Risk evaluation of bidding decision based on multi-factor clustering analysis

Risk management for general contract project is well experienced task, which must deal with much more qualitative factors that is easy influenced by individuals, so that the objectivity cannot be guaranteed. A novel method is proposed in order to overcome the shortcomings, which use the clustering analysis to evaluate bidding risk. An optimal objective function based clustering model is designed to explore the data collected from completed projects. Mixed scale is employed in clustering to handle qualitative and quantitative data without converting respectively. So the individual prejudice is eliminated from risk evaluate results and bidding decision making is supported. Moreover the quantitative results of risk estimate is good base for project cost reckoning quickly. An instance is carried out verifying proposed method validity.