Efficiency of Working Capital & Assets Management in the Function of SMEs Bankruptcy Prediction


  • Denis Kušter University of Novi Sad, Faculty of Economics, Serbia




Financial distress, bankruptcy prediction, SMEs, financial ratios, logistic regression, business failure, statistical modelling


Research Question: This research has been conducted with the aim of determining whether it is possible to generate a model that can reliably predict bankruptcy of Serbian small and medium-sized enterprises (SMEs) using Working Capital Management (WCM) and Asset Management (AM) efficiency ratios. Motivation: Motive for this research is the fact there are not many business failure prediction models related to SMEs. In addition, existing models are not focused on efficiency of the two above mentioned categories. Also, previously developed models, especially traditional and ground-breaking ones, are not necessarily aligned with accounting procedures and economic environment of all countries, which indicates the need to develop a model that is adapted for Serbian territory. Idea: The idea is to develop a model that has the ability to predict whether an entity has a tendency to initiate bankruptcy proceedings in the next year. This is useful both for external stakeholders and for SMEs’ owners themselves, as it allows them to better manage resources. Data: The research was conducted on a sample of 100 Serbian SMEs. Data for the calculation of ratio indicators is available on the Business Registers Agency webpage. Tools: The research was conducted as a combination of financial and statistical analysis instruments. Ratio indicators were used for financial analysis part, while statistical analysis was conducted in SPSS program v.26 and includes logistic (binary) regression. Findings: Results of the research indicate that AM efficiency indicators are suitable for SMEs bankruptcy prediction modelling, but also indicate that WCM ratios don’t have great contribution in bankruptcy prediction for Serbian SMEs. A model that has a classification accuracy of 79% has been developed. Contribution: This research empirically tests how selected ratio indicators support SMEs bankruptcy prediction, and therefore can be beneficial for all SMEs stakeholders, but also other researches since the research methodology is explained in details.

Author Biography

Denis Kušter, University of Novi Sad, Faculty of Economics, Serbia

Denis Kušter, MSc works full-time as Financial Controller at Schneider Electric Hub since 2019. Also, he works as part-time teaching associate (demonstrator) at the Faculty of Economics in Novi Sad. Denis is a PhD candidate in Corporate Finance, Accounting & Auditing program. He is the holder of several academic awards, of which he especially points out following: Award from Endowment Funds of Matica srpska, Serbian Association of Economists plaque award and Exceptional Award of the University of Novi Sad for academic achievements. Denis was the winner of several scholarships during his studies: Carlsberg & Dundjerski Scholarship, Scholarship of the University of Novi Sad, Scholarship of the Republic of Serbia, Young Talents Fund (Dositeja) Scholarship... During studies, he wrote several research and scientific papers, and for one of them he was awarded by the University of Novi Sad. His fields of interest are financial analysis and accounting.




How to Cite

Kušter, D. (2023). Efficiency of Working Capital & Assets Management in the Function of SMEs Bankruptcy Prediction. Management:Journal of Sustainable Business and Management Solutions in Emerging Economies, 28(3), 57–70. https://doi.org/10.7595/management.fon.2023.0007




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