Environmental Supply Chain Performance Mapping of an Enterprise by Exploring a Novel Vague-Intellectual Approach

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Abstract

The authors notified the two momentous Research Gaps (RGs) via conducting the relevant literature survey. The authors found as first RG that there are still no mathematical models that could address the generalized trapezoidal fuzzy set (GTFs) based green supply chain performance measurement (GSCPM) multi-level hierarchical index for computing the performance of a production enterprise in % except in the forms of GTF set/scale/crisp value. Next, as the second research gap, the authors identified that a few research articles are published in the extent of degree of similarity approaches. Entire approaches are limited to recognize the weak metrics under assessment of two GTFN sets from experts and also not competent to measure the performance gap of metrics from its ideal value. The objective of research work is turned to overcome the identified two RGs. To fulfill the first RG, the authors first of all proposed the two GTFN set-based mathematical models, which are executed to compute the priority weights and appropriateness ratings (PWsaARs) for 1st level measures from 2nd level PWsaARs of metrics (discarded the requirement of PWsaARs data for 1st level measures from experts). Furthermore, the authors developed GTFN set-based novel fuzzy performance index (NFPI) approach (by combining the crisp as well as fuzzy percentage rule over FPI) to compute the performance in %. To address the second RG, the degree of similarity (DoS) approach is modified by introducing idea of negative and positive ideal solution into DoS (eliminate the need for assessment of two GTFN sets from experts). Next, modified DoS is applied over evaluated FPII (fuzzy performance importance index) to identify the weak and strong metrics and also quantify the GSCP gap of metrics from its ideal value. Eventually, the research work is demonstrated with empirical case research of an automobile parts manufacturing industry.

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Wang, J., Prabhu, M., Sewagegn, A. A., & Sahu, A. K. (2023). Environmental Supply Chain Performance Mapping of an Enterprise by Exploring a Novel Vague-Intellectual Approach. Discrete Dynamics in Nature and Society, 2023. https://doi.org/10.1155/2023/2133346

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