Structuring Logistics and Supply Chain Complexity: A Systematic Review of Problem Structuring Methods

Background: Supply chains are becoming increasingly complex, interconnected, and stakeholder-intensive, making effective problem formulation as important as identifying optimal solutions. Although problem structuring methods (PSMs) have been widely applied in logistics and supply chain management (LSCM), the literature remains fragmented, providing limited guidance on selecting appropriate methodologies for different problem contexts. Methods: Following the PRISMA guidelines, this review analyzes 187 journal articles published between 1997 and 2026. Bibliometric analysis and qualitative synthesis were combined to examine the evolution of the field, compare the characteristics and applications of different PSMs, and identify emerging methodological trends. Results: PSM research has grown substantially since 2015, with System Dynamics, Cognitive Mapping, and Scenario Planning emerging as the dominant methodologies. The review also identifies a clear shift toward mixed-methodology approaches that integrate PSMs with optimization, simulation, and multi-criteria decision-making techniques. Stakeholder complexity, uncertainty, and system dynamics were identified as the primary factors influencing methodology selection. Conclusions: This study advances theory and practice by developing an integrated decision-support framework and methodological guidance for selecting appropriate PSMs in complex logistics and supply chain environments. The proposed framework provides a practical roadmap for diagnosing ill-structured problems and choosing suitable problem structuring approaches across diverse supply chain contexts.