Financial Distress among SMEs in Malaysia: An Early Warning Signal

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...

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Main Authors: Muhammad Ma'aji, Muhammad, Abdullah, Nur Adiana Hiau, Karren Khaw, Lee Hwei
Format: Article
Language:English
Published: Universiti Malaysia Sarawak 2019
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/24678/1/Vol20-no2-paper21.pdf
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author Muhammad Ma'aji, Muhammad
Abdullah, Nur Adiana Hiau
Karren Khaw, Lee Hwei
author_facet Muhammad Ma'aji, Muhammad
Abdullah, Nur Adiana Hiau
Karren Khaw, Lee Hwei
author_sort Muhammad Ma'aji, Muhammad
collection UUM
description 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.
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spelling uum-246782022-01-01T14:29:36Z https://repo.uum.edu.my/id/eprint/24678/ Financial Distress among SMEs in Malaysia: An Early Warning Signal Muhammad Ma'aji, Muhammad Abdullah, Nur Adiana Hiau Karren Khaw, Lee Hwei HG Finance 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. Universiti Malaysia Sarawak 2019 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/24678/1/Vol20-no2-paper21.pdf Muhammad Ma'aji, Muhammad and Abdullah, Nur Adiana Hiau and Karren Khaw, Lee Hwei (2019) Financial Distress among SMEs in Malaysia: An Early Warning Signal. International Journal of Business and Society, 20 (2). pp. 775-792. ISSN 1511-6670
spellingShingle HG Finance
Muhammad Ma'aji, Muhammad
Abdullah, Nur Adiana Hiau
Karren Khaw, Lee Hwei
Financial Distress among SMEs in Malaysia: An Early Warning Signal
title Financial Distress among SMEs in Malaysia: An Early Warning Signal
title_full Financial Distress among SMEs in Malaysia: An Early Warning Signal
title_fullStr Financial Distress among SMEs in Malaysia: An Early Warning Signal
title_full_unstemmed Financial Distress among SMEs in Malaysia: An Early Warning Signal
title_short Financial Distress among SMEs in Malaysia: An Early Warning Signal
title_sort financial distress among smes in malaysia an early warning signal
topic HG Finance
url https://repo.uum.edu.my/id/eprint/24678/1/Vol20-no2-paper21.pdf
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