Incidencia de la situación de uso con la integración de diferentes modelos moleculares y sus formas de pago; para medir la sensibilidad al precio en servicios de entretenimiento de centros de diversión nocturna, bares y discotecas, en la ciudad de Cuenca, en el periodo 2023

Son escasos los estudios que se centran en analizar el comportamiento del consumidor desde la perspectiva del marketing de servicios, siendo poca la información relacionada a modelos moleculares. Sin embargo, existen investigaciones que muestran que la situación de uso y la forma de pago inciden en la sensibilidad al precio de un servicio. Este estudio busca profundizar la relación entre estas variables que son cruciales para la gestión de centros de diversión nocturna. Para lograrlo, se llevó a cabo un cuasi experimento con la participación de sesenta sujetos, divididos en tres grupos de tratamiento y dos grupos de control. Se formularon tres hipótesis para examinar si la situación de uso afecta la integración de al menos dos modelos moleculares distintos, y si el contexto situacional y la forma de pago influyen significativamente en la sensibilidad al precio del servicio. Los resultados revelan que, aunque se identifica la integración de más de dos modelos moleculares, la situación de uso no explica esta integración. Además, se encontró una relación significativa entre el contexto situacional y la sensibilidad al precio del servicio absoluto considerado por el cliente. También, se comprobó que las formas de pago, como efectivo, tarjeta de crédito y transferencias, influyen en la sensibilidad al precio. El estudio concluye con recomendaciones que contribuyen a mejorar la gestión de bares y discotecas, y sugiere áreas de investigación para futuros estudios.Few studies focus on analyzing consumer behavior from a service marketing perspective, with little information related to molecular models. However, there is research showing that the usage context and the payment method have an impact on price sensitivity of a service. This study aims to further explore the relationship between these variables, which are crucial for the management of nightlife centers. To achieve this, a quasi-experiment was conducted with the participation of sixty subjects, divided into three treatment groups and two control groups. Three hypotheses were formulated to examine whether the usage context affects the integration of at least two different molecular models, and whether the situational context and payment method significantly influence price sensitivity of the service. The results reveal that although the integration of more than two molecular models is identified, the usage context does not explain this integration. Additionally, a significant relationship was found between the situational context and the absolute service price sensitivity perceived by the customer. Moreover, payment methods such as cash, credit cards, and transfers were found to influence price sensitivity. The study concludes with recommendations that contribute to improving the management of bars and nightclubs, as well as suggesting areas of research for future studies.0000-0001-6861-315

Breaking data silos with Federated Learning

Federated learning has been recognized as a promising technology with the potential to revolutionize the field of Artificial Intelligence (AI). By leveraging its decentralized nature, it has the potential to overcome known barriers to AI, such as data acquisition and privacy, paving the way for unprecedented advances in AI. This dissertation argues the benefits of this technology as a catalyst for the irruption of AI both in the public and private sector. Federated learning promotes cooperation among otherwise competitive entities by enabling cooperative efforts to achieve a common goal. In this dissertation, I investigate the goodness-of-fit of this technology in several contexts, with a focus on its application in power systems, financial institutions, and public administrations. The dissertation comprises five papers that investigate various aspects of federated learning in the aforementioned contexts. In particular, the first two papers explore promising venues in the energy sector, where federated learning offers a compelling solution to privately exploit the vast amounts of data and decentralized ownership of data by consumers. The third paper elaborates on another paradigmatic example, in which federated learning is used to foster cooperation among financial institutions to produce accurate credit risk models. The fourth paper makes a juxtaposition with the previous ones centered on the private sector. It elaborates on the use cases of federated learning for public administrations to reduce barriers to cooperation. Lastly, the fifth and last article acts as a finale of this dissertation, compiles the earlier work and elaborates on the constraints and opportunities associated with adopting this technology, as well as a framework for doing so.R-AGR-3787 - EU 2020 - MDOT (01/07/2020 - 31/12/2023) - FRIDGEN GilbertR-AGR-3728 - PEARL/IS/13342933/DFS (01/01/2020 - 31/12/2024) - FRIDGEN Gilber