Assessment of Respondents’ Responses in Advancing Quantitative Key Performance Indicators for Construction Project Management Systems: Utilization of Neural Network Fitting and Clustering

Delays, risks, and accidents (DRAs) in construction project management systems (CPMSs) negatively impact construction companies. Most construction projects are executed outdoors and are susceptible to extreme weather conditions (EWCs), which can cause DRAs. This study assesses the importance of using quantitative key performance indicators (QKPIs) through the respondents’ responses that could help the construction companies lessen the DRAs. Project managers, site engineers, and safety officers are the ones who are qualified to respond to this concern. Moreover, the respondents’ responses are evaluated using neural network fitting (NNF) and neural network clustering (NNC) to depict the professionals’ opinions. The results of NNF and NNC conclude the advancement of QKPIs and effectiveness in workplace hazards during EWCs. It shows a promising future for the advancement of CPMSs that would benefit different construction companies.