Big Data and Business Intelligence in Tourism: Analyzing Trends and Enhancing Customer Satisfaction Through Online Review Analytics

Leonidas Theodorakopoulos, Alexandra Theodoropoulou and Constantinos Halkiopoulos ()
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Leonidas Theodorakopoulos: University of Patras
Alexandra Theodoropoulou: University of Patras
Constantinos Halkiopoulos: University of Patras

A chapter in Innovation and Creativity in Tourism, Business and Social Sciences, 2025, pp 507-536 from Springer

Abstract: Abstract A review of the literature was performed with relevant studies and databases to assess how Big Data Analytics (BDA) & Business Intelligence will be utilized in tourism marketing specifically for online reviews. Adopting the PRISMA-2020 methodology, between 2017 and 2024 this paper synthesizes a research on how these technologies contribute to improve both customer watchful over tourism sector as well market feedback from clients. The topics reviewed touch upon the analysis of restaurant or hotel reviews, for instance to predict satisfaction in international tourism with advanced techniques like text mining, sentiment analysis and neural networks. Findings reveal the revolution of Big Data on improving service quality, marketing approaches and customer satisfaction in tourism. Together with this research, it provides a complete framework to integrate Big Data and Business Intelligence in tourism marketing proving insights for industry practices and contributing to the academic literature on digital transformation in tourism.

Keywords: BI; AI; Big Data; Tourism; Online Reviews; Customer Satisfaction; Text Mining; Sentiment Analysis; Hospitality Industry (search for similar items in EconPapers)
JEL-codes: L86 M31 O32 O33 Z32 Z33 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-87019-4_35

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DOI: 10.1007/978-3-031-87019-4_35

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