Building and Environment Forecast Models for Actual Construction Time and Cost

The actual construction time and cost of construction projects may be affected by the client, project and contractual characteristics and in many cases can be very different from the contract time and cost. In this paper, details of 93 Australian construction projects are used to develop several models for actual construction time and cost prediction. A forward crossvalidation regression analysis is used for the development of the model for actual construction time forecast when client sector, contractor selection method, contractual arrangement, project type, contract period and contract sum are known. The standard deviation of the deleted residual indicates the best model for actual construction time prediction to comprise the independent variables log contract time, lump sum procurement and non-standard contractor selection. Regression models are also developed for forecasting the actual construction time and cost when client sector, contractor selection method, contractual arrangement and project type are known while contract period and contract sum are estimated. Different forms of regression analyses, including the standard regression and the crossvalidation regression, are used and the crossvalidation regression model with the smallest deleted residual sum of squares is selected. Since these models for time and cost are dependent on the contract period and contract sum being known, it is necessary to investigate the effects in situations where these have to be estimated. The results of the sensitivity analyses show that the errors in predicted actual construction time become smaller as the contract period increases. In contrast, the errors in predicted actual construction cost are virtually the same for large and small projects.