Abstract
Service quality plays an important role in hotel competitiveness, being tools based on this concept a way to differentiate hotels within their sector. The main goal of this work is to develop a tool for client customization. Such a tool can personalize the importance that each client gives to four attributes: customer service, facilities, overall cleanliness and quality-price ratio. A questionnaire was conducted on the opinions of more than fifty thousand clients during a period of twelve months. Our approach makes use of the machine learning methodology known as k-Nearest Neighbor (kNN). Among other important facts, the results reveal that the quality price ratio is assessed by clients as one of the most important attributes in order to provide a positive recommendation of a hotel. Based on the proposed methodology, new recommendation models can be developed with the aim of finding out implicit preferences of customers for future stays.
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Acknowledgements
This work has been partially funded by projects of the Spanish Ministry of Science, Innovation and Universities: GROMA (reference: MTM2015-63710-P) and MODAS-IN (reference: RTI2018-094269-B-I00).
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Moguerza, J.M., Martín-Duque, C. & Fernández-Muñoz, J.J. The importance of service quality as an instrument for client customization: a methodological and practical approach within the hotel sector. Qual Quant 56, 1631–1642 (2022). https://doi.org/10.1007/s11135-021-01198-4
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DOI: https://doi.org/10.1007/s11135-021-01198-4