A Sequential Model of Dynamic Capabilities in Research Groups and Their Impact on Smart City Development

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dc.creatorBermon Angarita, Leonardo
dc.creatorOsorio-Londoño, Andrés Alberto
dc.creatorGonzález-Calixto, Mónica Bibiana
dc.date2026-05-28
dc.date.accessioned2026-05-29T06:00:32Z
dc.descriptionObjective: The aim of this study was to evaluate the systematic influence of the sensing, learning, integrating, and coordinating dimensions of dynamic capabilities on smart cities. Since dynamic capabilities have been examined mainly from the perspective of improving business performance, their relationship with smart cities has received little attention in the scientific literature.Design/Methodology: A correlational methodology with a quantitative approach was employed. The study proposed hypotheses about the relationships between the sensing, learning, integration, and coordinating capabilities and their impact on smart cities. These relationships were assessed in 82 research groups in Manizales, Colombia, through a structural equation model estimated using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.Findings: The results indicate that the dynamic capabilities developed by research groups exert a systematic, positive, and significant influence on smart city development. In addition, the constructs analyzed met the criteria for convergent and discriminant validity, and the model demonstrated acceptable predictive power.Conclusions: Dynamic capabilities are interdependent and evolve through a cumulative process in which research groups identify opportunities, acquire and manage knowledge, integrate this knowledge into strategic decision-making, and coordinate resources to generate innovations with an impact on urban environments. Therefore, the development and implementation of dynamic capabilities within research groups, aligned with public agendas, are essential to strengthen the shift toward smart cities.Originality: This study extends the analysis of dynamic capabilities within research organizations. Furthermore, it underlines the role of contextual learning and resource orchestration in fostering responsiveness and innovation across urban ecosystems.en-US
dc.descriptionObjetivo: el objetivo de este estudio fue evaluar la influencia sistemática de las dimensiones de detección, aprendizaje, integración y coordinación de las capacidades dinámicas en las ciudades inteligentes. Debido a que las capacidades dinámicas se han estudiado principalmente desde la perspectiva de la mejora del desempeño empresarial, su relación con las ciudades inteligentes ha recibido escasa atención en la literatura científica.Diseño/Metodología: se adoptó una metodología correlacional con enfoque cuantitativo. Se plantearon hipótesis de las relaciones entre las capacidades de detección, aprendizaje, integración y coordinación, así como su impacto en las ciudades inteligentes. Estas relaciones fueron evaluadas en 82 grupos de investigación de la ciudad de Manizales (Colombia) a través de un modelo de ecuaciones estructurales estimado mediante la técnica modelado de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM, por sus siglas en inglés).Resultados: los hallazgos indican que las capacidades dinámicas desarrolladas por los grupos de investigación ejercen una influencia sistemática, positiva y significativa en el desarrollo de ciudades inteligentes. Asimismo, los constructos analizados cumplieron con los criterios de validez convergente y discriminante, y el modelo mostró un nivel de capacidad predictiva aceptable.Conclusiones: las capacidades dinámicas son interdependientes y evolucionan mediante un proceso acumulativo donde los grupos de investigación detectan oportunidades, adquieren y gestionan conocimiento, integran dicho conocimiento en la toma de decisiones estratégicas y coordinan recursos para generar innovación con impacto en los entornos urbanos. Por lo tanto, el desarrollo y la aplicación de capacidades dinámicas en los grupos de investigación, alineadas con las agendas públicas, resultan fundamentales para fortalecer la transformación hacia ciudades inteligentes.Originalidad: este estudio extiende el análisis de las capacidades dinámicas en el contexto de las organizaciones de investigación. Además, subraya el papel del aprendizaje contextual y la orquestación de recursos para fomentar la capacidad de respuesta y la innovación en los ecosistemas urbanos.es-ES
dc.formatapplication/pdf
dc.identifierhttps://revistas.itm.edu.co/index.php/revista-cea/article/view/3596
dc.identifier10.22430/24223182.3596
dc.identifier.urihttps://hdl.handle.net/20.500.12622/8161
dc.languageeng
dc.publisherInstitución Universitaria ITMen-US
dc.relationhttps://revistas.itm.edu.co/index.php/revista-cea/article/view/3596/4081
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dc.rightsCopyright (c) 2026 Leonardo Bermon Angarita, Andrés Alberto Osorio-Londoño, Mónica Bibiana González-Calixtoen-US
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceRevista CEA; Vol. 12 No. 29 (2026); Art. e3596en-US
dc.sourceRevista CEA; Vol. 12 Núm. 29 (2026); Art. e3596es-ES
dc.source2422-3182
dc.source2390-0725
dc.subjectcapacidades dinámicases-ES
dc.subjectciudades inteligenteses-ES
dc.subjectgrupos de investigaciónes-ES
dc.subjectmodelado de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM)es-ES
dc.subjectintegración del conocimientoes-ES
dc.subjectdynamic capabilitiesen-US
dc.subjectsmart citiesen-US
dc.subjectresearch groupsen-US
dc.subjectPartial Least Squares Structural Equation Modeling (PLS-SEM)en-US
dc.subjectknowledge integrationen-US
dc.titleA Sequential Model of Dynamic Capabilities in Research Groups and Their Impact on Smart City Developmenten-US
dc.titleUn modelo secuencial de capacidades dinámicas en los grupos de investigación y su impacto en el desarrollo de ciudades inteligenteses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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