Financial Distress among SMEs in Malaysia: An Early Warning Signal - Muhammad Ma'aji, Muhammad; Abdullah, Nur Adiana Hiau; Karren Khaw, Lee Hwei (Universiti Malaysia Sarawak, 2019)
Small and medium-sized enterprises (SMEs) play an important role in the economy worldwide, and predicting financial distress among SMEs can have a significant impact on the economy as it serves as an effective early warning signal. The study develops distress prediction models by combining financial, non-financial, and governance variables. By using multiple discriminant analysis and logistic regression, controlling shareholders, the number of directors, the gender of managing director, earnings before interest and tax, the size, and the age of company are found to be significant in predicting financial distress of SMEs in Malaysia for the period from 2000 to 2012. The result shows that the logit model gives a higher predictive accuracy rate at 93.6 percent for the estimated sample as compared to the multiple discriminant analysis model.