Selection of project delivery approach with unascertained model
Article publication date: 2 February 2015
The construction project is implemented under uncertainty environment, and the product of construction is very complex. Selecting a project delivery system/approach is a critical task, which determines the project schedule, quality and investment objectives. The purpose of this paper is to propose a decision-making model for the selection of project delivery system which is based on information entropy and unascertained measure model.
A decision-making model based on information entropy and unascertained set is employed to select project delivery approach. In order to overcome the subjective evaluations from the experts, the theory of “entropy weight” is applied to modify the experts’ subjective weight. The multi-attribute unascertained measure decision making is fitted to deal with the uncertainty information for selection of project delivery system.
The proposed methodology is more comprehensive compared with the previous work, especially in the uncertainty environment.
There is some further work that should be considered, such as how to deal with the imprecise and subjective information given by the experts; how to determine the weight of the experts’; finding a set of importance factors influencing the selection of a delivery system is a complex task to further research.
The proposed method can help the construction owner to select a most fitted project delivery system of a construction project.
A new approach to select project delivery approach is proposed based on information entropy and unascertained set.
The authors thank the National Natural Science Foundation of China (No. project 71302191), Department of Education of Henan province, Humanities and social science projects (No. project 2013-QN-028) and Basic Science Research Project of Henan province, China (project No. 122300410029) for financially supporting this study.
Li, H., Qin, K. and Li, P. (2015), "Selection of project delivery approach with unascertained model", Kybernetes, Vol. 44 No. 2, pp. 238-252. https://doi.org/10.1108/K-01-2014-0012
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