Application of multiple criteria decision making methods in construction: a systematic literature review
Abstract
Decision making is a key to business or project success in any sectors, especially in construction that requires handling numerous information and knowledge. Multiple criteria decision making (MCDM) is an important tool for decision problem solving due to simultaneous consideration of multiple criteria and objectives. Various MCDM methods are continually emerging and tend to be increasingly adopted to address the real-world construction problems. Therefore, it is urged to systematically review the existing body of literature to demonstrate the evolution of the mainstream MCDM methods in general and their application status in construction. A total of 530 construction articles published from 2000 to 2019 are selected in this study and then categorized into seven major application areas using a novel systematic literature review (SLR) methodology. The bibliometric analysis is then used to describe the research trend. Subsequently, the qualitative discussion by themes is conducted to analyze the application of MCDM methods in construction. A further discussion makes it possible to identify the potential challenges (e.g. applicability, robustness, postpone effect, dynamic and prospective challenges and scale problem) to existing research. It also contributes to the recommendation of future directions for the development of MCDM methods that would benefit construction research and practice.
Keyword : decision support system, construction, multiple criteria decision making, multiple attribute decision making, multiple objective decision making, systematic literature review
How to Cite
Zhu, X., Meng, X., & Zhang, M. (2021). Application of multiple criteria decision making methods in construction: a systematic literature review. Journal of Civil Engineering and Management, 27(6), 372-403. https://doi.org/10.3846/jcem.2021.15260
This work is licensed under a Creative Commons Attribution 4.0 International License.
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