Green supply chain management and sustainable performance in Pakistan manufacturing sector with green innovation and big data analytics capability

Abstract Although the importance of green supply chain management (GSCM) in addressing climate change and enhancing performance has been acknowledged, the roles of green innovation (GI), green self-efficacy (GSE), and big data analytics capability (BDAC) in shaping environmental performance (EP) and financial performance (FP) remain underexplored. This study investigates these relationships using the dynamic capability view and self-efficacy theories. Data were collected through an online survey of 386 employees from Pakistani manufacturing firms and analyzed using partial least square structural equation modeling, validated and ranked through artificial neural network analysis. The findings show that GSCM practices significantly enhance EP and FP. GI and GSE serve as key mediators, while BDAC moderates the relationship between GSCM and EP, though its effect on FP is insignificant. This research addresses the overlooked interplay among these constructs, offering practical insights for firms and policymakers to institutionalize GSCM by prioritizing green training programs to strengthen GSE, while developing BDAC to enhance environmental monitoring, support informed decisions, and improve the sustainability outcomes of GSCM.