Simulation Analysis of Supply Chain Resilience of Prefabricated Building Projects Based on System Dynamics

Abstract

In light of the intricate dynamics and uncertain risk parameters inherent in the supply chains of prefabricated building projects, bolstering the resilience of these supply chains can substantially mitigate disruption risks and facilitate superior operational outcomes for involved enterprises. This study identifies key metrics emblematic of supply chain resilience within prefabricated building projects, spanning five critical resilience dimensions: predictive prowess, absorptive potential, adaptability, inherent resilience, and growth capability. Employing the Analytic Hierarchy Process (AHP) and system dynamics (SD), we formulate a resilience simulation model specific to these supply chains. Utilizing the Nanchang Yinwang Village Comprehensive Housing Community Project as a case study, we forecast the trajectory of supply chain resilience over a five-year span and simulate the resilience variations in response to diverse variable magnitudes. Our findings reveal a consistent upward resilience trend over the five-year period. Moreover, the resilience stature of the prefabricated building project supply chain exhibits variability under distinct variable shifts. Of all the subsystems, the most reactive secondary factors encompass risk cognizance, logistics support level, collaboration intensity, supply chain reconfiguration aptitude, and managerial strategic decision-making prowess. Notably, amplifying the absorptive potential of resilience yields the most profound enhancement in overall resilience.

Traditional Village Morphological Characteristics and Driving Mechanism from a Rural Sustainability Perspective: Evidence from Jiangsu Province

“…In recent years, the use of morphological indica models to study the spatial morphology of traditional villages has emerged as a new search field. The application of new technologies and methods is increasing, includ Space Syntax [26,27], machine learning [28,29], BIM technology [30,31], SD (system namics) technology [32,33], and CA (cellular automaton) technology [34,35]. Th…”

“…In recent years, the use of morphological indicator models to study the spatial morphology of traditional villages has emerged as a new research field. The application of new technologies and methods is increasing, including Space Syntax [26,27], machine learning [28,29], BIM technology [30,31], SD (system dynamics) technology [32,33], and CA (cellular automaton) technology [34,35]. These methods are applied in the fields of static and dynamic quantitative calculations for analyzing the spatial morphology of traditional villages [36], as well as their driving factors [37,38], and for simulating planning scenarios [39].…”

Research on the Prefabricated Building Supply Chain and Blockchain's Resiliency Theory

“…Furthermore, there is diversity in the supply chain's resilience for prefabricated construction projects when there are major changes. Risk awareness, logistical support level, collaboration intensity, supply chain restructuring capacity, and management strategic decision-making skill are the most sensitive secondary factors among all subsystems [9] . Zhu presents research findings that indicate the key influencing factors can be categorized into three levels and six levels: component manufacturing-based bottom level fundamental influencing factors, middle level indirect influencing factors, and top level direct influencing factors.…”

Risk Analysis and Simulation of Large Bridge Construction Based on System Dynamics

“…System dynamics is a discipline that analyzes and studies information feedback systems. The approach of system dynamics is to explore how to understand and solve problems through a cross-disciplinary and integrative method [16]. In dealing with complex system issues, system dynamics often employs a method that combines qualitative and quantitative analysis.…”