Sustainable synchromodal logistics: unveiling key enablers through neutrosophic interpretive structural modeling analysis

Purpose The purpose of this paper is to present a comprehensive analysis of the enablers pertaining to synchromodal logistics, emphasizing the identification of key decision criteria and the determination of their relative importance. Design/methodology/approach This study is rooted in the Natural Resource-Based View, Dynamic Capability and Social Well-Being theories, which provide essential frameworks for analyzing the diverse and interrelated factors shaping synchromodal logistics. The research involves an extensive literature review and consultations with experts from academia and industry to identify 11 enablers of synchromodal logistics. Neutrosophic interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement analysis are employed to analyze these enablers, leveraging the advantages of neutrosophic sets for handling ambiguous, unpredictable and indeterminate information. Findings The analysis identified “Electronic Data Exchange” and “Legal Political Framework” as crucial focal points for the successful implementation of synchromodal logistics. These elements were found to be essential for achieving the necessary synchronization and flexibility within transportation networks. Research limitations/implications The study's reliance on expert consultations and literature review may introduce subjectivity and may not encompass all potential enablers of synchromodal logistics. Future research could expand on these findings by incorporating a broader range of expert opinions and empirical data. Practical implications The findings provide valuable insights for stakeholders in the logistics industry, highlighting the importance of focusing on “electronic data exchange” and “legal political frameworks” to enhance the efficiency and effectiveness of synchromodal logistics. Originality/value This paper contributes to the existing body of knowledge by introducing a nuanced approach using neutrosophic sets to handle uncertain and vague data in the analysis of synchromodal logistics enablers, surpassing the limitations of fuzzy sets and offering greater flexibility in dealing with indeterminate information.