Predicting financial distress among SMEs in Malaysia
Predicting financial distress among Small and Medium Enterprises (SMEs) can have a significant impact on the economy as it serves as an effective early warning signal. The study develops distress prediction models combining financial, non-financial and governance variables which were used to analyze...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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European Scientific Institute
2018
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| Online Access: | https://repo.uum.edu.my/id/eprint/26014/1/ESJ%2014%207%202018%2091%20102.pdf |
| _version_ | 1803629044708671488 |
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| author | Ma’aji, Muhammad M. Abdullah, Nur Adiana Hiau Khaw, Karren Lee-Hwei |
| author_facet | Ma’aji, Muhammad M. Abdullah, Nur Adiana Hiau Khaw, Karren Lee-Hwei |
| author_sort | Ma’aji, Muhammad M. |
| collection | UUM |
| description | Predicting financial distress among Small and Medium Enterprises (SMEs) can have a significant impact on the economy as it serves as an effective early warning signal. The study develops distress prediction models combining financial, non-financial and governance variables which were used to analyze the influence of major corporate governance characteristics, like ownership and board structures, on the likelihood of financial distress. Multiple Discriminant Analysis (MDA) model as one of the extensively documented approaches was used. The final sample for the estimation model consists of 172 companies with 50 percent non-failed cases and 50 percent failed cases for the period between 2000 to 2012. The prediction models perform relatively well especially in MDA model that incorporate governance, financial and non-financial variables, with an overall accuracy rate of 90.7 percent in the estimated sample. The accuracy rate in the holdout sample was 91.2 percent for the MDA model. This evidence shows that the models serve as efficient earlywarning signals and can thus be beneficial for monitoring and evaluation. Controlling shareholder, number of directors, and gender of managing director are found to be significant predictors of financially distressed SMEs. |
| first_indexed | 2024-07-04T06:31:36Z |
| format | Article |
| id | uum-26014 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:31:36Z |
| publishDate | 2018 |
| publisher | European Scientific Institute |
| record_format | dspace |
| spelling | uum-260142019-05-02T01:35:09Z https://repo.uum.edu.my/id/eprint/26014/ Predicting financial distress among SMEs in Malaysia Ma’aji, Muhammad M. Abdullah, Nur Adiana Hiau Khaw, Karren Lee-Hwei HG Finance Predicting financial distress among Small and Medium Enterprises (SMEs) can have a significant impact on the economy as it serves as an effective early warning signal. The study develops distress prediction models combining financial, non-financial and governance variables which were used to analyze the influence of major corporate governance characteristics, like ownership and board structures, on the likelihood of financial distress. Multiple Discriminant Analysis (MDA) model as one of the extensively documented approaches was used. The final sample for the estimation model consists of 172 companies with 50 percent non-failed cases and 50 percent failed cases for the period between 2000 to 2012. The prediction models perform relatively well especially in MDA model that incorporate governance, financial and non-financial variables, with an overall accuracy rate of 90.7 percent in the estimated sample. The accuracy rate in the holdout sample was 91.2 percent for the MDA model. This evidence shows that the models serve as efficient earlywarning signals and can thus be beneficial for monitoring and evaluation. Controlling shareholder, number of directors, and gender of managing director are found to be significant predictors of financially distressed SMEs. European Scientific Institute 2018 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/26014/1/ESJ%2014%207%202018%2091%20102.pdf Ma’aji, Muhammad M. and Abdullah, Nur Adiana Hiau and Khaw, Karren Lee-Hwei (2018) Predicting financial distress among SMEs in Malaysia. European Scientific Journal, ESJ, 14 (7). pp. 91-102. ISSN 18577881 http://doi.org/10.19044/esj.2018.v14n7p91 doi:10.19044/esj.2018.v14n7p91 doi:10.19044/esj.2018.v14n7p91 |
| spellingShingle | HG Finance Ma’aji, Muhammad M. Abdullah, Nur Adiana Hiau Khaw, Karren Lee-Hwei Predicting financial distress among SMEs in Malaysia |
| title | Predicting financial distress among SMEs in Malaysia |
| title_full | Predicting financial distress among SMEs in Malaysia |
| title_fullStr | Predicting financial distress among SMEs in Malaysia |
| title_full_unstemmed | Predicting financial distress among SMEs in Malaysia |
| title_short | Predicting financial distress among SMEs in Malaysia |
| title_sort | predicting financial distress among smes in malaysia |
| topic | HG Finance |
| url | https://repo.uum.edu.my/id/eprint/26014/1/ESJ%2014%207%202018%2091%20102.pdf |
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