Applications of fsQCA in Logistics and Supply Chain Management: A Systematic Review

Causal complexity and systems thinking have long been recognized as inherent features of logistics and supply chain management (LSCM), yet they have received limited scholarly attention, partly due to the lack of appropriate methodological tools. The emergence of fuzzy-set qualitative comparative analysis (fsQCA) has reinvigorated systems thinking by introducing a configurational approach to LSCM research. Consequently, the use of fsQCA in this field has grown rapidly in recent years, warranting a systematic evaluation to support further disciplinary advancement. Drawing on a systematic review of 179 peer-reviewed articles published between 2015 and 2025, this study critically examines the application of fsQCA in LSCM. We found that fsQCA in past research was applied both as a standalone method and as a complement to conventional techniques such as regression, to identify alternative configurations of conditions for supply chain strategy, performance, sustainability, flexibility, resilience, digitalization, and collaboration. Evaluating these studies against established fsQCA methodological guidelines, the review reveals considerable inconsistencies in the analysis and reporting of data calibration, truth table construction, necessary and sufficient conditions, and robustness testing. Based on these findings, this study suggests best practice guidelines to strengthen the rigor and transparency of future configurational research and outlines agenda for advancing fsQCA-based LSCM studies. For practitioners, the configurational evidence synthesized in this review demonstrates that LSCM outcomes can be achieved through multiple distinct configurations of strategies, highlighting opportunities to adopt alternatives to one-size-fits-all best practices. The review thereby setting a benchmark to strengthen the methodological foundations for rigorous, theory-driven, and practically relevant configurational research in LSCM.