Assessment of quality of government funded construction works in local governments in Uganda : a case study of Buvuma district local government

Abstract

The study sought to assess the causes of the rampant non-compliance to quality standards of construction works in Local Governments (LGs) of Uganda. According to the Auditor General’s report of 2021, 80% of works in LGs under Uganda Intergovernmental Fiscal Transfers Program (UgIFT) constructions had defects such as honey combing, delayed completion and observed poor mixes. The study employed a cross-sectional research design that included the use of both quantitative and qualitative data collection approaches. Data were collected using stratified sampling and analyzed using Statistical Package for Social Sciences (SPSS) software version 16. Analysis of the findings based on both regression and Pearson correlation coefficient showed that, generally, the respondents agreed that funding had an impact on quality with an average mean value of 3.73 and a correlation coefficient of 0.520 indicating a strong positive relationship between funding factors and the quality of Government Funded Construction Projects (GFCPs) in Buvuma District Local Government (BDLG). The regression analysis indicated that the adjusted R-Square value of 0.30 was obtained implying that 30% of the variance in the quality of GFCPs is influenced by funding factors. The respondents were generally not sure whether personnel factors affected quality GFCPs with an average mean value of 2.887 and a correlation coefficient of 0.483 indicating a moderate positive relationship between personnel factors and quality of GFCPs in BDLG. However, the regression analysis indicated that the adjusted R-Square value of 0.93 was obtained implying that 93% of the variance in the quality of GFCPs is influenced by personnel factors. Procurement factors affecting quality of GFCPs had an average mean = 2.60 indicating that the respondents were generally not sure whether procurement factors affected quality of GFCPs with a correlation coefficient of 0.462 indicating a moderate relationship between procurement factors and quality of GFCPs. The regression analysis indicated that the adjusted R-Square value of 0.866 was obtained implying that 86.6% of the variance in the quality of GFCPs is influenced by the procurement factors. In conclusion, the impact of funding, personnel factors and procurement factors have a significant impact on quality of GFCPs in LGs. Therefore, the study recommended that BDLG and DLGs should address the issues on Funding, personnel and improving the procurement systems for better quality of GFCPs in LGs.