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Redefining Hotel Competitive Sets: A Data-Driven Approach
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| 1.28 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
Hotels commonly monitor competitors to benchmark their sales tactics. However, defining an
incorrect competitive set can pose risks at all levels of the business. It is essential to recognize
that today's customers have access to extensive information and are discerning in their
comparisons among various travel service providers. With the Internet significantly
influencing search and distribution, the hotel industry must adopt a strategic approach that
leverages the potential of online channels. This study surpasses traditional methods of
defining competitive sets by utilizing attributes such as social reputation and hotel facilities,
drawing from publicly available data. The methodology proposed in this study incorporates
pricing, capacity, and facilities (including restaurant, fitness, pool, and car parking), alongside
social reputation and rating. Data were collected from TripAdvisor, Booking, and the Registo
Nacional de Turismo for 4-star hotels in Lisbon, Portugal. Cluster analysis using the K-Means
algorithm was employed, explaining 73% of the variance in the data, which proved highly
effective in clustering. The academic contribution of this competitive set lies in its ability to
mitigate bias, enhance validation possibilities, and improve benchmarking efficiency. It
provides a comprehensive market perspective within the hospitality industry, serves as a tool
for comparing hotels with the five closest competitors within each respective group, and aids
in enhancing brand reputation.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
Palavras-chave
Competitive Set Benchmarking Hospitality Clustering Bias SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure