Interpretability analysis methods, such as LIME and SHAP, are widely employed to explain the predictions of artificial … intelligence models; however, they primarily function as post hoc tools and do not directly quantify the intrinsic interpretability … currently no standardized framework for evaluating interpretability as an inherent property of AI models. In this study, we …

interpretability and access significantly shape managerial trust, learning, and decision autonomy across supply chain tiers …. Conclusions: Sustainable and inclusive AI adoption in logistics requires balancing operational efficiency with interpretability …

tail-risk exposure, regime instability, limited interpretability, and regulatory and governance constraints in practical …, discretionary intervention, and interpretability review. This framework resonates with human-AI collaboration systems across other …