Investigating the impact of Artificial Intelligence on Environmental supply chain performance through the lens of supply chain resilience

Abstract

The objective of this research is to conceptualize the mechanisms by which artificial intelligence influences environmental supply chain performance, with a particular focus on the mediating role of supply chain resilience. The study seeks to address the theoretical gap in understanding how AI-driven capabilities translate into environmental benefits within supply chains, particularly in developing economies characterized by volatility and resource constraints. Employing a conceptual methodology, the study integrates the Dynamic Capabilities View with established models of AI capability, resilience, and green supply chain performance. AI is posited as a dynamic capability that enhances an organization’s ability to sense environmental shifts, forecast disruptions, and reconfigure operational processes. The framework theorizes that these capabilities collectively reinforce resilience, enabling supply chains to maintain environmentally responsible performance even under conditions of uncertainty. The results are presented as theoretically derived propositions linking AI capability to environmental performance both directly and indirectly through resilience. These propositions demonstrate that resilience serves as a critical transmission mechanism through which AI exerts its environmental impact, thereby expanding current knowledge on digital sustainability pathways. The conclusion underscores both conceptual and practical implications. For scholars, the study provides a foundation for advancing theoretical models that connect digital capabilities with environmental outcomes. For practitioners and policymakers, the framework highlights the strategic importance of investing in AI applications that bolster resilience as a prerequisite for achieving improvements in environmental performance.