1,720,980 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Determinants of viability in junior mining companies in the Witbank region of South Africa
Get PDFAn exploratory survey was undertaken in order to explore the underlying causes of bankruptcy in junior mining companies operating in the Witbank region of Mpumalanga Province based on data gathered from 120 highly experienced employees of junior mining companies operating at Witbank. Perception on barriers to productivity in junior mines was measured based on a scale introduced by Henisz, Dorobantu and Nartey (2014). Data was gathered on 24 socioeconomic variables. Data was analysed by performing logit analysis. The key finding of study was that 74.17% of respondents believed that their mines were profitable and productive. Productivity of mines was found to be undermined high cost of transport [OR = 4.51; P = 0.003; 95% CI = (2.26, 7.58)], low demand for mine products [OR = 2.65; P = 0.009; 95% CI = (1.86, 6.14)] and inability to improve the public images of junior mining companies [OR = 2.53; P = 0.015; 95% CI = (1.80, 5.76)]
Analysis of Factors That Affect the Long-Term Survival of Small Businesses in Pretoria, South Africa
No full textPredictors of satisfactory employee performance in the South African Department of Health
Get PDFA study was conducted at the South African Department of Health (DOH) in order to assess the perception held by employees of the DOH at national and provincial levels about the suitability of the Performance Management System (PMS) tool that was being used in the DOH for the assessment and evaluation of the performance of employees working for the DOH at national and provincial level based on their Key Performance Areas (KPAs) and Key Performance Indicators (KPIs). The study was based on a stratified random sample of size n=120 employees of the DOH working at national and provincial levels. The study was quantitative, and used methods of data analyses such as frequency tables, cross-tab analysis and binary logistic regression analysis. The degree of productivity of employees at work was measured by using a composite index defined by Le Brasseur, Zannibbi &amp;amp; Zinger (2013). Results obtained from the study showed that about 74% of employees held a favorable view of the PMS tool that was used for the assessment and evaluation of employees. The percentage of respondents who viewed the PMS tool as unhelpful was about 26%. The study showed that the view held by employees working in the DOH about the relevance and objectivity of the PMS tool used for the assessment of employee performance in the DOH was significantly and adversely affected by the perception that the PMS policy was incapable of promoting the effectiveness of the DOH as an organization, the perception that the PMS policy was incapable of rewarding deserving employees, and the perception that there were not enough training opportunities in the PMS, in a decreasing order of strength.</jats:p
A survival analysis of South African children under the age of five years
No full textThe South African Demographic Health Survey data set (SADHS) of 2003 contains massive individual-level information on South African children under the age of five years selected from a random sample of 7756 households. The data set contains data on socio-economic, demographic, health-related and sanitary variables gathered by using multistage cluster sampling. The objective of the study was to identify key predictors of mortality amongst children under the age of five years. Logistic regression analysis and Cox regression were used for data analysis.Under-five mortality was significantly influenced by three predictor variables (breastfeeding, marital status, and ownership of a flush toilet). The hazard ratio of the variable ‘breastfeeding’ was 3.09 with P = 0.000 and 95% confidence interval (CI) of (1.899, 5.033). The hazard ratio of the variable ‘toilet’ was 2.35 with P = 0.016 and 95% confidence interval of (1.172, 4.707). The hazard ratio of the variable ‘marital status’ was 1.74 with P = 0.035 and 95% confidence interval of (1.041, 2.912). Adjustment was factored in for the mother’s level of education and wealth index.OpsommingDie Suid-Afrikaanse Demografiese en Gesondheidsopname-datastel (The South African Demographic Health Survey data set [SADHS]) van 2003 bevat ‘n enorme hoeveelheid individuele-vlak inligting rakende kinders onder vyf jaar uit 7756 huishoudings in Suid-Afrika. Die datastel bevat inligting rakende sosio-ekonomiese, demografiese, en gesondheidsverwante veranderlikes, en sanitêre-veranderlikes, is versamel deur gebruik te maak van multistadiatrosanalise. Die oogmerk met die studie was die identifisering van sleutelpredikatore ten opsigte van sterftes van kinders onder die ouderdom van vyf jaar. Logistieke-opnameregressie analise en Cox-regressie is gebruik om die data te analiseer. Onder vyf-sterftes word beduidend beïnvloed deur drie predikatorveranderlikes (duurte van borsvoeding, huwelikstatus en toegang tot ‘n spoeltoilet). Die risikoverhouding van die borsvoeding-veranderlike was 3.09 met P = 0.000 en ‘n 95% sekerheidsinterval van (1.899, 5.033). Die risikoverhouding van die toiletveranderlike was 2.35 met P = 0.006 en 95% sekerheidsinterval van (1.172, 4.707). Die risikoverhouding van die huwelikstatus-veranderlike was 1.74 met P = 0.035 en 95% sekerheidsinterval van (1.041, 2.912). Aanpassings is gemaak vir die opvoedingsvlak van die moeder asook die welgesteldheidsindeks.</jats:p
Analysis of Predictors of Sustained Growth and Incubation of SMMEs in Gauteng Province, South Africa
No full textA socioeconomic analysis of Ethiopian migrant entrepreneurs in South Africa
Get PDFThe objective of study was to assess and evaluate factors that affect entrepreneurial activities carried out by formal and informal migrant entrepreneurs from Ethiopia who conduct business operations in the nine provinces of South Africa. The study was descriptive and exploratory in nature. The design of the study was descriptive and cross-sectional. Data were collected from a stratified random sample of 3,045 migrant entrepreneurs from Ethiopia who conduct business in the nine provinces of South Africa. Stratified random sampling was used for the selection of eligible entrepreneurs. The study found that about 76% of businesses operated by migrant entrepreneurs from Ethiopia were profitable, whereas the remaining 24% of businesses were not profitable. About 32% of entrepreneurs were attracted to South Africa due to better infrastructural facilities. About 25% of entrepreneurs were attracted to South Africa due to better socioeconomic conditions. About 78% of migrant entrepreneurs had conducted business in South Africa for five years or more at the time of data collection. About 34% of businesses paid tax to the South African Revenue Service (SARS) on a regular basis. About 38% of businesses employed at least one South African in their businesses. About 85% of entrepreneurs stated that they had good working relationships with members of the various local communities in South Africa
A survival analysis of South African children under the age of five years
Get PDFThe South African Demographic Health Survey data set (SADHS) of 2003 contains massive individual-level information on South African children under the age of five years selected from a random sample of 7756 households. The data set contains data on socio-economic, demographic, health-related and sanitary variables gathered by using multistage cluster sampling. The objective of the study was to identify key predictors of mortality amongst children under the age of five years. Logistic regression analysis and Cox regression were used for data analysis.
Under-five mortality was significantly influenced by three predictor variables (breastfeeding, marital status, and ownership of a flush toilet). The hazard ratio of the variable ‘breastfeeding’ was 3.09 with P = 0.000 and 95% confidence interval (CI) of (1.899, 5.033). The hazard ratio of the variable ‘toilet’ was 2.35 with P = 0.016 and 95% confidence interval of (1.172, 4.707). The hazard ratio of the variable ‘marital status’ was 1.74 with P = 0.035 and 95% confidence interval of (1.041, 2.912). Adjustment was factored in for the mother’s level of education and wealth index.
Opsomming
Die Suid-Afrikaanse Demografiese en Gesondheidsopname-datastel (The South African Demographic Health Survey data set [SADHS]) van 2003 bevat ‘n enorme hoeveelheid individuele-vlak inligting rakende kinders onder vyf jaar uit 7756 huishoudings in Suid-Afrika. Die datastel bevat inligting rakende sosio-ekonomiese, demografiese, en gesondheidsverwante veranderlikes, en sanitêre-veranderlikes, is versamel deur gebruik te maak van multistadiatrosanalise. Die oogmerk met die studie was die identifisering van sleutelpredikatore ten opsigte van sterftes van kinders onder die ouderdom van vyf jaar. Logistieke-opnameregressie analise en Cox-regressie is gebruik om die data te analiseer. Onder vyf-sterftes word beduidend beïnvloed deur drie predikatorveranderlikes (duurte van borsvoeding, huwelikstatus en toegang tot ‘n spoeltoilet). Die risikoverhouding van die borsvoeding-veranderlike was 3.09 met P = 0.000 en ‘n 95% sekerheidsinterval van (1.899, 5.033). Die risikoverhouding van die toiletveranderlike was 2.35 met P = 0.006 en 95% sekerheidsinterval van (1.172, 4.707). Die risikoverhouding van die huwelikstatus-veranderlike was 1.74 met P = 0.035 en 95% sekerheidsinterval van (1.041, 2.912). Aanpassings is gemaak vir die opvoedingsvlak van die moeder asook die welgesteldheidsindeks
- …
