Analysing supply chain coordination mechanisms dealing with repurposing challenges during Covid-19 pandemic in an emerging economy: a multi-layer decision making approach

Abstract

Following the outbreak of the Covid-19 pandemic, there was a serious need for the pharmaceutical industry to combat the disease more quickly and effectively. In this regard, numerous companies set out to repurpose current drugs. The noticed decision has major challenges in various dimensions, including the creation and management of an efficient supply chain. The present study attempts to examine the significance and relationships of the repurposing challenges and analyze the effectiveness of supply chain coordination contracts confronting them. In this regard, a combination of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) named DANP method is applied to investigate the relationships and extracting the weights of the mentioned challenges and the multi-criteria optimization and compromise solution technique called VIKOR is employed to prioritize the supply chain coordination contracts found on their impact facing with repurposing challenges. The mentioned techniques have been conducted under the condition of linguistic Z-numbers. The results demonstrated that financial support and digitalization are the most influential challenges. Moreover, collaboration and data availability have the most weight. In addition, four contracts including effort sharing, cost-sharing, credit option and buyback are the best contracts that companies in the merging economy of Iran should concentrate on them. This research proposes a novel framework of decision-making by integrating DANP and VIKOR with linguistic Z-numbers. Additionally, this study takes a new look at the use of coordination contracts from the viewpoint of repurposing challenges which is highlighted particularly during the Covid-19 pandemic.

Optimizing Production Supply Chain With Markov Jump System for Logistics Collaboration

“…To further verify the effectiveness and superiority of the production supply chain logistics information collaboration mechanism based on Markov jump system in this study, a comparison of control performance was made with improved BP neural network (IBP) (Mahdiraji et al, 2022), LMBP feedback neural network algorithm (LMFN) (Jackson et al, 2023), and traditional Markov jump system (TMJS) (Sathyan et al, 2023) From Figure 8, it can be seen that the Markov jump system constructed in this study has superior control performance, thanks to its dynamic memory Markov feedback system. However, compared to IBP, LMFN, and TMJS, the triggering rate is significantly lower.…”

“…In previous research, certain results were achieved in optimizing the logistics information collaboration mechanism of the production supply chain for enterprises to improve operational efficiency and reduce costs. For example, Mahdiraji et al (2022) proposed an information sharing model based on Bayesian rules to address the information barriers faced by traditional supply chain management and designed an information sharing strategy to improve the efficiency and accuracy of information transmission between nodes in the supply chain. Hammad et al (2023) proposed a production supply chain logistics information collaboration mechanism based on spatiotemporal flow and information sharing and verified the effectiveness of this mechanism through empirical cases.…”

Reverse Supply Chain Management Through a Quantity Flexibility Contract: A Case of Stochastic Remanufacturing Capacity

“…Since 2020, the COVID-19 scenario has wreaked havoc on SCs; it produces extreme supply and demand oscillations, disrupting the corporate system. Upstream participants cannot foresee demand, and downstream participants cannot fulfill their responsibilities [9], [10]. A measure we can take for this problem is adopting coordination mechanisms [11].…”