## 5 Conclusions  
In this study, a decision support model is proposed to identify the most effective CLP improvement strategies and quantify their impact on CLP. The provided model consists of three phases, namely, (1) identifying factors and strategies, (2) ranking strategies, which includes the utilization of the two fuzzy MCDM methods of fuzzy AHP and fuzzy TOPSIS, and (3) quantifying strategies' impact on CLP, which includes developing an FCM model of CLP in order to quantify the impact of improvement strategies on CLP. Implementation of the developed model on a case study of concrete-pouring activities in building projects was used to illustrate how construction practitioners can apply the proposed model to their projects in order to identify the improvement strategies that serve as the most effective management practices with respect to CLP. According to the case study results, the following ranked management practices were the most effective CLP improvement strategies for the project under study: (1) Develop clear instructions about the equipment used to transport materials, (2) Provide clear instructions to craftspeople on how to complete tasks before their execution, (3) Apply preventive maintenance to heating and air-conditioning systems to make sure they are in working order, (4) Perform project team activities, (5) Train laborers to achieve the latest concrete-pouring techniques, (6) Hold regular meetings with laborers about schedule and remaining tasks, and (7) Hire cheap labor for daily housekeeping tasks. These strategies are supported by previous studies that suggested similar strategies as the top management practices for improving CLP. Since CLP is a context-specific efficiency measure and CLP factors are mostly interconnected and affect each other, considering project characteristics and causal relationships among CLP factors made the results of this research more precise than previous studies that utilized statistical techniques to quantify the impact of improvement strategies on CLP. Statistical techniques such as \(t\)-test and regression analysis lack the capability to capture project characteristics and interconnections among the factors. The contribution of this paper is providing a decision support methodology for construction companies and practitioners to solve the problem of prioritizing CLP improvement strategies and quantifying their impact on CLP by integrating two fuzzy MCDM methods, fuzzy AHP and fuzzy TOPSIS, with FCM. The combination of fuzzy AHP and fuzzy TOPSIS captures experts' opinions and represents uncertainty and vagueness in the decision-making process of CLP improvement strategies selection without involving cumbersome mathematics. In addition, the utilized fuzzy MCDM methods support FCM by reducing the number of improvement strategies needed for FCM modeling according to various criteria including impact on CLP, implementation feasibility, workers' adaptation, and implementation risk. The developed FCM model takes into account the imprecision and uncertainty of CLP factors as well as the causality among them. The proposed methodology considers the causal relationships among CLP improvement parameters and captures the perspective of construction experts to consider project characteristics and address existing gaps in the CLP improvement strategies literature. Therefore, the results of this research are more accurate than previous studies that used statistical methods to quantify the impact of improvement strategies on CLP without considering the project characteristics and causal relationships among CLP factors. The decision support model provided in this study can be adapted to several construction problems, such as selection of policies for maximizing crew motivation and performance. The presented model will assist construction managers in identifying the most effective improvement strategies for given projects and help them quantify how implementing various strategies impacts CLP.