Karmaker Chitra Lekha, Ahmed Tazim, Ahmed Sayem, Ali Syed Mithun, Moktadir Md Abdul, Kabir Golam
Department of Industrial and Production Engineering, Jashore University of Science and Technology, Jashore, Bangladesh.
Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh.
Sustain Prod Consum. 2021 Apr;26:411-427. doi: 10.1016/j.spc.2020.09.019. Epub 2020 Sep 29.
Motivated by the COVID-19 pandemic and the challenges it poses to supply chain sustainability (SCS), this research aims to investigate the drivers of sustainable supply chain (SSC) to tackle supply chain disruptions in such a pandemic in the context of a particular emerging economy: Bangladesh. To achieve this aim, a methodology is proposed based on the Pareto analysis, fuzzy theory, total interpretive structural modelling (TISM), and Matriced Impacts Cruoses Multiplication Applique a un Classement techniques (MICMAC). The proposed methodology is tested using experienced supply chain practitioners as well as academic experts' inputs from the emerging economy. This study reveals the influential relationships and indispensable links between the drivers using fuzzy TISM to improve the SCS in the context of COVID-19. Findings also reveal that financial support from the government as well as from the supply chain partners is required to tackle the immediate shock on SCS due to COVID-19. Also, policy development considering health protocols and automation is essential for long-term sustainability in supply chains (SCs). Additionally, MICMAC analysis has clustered the associated drivers to capture the insights on the SCS. These findings are expected to aid industrial managers, supply chain partners, and government policymakers to take initiatives on SSC issues in the context of the COVID-19 pandemic.
受新冠疫情及其给供应链可持续性（SCS）带来的挑战的推动，本研究旨在调查可持续供应链（SSC）的驱动因素，以应对在特定新兴经济体——孟加拉国背景下此类疫情中的供应链中断问题。为实现这一目标，提出了一种基于帕累托分析、模糊理论、总体解释结构建模（TISM）和影响矩阵交叉相乘应用于分类分析（MICMAC）的方法。所提出的方法通过来自新兴经济体的经验丰富的供应链从业者以及学术专家的意见进行了测试。本研究利用模糊TISM揭示了驱动因素之间的影响关系和不可或缺的联系，以在新冠疫情背景下改善供应链可持续性。研究结果还表明，需要政府以及供应链合作伙伴的财政支持，以应对新冠疫情给供应链可持续性带来的直接冲击。此外，考虑健康协议和自动化的政策制定对于供应链（SC）的长期可持续性至关重要。此外，MICMAC分析对相关驱动因素进行了聚类，以获取有关供应链可持续性的见解。这些研究结果有望帮助行业管理者、供应链合作伙伴和政府政策制定者在新冠疫情背景下就供应链可持续性问题采取行动。
