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A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments

Small and Medium Enterprises play an important economic role in many countries. In South Africa, for example, a significant proportion of the formal business entities are SMEs; and they contribute between 52 and 57% to GDP, and provide about 61% to employment. However, despite their significance in...

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Main Author: Amparbeng, Kofi
Other Authors: Abor, Joshua
Format: Thesis
Language:English
Published: Research of GSB 2018
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access_status_str Open Access
author Amparbeng, Kofi
author2 Abor, Joshua
author_browse Abor, Joshua
Amparbeng, Kofi
author_facet Abor, Joshua
Amparbeng, Kofi
author_sort Amparbeng, Kofi
collection Thesis
description Small and Medium Enterprises play an important economic role in many countries. In South Africa, for example, a significant proportion of the formal business entities are SMEs; and they contribute between 52 and 57% to GDP, and provide about 61% to employment. However, despite their significance in the local economy, SMEs regularly encounter the threat of failure. Business failure can be disruptive and costly to a large number of stakeholders, which include the owner, the employees, suppliers, customers, investors, bankers, communities, etc. This study examines failed SMEs and compares them with SMEs that are going concerns in order to discover significant differences between the two groups. The study adopted non-parametric tests and binary logistic regression methods. The final data set included 50 failures covering the calendar years July 2009 and June 2012, and 50 going concerns listed in the IDC database on 30 June 2012. The dataset was limited to industrial sector firms from the Chemicals, Metal, Textiles and Wood & Paper industry. The results of this study indicate that, the going concern sample of SMEs were larger than the failures in terms of firm size; led by more experienced management; older in terms of years in existence; and were supported by a stronger equity structure and interest cover ratio. The binary logistic regression results also show that SMEs located in provinces with high per capita income are associated with high probability of failure. But SMEs with increase in annual turnover or increase in equity structure are less likely to fail. Understanding which variables are statistically significantly different between the two groups can enable business owners to develop plans to increase their likelihood of survival. They can also help other stakeholders such as funders implement policies and controls for funding SMEs that mitigate these risk factors.
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institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:34:25.395Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2018
publishDateRange 2018
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spelling oai:open.uct.ac.za:11427/29006 A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments Amparbeng, Kofi Abor, Joshua Development Finance Small and Medium Enterprises play an important economic role in many countries. In South Africa, for example, a significant proportion of the formal business entities are SMEs; and they contribute between 52 and 57% to GDP, and provide about 61% to employment. However, despite their significance in the local economy, SMEs regularly encounter the threat of failure. Business failure can be disruptive and costly to a large number of stakeholders, which include the owner, the employees, suppliers, customers, investors, bankers, communities, etc. This study examines failed SMEs and compares them with SMEs that are going concerns in order to discover significant differences between the two groups. The study adopted non-parametric tests and binary logistic regression methods. The final data set included 50 failures covering the calendar years July 2009 and June 2012, and 50 going concerns listed in the IDC database on 30 June 2012. The dataset was limited to industrial sector firms from the Chemicals, Metal, Textiles and Wood & Paper industry. The results of this study indicate that, the going concern sample of SMEs were larger than the failures in terms of firm size; led by more experienced management; older in terms of years in existence; and were supported by a stronger equity structure and interest cover ratio. The binary logistic regression results also show that SMEs located in provinces with high per capita income are associated with high probability of failure. But SMEs with increase in annual turnover or increase in equity structure are less likely to fail. Understanding which variables are statistically significantly different between the two groups can enable business owners to develop plans to increase their likelihood of survival. They can also help other stakeholders such as funders implement policies and controls for funding SMEs that mitigate these risk factors. 2018-11-06T14:03:34Z 2018-11-06T14:03:34Z 2012 Master Thesis Masters MCom http://hdl.handle.net/11427/29006 eng application/pdf Research of GSB Faculty of Commerce University of Cape Town
spellingShingle Development Finance
Amparbeng, Kofi
A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
thesis_degree_str Master's
title A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
title_full A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
title_fullStr A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
title_full_unstemmed A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
title_short A cross sectional analysis of SME failure within the industrial sector: focus on IDC funded investments
title_sort cross sectional analysis of sme failure within the industrial sector focus on idc funded investments
topic Development Finance
url http://hdl.handle.net/11427/29006
work_keys_str_mv AT amparbengkofi acrosssectionalanalysisofsmefailurewithintheindustrialsectorfocusonidcfundedinvestments
AT amparbengkofi crosssectionalanalysisofsmefailurewithintheindustrialsectorfocusonidcfundedinvestments