This study aims to significantly enhance the predictive modeling of credit risk within Egypt's banking sector, particularly by differentiating between retail and corporate credit risks and categorizing banks into listed and non-listed groups. By utilizing a comprehensive dataset from Middle...

Workplace surveillance is a sociotechnical practice shaped by both human actors and digital technology. Although existing surveillance frameworks acknowledge the role that social context plays in shaping the outcomes of surveillance, they overlook the impact organisational culture, leadership,...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in nowcasting across simulation and six country cases, traditional econometric models tend to outperform...

This study aims to improve the accuracy of transportation delay prediction in supply chains by developing a machine learning-based model. The proposed approach addresses the challenges of parameter tuning and feature selection by integrating the Firefly Algorithm with decision tree regression,...

Timely delivery is a critical performance metric in supply chain management, yet achieving consistent on-time delivery has become increasingly challenging in the face of global uncertainties and complex logistics networks. Recent disruptions, such as pandemics, extreme weather events, and...

Effective management of inventory is essential for achieving high service levels, minimizing costs, and maintaining the overall resilience of retail supply chains-particularly in complex, real-world environments. Conventional strategies often prove inadequate because they rely on rigid...