2026-04-13T16:52:21Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4058812025-07-22T22:15:34Zcom_2072_1033col_2072_452951

00925njm 22002777a 4500 dc Hannemann, Ian-Hendrik Steffen author 2024-02-09 This thesis undertook a comprehensive exploration, weaving together theoretical foundations, practical applications, and real-world implications at the intersection of project management and advanced technologies. The initial chapters meticulously defined projects, project managers, and the complexities inherent in project landscapes. Current project management methodologies were dissected, providing a solid backdrop for the subsequent investigations. A significant focus was placed on big data analytics, artificial intelligence, and machine learning, delving beyond theoretical definitions. This exploration led to the formulation of a unique framework, guiding the subsequent investigations into the practical implementation of data-driven approaches in project management. The thesis critically examined methodologies, scrutinized a real-world case study, and investigated implementation methods, applications, and benefits of data-driven techniques. Qualitative research played a pivotal role, diving into the depths of data-driven techniques, tools, and the intricate process of implementation. The real-world adaptation of these approaches was closely scrutinized, with a detailed comparison between current and datadriven methodologies. The challenges and limitations of implementing such transformative approaches were examined. The culmination of the quantitative research was a comprehensive survey, capturing the perspectives of fourteen project managers. These survey findings were intricately compared and contrasted with the qualitative results, creating a robust synthesis of insights from both research methodologies. In conclusion, this thesis presents a holistic view of project management in the digital age. By seamlessly integrating theoretical foundations, practical applications, and empirical research, it advocates for the strategic integration of data-driven approaches. The comparison between traditional and data-driven methodologies, coupled with a thorough understanding of challenges and benefits, positions this work as a valuable resource for practitioners and researchers navigating the evolving landscape of project management. The synthesis of qualitative and quantitative findings enriches the discourse, offering a nuanced and comprehensive understanding of the transformative potential embedded in the fusion of traditional project management principles with innovative data-driven methodologies Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions Project management Big data Artificial intelligence -- Industrial applications Comparative study Project management Data analytics AI Big data Project mangement methods Tools Techniques Gestió de projectes Dades massives Intel·ligència artificial -- Aplicacions industrials A comparative study of traditional and data-driven approaches in the project management performance