... on critical infrastructure and for public policies to support CS adoption in SMEs. Originality/Value This study explores the drivers of CS adoption using machine learning (ML) and econometrics for unbalanced data, with a focus on developing regions. It highlights regulatory, technological and structural...

.... Design/methodology/approach Using advanced machine learning techniques, such as the LightGBM predictive model and SHapley Additive exPlanations (SHAP) analysis, we investigate how age, gender, educational level and access barriers, such as economic limitations and lack of time, influence the diversity...

...Iñigo Martin-Melero; Raul Gomez-Martinez; Maria Luisa Medrano-Garcia; Felipe Hernández-Perlines Purpose This paper aims to predict corporate insolvency by comparing machine learning (ML) and analytical formulas applied on 8 financial ratios. Design/methodology/approach This study uses...

... to a final selection based on their individual significance and machine learning. Findings The results show the prevalence of a limited number of financial variables related to equity, indebtedness, profits and liquidity as predictors of the failure of reorganization processes. The use of financial...