A Dynamic Analysis for Mitigating Disaster Effects in Closed Loop Supply Chains

Abstract

The increased level of complexity in the case of Closed Loop Supply Chains (CLSCs) turns them into vulnerable systems under a disaster event. The latter calls for a methodological approach that allows a dynamic study under alternative policies in mitigating the disaster effects with a focus on creating sustainable CLSCs. For this reason, we provide a System Dynamics (SD)-based analysis for disaster events on the operation of CLSCs. By “disaster event”, we mean three different categories taking shape on the basis of duration. Furthermore, three different demand patterns emerging due to the disaster event are examined. We assume that the disaster event affects the manufacturer, and we examine the system response under different mitigation policies. For each demand pattern two different mitigation policies at the manufacturer level are examined by considering the total CLSC profit and demand backlog as measures of policy performance. For each combination, extensive simulation experimentation reveals sustainable policy recommendations under alternative settings regarding the reduction in the manufacturer’s production.

A Dynamic Analysis to Examine Regional Development in the Context of a Digitally Enabled Regional Innovation System: The Case of Western and Central Macedonia (Greece)

“…Within SD models, the portrayal of stocks and flows allows for the representation of time as a continuous variable, facilitating the occurrence of events and changes at any continuous point in time. These stock-flow dynamics are typically converted into a system of differential equations for computational analysis, with simulations generally conducted using sophisticated graphical simulation software such as PowerSim 10 ® , Vensim ® , i-think ® , and Stella ® [43,44].…”

Research on the Impact of New Parts Price Increase on the Stability of Closed-Loop Supply Chain

“…In regard to the impact of carbon emission constraints on closed-loop supply chains, Jiao et al combined game theory and system dynamics to explore the impact of carbon trading strategies and technological progress on the closed-loop supply chain system of power batteries, and found that with the reduction in free carbon quotas and the rise of carbon trading prices, the recycling of waste power batteries will be greatly promoted, but the production and social welfare of power batteries will be greatly affected [38]. In reference to the impact of force majeure events on closed-loop supply chain, Katsoras and Georgiadis constructed a system dynamics model suitable for closed-loop supply chain disaster situations, and used the total supply chain profit and demand backlog as measures of the strategic performance to explore the response of the closed-loop supply chain to two different mitigation policies under three demand modes [39].…”

“…Although there are many studies that explore the impact of internal and external factors on closed-loop supply chain systems, few have studied the impact of external raw material supply on component remanufacturing or closed-loop supply chain systems, such as new parts required for component remanufacturing. The existing studies focus on reflecting the operation advantages and disadvantages of closed-loop supply chain systems from the perspective of profit acquisition ability, for example, literature [30,33,34,39] However, the existing works rarely analyze the system operation from multiple perspectives. At the same time, the above literature also ignores the dynamic adjustment of government reward and punishment strategies when considering government reward and punishment strategies, for example, literature [36,37].…”

Pemodelan Dinamika Sistem untuk Sistem Produksi dan Inventori dalam Remanufakturing Proses Studi Kasus: Perusahaan Kimia di Indonesia

“…Sistem dinamik memiliki kemampuan untuk mengintegrasikan faktor lunak ke dalam analisis operasi. Sistem Dinamik dapat menangani peningkatan kompleksitas yang disebabkan oleh pengaruh kausal antara aktor yang terlibat yang berbeda, perilaku non-linier dan penundaan waktu [5].…”

“…SD dipahami dengan baik oleh banyak manajer dan menjadi instrumen untuk brainstorming sehingga ketergantungan pada data dapat dikurangi. Metodologi ini memberikan pemahaman tentang perubahan yang terjadi dalam suatu sistem dengan berfokus pada interaksi antara arus fisik, arus informasi, penundaan dan kebijakan yang menciptakan dinamika variabel yang diminati [5].…”