Our study forecasts the likelihood of firms resuming growth after periods of stagnation or declining sales. We employ machine learning methods, including Random Forest, LightGBM, and CatBoost, alongside logistic regression models. To address class imbalance, we incorporate oversampling...

This study analyzes factors affecting the efficiency (profitability) of enterprises in foreign, joint and domestic ownership in countries with unstable economy. The novelty of the study is that for the first time this kind of analysis has been carried out for the manufacturing industry in...

The present study analyses BRICS (Brazil, Russia, India, China, South Africa) capital markets in both time and frequency domain using wavelets. We used artificial neural network techniques to forecast the co-movement among BRICS capital markets. Wavelet coherence and clustering estimates uncover...

This study examines the impact of traditional working capital management (WCM) and modern technological factors, specifically digital communications with customers as part of a customer relationship management strategy (CRM), on the performance of retail consumer-focused industrial and service...