Modeling Organizational Performance with Machine Learning

Identifying the performance factors of organizations is utmost importance for labor studies both empirical and theoretical research. The present study investigates essential intra- extra-organizational in determining firms using European Company Survey (ECS) 2019 framework. evolutionary computation method genetic algorithm machine learning Bayesian additive regression trees (BART), are used to model each identifying firms’ as well employee well-being. standard metrics further evaluate accuracy proposed method. mean value evaluation impact on firm MAE = 0.225, MSE 0.065, RMSE 0.2525, R2 0.9125, these well-being 0.18, 0.0525, 0.2275, 0.88. low values MAE, RMSE, high R2, indicate level results revealed that two variables work organization innovation improving well-being, collaboration outsourcing, job complexity autonomy, have greatest role performance.