Risk is mitigated in the course of reliable prediction. A probabilistic model is proposed to predict the risk effects on time and cost of construction projects. Project managers and consultants can use the model in estimating project cost and duration based on historic data. Statistical regression models and sample tests are developed using real data of 140 projects. The research objective is to develop a model to predict project cost and duration based on historic data of similar projects. The model result can be used by project managers in the planning phase to validate the schedule critical path time and project budget. Research methodology is steered per the following progression: i) Conduct nonparametric test for project cost and time performance. ii) Develop generic multiple-regression models to predict project cost and duration using historic performance data. iii) The percent prediction error is statistically analyzed; and found to be substantial; thus, iv) Custom multiple regression models are developed for each project type to obtain statistically reliable results. In conclusion, the 95% point estimation of error margin= ±0.035%. Therefore, at a probability of 95%, the proposed model predicts the project cost and duration with a precision of ±0.035% of the mean cost and time.
|Number of pages||17|
|Journal||Jordan Journal of Civil Engineering|
|Publication status||Published - Jan 1 2008|
- Construction projects
- Prediction model
ASJC Scopus subject areas
- Civil and Structural Engineering