Personalization of the tourism experience through machine learning techniques
DOI:
https://doi.org/10.61467/2007.1558.2025.v16i4.803Keywords:
Machine Learning, Clustering Algorithms, Tourism Personalization, Alameda CentralAbstract
This research focuses on analysing the experiences of visitors to Alameda Central during the Easter period in order to examine the degree of personalisation of the tourist experience. To this end, the study adopts a quantitative research paradigm and a non-experimental, cross-sectional design, and applies machine learning (ML) clustering algorithms. The main conclusions suggest that ML can function as a clustering tool through which visitors are grouped according to behavioural patterns, thereby potentially informing decision-making processes.
Smart citations: https://scite.ai/reports/10.61467/2007.1558.2025.v16i4.803
References
Días, I. & da Silva, I. M. (2020). The user experience in the process of acquiring information for trip planning: The case of Kayak's
Chatbot. Tourism Studies and Perspectives, 29 (3), 792-816. https://www.redalyc.org/articulo.oa?id=180764278016
Ezugwu, A. E., Ikotun, A. M., Oyelade, O. O., Abualigah, L., Agushaka, J. O., Eke, C. I., & Akinyelu, A. A. (2022). A comprehensive
survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects.
Engineering Applications of Artificial Intelligence, 110, 104743. https://doi.org/10.1016/j.engappai.2022.104743
Fernández, A.A. (2019). Who they are, what they think and what they value: tourism in the CDMX. Kalpana, Research Journal, 17,
-82. https://www.researchgate.net/publication/361222306
Forero-Corba, W., & Negre Bennasar, F. (2024). Técnicas y aplicaciones del Machine Learning e inteligencia artificial en educación:
una revisión sistemática. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491.
Hernández-Sampieri, R. & Mendoza, C. (2018). Research methodology. Quantitative, qualitative and mixed routes (6a ed.). Mc Graw
Hill Education: México.
Jayawardena C., Ahmad A., Valeri M., Jaharadak A.A. (2023). Antecedentes de la aceptación de la tecnología en la transformación
digital en la industria hotelera. International Journal of Hospitality Management, 108, artículo 103350.
https://doi.org/10.1016/j.ijhm.2022.103350
Kim, S., Fong, L. H. N., Choi, M., & Law, R. (2024). Editorial for the Special Issue: Impacts of Future Technology on Hospitality and
Tourism. Journal of Hospitality and Tourism Research, 48(6), 947-948. https://doi.org/10.1177/10963480241262478
Lim, W. (2024). What Is Quantitative Research? An Overview and Guidelines. Australasian Marketing Journal (Amj), 33(3), 325-
https://doi.org/10.1177/14413582241264622
Lind D. A., Marchal W. G. & Wathen. (2019). Estadística aplicada a los negocios y la economía. (17a ed.). Ciudad de México:
McGraw-Hill Interamericana.
Matovelle, R. & Salas, E. (2018). Brand building through ATL and BTL media. Contributions to Economics, 16 (4), 1-9.
https://dialnet.unirioja.es/servlet/articulo?codigo=9025075
Nazar Neiva, D., Costa, H., & Ruas, R. (2021). Destinos turísticos inteligentes (DTI): a visão de atores chaves do turismo em Brasília
(DF, Brasil). Revista Turismo & Desenvolvimento, 36(1), 451-464. https://doi.org/10.34624/rtd.v1i36.9167
Secretary of Tourism. (2022), Statistics of tourism activity, available in: https://www.turismo.cdmx.gob.mx/actividadturistica/estadisticas-de-la-actividad-turistica
Ulu, M. & Türkan, Y.S. (2024). Cluster Analysis and Comparative Study of Different Clustering Performance and Validity Indices,
In: Durakbasa, N.M., Gençyılmaz, M.G. (Ed.s) Industrial Engineering in the Industry 4.0 Era. ISPR 2023: Lecture Notes in Mechanical
Engineering. Springer, Cham., pp. 33-45. https://doi.org/10.1007/978-3-031-53991-6_3
Zurita, S., Jaime, V., Herrera, S. del P., Crespo, X. & Cadena, G.N. (2024). Use of Artificial Intelligence in the Organization and
Planning of Travel Quito-Ecuador. Latin Science: Multidisciplinary Scientific Journal, 8 (1), 228-243.
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