Purpose Despite long-term, sustained research and industry practice, predicting
construction labour productivity (CLP) using existing factor and activity modelling …

Fuzzy inference systems (FISs) are a predictive modeling technique based on fuzzy sets that
utilize approximate reasoning to mimic the decision-making process of human experts …

Construction labour productivity (CLP) is affected by numerous variables made up of
subjective and objective factors. Thus, CLP modelling and prediction are a complex task …

Organizational competencies have a significant influence on performance; therefore, it is
vital that organizations in the construction industry assess and enhance their competencies …

Construction labor productivity (CLP) is one of the most studied areas in the construction
research field, and several context‐specific predictive models have been developed …

Construction labour productivity (CLP) significantly influences the profitability of construction
companies; however, CLP exhibits the highest variability among project resources and is a …

Fuzzy inference systems have been successfully applied to many real-world applications.
Traditional fuzzy inference systems are only applicable to problems with dense rule bases …

The variables that characterize construction organizational competencies are both
quantitative and qualitative in nature, and thus require measurement methods and modeling …

Construction labor productivity (CLP) is affected by numerous context-sensitive influencing
variables made up of subjective and objective factors, practices, and work sampling …

Discovering and extracting knowledge from large databases are key elements in granular
computing (GrC). The knowledge extracted, in the form of information granules can be used …