Green synergy: unveiling the nexus of green supply chain practices, training and innovation for sustainable manufacturing

Purpose

Due to extensive industrial activities, the manufacturing sector is deteriorating the environment through resource depletion and rising pollution levels which led to a significant transition toward green supply chain practices (GSCP). Therefore, internal and external GSCP and green training (GT) gaining momentous attention. This study aims to explore the interconnections among the internal and external GSCP, GT, green innovation (GI), pro-environmental behavior (PEB), competitive advantage (CA), green knowledge sharing (GKS), green self-efficacy (GSE), environmental and financial performance (EP) and (FP).

Design/methodology/approach

To check the hypothesized model, researchers used cross-sectional data based on survey questionnaires which were gathered from Pakistani manufacturing firms. The theoretical framework was validated through the utilization of partial least square structural equation modeling.

Findings

The findings suggest that internal and external GSCP and GT are correlated with GI, PEB, CA, EP and FP. Additionally, this study discovers that PEB and GI act as intermediaries among internal and external GSCP, GT and CA. GKS positively moderates the connection among internal and external GSCP, and GT, GI, and PEB. Similarly, GSE also serves as a moderator among between PEB and GI.

Research limitations/implications

This study is a significant contribution to the literature by studying potential mediators and moderators that improve the association among outlined constructs. Moreover, findings suggest that firms should adopt an integrated and holistic green approach to combat environmental deterioration, maintain environmental integrity and attain sustainable development.

Originality/value

There is a scarcity of studies concerning the holistic framework of interrelated constructs studied in this research and it is the pioneer research to offer insights with an innovative model and empirical evidence.