Assessment of sustainable electronic waste management strategies: q-rung orthopair fuzzy decision-making method

Journal Article

2026

Published in: https://doi.org/10.1016/j.asoc.2026.115943

Inappropriate treatment of electronic waste (e-waste) poses substantial risks to the environment and ultimately
leads to negative consequences on human health. Selecting an appropriate strategy for electronic waste management
(EWM) is crucial before treating e-waste. This research aims to propose an innovative model for
evaluating and prioritizing sustainable EWM strategies based on the most influential criteria. This model combines
the relative closeness coefficient-based tool, the step-wise weight assessment ratio analysis tool, and the
alternative ranking order method accounting for two-step normalization (AROMAN) within the setting of q-rung
orthopair fuzzy sets (q-ROFSs). Based on the proposed score function, the weights of decision experts (DEs) are
derived, while the weights of criteria are estimated using an integrated objective-subjective weighting approach.
For the relative closeness coefficient-based objective weighting tool, a novel divergence measure on q-ROFSs is
developed, which describes the discrimination between them. By combining these steps, an integrated AROMAN
is presented to critically assess EWM strategies, demonstrating its practicality and efficacy through a case study
of the EWM strategy selection problem. The findings of the integrated weighting model indicate that the criterion
“quality management systems” is the most important for EWM strategies’ prioritization. Based on the ranking
results, it is revealed that “Organizing the informal recycling sector” has the maximum preference among the others
with respect to the 21 criteria considered. Sensitivity analysis is further conducted with respect to varying values
of the used parameters, which reveals that the strategy “Organizing the informal recycling sector” constantly obtains
its top ranking despite how the parameters’ values vary. Moreover, this study compares the proposed
method with q-ROFS-based decision-making methods to evaluate its effectiveness. The outcomes of this work
aim to encourage a more proactive attitude towards EWM.

• Publisher Name: ELSEVIER
• Publishing City: Netherlands
• Volume Number: 202
• Magazine \ Newspaper: Applied Soft Computing
• Pages: 1 to 23