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Tourist Behaviour Analysis Using Data Analytics
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Author(s): L. Maria Michael Visuwasam (RMK College of Engineering and Technology, India), M. Srinath (RMK College of Engineering and Technology, India), V. S. Aswin Raj (RMK College of Engineering and Technology, India), A. Sirajudeen (RMK College of Engineering and Technology, India), S. Sudhir Maharaaja (RMK College of Engineering and Technology, India)and Dakshin Raja (RMK College of Engineering and Technology, India)
Copyright: 2024
Pages: 13
Source title:
Data-Driven Decision Making for Long-Term Business Success
Source Author(s)/Editor(s): Sonia Singh (Toss Global Management, UAE), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India), Slim Hadoussa (Brest Business School, France), Ahmed J. Obaid (University of Kufa, Iraq)and R. Regin (SRM Institute of Science and Technology, India)
DOI: 10.4018/979-8-3693-2193-5.ch023
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Abstract
There has been a lot of hurry in the tourism business in recent years, and the rise of IT technology has had a major impact on vacationers. In recent years, numerous studies of big data have been devoted to analysing tourists' behaviour. Decision-making support from big data analytics has only been shown in a small number of studies. The proliferation of social media's ability to gather massive amounts of data has opened up new avenues for research and improved insights for policymakers. The purpose of this chapter is to gain a deeper comprehension of the motivations behind visitors' actions, as well as the environmental and social influences that shape their experiences. The digital lifestyle pattern outlines the idea of tourist behaviour, bridges the gap between the tourist and the digital world, and allows us to zero in on how that behaviour evolves over time. Using the idea of a digital lifestyle pattern, we may build strategies for the behaviour of tourists.
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