The application of an ANP-Fuzzy comprehensive evaluation model to assess lean construction management performance

Purpose The purpose of this paper is to propose a method for assessing the lean construction management performance (LCMP) of engineering projects using the analytic network process-fuzzy comprehensive evaluation (ANP-FCE) model. Design/methodology/approach Literature review and questionnaire surveys were used to achieve an evaluation index system for LCMP. The data needed to calculate the weights of the indices were derived from questionnaire surveys. The ANP and the Super Decisions (SD) software were used to calculate the weights of the indices and verify the validity of the weights. The FCE was adopted to carry out a comprehensive evaluation of LCMP, and the validity of the evaluation results was verified by applying the validity degree of maximum membership principle. The applicability of the method for evaluating LCMP was validated by empirical research. Findings The proposed method for assessing the LCMP using the ANP-FCE model is validated to be feasible. Decision makers can easily identify the strengths and weaknesses of lean construction (LC) management of the evaluated project from the evaluation results. Research limitations/implications Some subjectivity may exist in the assessment process due to questionnaire surveys, and only one case has been studied to validate the applicability of the method. Therefore, researchers are encouraged to increase the number of LC experts and cases over the world to make the proposed method more standard. Practical implications The research is expected to propose an assessment method of LCMP for construction enterprises, provide a reference to develop assessment standards for LCMP for building associations or governments and help decision makers know the improving path of LC management. Originality/value This research contributes to the literature by summarizing the commonly used lean management tools for quality, cost, time, safety and organization in practice, and proposing a novel approach for assessing the LCMP of engineering projects. The study is useful for researchers, project managers and decision makers engaged in LC.