In recent years, the increasing complexity of natural disasters has highlighted the limitations of existing emergency material assistance systems. To address these challenges, this study proposes a collaborative adaptation mechanism for “peacetime and emergency integration” and develops a supplier evaluation framework. The framework incorporates multi-dimensional indicators such as profit, business credit, regional advantages, and emergency capability. Using a DEMATEL-ANP-based model, supplier L2 is identified as the optimal choice with a weight of 0.285. A fuzzy comprehensive assessment approach is applied to classify emergency materials based on demand urgency, identifying drinking water, rescue tools, medical supplies, and other critical items as priority resources. The evaluation vectors for these materials range from 0.1540 to 0.9909. This study enhances emergency material management through improved information systems, a better control of critical processes, and a unified assurance strategy. It provides theoretical support and practical guidance for more scientific and standardized disaster management practices.

In the post-epidemic era, the labor market has become increasingly complex, making it even more crucial to incorporate sustainability into employment demand. As we enter the post-pandemic era, a globalization trend has become more apparent. It is crucial to modernize employability through educational reform in order to assist employees in enhancing their professional skills. This study began by analyzing the importance of financial engineering practice instruction and graduate employability in the post-epidemic era. Second, the study proposed the content and a plan for inter-disciplinary teaching reform to address talent cultivation needs based on labor market requirements. Third, a face-to-face survey and interview were conducted with students affected by changes in teaching, and the results were analyzed and summarized. On this basis, the impact of education reform was evaluated using both the expert scoring method and the analytic hierarchy approach. The results indicated that the suggested financial engineering teaching reform program improved the school’s discipline strength, enrollment rate, employment rate, and competition awards, especially discipline strength. This research can be used to inform the teaching of financial engineering majors in various countries, assist job candidates in enhancing their professional skills, and build a formidable talent pool for the labor market.

Local recovery decisions made by individual supply chain members may improve node-level performance. Such improvements do not necessarily enhance system-level resilience. This study examines how information generated by a digital supply chain twin can be translated into coordinated recovery decisions. The study assesses whether such coordination can mitigate the mismatch between local recovery and system-level resilience. A digital twin-driven multi-agent simulation–optimization framework is developed to integrate state synchronization, causal forecasting, cross-node coordination, and rolling-horizon feedback within a common physical execution environment. Seven recovery strategies are evaluated through a structured capability comparison, functional ablation, information-quality sensitivity analysis, network-structure robustness tests, and paired statistical inference. The results show that the transition from decentralized local decision-making to a system-level coordinated optimization architecture produces the largest resilience improvement among the architecture transitions examined. Local prediction alone provides only limited gains. Rolling-horizon prediction and feedback provide conditional incremental value, primarily through improved intertemporal cost control rather than uniform improvements across all resilience indicators. Information delays and prediction errors weaken coordination effectiveness, while greater effective utilization of the latest available operational information generally improves recovery outcomes. Network structure further shapes the value of coordination: sparse networks constrain its effectiveness through insufficient alternatives, whereas high redundancy reduces its marginal value, with moderately redundant networks providing the clearest scope for coordination gains. This study conceptualizes the digital supply chain twin as an information-to-coordination mechanism. The mechanism links local recovery decisions with system-level resilience. The study clarifies the mechanisms and boundary conditions under which digital twin-driven coordination contributes to supply chain recovery.