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Repositorio Institucional de la Universidad de Murcia

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Browsing by Subject "Bibliometric analysis"

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    Open Access
    A thematic study of creativity research in Spain within the social sciences and psychology
    (Universidad de Murcia. Servicio de Publicaciones, 2023) De-Marchis, Giorgio P.; Shchebetenko, Sergei
    Creativity is becoming one necessary human skill in a world where robots increasingly outperform people in daily routines. In order to efficiently develop creativity as a research field, scholars need to know where they are. We employed a bibliometric approach to study themes and characteristics of creativity research in Spain.The results indicated that publication production in the field has been growing during the last decades. Compared to psychology, creativity in the social sciences seemed to be an undercited, local,and endogamic area. For social sciences, motor themes in the last decade were a) creativity in children and students in the educational environment, b) innovation and knowledge creation in a work-ing environment, and c) cities and creativity. The motor themes in psychology were a) individual characteristics for generating insights (e.g., skills, improvisation, executive functions) and b) emotional intelligence. We suggest some themes for future research, such as creative collaboration in virtual environments, value co-creation, and how machines can help humans boost their creativity
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    Inteligencia artificial (IA) en turismo sostenible: análisis bibliométrico
    (Servicio publicaciones. Universidad de Murcia, 2024) Hermosa del Vasto, Paola Mercedes; Arco Castro, María Lourdes
    Artificial Intelligence (AI) has gained attention in tourism, which requires its sustaina-bility. Our study focuses on a bibliometric analysis of AI in sustainable tourism using 174 manuscripts from 2000 to 2022. One of the main findings is that ‘intelligence’ appears fre-quently, followed by related terms such as work, performance, resources, sustainability, impact, optimization and management. There is no previous evidence on AI in the context of sustainable tourism to explain how public managers or politicians design public policies to create and improve resource efficiency.

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