Abstract
The construction industry has been increasingly adopting green building because of its advantages over conventional building. However, implementing successful green building projects entails difficulties in terms of cost performance. The objective of this study is to identify the critical factors that affect the cost performance of green building projects during their pre-project planning phase. This study validates the relationship between certain critical factors and the cost performance of green building projects. Support vector machine-recursive feature elimination (SVM-RFE), a data mining-based feature selection method, is applied to a data set comprising 53 green building projects. The results of the study show that 10 out of 64 project definition rating index (PDRI) factors exert most of the influence on the cost performance of the green building projects. These results will help the project stakeholders deliver green building projects more successfully in terms of cost performance.
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