Publicação
Redefining Hotel Competitive Sets: A Data-Driven Approach
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | António, Nuno Miguel da Conceição | |
| dc.contributor.author | Ottavi, Ana Carolina | |
| dc.date.accessioned | 2024-12-02T15:16:22Z | |
| dc.date.embargo | 2026-10-31 | |
| dc.date.issued | 2024-10-31 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics | pt_PT |
| dc.description.abstract | 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. | pt_PT |
| dc.identifier.tid | 203782763 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/176123 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Competitive Set | pt_PT |
| dc.subject | Benchmarking | pt_PT |
| dc.subject | Hospitality | pt_PT |
| dc.subject | Clustering | pt_PT |
| dc.subject | Bias | pt_PT |
| dc.subject | SDG 8 - Decent work and economic growth | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.title | Redefining Hotel Competitive Sets: A Data-Driven Approach | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | embargoedAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Ciência de Dados e Métodos Analíticos Avançados, especialização em Métodos Analíticos para a Gestão | pt_PT |