Big Data-Driven Implementation in International Construction Supply Chain Management: Framework Development, Future Directions, and Barriers - Ali Elkliny; Amin Mahmoudi; Xiaopeng Deng (Buildings)
Background: In any country, supply chain management is crucial to the economy. Big data-driven (BDD) implementation can be used in different disciplines, especially in construction supply chain management (CSCM). While BDD has a lot of opportunities for optimizing workflows, reducing costs, and improving collaboration among stakeholders to enhance efficiency and decision-making, its adoption is fraught with significant barriers. Thus, identifying these challenges is an important research concern. Methods: This study adopts a systematic review methodology aligned with PRISMA guidelines, combining bibliometric and thematic analyses to explore the integration of BDD approaches in CSCM. A comprehensive search of the Scopus database was conducted, focusing on articles published between 2014 and 2024 with a multi-phase screening process until 62 relevant studies were adopted. Results: This study summarizes the challenges associated with integrating BDD into CSCM and presents solutions to solve them and a framework for implementing BDD in CSCM. Moreover, providing future directions that require further consideration and research. Conclusions: By overcoming these barriers, the construction supply chain will be able to adopt big data for improving efficiency and reshaping CSCM. This study provides a clear view of how CSCM scholars and practitioners should develop along with promising research on BDD.