Blockchain-Driven Supply Chain Analytics and Sustainable Performance: Analysis Using PLS-SEM and ANFIS

This study investigates the impact of blockchain-driven supply chain analytics on the dimensions of lean, agile, resilient, green, and sustainable (LARGS) supply chain management, as well as supply chain innovation (SCI) and sustainable supply chain performance (SSCP). The research involved 262 managers and vice presidents of supply chains from large and medium-sized manufacturing companies listed in the Tehran Stock Exchange. A hybrid approach utilizing Structural Equations Modelling with partial least squares-structural equation modeling (PLS-SEM) and the adaptive neuro-fuzzy inference systems (ANFIS) technique was employed for data analysis. The findings demonstrate a significantly positive effect of blockchain-driven supply chain analytics on SCI, LARGS supply chain, and SSCP. Additionally, SCI exhibits a significantly positive impact on LARGS supply chain and SSCP. Moreover, the LARGS supply chain is shown to have a significantly positive influence on SSCP. Both SCI and LARGS supply chain play a positive and significant mediating role in the impact of blockchain-driven supply chain analytics on SSCP. Furthermore, the LARGS supply chain also acts as a significant mediator in the effect of SCI on SSCP. Lastly, SCI has a positive and significant mediating role in the impact of blockchain-driven supply chain analytics on the LARGS supply chain. In conclusion, it can be inferred that blockchain-driven supply chain analytics contributes to the enhancement of SSCP through the facilitation of SCI and the promotion of LARGS supply chain principles.