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Application of fuzzy fault tree analysis to identify factors influencing construction labor productivity: a high-rise building case study

    Shahab Shoar   Affiliation
    ; Audrius Banaitis   Affiliation

Abstract

The aim of this research is to develop a systematic approach to identify and prioritize the most influencing factors on labor productivity in a construction project, with respect to their interrelations, and also investigate different scenarios which can affect it. In the first step, factors influencing construction labor productivity were identified through reviewing previous researches. Applying a group of experts, the most important factors were then determined using their relative importance index in the second step. In the third step, the interrelations among factors were determined through several sessions and interviewing those experts. Finally, the efficiency of the proposed methodology is proved by implementing in a real high rise building construction project. In this step, the selected factors from previous steps were used subsequently for analyzing their impact on labor productivity through fuzzy fault tree analysis. The probability of occurrence of events was determined according to the opinions of four members of the project management team who involved in that project. The most critical causes were also identified using importance analysis. It is believed that using the proposed methodology, appropriate response strategies could be adopted against the identified critical events to enhance the overall productivity of a construction project.

Keyword : construction management, quantitative risk analysis, labor productivity, influential factors, fault tree analysis, fuzzy set theory

How to Cite
Shoar, S., & Banaitis, A. (2019). Application of fuzzy fault tree analysis to identify factors influencing construction labor productivity: a high-rise building case study. Journal of Civil Engineering and Management, 25(1), 41-52. https://doi.org/10.3846/jcem.2019.7785
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Jan 25, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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