Cyber-physical and data-oriented framework for construction project management: design and validation in real-world contexts
DOI:
https://doi.org/10.26439/interfases2026.n023.8789Keywords:
project management, construction sector, digital transformation, artificial intelligence, data analytics, frameworkAbstract
The construction industry faces persistent challenges associated with information fragmentation, low interoperability between systems, and limited capacity to manage data in real time, which affects decision-making in complex projects. In this context, this study aims to design and validate a framework focused on integrating emerging technologies and data-driven approaches to strengthen project management. The research adopts a mixed-method approach, combining quantitative validation through the Delphi method with the participation of five international experts and qualitative evaluation through focus groups with representatives from 34 construction sector companies. The framework is structured based on a multi-layer architecture, a continuous data flow, and six operational dimensions that articulate data capture, processing, analysis, and use. The results show high acceptance of the framework, with a global mean of 4.51 out of 5.00, an average coefficient of variation of 0.019, a Cronbach’s alpha of 0.87, and a Kendall’s coefficient of concordance of 0.79, indicating high levels of consensus and reliability. Additionally, the qualitative evaluation confirms its applicability in real contexts, highlighting improvements in decision-making, resource optimization, and risk anticipation, although challenges related to interoperability, technological investment, and availability of specialized talent are identified. It is concluded that the framework represents a viable proposal to advance toward more intelligent, integrated, and data-driven management models in the construction sector.
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