1. Introduction
As the construction industry evolves, a complex supply chain network has emerged, with the general contractor positioned at its core. This network encompasses various entities, such as material suppliers, engineering subcontractors, labor subcontractors, equipment lessors, design units, owners, and other node enterprises. The construction supply chain manages multiple functions, including raw material procurement, sub-project production, and final product completion and delivery, by controlling information flow, logistics, and capital flow [
1]. However, it is important to note that supply chain disruptions have become increasingly common in recent years, significantly impacting the global economy. Events like the 2020 COVID-19 outbreak, the 2021 Suez Canal blockage, the 2022 Russian–Ukrainian conflict, and other major incidents have posed unprecedented challenges to the global supply chain network, potentially leading to a broken chain [
2]. Various industries, including food, energy, industrial manufacturing, and construction, are vulnerable to such disruptions. The adverse effects on the construction industry supply chain are particularly pronounced and concerning. For instance, in 2020, the COVID-19 epidemic caused significant disruptions in transportation and logistics, prompting some countries and regions to impose restrictions on product imports and exports, affecting numerous building materials and construction firms. Consequently, construction activities and production were halted. In 2021, the Suez Canal blockage resulting from the grounding of the Ever-Given ship led to a spike in the market price of aluminum metal, subsequently increasing the costs of aluminum alloy plates, window frames, protective railings, and other products in the international building materials market. This disruption in the supply and demand of aluminum products within the construction industry supply chain had severe repercussions. The supply–demand imbalance for aluminum products in the construction sector created several challenges in the supply chain. In 2022, media reports indicated that the Russian–Ukrainian conflict and other factors caused price surges in concrete, steel, and other raw materials. Economic sanctions hindered the normal delivery of construction materials, leading to a disruption in capital flow and the closure of nearly 10,000 construction companies in Turkey. Given the construction industry’s crucial role in the global economy, it is imperative to enhance the security level of the construction supply chain [
3]. This study examines the contradictions arising from the uncertainty in both the internal and external environments of the construction industry and the complexity and vulnerability of the construction supply chain. It initiates the discussion by presenting two perspectives: the node and the chain. This study addresses two primary scientific concerns: the identification of key risk nodes and the analysis of the invulnerability of the construction supply chain network. By conducting a systematic analysis and summarization of the distribution characteristics of key risk nodes within the construction supply chain and the evolution of network invulnerability under the influence of various parameters, the aim is to advance the scientific understanding of disruptions in the construction supply chain among node enterprises, industry associations, and other pertinent entities. Moreover, this study can provide valuable insights and assistance for management personnel and decision-makers in construction enterprises to implement preventive measures against supply chain disruptions. Ultimately, this study can contribute to the sustainable, secure, and steady progress of the construction supply chain.
The identification of key nodes and the analysis of network invulnerability are essential elements of complex network research. The effective identification of key risk enterprises within the construction supply chain, particularly in the context of interruption risk, is of great significance. This, in turn, allows for the formulation of network destructive enhancement strategies that can contribute to the safe and stable development of construction supply chain networks [
4]. However, at present, construction supply chain risk-related research is primarily focused on risk evaluation, early warning, and influencing factors. Notable studies include those of Koc K., who investigated the supply chain risk in construction projects throughout their life cycle and stakeholders, contributing to the supply chain risk indicator system [
5]. Alamdari A.M. addressed the risk characteristics of the green building supply chain and systematically constructed a seven-layer risk factor influence through explanatory structural modeling (ISM) relationship structure [
3]. Liu J. highlighted that small and medium-sized enterprises (SMEs) upstream of the construction supply chain exhibit a strong demand for financing and assessed the credit risk in the process of online supply chain financing [
6]. Malik A. emphasized that the construction supply chain is particularly vulnerable to pandemics, budget overruns, poorly coordinated information, inadequate management supervision, and decision-making errors by stakeholders [
7]. While this kind of research certainly provides a valuable theoretical basis and decision-making reference for construction supply chain risk management, the exploration of key nodes in the construction supply chain and network invulnerability remains an underexplored area [
8].
With the ongoing advancement of the economy, the product supply chain has become intricately interconnected and integrated, leading to a progressively complex and networked construction supply chain. The relevance of significant theoretical frameworks, such as complex network theory, has been on the rise. As early as 2000, Dubois A. highlighted the network effect within the construction industry in his research [
9]. Subsequently, numerous scholars have conducted studies related to construction supply chain networks. For instance, Oludare S.O. investigated the substantial influence of construction material supply chain networks on project delivery [
10]. Dudziak G. examined the application of complex network models in construction and logistics supply chain networks [
11]. Haikal M. S. focused on the construction supply chain network and reviewed the advancements in sustainability-related research [
12]. The integration of complex network theory into construction supply chain risk management has garnered widespread recognition and support from scholars, enabling a broader exploration from a “network” perspective. However, the existing research on the identification of key risk nodes and network invulnerability analysis has predominantly concentrated on networks such as goods transport, disease transmission, power distribution, and urban transport, rather than specifically on the construction supply chain network. For example, Li X. examined the critical role of key nodes in the stability of global supply chains within maritime corridors [
13]. Crescio M. I. identified key nodes in the Italian swine fever contagion network [
14]. Zhang W. emphasized the significant impact of key nodes in the electricity distribution network on network security, economy, and structural stability [
15]. Wu P. simulated the disruption of transport stations within an urban agglomeration by targeting nodes to evaluate the resilience of transport networks against disruptions [
16]. Therefore, to address the existing research gaps in identifying key risk nodes and analyzing network invulnerability in construction supply chain risk management and to effectively tackle the two critical “scientific problems” outlined in the preceding section within the current context, it is imperative to explore the identification of key nodes and methods to enhance the invulnerability of the construction supply chain based on complex network theory. This study aligns with the characteristics and requirements of the supply chain in the contemporary construction industry.
In the context of selecting specific research methods, the current study summarizes the research methods for identifying key nodes and assessing the invulnerability of undirected and unweighted networks similar to the construction supply chain. These methods can be categorized into three main groups based on their characteristics [
17]. Firstly, the network characteristic analysis method determines the importance of nodes by assigning and aggregating network centrality indices [
9]. Secondly, the system science analysis method involves deleting network nodes to observe changes in network connectivity and assessing the importance of nodes based on the degree of change in network connectivity, which is a common approach in the cascade failure model [
2]. Thirdly, the information search analysis method evaluates the importance of nodes based on information flow within the network [
6]. Considering the complex structure of the construction supply chain network, involving numerous participating enterprises and unspecified information flow, it is evident that the network characteristic analysis method and the system science analysis method are more suitable for this study, demonstrating stronger applicability. Consequently, this study introduces a method for identifying key risk nodes in the construction supply chain and analyzing their invulnerability. It is based on the characteristics and principles of the aforementioned two applicable methods, in conjunction with the specific characteristics of the example construction supply chain network. To underscore the value and significance of this study, a systematic comparison is conducted with studies related to the topic of this study, focusing on research methodology, content, and object. This comparative analysis highlights the distinctions between this study and similar research endeavors, as presented in
Table 1.
In conjunction with
Table 1 and the preceding assertions, the primary research gaps in construction supply chain risk management are evident in the failure to transition the research focus from “chain” to “network”. In contrast to other fields, there is a deficiency in scientific methods that can identify the key risk nodes and analyze the invulnerability of the network. This makes it difficult for relevant decision-makers to recognize which enterprises are more worthy of attention in the process of risk management in the construction supply chain and which types of strategies are more likely to play an obvious role in improving the overall security and stability of the supply chain network, which is not conducive to taking targeted and efficient risk management measures. To fill the research gap, this study introduces a complex network theory and a cascade failure model simultaneously. It makes corresponding improvements to the research method according to the characteristics of the construction supply chain, such as the selection of node importance, risk propagation, and other indicators, and the setting of rules for the parameters of load, capacity, and resilience of the cascade failure model. Secondly, this study fully considers the close relationship between the risk status of node enterprises and supply chain network invulnerability in the research process and realizes the unification of the methods by setting network invulnerability evaluation indexes based on node risk propagation force indexes. Finally, utilizing the example network, this study systematically analyzes the distribution characteristics of key risk nodes in the construction supply chain network and the fluctuation trend of network invulnerability under the key parameter change. Overall, the necessity and importance of this study are mainly reflected in the following: under the current research status in the same field and the background of industry development, it can comprehensively consider the unique characteristics of the construction supply chain, introduce, improve, and apply the methods of complex network theory and cascade failure model, and systematically come up with a series of important conclusions on the maintenance of a safe and stable development of the construction supply chain network, which can provide scientific and practical solutions for the relevant decision-makers in risk management.
The research idea and work process are depicted in
Figure 1. The main tasks include the following: (1)
Section 2 focuses on establishing a model to evaluate the importance of nodes in a construction supply chain network from the perspectives of business, resources, and information flow. The TOPSIS method is utilized to comprehensively rank network centrality indexes, identifying hub node enterprises in the static network topology. (2)
Section 3 develops a model to evaluate the propagation force of risks in the construction supply chain based on the load–capacity–elasticity cascade failure process, considering the impact of enterprise disruptions from network loss due to intentional attacks. (3)
Section 4 outlines the methodology for identifying key nodes and analyzing network invulnerability in construction supply chain networks based on node importance, risk propagation force, network invulnerability indexes, and the cascading failure model. (4)
Section 5 uses the construction supply chain network of China Beijing Urban Construction Group as an example to analyze the distribution of key risk nodes and propose strategies to enhance network invulnerability by considering node capacity, load, and resilience. This analysis aims to offer insights for decision-making in construction supply chain security and risk management.
4. Key Risk Node Identification and Invulnerability Analysis Steps
Taking a construction supply chain network with N-node enterprises as an example, this study follows
Figure 3 to illustrate the process of identifying key risk nodes and analyzing the invulnerability of the construction supply chain network.
The implementation process of the key risk node identification and network invulnerability analysis method for the construction supply chain, as proposed in this study, involves several steps. Initially, it is essential to create and input the adjacency matrix of the construction supply chain network based on the actual business relationships of the enterprise. This leads to the generation of the construction supply chain network (
V,
E) comprising nodes and edges and the calculation of node importance
K using the complex network centrality indicators (
D,
B,
C) as defined earlier. Subsequently, after determining the importance of each node, the initial service load, node capacity, and other relevant parameters are set based on Equations (7), (8) and (10). Following this, nodes are systematically removed to simulate intentional destruction, triggering the cascading failure process of the network as per Equations (9) and (10). The state of the node is assessed according to Equation (9), and the load of the failed node is redistributed among neighboring nodes using Equation (10). If the neighboring nodes meet the failure criteria post-allocation, the cascading failure process continues until no new failure nodes emerge in the network. Finally, Equations (11) and (12) are utilized to compute the node scale loss, business loss indicators (
S,
U), and the risk propagation force
R for each node. By considering the hub node threshold
q and the risk node threshold
w, the key risk nodes are identified. Here,
q represents the sum of the mean and standard deviation of
K, while
w denotes the sum of the mean and standard deviation of
R. The node type and identification criteria are specified in
Table 3.
Furthermore, to examine the variability in the resilience of the construction supply chain network under varying values of critical parameters, following the aforementioned procedure, the model parameters such as node capacity (α), node load (β), and node elasticity (γ) are adjusted independently. Subsequently, the aforementioned steps are repeated to calculate and document the invulnerability (V) of the construction supply chain network under different parameter configurations as per Equation (14).
6. Conclusions
This study presents a methodology for identifying key risk nodes and analyzing the invulnerability of the construction supply chain based on a complex network theory and a cascading failure model. The approach initially employs TOPSIS to evaluate node importance based on complex network centrality indices. Subsequently, each node enterprise is intentionally targeted to gauge its risk propagation ability when disrupted, considering network loss. The integrated performance of node importance and risk propagation ability is quantitatively assessed to pinpoint key risk nodes. Furthermore, network invulnerability is analyzed by considering node capacity, load, resilience, and the effectiveness of invulnerability enhancement strategies. This research focuses on the construction supply chain of Beijing Urban Construction Group in China, comprising 152 enterprises, as a case study. By identifying key risk nodes and conducting network invulnerability analysis under a multi-class strategy, this study derives key findings and managerial implications:
(1) The hub nodes of the construction supply chain network are predominantly situated upstream of the supply chain, encompassing general contractors and their primary suppliers. Consequently, it is evident that upstream core enterprises, such as general contractors, possess distinct advantages within the construction supply chain network. To foster the stable progression of the construction supply chain network, governmental bodies and market regulators should prioritize initiatives aimed at safeguarding and augmenting the operational capacity of core enterprises, as exemplified by general contractors. Simultaneously, there is a need to intensify risk oversight concerning core enterprises like general contractors.
(2) The risk nodes within the construction supply chain network are predominantly situated downstream, encompassing general contractors and their tertiary suppliers. Consequently, the overall level of interruption risk for downstream enterprises in the construction supply chain network is elevated. Each enterprise node within the construction supply chain is advised to facilitate the development of a robust and dependable partner selection system. They should proactively implement strategies such as diversifying their sources of supply to enhance the stability of the supply reserve for essential services. Furthermore, efforts should be made to enhance the capacity to prevent and mitigate supply risks at the end of the construction supply chain.
(3) The distribution of hub nodes and risk nodes within the construction supply chain network varies, with key risk nodes comprising core enterprises and a select few strong suppliers. Consequently, aside from focusing on core enterprises within the supply chain, the entire supply chain should also actively consider the strong suppliers located at these key risk nodes. Governments, market regulators, and industry associations can facilitate the establishment of a supplier risk evaluation system and establish market entry criteria that factor in enterprise risk. This approach can effectively mitigate the potential widespread adverse effects resulting from disruptions to such enterprises.
(4) The adjustment of business capacity, load, resilience, and other parameters of node enterprises has a differentiated impact on the invulnerability of the construction supply chain network. From the perspective of the construction supply chain as a whole, enterprises can actively engage in activities such as business training and business transfer to reduce disparities in business load capacity and manage variations in business volume among node enterprises. Simultaneously, risk mitigation expenses can be determined in collaboration with the risk management and finance departments to ensure that the enterprise can allocate an appropriate and substantial amount towards risk mitigation costs to enhance the invulnerability of the construction supply chain network.
This research conclusion summarizes the distribution characteristics of key risk nodes in the construction supply chain network and the changing trend of network invulnerability under various strategies. It can be utilized to propose corresponding policy recommendations from different perspectives, including government entities, market management departments, industry associations, inter-enterprise, and stakeholders. It also offers methodological support and strategic guidance for risk management in the construction supply chain, which holds practical significance. Nevertheless, it is important to acknowledge that this study has certain limitations. The process of load redistribution primarily relies on enterprise load capacity and overlooks the weighted impact of actual business volume on the strength of business relationships and its potential influence on network load redistribution. Future research could delve deeper into empirical investigations to provide more comprehensive insights for the secure and steady advancement of the construction supply chain.