Big Data applications to improve tourism management in destinations: the case of the hotel industry in the City of Buenos Aires
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Matías Belacín [1]
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[1] London School of Economics
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- Localización: Transitioning towards the future of tourism destinations: resilient, smart, and green development / coord. por Francisco Femenia Serra, Aurkene Alzua Sorzabal, Zheng Xiang, 2022, ISBN 978-84-1125-632-2, págs. 343-379
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
How can Big Data contribute to evidence-based tourismmanagement? This chapter introduces a case study analyzingcompetitiveness in the Buenos Aires hotel industry in order to illustrate the potential of Big Data at each stage of the policymaking process, from data collection to policy design. By collecting and analyzing over a million publicly available hotel and user-generated content records from digital accommodation platforms, this approach uses data intelligence tools (web scraping, machine learning, and econometric analysis) to examine key components of the competitiveness of four- and five-star hotels in Buenos Aires. Based on econometric and sentiment analysis techniques, the study shows compelling empirical evidence of Buenos Aires hotels’underperformance in the four-star category. The outcomes of the research motivated and helped shape the Program of Fiscal Incentives for Hotel Investments, a local scheme passed in 2018 that incentivizes investment in hotels (both greenfield and remodelling) through tax rebates. Through this case study, the chapter encourages destinations to introduce innovative market intelligence techniques to improve evidence-based policymakingin tourism management.
