Predicting delivery delays is crucial for companies, especially in times of increasing global uncertainty and vulnerable supply chains. Machine learning (ML) offers significant potential to improve the forecast performance and quality of delivery delay prediction. Although various prediction...

Multi-objective optimization problems (MOPs) are common in real-world applications, including scheduling, vehicle routing, and engineering design. A key challenge in solving MOPs is balancing convergence and diversity, as these problems often involve conflicting objectives and complex...

This study integrates the House of Risk (HOR) approach with the Fuzzy Inference System (FIS) to manage supply chain risks in steel fabrication by addressing market uncertainties and operational challenges to enhance stability and productivity. The study begins with risk identification using HOR...

This study examines the nexus between Google Trends’ collective interest in specific keywords related to technological advancements utilized in design and the stock performance of major companies in design-related sectors. Specifically, the paper examines causality patterns between Google...

Organizational resilience is vital for the sustainability of SMEs in emerging economies like Ecuador. This study proposes and validates a conceptual model integrating reactive and organizational-financial resilience to assess their impact on financial performance. Based on data from 333 SMEs,...