Analysis of barriers in e-waste management in developing economy: an integrated multiple-criteria decision-making approach

• Published in: Environmental science and pollution research international 2022-10, Vol.29 (48), p.72294-72308
• Main Authors: Jangre, Jogendra, Prasad, Kanika, Patel, Dharmendra
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Decision making; Earth and Environmental Science; Ecotoxicology; Electronic waste; Environment; Environmental Chemistry; Environmental conditions; Environmental Health; Environmental science; Fuzzy logic; Heavy metals; Long-term planning; Multiple criterion; Multiplication; Recent Trends in Tertiary Treatment of Water/Wastewater; Waste management; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-022-21363-y

An increasing amount of electronic waste (e-waste) is not a new concern. It has been causing trouble globally. This waste comprises valuable metals and harmful compounds that lead to detrimental environmental conditions. Managing this kind of waste in developing economies is difficult due to different barriers hindering the process. Therefore, the goal of this research work is to determine the barriers while taking expert opinions and through available literature, and subsequently prioritize them to address the challenges in e-waste management. Moreover, this study utilizes an integrated Fuzzy Decision-Making Trail and Evaluation Laboratory (F-DEMATEL) and Fuzzy Interpretive Structural Modeling (F-ISM) approaches to determine the interrelationship between these identified barriers. Performance data obtained from this combined approach is applied to determine an overall rank for 15 identified barriers. The F-DEMATEL technique facilitates in obtaining the influence of barriers on each other and categorizes them into causal or effect groups. In addition, a Fuzzy Matrice d’impacts Croisés Multiplication Appliquée an un Classeement (F-MICMAC) analysis is exercised to sort them into dependent or driving factor. The findings suggest that the underlying cause barriers include “lack of customer awareness about return,” “less policies addressing e-waste problem,” “lack of long-term planning,” and “insensitiveness of public towards environmental issues.” The methodology is integrated with fuzzy logic to take uncertainty in the data gathered into consideration. This approach aids policymakers and decision-makers in determining the barriers’ mutual relationships and interconnections.