Testing Regression Models To Estimate Costs Of Road Construction Projects

At the outset of the project, when the scope definitions are in the early stages of development, littlerninformation was available, yet there is often a need for some assessment of the potential cost. Thernowner needs to have a rough or approximate value for the project’s cost for purposes of determiningrnthe economic desirability of proceeding with design and construction. Special quick techniques arernusually employed, utilizing minimal available information at this point to prepare a conceptualrnestimate. Little effort is expended to prepare this type of estimate, which often utilizes only a singlernproject parameter, such as square meter of floor area, or span length of a bridge. Using available,rnhistorical cost information and applying like parameters, a quick and simple estimate can bernprepared.rnThe objective of this study is to develop conceptual and preliminary cost estimating models forrnasphalt road construction projects using historic data using statistical tools such as spss, and Rsoftware’s,rnbased on sixteen sets of data collected in the Federal Road Projects. As the cost estimatesrnare required at early stages of a project, considerations were given to the fact that the input data forrnANNOVA F-test regression analysis to develop the cost models could be easily extracted fromrnsketches or scope definition of the project. As a result in this study Six regression cost estimatingrnmodels are developed to estimate the total cost of road construction project; among these models tworninclude bid quantities, and four include project size ( i.e. road length and road width) as inputrnvariables. The coefficient of determination (r2) for the developed models is ranging from 0.65 to 0.98rnwhich indicate that the predicted values from a forecast models fit with the real-life data. The valuesrnof the mean absolute percentage error (MAPE) of the developed regression models are ranging fromrn±16.3% for preliminary cost estimating and to ±38.9% for conceptual or ball park method of costrnestimation, the results compare favorably with past researches which have shown that the estimaternaccuracy in the early stages of a project is between ±25% for preliminary method of cost estimatingrnthat can be related to specific characteristics of known sections or areas of the project and ±50% forrnconceptual method of cost estimating where early informed guesses made when virtually norndrawings exist.rnThe research finding shows how regression models based on the significant variables or bidrnquantities can be used to develop regression models as tools in forecasting future road constructionrncost that carry much greater reliability than the previous estimated value. The paper introduces therndevelopment of cost estimating techniques and principles from historic data in the archives from bothrna client and consultants viewpoint both in the early stage of pre-tendering or the planning phase andrnproject-levelrnKeywords: Cost estimating, Regression Model, Early cost estimate

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