Survival analysis for predicting bankruptcy in small and medium-sized enterprises (SMEs): A case study approach

Abstract

This study investigates the determinants of small and medium-sized enterprise (SME) survival through a quantitative analysis of financial and managerial factors. Using a dataset of SMEs observed over a ten-year period, the research applies survival analysis techniques based on the nonparametric Kaplan–Meier estimator and complementary log–log regression to identify predictors of business insolvency. The results show that firm survival is positively influenced by financial structure, return on assets, EBITDA, and human capital productivity, whereas excessive working capital is negatively associated with longevity. By incorporating underexplored variables such as financial results and employee productivity, this study broadens the empirical scope of survival analysis beyond traditional financial ratios. The findings contribute to the strategic management literature by identifying measurable financial and operational indicators that can serve as early warning signals of business failure. Although the data are drawn from a regional sample, the managerial implications are broadly applicable to SMEs operating across diverse economic and institutional contexts.