Enablers of Green Logistics Adoption in Developing Versus Emerging Economies: An Integrated PLS-SEM and fsQCA Analysis

Abstract

Decarbonising freight transport and warehousing is now central to national climate commitments, yet the firm-level enablers that move green logistics from intention to reported performance remain unevenly understood across economic contexts. This study examines how seven enabler constructs influence green logistics performance and whether their effects and configurations differ between developing and emerging economies. Drawing on a survey of 220 logistics and supply chain managers in India and China, the study applies partial least squares structural equation modelling (PLS-SEM) with multi-group analysis (MGA) to estimate net effects, complemented by fuzzy-set qualitative comparative analysis (fsQCA) to surface equifinal configurations. The seven enabler constructs were operationalised by inverting the empirically validated barrier dimensions established in a companion Total Interpretive Structural Modelling (TISM) study, a grounding that the authors argue strengthens construct validity. Top management commitment and green supply chain integration emerge as the proximate drivers of performance, while knowledge and skill readiness unlock digital infrastructure readiness. MGA reveals that the digital-integration path is significantly stronger in emerging economies, whereas the regulatory-to-management path is stronger in developing economies. Endogeneity checks and comparisons against reversed specifications support the modelled directions. fsQCA identifies three sufficient configurations in developing economies and two in emerging economies, all built on a shared core of integration and managerial commitment, and demonstrates that no single enabler is necessary. The configurations diverge in what completes that core, with eased cost constraints and regulatory obligation forming substitutable routes in developing economies and cost ceasing to discriminate in emerging ones. By integrating a symmetric variance-based method with an asymmetric configurational method across two economy types, and by grounding the enabler set in a prior structural model of barriers, the study offers a context-sensitive account of how green logistics performance is achieved and provides differentiated guidance for policymakers and managers.