Article citationsMore>>

Doğan, S., Koçak, D., & Atan, M. (2022). Financial Distress Prediction Using Support Vector Machines and Logistic Regression. In M.K. Terzioğlu (Eds.), Advances in Econometrics, Operational Research, Data Science and Actuarial Studies (pp. 429-452). Springer International Publishing.
https://doi.org/10.1007/978-3-030-85254-2_26

has been cited by the following article:

• TITLE: Business Failure Prediction: The Case of Moroccan SMEs

  AUTHORS: Nabil Arzou, Miloudi Kobiyh, Marouane Mkik

  KEYWORDS: SMEs, Financial Management, Failure Prediction, Discriminant Analysis, Business Sustainability

  JOURNAL NAME: Open Journal of Business and Management, Vol.13 No.1, January 10, 2025

  ABSTRACT: This research examines the financial challenges faced by small and medium enterprises (SMEs) in Morocco, which play a vital role in the country’s economy. However, many SMEs struggle with financial instability, leading to high failure rates. This study focuses on identifying key factors that contribute to business failure. A quantitative approach was applied, utilizing discriminant analysis to assess the differences between successful and failing SMEs. The findings reveal that liquidity and profitability are critical to distinguishing between the two groups, with failing companies showing weaker performance in these areas. This research highlights the importance of financial management practices in mitigating the risk of failure in Moroccan SMEs. It emphasizes the need for effective financial strategies, particularly in managing liquidity and improving profitability, to ensure the sustainability and success of SMEs in the Moroccan context.