Identifying and analyzing obstacles to ESG-driven sustainable transition in third-party logistics: A WINGS–ISM approach under interval-valued spherical fuzzy modeling

Abstract

This study investigates the hierarchical structure and causal relationships among obstacles hindering the ESG driven sustainable transition of small and medium sized third-party logistics firms. Drawing on the resource-based view (RBV) and institutional (INT) theory, eleven obstacles are identified and validated, comprising eight endogenous and three exogenous factors. To address ambiguity, hesitation, and partial knowledge in expert judgments, the study adopts interval valued spherical fuzzy sets, which allow the simultaneous representation of membership, non-membership, and hesitancy degrees within bounded intervals. Compared with conventional Type 1 and Type 2 fuzzy sets, this approach provides greater expressive flexibility without imposing excessive computational or interpretability burdens in small expert panel studies. Using the Weighted Influence Nonlinear Gauge System (WINGS), six endogenous obstacles are revealed as dominant driving barriers, indicating that limitations in financial capacity, technological and digital infrastructure, process standardization, and sustainability capabilities primarily constrain ESG implementation, consistent with RBV logic emphasizing firm specific resources. In contrast, exogenous obstacles related to organizational culture, strategic alignment, regulatory coherence, governmental incentives, and stakeholder collaboration function mainly as dependent effect factors shaped by institutional conditions. Using Interpretive Structural Modeling (ISM) further identifies a five-level hierarchy, with obsolete technological infrastructure emerging as the root barrier. The study provides actionable insights for managers and policymakers seeking to design capability-oriented interventions and supportive institutional mechanisms to accelerate ESG transitions in SME logistics and other service intensive sectors.