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RADS Journal of Business Management
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Evaluating Green Supply Chain Performance Using Multi-Criteria Decision-Making (MCDM) Models

Authors: null Nasrullah Khan; Muhammad Naeem; null Muzzammil Siraj;

Evaluating Green Supply Chain Performance Using Multi-Criteria Decision-Making (MCDM) Models

Abstract

Purpose: This study aims to examine how Green Supply Chain Management (GSCM) practices, i.e., environmental impact, cost efficiency, customer satisfaction, and regulatory compliance, affect the Green Supply Chain Performance Score (GSCPS), considering the mediating roles of supplier engagement and technology adoption. Resource-Based View (RBV) theory is used, and the study fills a gap in previous research by investigating the combined and overall impact of these variables in a global context, as well as the effects of control variables such as company size, industry type, and annual revenue. Methodology: A quantitative research methodology was employed, with secondary data obtained from the sustainability and annual reports of 100 global firms. The study used a deductive approach based on a positivist research philosophy, with data analysis performed using SPSS for hypothesis testing and regression analysis. Findings: The findings indicate that environmental impact and technology adoption have a significant positive effect on GSCPS. However, cost efficiency, customer satisfaction, and regulatory compliance do not exhibit significant effects. Furthermore, supplier engagement did not mediate the relationship. Conversely, the control variables demonstrated a significant positive effect on GSCPS. Significance: This study contributes to the existing literature on Green Supply Chain Performance (GSCP) and provides practical implications for firms' stakeholders and policymakers.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid