Data crossroads: turning towards a smarter travel experience. Amadeus IT Group
Davenport TH (2014) Big Data @ Wor. Türk Hava Yolları Yayınları, Istanbul
Fuchs M, Höpken W, Lexhagen M (2014) Big data analytics for knowledge generation in tourism destinations: a case from Sweden. J Destination Mark Manag 3(4):198–209
Global Digital Report (2018) Digital in 2018: world’s internet users pass the 4 billion mark. https://wearesocial.com/blog/2018/01/global-digital-report-2018. Accessed on 5 Mar 2018
Gong L, Liu X, Wu L, Liu Y (2016) Inferring trip purposes and uncovering travel patterns from taxi trajectory data. Cartography and Geogr Inf Sci 43(2):103–114
Höpken W, Fuchs M, Keil D, Lexhagen M (2015) Business intelligence for cross-process knowledge extraction at tourism destinations. Inf Technol Tourism 15(2):101–130
International Data Corporation (2018) Worldwide Big Data technology and services forecast 2016–2020. Accessed on 6 Feb 2018. https://www.idc.com/getdoc.jsp?containerId=US40803116
Li D, Yang Y (2017) GIS monitoring of traveler flows—based on Big Data. In: Xiang Z, Fesenmaier DR (eds) Analytics in smart tourism design concepts and methods. Springer, Cham, pp 111–126
Lisi FA, Esposito F (2015) An AI application to integrated tourism planning. In: Gavanelli M et al (eds) I*IA 2015, LNAI 9336. Springer, Cham, pp 246–259
Menner T, Höpken W, Fuchs M, Lexhagen M (2016) Topic detection: identifying relevant topics in tourism reviews, information and communication technologies in tourism 2016. In: Proceedings of the international conference, Bilbao, Spain, pp 411–423
O’Leary DE (2013) Big Data2, the ‘Internet of Things’, and the ‘Internet of Signs’. Intell Sys Account, Finance and Manag 20:53–65
Önder I, Koerbitz W, Hubmann-Haidvogel A (2016) Tracing tourists by their digital footprints: the case of Austria. J Travel Res 55(5):566–573
Parahalad CK, Ramaswamy V (2002) The future of competition. Harvard Business School Press, Boston M.A
Park SB, Ok CM, Chae BK (2016) Using Twitter data for cruise tourism marketing and research. J Travel Tourism Mark 33(6):885–898
Scaglione M, Johnson C, Favre P (2018) When “last minute” really is “last minute”. In: Stangl B, Pesonen J (eds) Information and communication technologies. Springer, Cham, pp 501–514
Scaglione M, Favre P, Trabichet J.-P (2016) Using mobile data and strategic tourism flows: pilot study MoniTour in Switzerland. In: Proceedings of the big data & business intelligence in the travel & tourism domain workshop, Östersund, Sweden, 11–12 Apr
Scharl A, Lalicic L, Onder I (2017) Tourism intelligence and visual media analytics for destination management organizations. In: Xiang Z and Fesenmaier DR (eds) Analytics in smart tourism design concepts and methods (pp 165–178). Springer, Cham
Song H, Liu H (2017) Predicting tourist demand using Big Data. In: Xiang Z, Fesenmaier DR (eds) Analytics in smart tourism design concepts and methods. Springer, Cham, pp 13–28
Stienmetz JL (2018) Reconstructing visitor experiences: structure and sentiment. In: Stangl B, Pesonen J (eds) Information and communication technologies. Springer, Cham, pp 489–500
Turner V, Gantz JF (2014) The digital universe of opportunities: rich data and the increasing value of the Internet of Things. http://www.emc.com/leadership/digital-universe/index.htm. Accessed on 8 Feb 2018
Wang D, Xiang Z, Fesenmaier DR (2016) Smartphone use in everyday life and travel. J Travel Res 55(1):52–63
Xiang Z, Schwartz Z, Gerdes J, Uysal M (2015) What can big data and text analytics tell us about hotel guest experience and satisfaction? Int J Hospitality Manag 44:120–130
Zach FJ, Wallace SA, Tussyadiah IP, Narayana SP (2018) Developing and testing a domain-specific lexical dictionary for travel talk on Twitter (#ttot). In: Stangl B, Pesonen J (eds) Information and communication technologies. Springer, Cham, pp 528–539
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Inanc–Demir, M., Kozak, M. (2019). Big Data and Its Supporting Elements: Implications for Tourism and Hospitality Marketing. In: Sigala, M., Rahimi, R., Thelwall, M. (eds) Big Data and Innovation in Tourism, Travel, and Hospitality. Springer, Singapore. https://doi.org/10.1007/978-981-13-6339-9_13
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