A fuzzy DEA–Neural approach to measuring design service performance in PCM projects

In Professional Construction Management (PCM), service performance in the design stage most affects the overall project results. However, currently it is hard to quantify the results and make a proper determination of the quality of the PCM design service because the evaluation mechanism and procedures have not been completely implemented yet. To deal with the problem, this study investigates owners' opinions and thereby establishes the representative performance indicators of PCM design service. An effectiveness analysis method and a neural network method are successfully combined, so as to construct an evaluation approach of PCM service performance in the design stage. This approach can offer a listing of rank and level of design service performance in PCM projects, and further provides a simple appraisal table, so that the owner can effectively measure the performance of PCM design service. Finally, through the case study, this approach is verified to be reasonable and acceptable in practice. The approach can be an effective tool when measuring the PCM design service performance and can help owners to evaluate and choose PCM consultants in the design stage.