Evaluating sub-contractors performance using EFNIM

In the construction industry, sub-contractor's performance is a crucial factor in their awards of a new job by a general contractor. The objective of this study is to improve the current practices for evaluating sub-contractors performance.Drawbacks of current evaluation process are discussed firstly. The appropriateness for adopting the Evolutionary Fuzzy Neural Inference Model (EFNIM) for improving the drawbacks is studied. A Sub-contractor Performance Evaluation Model (SPEM) is then developed by employing the EFNIM. The effectiveness of the proposed SPEM is validated by performing case study of a real general contractor. Validation results show that the proposed method accurately measures sub-contractor's performance enhancing the current practice of evaluation.