Project delivery system selection of construction projects in China

被引:81
作者
Chen, Yong Qiang [1 ]
Liu, Jun Ying [1 ]
Li, Bingguang [2 ]
Lin, Binshan [3 ]
机构
[1] Tianjin Univ, Sch Management, Tianjin 300072, Peoples R China
[2] Shenandoah Univ, Harry F Byrd Jr Sch Business, Winchester, VA 22601 USA
[3] Louisiana State Univ, Dept Management & Mkt, Shreveport, LA 71115 USA
基金
中国国家自然科学基金;
关键词
Construction project; Project delivery system; Data envelopment analysis; Artificial neural network; China; DESIGN-BUILD; PERFORMANCE; EFFICIENCY; MODEL;
D O I
10.1016/j.eswa.2010.10.008
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
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 owner's decision making in the selection of the PDS. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5456 / 5462
页数:7
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