Maestría en Dirección Empresarial
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Browsing Maestría en Dirección Empresarial by Author "Aranguren Torres, Juan Sebastián"
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Item Determinantes de la resistencia del talento humano a los procesos de transformación organizacional: revisión de los últimos 10 años(Universidad Santiago de Cali, 2025) Aranguren Torres, Juan Sebastián; Diosa Ramírez, Jacqueline; Vargas García, Lina Marcela (Directora)This research focuses on identifying the determinants of human talent resistance in organizational transformation processes. The descriptive study under the deductive method will be carried out through the systematic review of secondary sources where it is intended, based on general theoretical references, to glimpse a particular phenomenon where the main drivers of internal transformation in companies have been identified in recent years, the new economic and market dynamics, technological changes, big data and AI, new consumer habits, the post-pandemic and the generational crisis, while different authors relate the resistance of human talent as a key and normal element in the face of changes, where factors such as ignorance, lack of communication strategies, risk aversion, lack of planning of the transformation process, the existence of negative leadership and the absence of skills to face technological advances are identified as triggers. Finally, the study concludes with the premise that human talent should be viewed as a strategic factor and facilitator of organizational transformation processes, rather than just another element of the structure to be changed. Furthermore, it details the implications of resistance on organizations' ability to implement effective change, and proposes strategies for managing it appropriately. These factors can be associated with adaptation to new technologies, the evolution of internal processes, and the lack of synchronization between digitalization and innovation. Additionally, adequate leadership and change management strategies are crucial to mitigate resistance and facilitate an effective transition to new models and processes.