System Dynamics Approach for Forecasting Performance of Construction Projects

Abstract

Accurate and reliable prediction of project performance is critical to the success of construction projects and companies alike. Such prediction assists in obtaining early warnings against potential problems. Existing project performance forecasting models are fragmented, especially regarding the consideration of interdependency between multidimensional performance indicators. To address these limitations, a system dynamics (SD) model was developed to simulate the complexities that exist among interdependent variables and forecast their dynamics over time. The proposed model integrates eight construction project performance indices, which have been identified through literature review and interviews with domain experts. Performance dimensions include cost, schedule, quality, profitability, safety, environment, team satisfaction, and client satisfaction. This model focuses on the construction phase of projects under unit price contracts and is intended for use by contractors. The model was tested on a road construction project to assess its practicality and accuracy. Results demonstrate general agreement between actual and forecasted performance indices. The model was also used to simulate four possible intervention scenarios by the project manager. Results of various scenarios show overall agreement with expected impacts of the interventions. The research advances the state of practice and knowledge of project performance forecasting through the creation of a more holistic and interdependent model of project performance metrics.