Advancement of Big Data Analytics Capabilities in Construction Industry: A Resource-Based Theory and Dynamic Capabilities Perspective

Abstract

The potential of big data analytics (BDA) to boost productivity and performance is reshaping business models in various industries including construction. As construction data grows exponentially, BDA’s role in driving a competitive edge becomes increasingly critical. Through advancements in big data technology, big data analytics capabilities (BDAC) have emerged as essential tools for construction organizations to transform their organizational resources into competitive advantages. However, while existing studies highlighted the benefits of BDA in construction, they paid little attention to the specific capabilities required to leverage these advantages from a strategic management perspective. Hence, this study aims to identify the BDAC that enables construction organizations to strategically leverage their resources for BDA adoption. To achieve the aim, this study employed the systematic review approach following the PRISMA methodology in which 781 relevant publications from Scopus and the Web of Science databases were identified. Following a set of inclusion and exclusion criteria, 58 articles were included in the review to identify the critical dimension of BDAC, grounded from resource-based theory (RBT) and dynamic capabilities theory (DCT) alongside literature on BDA. Findings were then validated through semi-structured interviews with big data experts in Malaysia’s built environment that supports the outcomes. This study identified eight dimensions of BDAC which further categorized into three domains of technological capability, human capability and organizational management capability necessary for the conceptualization of BDAC. The findings offer specific capability domains necessary to foster BDA adoption among construction organizations, potentially shifting their competitive strategies through innovative use of BDA.