Circular Economy Determinants in Electronics Supply Chain: A Pythagorean Fuzzy Clustering Approach

Samiksha Budakoti (Jaypee Institute of Information Technology, Sec-62, Noida, Uttar Pradesh India Institute of Technology & Science, Ghaziabad, Uttar Pradesh, India)
Vishal Gupta (Jaypee Institute of Information Technology, Sec-62, Noida, Uttar Pradesh.)

Journal of Applied Data Sciences
Vol 7, No 3: September 2026

The realignment from traditional linear models to circular economy has become indispensable in Electronics industry of developing nations such as India. This transition is crucial to combat issues related to resource scarcity and burgeoning e-waste. This research seeks to determine and classify the pivotal determinants impacting circular economy assimilation in India’s electronics supply chain. An extensive literature review coupled with feedback from industry and academic experts, identified twenty-three such determinants. These determinants were integrated with six supply chain stages in order to develop a structured questionnaire. A five-point linguistic scale was used in the questionnaire to gather expert responses on each determinant-stage combination. The experts’ responses were then converted to Pythagorean fuzzy numbers for quantitative analysis of the information. Using multi-criteria decision-making framework involving aggregation, score function and normalization, a de-fuzzified similarity matrix of determinants was obtained. Ward’s method of agglomerative hierarchical clustering in RStudio was applied to the similarity matrix in order to obtain four different clusters of determinants. Strategic and technological determinants formed cluster 1; regulatory and resource-efficiency determinants were highlighted in cluster 2; cluster 3 reflected market and network drivers; macro-institutional and contextual determinants were represented in cluster 4. These clusters together indicate varied yet interconnected determinants affecting implementation of circular economy practices in India’s electronics supply chain. The robustness of the study was also validated by performing sensitivity analysis of the results. This analysis resulted in a mean Adjusted Rand Index of 0.862 reflecting a high degree of consistency in the analytical results. By integrating two robust quantitative methodologies, this research introduces a novel empirical framework for classification of circular economy determinants. This study can aid policymakers, industry practitioners and academicians to formulate coordinated measures for circular economy adoption in India’s electronics supply chains.