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Hybrid Recommender System Model for Tourism Industry Competitiveness Increment

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Computer Information Systems and Industrial Management (CISIM 2023)

Abstract

In the tourism industry, recommender systems (RS) are information technology (IT) tools used to strengthen competitiveness indicators since allow interaction with tourists, generate mobility in the environment and with other users, and provide helpful information about the destination. However, recommender systems applied to tourism tend to focus mainly on the indicator of destination promotion and management, neglecting other competitiveness indicators that make destinations more attractive, such as tourist safety. This study proposes a model to strengthen various indicators of competitiveness, such as destination management, tourism promotion, marketing, and safety tourism, following a three-step methodology. First, the documentation and analysis of sources in scientific databases to identify the fields of uses of recommender systems in the tourism industry; second selection of techniques and models of recommender systems applied in the tourism industry; third, the construction of a model for the improvement of indicators in a tourist destination. The developed model uses a hybrid recommender system strengthen indicators such as promotion and visitor growth but also provides safe recommendations to users while contributing to the promotion of the tourism offer.

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Correspondence to Andres Solano-Barliza .

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Solano-Barliza, A., Acosta-Coll, M., Escorcia-Gutierrez, J., De-La-Hoz-Franco, E., Arregocés-Julio, I. (2023). Hybrid Recommender System Model for Tourism Industry Competitiveness Increment. In: Saeed, K., Dvorský, J., Nishiuchi, N., Fukumoto, M. (eds) Computer Information Systems and Industrial Management. CISIM 2023. Lecture Notes in Computer Science, vol 14164. Springer, Cham. https://doi.org/10.1007/978-3-031-42823-4_16

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  • DOI: https://doi.org/10.1007/978-3-031-42823-4_16

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