Abstract:
Over 50% of the world's economies face high enterprise failure with African countries being on the top of the list. Specifically, South Africa is among nations with the highest rate of enterprise failure, estimated at 70%, despite sustained investments by the government to support the growth of enterprises. It has been argued that the country has no entrepreneurship models to support enterprise development, as a result, policies for entrepreneurial-supporting initiatives are not driven by correct or informed mechanisms that can adequately transform enterprises. This study investigated the indicators and critical exogenous and endogenous components associated with successful enterprises, borrowing some aspects from the Economic base theory. A mixedmethod was followed and 280 participants were drawn from 16 villages in four local municipalities of Vhembe District using snowball, purposive and cluster sampling techniques. A desktop review, semi-structured and structured questionnaires were tools used for the data collection. An analysis of the qualitative data was achieved through a thematic technique using MAX QDA and Atlas-ti v8. Microsoft Excel functions; descriptive statistics through STATA, while, Crosstabulation, Principal Component Analysis (PCA) and Multilayer Perceptron (MLP) model through SPSS v26, as well as Multiple Linear Regression (MLR) model using R v3.0, were exploited with the quantitative data. The results indicate that - profit margin, trends of new products, enterprise expansion and enterprise survival - are common success indicators in the area. The PCA fitted on exogenous data structure (n=280) computed 6 principal enterprise challenges from 45 items identified qualitatively. These are - Access to finance (AF: 14.887%), Access to market (AM: 10.297%), Physical capacity (PC: 8.858), Operational cost (OC: 6.052%), Socio-cultural issues (SC: 5.628%) and Competition (Co 4.460%). The MLP based on 83 sample structure of success enterprises, however, revealed that Co presents the most challenge followed by AM, OC, SI, AF and PC which was the least challenging. Similarly, PCA post-endogenous qualitative study computed 5 principal components from 49 initial items. Bridging networks (BN) constituted 38.044% of the variance followed by Self-belief (SB:15.802), Risk Awareness (RA:6.144), Resilience (R: 4.532), and Nonconformist (NC:4.271). The MLR employed to investigate the linear relationship of the parameters revealed that BN (𝛽1 = 7.57) is most influential and statistically significant (p=0.01). Except for SI which is negatively related to enterprise success, R, RA and NC parameters demonstrate positive influences to enterprise success. A model for successful enterprises centred on entrepreneurs’ exogenous and endogenous attributes is proposed as the main contribution of the study towards enterprises’ success in the areas of the research. The key recommendation in this study is that support to enterprises should be informed by the area-specific indicators outlined in the study.
Keywords: African model, enterprise development, endogenous attributes, exogenous factors, rural areas
