A knowledge-based system approach to the contractor prequalification process

This thesis presents the results of research analyzing the contractor prequalification process and its relevant decision parameters. Prequalification consists of a wide range of criteria of which information is both qualitative and subjective. This process is typically performed in an unstructured intuitive manner with considerable reliance on the judgment of a prequalification official. Thus, the thesis focuses on a more formalized approach to contractor prequalification. The research began with an analysis of contractor prequalification as it is currently performed in industry. The initial analysis is based on 8 personal and 24 telephone interviews with industry professionals who have extensive experience with prequalification. Next, a questionnaire was used to gather more data on significant decision parameters. Qualitative and quantitative statistical analyses of these data was performed. A computerized decision model for contractor prequalification, QUALIFIER-1 was developed. Data on prequalification practices collected during research were utilized in the formulation and quantification of the model. The model uses a dimensional weighting approach prequalification decision-making. This approach, when applied in practice, provides a valuable tool for prequalification officials by structuring and automating the decision process support. A knowledge intensive prototype expert system program for contractor prequalification, QUALIFIER-2 has been developed. The program represents a significant amount of effort expended for knowledge acquisition and compilation. The results of this research have been reviewed by numerous prequalification officials and positive comments have been received regarding their practicality. The developed prequalification programs have been successfully applied to actual construction project cases.