- Title
- Lending technologies and small, micro and medium enterprise borrowing: evidence from the Eastern Cape province of South
- Creator
- Mbedzi, Edson
- Subject
- Financial services industry -- Information technology Banks and banking -- Information technology Small business -- South Africa -- Eastern Cape
- Date Issued
- 2019
- Date
- 2019
- Type
- Thesis
- Type
- Doctoral
- Type
- PhD (Economics)
- Identifier
- http://hdl.handle.net/10353/12621
- Identifier
- vital:39293
- Description
- Small, Micro and Medium Enterprises (SMMEs) play a major role in contributing to the development of most economies globally. However, such small firms often lack external financing due to their information opacity. Besides, the small firm size nature of most SMMEs impairs their ability to access finance as motivated by the market power theory. In order to address the information asymmetry problem associated with such small firms, financial institutions use different forms of lending technologies as the basis upon which lending decisions are made, that is, whether to loan or not and if the decision to lend is taken, how the intrinsic credit risks are taken into consideration. In the evaluation of the credit worthiness of small businesses, the decision to lend or not depends on soft or hard information acquired through use of a particular lending technology. Many studies in the literature cite access to credit as the main hindrance to SMMEs success. Lending technologies being the conduits transmitting that credit access, the study hypothesises that more emphasis be placed on the relationship between lending technologies and the success of small firms. Success in this case is measured in two ways; the level of SMME credit rationing that small firms endure and the resultant growth of small businesses if they access funding. However, the use of lending technologies as a measure of SMME finance access is missing in academic literature. Specifically, literature on SMMEs in South Africa only narrate the structure of SMMEs and factors affecting SMMEs funding and growth without providing a link on how these eventually influence lending technologies used that determine the lending process. This study therefore traces types of lending technologies used, factors influencing their usage and the subsequent level of credit rationing and growth of small firms. The study uses only formal and registered small firms that are members of the Border-Kei Chamber of Business and Nelson Mandela Bay Business Chamber and listed in their data bases. The study adopts a mixed methods methodology in a two stage analysis approach. In the first stage, the study identifies types of lending technologies used by funding institutions in the study area and factors lenders take into account in order to extend funding to small vi businesses. Based on interview data gathered from eight financial institutions, the types of lending technologies and factors that influence lending decisions are identified using thematic analysis method. In the second stage, the study then interrogates how lending technologies shape the credit rationing and growth of SMMEs within the Eastern Cape Province in South Africa. A sample of three hundred and twenty one (321) randomly selected SMMEs from Buffalo City and Nelson Mandela Bay metropolitans in the Eastern Cape Province is used. Data collected from SMMEs using questionnaires has been analysed to reveal the extent of credit rationing and firm growth variations among SMMEs based on the main lender and firm characteristics identified in the first stage. Credit rationing is both dichotomous, by the firm being either rationed or not, and categorical, by forms of credit rationing experienced by firms. The analysis therefore uses a combination of binary and multinomial logistic regression to evaluate effects of determinants of lending technologies on credit rationing of firms. Financial efficiency scores of firms are used as the proxy for growth of firms. The financial efficiency score is preferred because in its derivation several firm activities are incorporated as opposed to using only one growth indicator such as sales volume. The efficiency scores are generated using Data Enveloping Analysis based on selected main activity inputs and outputs of sampled firms. Since efficiency scores of a firm representing growth are a scale dependent variable, a two-way factorial analysis is used to determine the effect of lender and firm characteristics on the firm’s growth. Both the main and interaction effects of the lender and firm characteristics are captured in the analysis of both credit rationing and growth of firms. Results show that four classes of financial institutions financed formal and registered SMMEs. These are commercial banks, government-owned development financial institutions, private-owned development financial institutions and microfinance institutions. In addition, four types of lending technologies have been used to finance SMMEs in which financial institutions consider people, firm and financial information vii factors as pillars of financing decisions. Findings indicate extensive discriminatory credit rationing among SMMEs in South Africa and that growth paths followed by firms vary significantly as a result of these characteristics. The study therefore recommends the implementation of a financing framework model that allocates funds to different company structures based on credit rationing risk profiles of enterprises so as to minimize the extent of inequality exhibited in the South African population structures which have historical differences on the basis of enterprise size, ownership structure and race. The study further recommends matching of types of lending technologies with types of lenders in order to minimize overall industry credit rationing level in the SMME sector as a supplementary funding model. However, this may need further research to evaluate its application. This is important given that financial institutions use different lending technologies at the same time and further, not all financing institutions may use all forms of lending technologies. For example, microfinance institutions may not have the capacity to use venture capital lending technologies
- Format
- 256 leaves
- Format
- Publisher
- University of Fort Hare
- Publisher
- Faculty of Management and Commerce
- Language
- English
- Rights
- University of Fort Hare
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UFH Department of Economics
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | MBEDZI E 201615007 PHD ECO.pdf | 3 MB | Adobe Acrobat PDF | View Details Download |