Effectiveness of prediction models for business failure in the Singapore context
206 p.
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2014
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Online Access: | http://hdl.handle.net/10356/57669 |
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sg-ntu-dr.10356-576692023-05-19T05:41:41Z Effectiveness of prediction models for business failure in the Singapore context Ang, Siew Peng Lim, Swee Keng Wee, Seo Yen Premila Gowri Shankar Nanyang Business School DRNTU::Business 206 p. Business failure is an area of utmost concern to the corporate world. It is important for the management of firms to identify problems and devise prompt corrective actions to rescue the businesses. Since the 1960s, researchers have engaged in numerous studies on business failure prediction. Various prediction models were developed based on different techniques with the hope of helping the firms to better predict their financial health. ACCOUNTANCY 2014-04-07T10:54:05Z 2014-04-07T10:54:05Z 1997 1997 Final Year Project (FYP) http://hdl.handle.net/10356/57669 Nanyang Technological University application/pdf |
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DRNTU::Business Ang, Siew Peng Lim, Swee Keng Wee, Seo Yen Effectiveness of prediction models for business failure in the Singapore context |
description |
206 p. |
author2 |
Premila Gowri Shankar |
author_facet |
Premila Gowri Shankar Ang, Siew Peng Lim, Swee Keng Wee, Seo Yen |
format |
Final Year Project |
author |
Ang, Siew Peng Lim, Swee Keng Wee, Seo Yen |
author_sort |
Ang, Siew Peng |
title |
Effectiveness of prediction models for business failure in the Singapore context |
title_short |
Effectiveness of prediction models for business failure in the Singapore context |
title_full |
Effectiveness of prediction models for business failure in the Singapore context |
title_fullStr |
Effectiveness of prediction models for business failure in the Singapore context |
title_full_unstemmed |
Effectiveness of prediction models for business failure in the Singapore context |
title_sort |
effectiveness of prediction models for business failure in the singapore context |
publishDate |
2014 |
url |
http://hdl.handle.net/10356/57669 |
_version_ |
1770567216768483328 |