Predicting Cost and Schedule Performance of Green Building Projects Based on Preproject Planning Efforts Using Multiple Linear Regression Analysis

Abstract

Although the building industry has attempted to adopt the green construction paradigm worldwide, evidence shows that it has not been fully implemented. Consequently, an efficient preplanning tool is pressingly needed to motivate project teams to adopt the green construction concept to increase project success. Other research has focused on essential planning elements that enable projects to achieve green building certification. However, only a few attempts have emphasized cost and schedule performance. This paper developed an efficient-yet-simple predictive model for predicting the project performance (cost and time) of green building construction projects, associated with the effectiveness of preproject planning at the initial stage represented in terms of the Project Definition Rating Index (PDRI). The analysis was conducted in three steps: (1) identifying significant planning elements affecting cost and schedule performance using an independent t-test, (2) constructing predictive models by applying multiple linear regression, and (3) validating the constructed models using a paired sample t-test. Sample data from 17 certified green buildings were utilized. The results identified 10 planning elements that differed significantly between under- and overbudget projects, related to the project requirements, procurement strategy, schedule control, project design, and safety considerations. Similarly, six elements were identified for schedule performance that were classified under the business strategy, economic analysis, and values analysis. Then, predictive models were proposed with coefficients of determination of 0.94 for cost performance and 0.60 for schedule performance. The developed models not only contributed to the preliminary assessment of the possible cost and schedule performance for the current level of a project team’s preplanning efforts but also could be further adapted for exploratory evaluation of expected outcomes due to a certain level of improvement in preproject planning.