Bouncing back to the surface: Factors determining SME recovery

Limited attention has been devoted to the key determinants of survival in situations of severe financial distress for small and medium-sized enterprises (SMEs). Against this backdrop, drawing from turnaround management literature, we develop hypotheses about SMEs investigating the importance of prior financial blockages, financial indicators, personnel characteristics, and the dynamics between SMEs and their personnel on recovery probability. By relying on advanced machine learning techniques, we analyze and select key predictors of recovery likelihood for SMEs in situations of severe distress. The results provide empirical support for our hypotheses, showing the significant roles of prior bank account blockages, creditworthiness, mean employee age, firing ratio, and the share of permanent work contracts in influencing recovery odds. The implications extend knowledge on SME turnaround strategies and offer practical suggestions for managers and policymakers in tailoring interventions.