Small and Medium Enterprises’ Risk Modeling

Small and Medium Enterprises’ Risk Modeling

Small and medium enterprises (SMEs) in Malaysia keep failing year to year due to economic fluctuation and challenges. This affects the industry and economy growth of Malaysia. This research was conducted to identify criteria of performance prediction model that can predict success or failure risk of...

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Main Authors: Sorooshian, Shahryar, Ahmad Suffian, Nursofea Iman
Format: Article
Language:English
Published: IRMM 2017
Subjects:
AI Indexes (General)
Online Access:http://umpir.ump.edu.my/id/eprint/17402/
http://umpir.ump.edu.my/id/eprint/17402/
http://umpir.ump.edu.my/id/eprint/17402/1/4107-11489-1-PB.pdf
id ump-17402
recordtype eprints
spelling ump-174022017-11-01T06:53:34Z http://umpir.ump.edu.my/id/eprint/17402/ Small and Medium Enterprises’ Risk Modeling Sorooshian, Shahryar Ahmad Suffian, Nursofea Iman AI Indexes (General) Small and medium enterprises (SMEs) in Malaysia keep failing year to year due to economic fluctuation and challenges. This affects the industry and economy growth of Malaysia. This research was conducted to identify criteria of performance prediction model that can predict success or failure risk of SMEs and to develop the predictive model, based on logit regression method, for SMEs of Malaysia. Developing a model of logit regression is by using the four perspectives of the balanced scorecard approach. The four perspectives are independent variables, including the success and failure of SMEs as the dependent variable. The variables would help in developing the model through Statistical Package for the Social Science. data software to gain the binomial regression results. The modeled result is based on the probability of the SME success and bankruptcy risk, useful for policy makers. IRMM 2017 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/17402/1/4107-11489-1-PB.pdf Sorooshian, Shahryar and Ahmad Suffian, Nursofea Iman (2017) Small and Medium Enterprises’ Risk Modeling. International Review of Management and Marketing, 7 (2). pp. 197-201. ISSN 2146-4405 http://econjournals.com/index.php/irmm/article/view/4107
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic AI Indexes (General)
spellingShingle AI Indexes (General)
Sorooshian, Shahryar
Ahmad Suffian, Nursofea Iman
Small and Medium Enterprises’ Risk Modeling
description Small and medium enterprises (SMEs) in Malaysia keep failing year to year due to economic fluctuation and challenges. This affects the industry and economy growth of Malaysia. This research was conducted to identify criteria of performance prediction model that can predict success or failure risk of SMEs and to develop the predictive model, based on logit regression method, for SMEs of Malaysia. Developing a model of logit regression is by using the four perspectives of the balanced scorecard approach. The four perspectives are independent variables, including the success and failure of SMEs as the dependent variable. The variables would help in developing the model through Statistical Package for the Social Science. data software to gain the binomial regression results. The modeled result is based on the probability of the SME success and bankruptcy risk, useful for policy makers.
format Article
author Sorooshian, Shahryar
Ahmad Suffian, Nursofea Iman
author_facet Sorooshian, Shahryar
Ahmad Suffian, Nursofea Iman
author_sort Sorooshian, Shahryar
title Small and Medium Enterprises’ Risk Modeling
title_short Small and Medium Enterprises’ Risk Modeling
title_full Small and Medium Enterprises’ Risk Modeling
title_fullStr Small and Medium Enterprises’ Risk Modeling
title_full_unstemmed Small and Medium Enterprises’ Risk Modeling
title_sort small and medium enterprises’ risk modeling
publisher IRMM
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/17402/
http://umpir.ump.edu.my/id/eprint/17402/
http://umpir.ump.edu.my/id/eprint/17402/1/4107-11489-1-PB.pdf
first_indexed 2023-09-18T22:24:00Z
last_indexed 2023-09-18T22:24:00Z
_version_ 1777415844729454592

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