Search

The newly elected South African President, Cyril Ramaphosa, set an ambitious objective to attract US$100 billion Foreign Direct Investment (FDI) for South Africa’s sustainable socio-economic development. This paper determines differential factors that influence the flow of FDI into South Africa. The objective of this study is to assess factors that affect the flow of FDI into South Africa. Data analysis is performed from the 217 foreign exchange practitioners, registered and working at the Johannesburg Stock Exchange in South Africa by performing both ordered logit and Bayesian analyses. Our results showed that the following are the most important FDI determinants factors: (1) the provision of economic incentives; (2) trade regulation and policies; and (3) high expectations of economic return on investments.

The purpose of the study was to identify and quantify factors that are responsible for the high rate of failure in newly established SMMEs in the Vaal Triangle region of Gauteng Province in South Africa. The study was based on a stratified random sample of size N= 303. Stratified random sampling was used for collecting data by using a structured, pre-tested and validated questionnaire of study. Statistical analyses were performed by using descriptive methods such as frequency tables, cross-tab analyses and factor analysis. The study found that 21% of businesses were not viable financially. The study also showed that viability in small and medium-sized enterprises in the Vaal Triangle area was adversely influenced by difficulty in securing loans, lack of training opportunities, and shortage of entrepreneurial skills. The study showed that the growth of newly established businesses was hampered due to difficulty in securing credit on favourable terms from micro lending institutions and the lack of training opportunities on entrepreneurial activities.

This paper is a result of a 6-year long follow-up study that was conducted in Pretoria, South Africa between 2004 and 2009 in order to assess the impact of underutilization of modern family planning methods on adverse outcomes of pregnancy in women of the childbearing age of 15–49 years. The Cox Proportional Hazards Model was used for estimating hazard ratios. Multilevel analysis was used for estimating variability in the utilization of modern family planning methods at service delivery wards and health service facilities. The study showed that women who experienced adverse outcomes of pregnancy were characterized by poor utilization of reproductive health and modern family planning services. The percentage of women who regularly used modern family planning methods such as condoms, pills, injections, intra-uterine devices and sterilization was 41.74%. The average ages of women at first sex and pregnancy were 18.72 and 19.36 years, respectively. Adverse outcomes of pregnancy occurred in 12.19% of women. Based on odds ratios (ORs) estimated from binary logistic regression analysis, utilization of contraceptives was significantly influenced by the degree of access to family planning services, level of support from sexual partner, and young age at first pregnancy. The occurrence of adverse outcomes of pregnancy was significantly influenced by easy access to family planning services, unwanted pregnancy, and young age at first pregnancy. There was a significant difference among the 20 health service delivery wards and 11 health service facilities in which reproductive health services were delivered to women with regards to the quality of service delivery.

This study attempts to identify and quantify factors that affect service delivery by local government counsellors in the Gauteng and North-West provinces. The study is based on a stratified random sample of size n=300 respondents. Both quantitative and qualitative research methods were used for data collection and analysis in the study. The study showed that overall satisfaction with the quality of services provided at the two sites of study (Tshwane District and Madibeng municipalities) was influenced by similar factors based on results obtained from data analysis. This shows that there was no significant difference between the residents of Tshwane District and Madibeng municipalities with regards to expectations from service providers and elected officials who are responsible for the delivery of municipal services. Significant results obtained from Pearson's chi-square tests of associations (P=0.000) showed that young men protesting about the poor quality of services in urban and semi-urban areas were characterized by low levels of household income (below 10,000 Rand per month), inability to find employment opportunities, low level of formal education (below matric level), young age (below 30 years of age), and poor level of artisan skills. Results obtained from binary logistic regression analysis showed that dissatisfaction with the quality of services provided by elected counsellors was significantly influenced by four factors. These four factors were: (1) low household income [OR = 9.03; P= 0.000; 95% CI = (3.55, 22.36)]; (2) unemployment [OR = 7.11; P= 0.000; 95% CI = (2.34, 19.87)]; (3) poor education [OR = 5.47; P= 0.001; 95% CI = (2.08, 11.39)]; and (4) young age [OR = 3.01; P= 0.003; 95% CI = (1.86, 8.63)], in a decreasing order of strength. The study showed that although sufficient resources were provided by the local municipalities for service delivery, the resources allocated for service delivery were not effectively utilized mostly due to lack of skills, poor spending capacity, lack of transparency and accountability by service providers to the various communities. A recommendation has been made to the local municipalities in Tshwane District and Madibeng to establish comprehensive monitoring and evaluation mechanisms in order to ensure the delivery of adequate services.