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dc.contributor.authorWainaina, Gituro
dc.contributor.authorNjoroge, Brian M.
dc.date.accessioned2013-09-11T13:24:06Z
dc.date.available2013-09-11T13:24:06Z
dc.date.issued2013-08
dc.identifier.citationDBA Africa Management Review, August 2013, Vol 3 No 2. Pp. 24-39en
dc.identifier.urihttp://journals.uonbi.ac.ke/damr/article/view/1162
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/56364
dc.descriptionFull Text Articleen
dc.description.abstractForecasts are crucial for practically all economic and business decisions. The focus of this research paper is in the area of forecasting. The research approach adopted is a case study of the Nutrition and HIV Program (NHP), which is a donor funded public health project. The general objective of this paper was to forecast the demand for patient needs in a donor funded project. Specifically, this paper sought to establish a suitable forecasting method that can accurately predict demand for nutrition commodities. In order to establish a more suitable forecasting method, Univariate Box – Jenkins (UBJ) methodology was used and two models were tested and Auto Regressive Integrated Moving Average (ARIMA (0, 1, 2)) model provided a better fit and was chosen as the model of choice for a short run forecast horizon. The main conclusion drawn from this paper is that, UBJ-ARIMA models are useful as benchmarks for forecasting and therefore they should be viewed as complements to a reliable forecasting process. This paper recommends that public health projects need to consider adopting business forecasting methods that will provide a better glimpse of the future based on historical events rather than relying on disease morbidity data trends.en
dc.description.sponsorshipUniversity of Nairobi, School of Businessen
dc.language.isoenen
dc.publisherDBA Africa Management Reviewen
dc.subjectAuto-correlation functionen
dc.subjectPartial auto-correlation functionen
dc.subjectResidual auto-correlations short run forecasten
dc.subjectPublic health projecten
dc.subjectUn-differenceden
dc.subjectStationarityen
dc.subjectARIMAen
dc.subjectUBJen
dc.titleForecasting Patient Needs in a Donor Funded Health Care Project in Kenyaen
dc.typeArticleen
local.publisherSchool of Business, University of Nairobien


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