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Analyzing supply chain risk factors in the small and medium enterprises under fuzzy environment: Implications towards sustainability for emerging economies

供应链 业务 持续性 风险管理 产业组织 供应链风险管理 可持续发展 全球化 新兴市场 风险分析(工程) 政治风险 弹性(材料科学) 供应链管理 经济体制 经济 政治 营销 市场经济 财务 服务管理 生物 热力学 物理 生态学 法学 政治学
作者
Chitra Lekha Karmaker,Ridwan Al Aziz,Tanmoy Palit,A.B.M. Mainul Bari
出处
期刊:Sustainable technology and entrepreneurship [Elsevier]
卷期号:2 (1): 100032-100032 被引量:108
标识
DOI:10.1016/j.stae.2022.100032
摘要

Changing customer demand, globalization, pandemics, and the ongoing Russia-Ukraine war have introduced a lot of complexities, uncertainties, risks, and challenges in various global businesses, especially in the small and medium enterprises (SMEs) of emerging markets. This sector plays a significant role in fostering economic growth, generating employment, and reducing poverty. In such a situation, proper identification of supply chain risk (SCR) factors is pivotal for this sector to achieve a resilient and sustainable SC, specifically since a sustainable and resilient supply chain can withstand the impacts of various uncertain situations. However, no studies have yet explored these risk factors from an emerging economy perspective. This study fills this research gap by identifying the SCR factors and analyzing their interactions using an integrated approach, including Pareto analysis, fuzzy theory, total interpretive structural modeling (TISM), and a Matriced' Impacts Cruoses Multiplication Applique a un Classement (MICMAC) analysis. The findings from the fuzzy TISM imply that the “lack of enthusiasm in top management regarding sustainable practices” is the most significant factor. Besides that, lack of skilled and educated workers, lack of knowledge about modern technologies, labor strikes, and political instabilities are also some crucial risks that may hinder the sustainable development and smooth operation of SMEs. Fuzzy MICMAC analysis confirms that all identified risk factors are interrelated. The study insights can guide managers to successfully identify the risk factors for achieving long-term sustainability and operational resilience and can enhance policymakers’ ability to formulate proactive and efficient mitigation strategies.

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