PLS-SEM and ANN Model for Risk Management Effects on Re-Engineering Capabilities Small-Medium Enterprises

Data reveals that AI has the potential to assist SMEs by reducing decision-making costs and providing supply chains with more flexibility to respond to unpredictable events. This study uses a resource-based approach to examine how AI has affected SC risk management for SMEs. Staff members at all levels of management in SMEs contributed to the data set that was used to build and verify the structural model. All three of these concepts SC reengineering, SCA, and AI risk management are part of this larger framework. An analysis of neural networks (ANN), partial least squares structural equation modelling (PLS-SEM), or both is used extensively in this study. The findings demonstrate that AI risk management and SC reengineering agility are affected—the ability to re-engineer influences responsiveness indirectly. Consistency was found when comparing models, A and B using PLS-SEM and ANN. With much demand uncertainty in the SC, managers must make difficult trade-off judgments with few resources. With the help of AI, simulate a variety of scenarios and discover solutions to critical issues that traditional, antiquated methods miss. This study integrated a concept of agility with several components and discovered non-linear interactions within the model.