| dc.description.abstract | Variable costs contrary to fixed costs increase with machine age. Decisions made by farm power to or not to replace the farm machinery are based on available variable cost records. This study aimed at developing a mathematical model for predicting variable costs of a farm tractor. Specifically, the study identified and established numerical values of cost parameters pertinent to variable costs of tractors in Juba, South Sudan and modelled the data obtained.
The study was carried out in Jubek State of South Sudan using questionnaires for collecting variable costs data of tractor models available. These were MF375, Belarus800, JD5503, MF385, JD5510, JD5425, Mahindra8000, Mahindra705DI, Sonalika DI-90, and Sonalika DI-75. Data collected included age of the tractor, cost of fuel, cost of oil, cost of filters replacement, labor cost and cost of workmanship.
The correlation regression method of statistic was used to analyze the data collected and to represent the correlation relationship between the (accumulated variable cost as percentage of purchase price) and the (accumulated operating hours). The relationship between the accumulated hours of use and the accumulated variable cost as percentage of purchase price for the ten models of tractor studied was represented by carrying out the correlation regression analysis on the data. Five mathematical regression models together with their coefficients of correlation were all evaluated and It was observed that among the five mathematical models evaluated, the polynomial model showed the highest coefficient of correlation (R2) followed by the power model. However, the power model y = axb, where y is the accumulated variable cost as the percentage of purchase price, x is the accumulated hours of use, a and b are the constants was the best fit for the ten tractor models studied and accounted for 99% of the observed variations in accumulated variable costs as percentage of list price for each of the ten tractor models studied.
The results obtained indicated that the cost of repair and maintenance for all tractor models studied showed the highest cost percentage of the total percentage followed by the fuel cost, cost of labor, then oil cost respectively, for example, for belarus800, the repair and maintenance cost was $538 which represent 39.9% of the total cost, followed by the fuel cost which was $446 which is 33%, then labor (operator) cost which was $291 which is 21.6% and finally oil cost was $75 which represent 5.6% of the total cost.
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This study suggested that the derived mathematical models could be used to predict the variable cost of tractor studied operating in the area of study, the study is also important in guiding farmers and other institutions on tractor model selection and/ or to make tractors replacement decisions.
Keywords: Modeling, South Sudan, Tractors, Variable Cost | en_US |
