Mahdi Esmaeili

A hybrid machine learning framework for supplier risk prediction and segmentation: an automotive supply chain case study

Purpose This study aims to develop a hybrid data-driven framework for supplier risk assessment in automotive supply chains. It seeks to integrate predictive modeling with clustering techniques to proactively identify and categorize supplier risks, enabling enhanced operational st...