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<p>Electronic waste (e-waste) poses environmental and health challenges, necessitating efficient and sustainable management systems, especially in developing countries. To design such a system, a comprehensive examination of the current e-waste handling and recycling in cities of emerging countries is crucial. This study identifies 16 influencing factors (IFs) and categorizes them into five implication sectors based on the inter-consistency test, literature review, and expert opinions. The Fuzzy Interpretive Structural Modelling (F-ISM) and Best–Worst Method (BWM) analyze and evaluate these factors. Fuzzy MICMAC (cross-impact matrix multiplication applied to classification) analysis ensures the robustness of the proposed framework and characterizes identified IFs. The results reveal that ‘education and social behaviour’ and ‘research and development’ are the most significant sectors for sustainable e-waste management in developing countries. ‘Public awareness’ emerges as the most influential factor with a weightage of 20%. This research provides a valuable contribution towards attaining the sustainable development goals (SDGs) by presenting a structured approach to designing sustainable e-waste management systems in resource-constrained environments. Policymakers, environmental agencies, and stakeholders can use this framework to implement effective e-waste management strategies, mitigating improper e-waste disposal and promoting a cleaner and greener future for developing countries.</p>

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A sustainable framework to address e-waste management solutions: an Indian perspective

  • 期刊论文

  • 发表日期：

    2025年4月1日

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  • Varun Kumar,
  • Om Ji Shukla

摘要

Electronic waste (e-waste) poses environmental and health challenges, necessitating efficient and sustainable management systems, especially in developing countries. To design such a system, a comprehensive examination of the current e-waste handling and recycling in cities of emerging countries is crucial. This study identifies 16 influencing factors (IFs) and categorizes them into five implication sectors based on the inter-consistency test, literature review, and expert opinions. The Fuzzy Interpretive Structural Modelling (F-ISM) and Best–Worst Method (BWM) analyze and evaluate these factors. Fuzzy MICMAC (cross-impact matrix multiplication applied to classification) analysis ensures the robustness of the proposed framework and characterizes identified IFs. The results reveal that ‘education and social behaviour’ and ‘research and development’ are the most significant sectors for sustainable e-waste management in developing countries. ‘Public awareness’ emerges as the most influential factor with a weightage of 20%. This research provides a valuable contribution towards attaining the sustainable development goals (SDGs) by presenting a structured approach to designing sustainable e-waste management systems in resource-constrained environments. Policymakers, environmental agencies, and stakeholders can use this framework to implement effective e-waste management strategies, mitigating improper e-waste disposal and promoting a cleaner and greener future for developing countries.