Influencing factors in smart construction site development: a network theory perspective

Purpose The development of smart construction sites (SCS) enhances construction efficiency, safety management and sustainability. However, the underlying factors influencing SCS remain insufficiently explored, hindering the creation of effective strategies within the construction industry. The aim of this study is to identify the key factors influencing the development of SCS and to construct a complex network model where these factors are represented as vertices and their interrelationships as edges. This model facilitates a dual-level analysis: examining both the significance of individual factors and the structural patterns of their interconnections, providing theoretical insights that could inform the future advancement of SCS. Design/methodology/approach Through a comprehensive review of the literature, 31 influencing factors across seven dimensions were identified. A questionnaire survey was conducted to gather insights from 58 professionals in the construction industry. Based on the survey data, an adjacency matrix was constructed, with the influencing factors represented as vertices and their interrelationships as edges within the network. Using these vertices and edges, the Smart Construction Site Influencing Factor Network (SCSIFN) was constructed, and its topological characteristics and network efficiency were analyzed to derive the findings. Findings The degree distribution, betweenness centrality and clustering coefficient of the various vertices differ significantly, highlighting that the influencing factors exert varying levels of impact within the SCSIFN. The topological characteristics of SCSIFN reveal that it exhibits characteristics of both a small-world network and a scale-free network, indicating that influence among factors can spread rapidly and concentrate on a few key factors. The technical standard and scientific research system are the two vertices within the SCSIFN that have the most significant impact on network efficiency. Research limitations/implications A key challenge lies in quantitatively identifying and establishing the relative importance of influencing factors, particularly in assigning appropriate weights to vertices and edges during the construction of the SCSIFN. Practical implications The network-based approach provides a practical framework for comprehensively understanding the influencing factors in SCS development. This study offers targeted guidance for policymakers and practitioners by identifying the most critical factors, such as technical standard and scientific research system. These insights can help prioritize resource allocation, enhance technical training programs and support the development of standardized regulations, among other things. Originality/value By developing a new SCSIFN model, this study provides valuable insights into the key characteristics of critical factors and their interactions, making contributions to both academic research and industry practice. The findings could aid in the formulation of more flexible strategies for advancing the development of SCS.