Establishing a quantitative performance evaluation framework through fuzzy membership functions

Past practice of proposal-oriented Prequalification and Selection (PS) of Engineering Consultants (EC) is found problematic. Nowadays, public sectors and quasigovernmental organizations in many advanced countries emphasize on gauging ECs’ performance at different project stages to congregate a set of Consultant Performance Evaluation (CPE) data for future PS. It is believed that the performance of ECs in previous projects could directly reflect its real strength and ability for succeeding assignments. To further enhance the reliability, it is desirable to merge all the CPE data from different clients into an integrated repository. A universal set of CPE criteria and corresponding Quantitative Indicators (QI) were compiled in previous research to provide a common evaluation platform. However, evaluation variations still exist as the QI require assessors’ subjective value judgement based on their own expectations. The paper summarized the CPE criteria and QI identified in previous research, and illustrated the discrepancies arisen from applying subjective judgement in the evaluation. To tackle this deficiency, the paper further described how Quantitative Requirements (QR) of each QI against different performance levels could be established, by utilizing modified horizontal approach to develop fuzzy membership functions for each QI. Finally, an objective evaluation framework for CPE is proposed.

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