Future-Proofing Strategies: Machine Learning Models for Organizational Resilience in Emerging Markets

The research investigates the predictive factors of organizational resilience using machine learning methods like decision trees, random forests, Ensemble Models, SVM, deep learning, and k-nearest neighbors (KNN). Among these methods, Ensemble Models (Voting Classifier) show the best combination of metrics. Investing in research and development (R&D), guaranteeing employee satisfaction, and providing capital seem to improve the prospects for resilience in emerging markets significantly. This examination reveals connections and undisclosed interactions between the factors, offering interpretations of the tightly-knit character of resilience.