Afshan Naseem

A hybrid data-driven and qualitative approach for critical factor identification in pharmaceutical supplier selection: safeguarding the continuity of pharmaceutical in disruption-prone settings

Purpose This study aims to develop a comprehensive and integrated approach for identifying and prioritizing critical factors influencing pharmaceutical supplier selection and supply chain performance, with direct implications for health system resilience and access to essential m...

Revolutionizing hospital supply chain: machine learning for predictive risk assessment

Purpose The purpose of this study is to identify and prioritize the risks associated with healthcare supply chain with a focus on hospital’s internal supply chain. Design/methodology/approach The study presents a machine learning model for hospital supply chain risk assessment. T...

Integration of Quality Function Deployment and Monte Carlo Simulation for risk prioritization in a textile sector

Purpose Following the COVID-19 pandemic, the home-textile industry has experienced a decline in production orders, heightening competition and making it more difficult to maintain consistent customer satisfaction and operational performance. To address these challenges, this stud...