Abstract

The importance of small and medium construction enterprises (SMEs) in the South African economy has been recognised. However, construction SMEs are faced with difficulties in accessing credit from financial institutions. Furthermore, past research has failed to reach consensus on the demographic and socio-economic factors that predict credit accessibility for construction SMEs in South Africa. This study determines the predicting demographic and socio-economic factors for credit accessibility for construction SMEs from financial institutions in South Africa. A quantitative research approach was used and data was collected, using a questionnaire survey from 250 construction SMEs who were conveniently sampled. The demographic and company profile factors predicting credit accessibility were modelled and set as the independent variables with credit accessibility to the construction SMEs as the dependent variable, irrespective of the amount obtained from financial institutions. The data was analysed using the Statistical Package for the Social Sciences (SPSS) version 22. Binary logistic regression analysis was used to analyse the predictors of obtaining credit. In the first model, the results revealed that the credit accessed irrespective of the amount and those who did not receive credit at all, when modelled with the conceptualised predictors suggested, showed no significant predictors of obtaining credit. However, in the second model, when the conceptualised predictors were modelled with full and partial credit, the results established that age group, current position in the organisation, tax number and location were good predictors of obtaining full credit. The findings of this study cannot be generalised across South Africa, as the study was conducted only in the Gauteng province. The value of this study informs owners of SMEs in the construction industry to provide their age and current position in the organisation when applying for credit. They should also provide the tax number and the location of the business in order to improve their chances of obtaining full credit from financial institutions. Keywords : Credit accessibility, determinants of credit accessibility, full credit, small and medium enterprises

Highlights

  • The term ‘Small and Medium Enterprises’ (SMEs) is defined by commonly used criteria such as the number of employees, total net assets, sales and investment level

  • The study elicited data from construction small and medium construction enterprises (SMEs) personnel who are conversant with the credit accessibility within their enterprise

  • The construction SMEs that obtained credit partially can be impeded in their progress

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Summary

Introduction

The term ‘Small and Medium Enterprises’ (SMEs) is defined by commonly used criteria such as the number of employees, total net assets, sales and investment level. In the South African construction industry, the term ‘small enterprise’ is defined as a company that employs 50 or less employees and has an annual turnover of less than R5 million. Despite the importance of SMMEs to the South African economy, the small and medium construction enterprises (SMEs) sector is still described as, to a large extent, underdeveloped; lacking the sophistication enjoyed by larger well-established contractors; left on the periphery of the mainstream economy, and not participating fully in the economy (Department of Public Works, 1999). It is accepted that SMEs are a vehicle of economic empowerment in the construction and other industries in South Africa. They are faced with numerous constraints to enable them to maximize their economic potential. The socio-economic and demographic determinants predicting full credit accessibility for SMEs from financial institutions were assessed and evaluated by means of regression statistics testing whether participating SMEs received full credit, part of the credit, or no credit at all

Challenges preventing SMEs from accessing credit
Predictors of credit accessibility
The demographic and socio-economic determinants of credit accessibility
Gender
Age group
Current position
Types of business ownership
Tax number
Location of the business
Collateral security
Research method and design
Sampling method and size
Response rate
Data collection
Data analysis and interpretation of findings
Results and discussions
Conclusions
Recommendations to government
Recommendation to construction SMEs
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