Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/16702
Autoria: Moro, S.
Rita, P.
Oliveira, C.
Batista, F.
Ribeiro, R.
Data: 2018
Título próprio: Leveraging national tourist offices through data analytics
Volume: 12
Número: 4
Paginação: 420 - 426
ISSN: 1750-6182
DOI (Digital Object Identifier): 10.1108/IJCTHR-04-2018-0051
Palavras-chave: Data mining
Data analytics
Sensitivity analysis
Online reviews
National tourist offices
Web scraping
Resumo: Purpose This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole country. Design/methodology/approach The method starts by extracting information from all hotels of Portugal available at TripAdvisor through Web scraping. Then, a support vector machine is adopted for modeling the TripAdvisor score, which is considered a proxy of customer satisfaction. Finally, knowledge extraction from the model is achieved using sensitivity analysis to unveil the influence of features on the score. Findings The model of the TripAdvisor score achieved a mean absolute percentage error of around 5 per cent, proving the value of modeling the extracted data. The number of rooms of the unit and the minimum price are the two most relevant features, showing that customers appreciate smaller and more expensive units, whereas the location of the hotel does not hold significant relevance. Originality/value National tourist offices can use the proposed approach to understand what drives tourists’ satisfaction, helping to shape a country’s strategy. For example, licensing new hotels may take into account the unit size and other characteristics that make it more attractive to tourists. Furthermore, the procedure can be replicated at any time and in any country, making it a valuable tool for data-driven decision support on a national scale.
Arbitragem científica: yes
Acesso: Acesso Aberto
Aparece nas coleções:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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