Data-centric organizational capabilities and project management performance in digitally evolving construction environments: a PLS-SEM investigation

Purpose This study aims to investigate the extent to which data-centric organizational capabilities influence project management performance in Construction 5.0 environments. Specifically, it examines the roles of data governance capability, digital infrastructure capability, and organizational data culture as foundational drivers, and how these shape data integration capability, knowledge analytics capability, intelligent decision support capability, and predictive project management capability. Collectively, these capabilities are posited to enhance overall project management performance. Design/methodology/approach A quantitative research design was adopted using a structured survey instrument administered to 331 construction professionals selected through purposive sampling. The proposed conceptual model was empirically tested using partial least squares structural equation modeling (PLS-SEM) via SmartPLS. Reliability and validity were assessed through Cronbach's alpha, composite reliability, average variance extracted (AVE), and discriminant validity using the Fornell–Larcker criterion and the heterotrait-monotrait (HTMT) ratio, with mediation effects examined via bootstrapping. Findings Data governance capability is significantly and positively associated with data integration capability, intelligent decision support capability, and knowledge analytics capability. Digital infrastructure capability is positively associated with data integration capability and predictive project management capability. Organizational data culture is significantly associated with data integration capability, knowledge analytics capability, and predictive project management capability. All four intermediate capabilities, namely data integration, knowledge analytics, intelligent decision support, and predictive project management, are significantly and positively associated with project management performance. Of the 12 specific indirect effects examined, eight were statistically significant and four were non-significant, with data integration capability emerging as the most consistent indirect pathway. Research limitations/implications The present study is confined to examining how data-centric organizational capabilities contribute to improved project management performance within construction environments undergoing a transition toward Construction 5.0. Future research should extend the framework by incorporating additional organizational and technological variables to further substantiate and strengthen the proposed model. Practical implications Construction organizations seeking improved project outcomes should invest in robust data governance mechanisms, advanced digital infrastructure, and a data-driven organizational culture. These foundational capabilities are best treated as interdependent enablers rather than standalone investments, since their combined alignment is associated with organizational conditions that support intelligent, analytical, and predictive project management practices. Originality/value This study offers an original, empirically validated framework for data-centric organizational capability development in digitally evolving construction environments associated with the Construction 5.0 transition. Unlike prior research that primarily examined the effects of individual digital technologies, the study contributes a layered, organization-level capability-chain architecture that distinguishes foundational, intermediate, and predictive capabilities, and empirically traces the mediating pathways through which foundational data resources are converted into project management performance. By integrating the Resource-Based View, Dynamic Capability Theory, and Socio-Technical Systems Theory into a single capability-development logic, the study clarifies not only whether data-centric capabilities are associated with improved project management outcomes, but how and through which routes these associations occur.