Quality as a Measure of Quality Management Performance in South African Companies

Abstract : The current disruptive business environment forces companies to constantly search for improved ways of meeting customer requirements. South African companies are not excluded from daily business challenges. This research assesses the adoption of cost of quality practice as the measure of quality management performance. The study uses the snowball sampling approach to identify the target sample members. It collected information from 45 companies around the Johannesburg area. The convergent validity and discriminant validity were used as the measure of study construct validity. The study identifies preventive cost and appraisal cost as two costs of quality categories which receive high attention from South African companies. The failure cost was identified to be in third place. The opportunity cost was identified as the ignored cost of quality (CoQ) category. Hence, it was recommended that the companies start to pay attention to their opportunity cost and it was also recommended that further research should focus on identifying the challenges experienced by companies in the implementation of cost of quality

The Incidence and Risk Factor Analysis of Drug Induced Liver Injury (Dili) in a Surabaya Hospital

The research has been conducted on the incident and analysis of risk factors drug liver injury (DILI) in a Surabaya Hospital. The aim of this study was to determine the incident of DILI, know which drugs cause DILI, and see the association of risk factors to DILI. The research method was descriptive and analytical observational (prospective cohort). Danan-Benichou scale is a tool used to ascertain drugs that cause DILI. Based on data collected for 3 months, the population was 1202 patients. Samples fulfilling the inclusion and exclusion criteria were 310 patients, the risk drug group of DILI were 285 patients (11 DILI, 274 Non-DILI), and the non-risk drug group 25 patients (11 DILI, 14 Non-DILI). The incident of DILI was 3.55%. Drugs that cause DILI are ranitidine (4 cases), omeprazole (1 case), rifampicin (2 cases), meropenem (1 case), ciprofloxacin (1 case), methotrexate (1 case), and dexamethasone (1 case). Characteristic of patients with DILI (11 patients) are average age of 59.27 ± 15.54 years (23-73 years), belonging to high risk group (54.55%), male gender (81,82%), have moderate comorbid disease (54.55%), and are not comsumsing alcohol (100%). This research use logistic regression analysis through SPSS 17.0 program to see the relation of risk factor to DILI incident. The p results were obtained from sex (0,156), age (0,534), and comorbid isease (0,213)> α (0,05) which means gender, age, and comorbid disease do not significantly affect the incident of DILI

A factorial analysis of safety performance measures: a study among construction workers in Gauteng, South Africa

Abstract: The health and safety (H&S) of construction workers has been a subject of much deliberation for decades. However, there is scant literature focusing on aspects of workers’ safety performance (SP) relating to their unhealthy and unsafe eating behavior. The paper presents findings on an exploratory factor analysis of H&S performance measures. A 10- item questionnaire which was developed after an extensive literature review was used to collect empirical data on SP of construction workers in the Gauteng Province of South Africa. Results showed that SP could be reasonably measured by two constructs. The two constructs were clearly defined as trailing and prevailing. The emerged trailing measures were named lagging indicators while the prevailing ones were designated as leading indicators. The results lend support to extant literature which advocates the use of both leading and lagging safety performance indicators for effectively assessing construction workers’ safety performance. The study provides evidence which could be beneficial in psychometric evaluation of construction workers’ safety performance and behaviours on construction sites

Expandable Factor Analysis

Bayesian sparse factor models have proven useful for characterizing dependence in multivariate data, but scaling computation to large numbers of samples and dimensions is problematic. We propose expandable factor analysis for scalable inference in factor models when the number of factors is unknown. The method relies on a continuous shrinkage prior for efficient maximum a posteriori estimation of a low-rank and sparse loadings matrix. The structure of the prior leads to an estimation algorithm that accommodates uncertainty in the number of factors. We propose an information criterion to select the hyperparameters of the prior. Expandable factor analysis has better false discovery rates and true positive rates than its competitors across diverse simulations. We apply the proposed approach to a gene expression study of aging in mice, illustrating superior results relative to four competing methods.Comment: 28 pages, 4 figure

Application of Factor Analysis to Public Sector Integrity in Indonesia

The main purpose of this study is to analyze interrelationships among variables used on the survey of public sector integrity by Indonesiaâs Corruption Eradication Commission (Komisi Pemberantasan Korupsi, KPK). The nine variables include corruption experiences, corruption perceptions, working environments, administration systems, the behavior of individuals, corruption prevention efforts, integrity experiences, integrity potencies, and integrity total. Using factor analysis, the approach is to explain these variables in terms of their common underlying dimensions, well-known as factors. Technically, factor analysis involves condensing the information contained in a number of original variables into a smaller set of new composite factors with a minimum loss of information. The results show that based on eigen values the first factor alone accounts for 70.7% of the common variance. The second factor alone accounts for 13,4%. The common variance of the nine variables explained by two factors is 84.1%. Using the varimax rotation and based on values of factor loadings the first factor makes high contribution to the variance of corruption experiences, corruption perceptions, working environments, the behavior of individuals, integrity experiences, and integrity total variables. The second factor makes high contribution to the variance of corruption prevention efforts and integrity potencies variables. Similar results, also, are obtained by quartimax rotation and equamax rotatio

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods