Project delivery system selection of construction projects in China
The suitability of the project delivery system (PDS) selected for a project greatly influences the efficiency to conduct a project. It is not an easy task to select an appropriate PDS as a large amount of ambiguous information exists. The paper aims to develop a PDS selection model to help owners to make a decision. The similar projects are identified through the similarity metrics between the target project to be predicted and those in the database. In addition, some of the indicator values are examined and modified through DEA-BND model, and then they are trained by ANN model to predict an appropriate PDS for the target project. A survey was conducted by postal questionnaire to empirically validate the reliability of the model in China. The indicator system for the selection of an appropriate PDS is established. Through the comparison of results predicted by different models, it is found that the PDS selection model developed in this paper can predict PDS precisely, and shows higher reliability than the ANN model. A PDS selection model is developed by inputting project-specific data, which proves to be more accurate and less dependent on experts judgment. Its practical application will benefit the owners decision making in the selection of the PDS.
project delivery system construction project china data envelopment analysis artificial neural network