Marín Díaz, G.; Galdón Salvador, J.L.; Galán Hernández, J.J. Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations. Electronics2023, 12, 3395.
Marín Díaz, G.; Galdón Salvador, J.L.; Galán Hernández, J.J. Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations. Electronics 2023, 12, 3395.
Marín Díaz, G.; Galdón Salvador, J.L.; Galán Hernández, J.J. Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations. Electronics2023, 12, 3395.
Marín Díaz, G.; Galdón Salvador, J.L.; Galán Hernández, J.J. Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations. Electronics 2023, 12, 3395.
Abstract
Due to the irruption of new technologies in cities such as mobile applications, geographic infor-mation systems, Big Data, Internet of Things (IoT) or Artificial Intelligence (AI), new approaches to citizen management are being developed with the aim of adapting citizen services to this new en-vironment. These new services can enable city governments and businesses to offer their citizens a truly immersive experience that facilitates their day-to-day lives and ultimately improves their quality of life. In this sense, it is important to emphasize that all investments in infrastructure and technological developments in smart cities will be wasted if the citizens for whom they have been created eventually do not use them for whatever reason. To avoid these kinds of problems, the citizen's level of adaptation to the technologies should be evaluated. However, although much has been studied about new technological developments, studies to validate the actual impact and user acceptance of these technological models are much more limited. This paper tries to fill this gap presenting a new model of recommender system based in the most cited and used model in the scientific and academic literature: the Technology Acceptance Model (TAM) and using the most cited and agreed upon criteria in the existing literature. To accomplish the objective, this study in-troduces a novel recommender system that utilizes a fuzzy 2-tuple linguistic model in conjunction with the analytic hierarchy process (AHP) method to prioritize and personalize the relationship between tourists and smart cities. The methodology proposed in this paper was tested and validated in a case of study through different clusters to derive global recommendations tailored to each specific cluster. The main findings reveal that the use of technology is closely linked to the ability to enjoy personalized experiences in the realm of Smart Cities and Smart Tourism. As future works, authors recommend extending the recommender system model to any cluster of tourists using the proposed methodology and evaluate also other kind of disruptive technologies such as artificial intelligence (AI) in supporting the citizens.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
