Publicação
A Data-driven Competitive Set Framework for the Hotel Industry: Mapping Customer Perceptions through Clustering Analysis
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | António, Nuno Miguel da Conceição | |
| dc.contributor.author | Wroclawska, Alicja Urszula | |
| dc.date.accessioned | 2025-11-11T15:04:19Z | |
| dc.date.embargo | 2028-10-29 | |
| dc.date.issued | 2025-10-29 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and Analytics | pt_PT |
| dc.description.abstract | Competitor identification is crucial in the hospitality industry. However, identifying the correct competitors is a complicated and often biased task. This study investigates the problem of defining competitive sets in the hospitality industry, particularly in the five-star hotel sector, where traditional supply-side methods are often insufficient to capture the complexity of modern market dynamics. Motivated by the increasing importance of customer perception and the availability of online data, the study proposes a data-driven methodology that leverages clustering techniques to identify meaningful groupings of competing hotels. The dataset comprises 43 five-star hotels in Lisbon, with features extracted from online travel agency and from the official record of tourism properties, including, among others, guest satisfaction ratings and geographic coordinates. Following exploratory data analysis and feature preprocessing, three clustering algorithms were tested. Based on DBSCAN combined with K-Means clustering with five clusters, the final model utilized ratings and location data. Results indicate that location and experiential attributes, particularly staff, cleanliness, and comfort ratings, are more influential than price in shaping competitive structures among fivestar hotels. This finding aligns with recent literature emphasizing the limited influence of price on competition among five-star hotels. The study offers a replicable, data-driven method for defining competitive sets based on customer experience and location data. The findings highlight the significance of customer experience variables in distinguishing five-star hotel offerings. | pt_PT |
| dc.identifier.tid | 204073456 | |
| dc.identifier.uri | http://hdl.handle.net/10362/190492 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Competitive Sets | pt_PT |
| dc.subject | Clustering | pt_PT |
| dc.subject | Hospitality | pt_PT |
| dc.subject | Hospitality Analytics | pt_PT |
| dc.subject | SDG 8 - Decent work and economic growth | pt_PT |
| dc.title | A Data-driven Competitive Set Framework for the Hotel Industry: Mapping Customer Perceptions through Clustering Analysis | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.embargofct | Potential publication | pt_PT |
| rcaap.rights | embargoedAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Marketing Analítico, especialização em Digital Marketing and Analytics | pt_PT |