Faculty of Accounting and Informatics

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Examination of employee factors influencing organisational productivity: Perspective of a public entity
(Virtus Interpress, 2015) Green, Paul; Adekanmbi, Oluwole
The influence of employees’ challenges on productivity at a provincial department in KwaZulu-Natal has been notably affecting the overall provision of houses and sanitation (service delivery). According to the Annual Performance Plan 2013/14 – 2015/16, the improvement of efficiency and quality of human settlements’ services is one of the strategic goals which focuses on the overall organisational productivity; however, it fails to consider employees’ day-to-day challenges. Thus, the primary purpose of this paper is to investigate challenges at an operational level and determine the impact they have on productivity. Using a quantitative approach, a questionnaire was distributed to a convenience sample of 180 employees within the department. Applying factor analysis, the findings indicate Leadership as having the highest impact while Work-Life Balance displayed the least impact on Organisational Productivity. The results of this study are beneficial to other local, provincial and national public entities.
Predicting the microbial safety of irrigation water and fresh produce : a collaborative approach
(2013-06-11) Ijabadeniyi, Oluwatosin Ademola; Olugbara, Oludayo O.
Outbreak of food borne illnesses as a result of consumption of fresh vegetables and fruits is occurring regularly. In USA for example, it has become business as usual to hear and read about fresh produce recalls. Although, the increase has been attributed to many factors it is however more important to find solution to the problem. An effective solution will be a proactive approach such as prediction and forecasting which are not new in the field of meteorology. For many years now, meteorologists have been predicting the weather. It is indeed high time that food scientists in collaboration with other professionals found out dependable and realistic methods to predict the presence of pathogens in irrigation water and fresh produce. In this review, several prediction tools such as factor analysis, artificial neural network, support vector machine, logistic regression analysis, partial least square and ‘nanosensing’ were discussed. The problem of produce safety may in fact be solved when food scientist collaborate with I.T professionals, biotechnologists and others.