Browsing by Author "Muhwezi, Lawrence"

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    A Regression Model to Enhance the Profitability of Local Construction Contractors in Uganda
    (Journal of Construction in Developing Countries, 2021-08-23) Buhamizo, Isaac; Muhwezi, Lawrence; Sengonzi, Ruth
    Doubtlessly, the primary goal of every construction company is to maximise profitability. Without this, construction companies cannot survive. Incidentally, Ugandan local construction contractors (LCCs) continue to collapse in a short period, despite enormous public and private investments in the construction sector. This study investigates the profitability of LCCs in Uganda. An investigation was conducted to develop a regression model that would enable LCCs to enhance their profitability and minimise business failure. A questionnaire survey was conducted to collect primary data from 47 local construction companies registered with the Uganda National Association of Building and Civil Engineering Contractors (UNABCEC) and secondary data were collected from audited books of accounts covering from year 2016 to 2018. Thirty-five valid responses were received, representing a response rate of 74%. Data were coded into SPSS version 25, analysed and displayed using the relative importance index (RII), statistical correlation and regression analysis. The findings indicated that the profitability of LCCs was unsatisfactory when compared to the profitability ratios recommended for the construction industry and those of contractors in other countries. The results also indicate that the profitability of LCCs is significantly affected by the timeliness of payments, cost of f inance, competitive bidding environment, project delays, price fluctuations and corruption tendencies, in that order. The findings of this study will benefit construction industry players by providing awareness about the factors affecting the profitability of LCCs. A regression model to enhance profitability was developed using regression analysis. This will help LCCs enhance their profitability by developing mitigation strategies that prevent low profitability; consequently, business failure will be minimised.
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    Investigating the cost of mechanized unpaved road maintenance operations in Uganda
    (Elsevier Ltd., 2024) Obeti, Andrew Moses; Byaruhanga, Chris Bic; Muhwezi, Lawrence; Kakitahi, John Muhumuza
    Force Account Mechanism (FAM) is the predominant road maintenance system in Uganda’s local government setup and a similar, though slightly different approach, is used in some large private sector agriculture planta tions. With the Uganda Road Fund (URF) 2021/2022 annual report and previous research citing challenges in cost management and efficiency of the FAM method of road maintenance, it becomes paramount to analyse how FAM is implemented in government-led operations, in comparison to similar private sector approaches, while proposing possible solutions to these challenges. This research offered to analyse unpaved road maintenance cost drivers alongside providing a cost model solution to improve on cost prediction of the FAM system. Gulu District Local Government (DLG) and Kakira Sugar Limited (KSL) were selected as case study areas. Two descriptive research methods were used: observations and case study approach. The selected case study areas were accessible and reachable in terms of data. Control parameters affecting unpaved mechanized road maintenance were identified as machine repair costs, tool costs, labour costs, material costs, fuel costs and machine fuel costs. Unpaved mechanized road maintenance costs at KSL and Gulu DLG were computed as a cost/km ratio of 26,442,032Ugx/km (6,958.4USD/km) and 32,674,895Ugx/km (8,598.65USD/km) respectively. The Uganda National Roads Authority (UNRA) unpaved road maintenance costs were calculated as an average of 34,987,122.9Ugx/km (9,165USD/km) while the World Bank ROCKS database provided a comparable figure of 7,971USD/km (30,553,440.83Ugx/km). A USD to Ugx conversion rate of 3,800 was used. Two linear regression cost models with a 0.679 and 0.687 R 2 value were computed, and these can be used in preliminary road maintenance cost prediction. The study recommends the need for an effective, digital road maintenance cost database system for mechanized unpaved road maintenance works, cost driver analytics and management, alongside improvement in aspects of maintenance processes at both the DLG and KSL. Further research can be conducted on equipment condition level prediction and analytics in the private sector and at the DLG.
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    Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
    (East African Journal of Interdisciplinary Studies, 2024-08-25) Okiza,Humphrey; Muhwezi, Lawrence; Omwonylee, Okello Joseph; Awichi, Richard Opaka; Nuwagaba, Savannah
    The purpose of the study was to investigate the variables affecting traffic flow in Kampala Central Business District (CBD), employing a quantitative approach. The rapid urbanization has led to a huge increase in the number of vehicles, resulting in traffic congestions, delays, and financial losses especially in the Kampala CBD area. Data on traffic density, speeds, and driver behaviors were collected for a period of 20 days from five selected road sections leading into and out of the city which included traffic on Entebbe Road, Jinja road, Sir Apollo Kaggwa Road, Yusuf Lule and Wandegeya roads using the moving observer method. Regression analysis was done to identify the relationships between the variables, leading to the development of a predictive model for traffic flow. The study found out that the flow tends to increase as the day progresses and as well flow rate increases with increase in density. As the week progressed, the flow rate decreased as number of people coming to town on weekends is low since there is no work. A mathematical model was generated which could be used to predict the traffic intensity on the road at a given day and time. The model shows that changing from weekdays to weekend, the flow decreases by about 29%, and as density increases by 1%, the flow also increases by 1.5% over time. The study recommends prioritizing public transportation improvement, establishment of out of city parking yards, utilizing the other various means of transport other than road and promoting non-motorized modes of transportation in order to reduce traffic density on the road and subsequently manage congestion.