Decision Support Tool for Design-Build Assessment: A Quasi-Experimental Study in Malaysia

被引:0
作者
Lee, Zheng Ping [1 ]
Rahman, Rahimi A. [1 ]
Doh, Shu Ing [2 ]
机构
[1] Univ Malaysia Pahang, Fac Civil Engn Technol, Kuantan 26300, Malaysia
[2] Univ Malaysia Pahang, Coll Engn, Dept Civil Engn, Kuantan 26300, Malaysia
关键词
Construction industry; Decision support tool; Design-build; Multivariate analysis; Quasi-experiment; CRITICAL SUCCESS FACTORS; PROJECT DELIVERY; CONSTRUCTION; MANAGEMENT; SELECTION; SYSTEM; MODEL; INTEGRATION; READINESS; DRIVERS;
D O I
10.1061/(ASCE)AE.1943-5568.0000558
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The interventions of decision support tools and techniques are necessary for making decisions on complex issues that involve numerous parameters. In the construction industry, the identified barriers that affect the implementation of decision support tools revolve around the issues of scarce information, diverse project characteristics, bureaucracy, and low precision of statistical decision models. This study aimed to design a decision support tool for the assessment of the suitability of a design-build method (hereafter DST-DB), which can efficiently assist practitioners in the adoption (or rejection) of the design-build method with greater convenience. The selection factors were identified by compiling and validating key design-build selection factors of critical success factors (CSFs) and design-build-drivers (DBDs) through an extensive literature review and consulting with industry experts, resulting in the development of DST-DB. The obtained results showed the influence of DST-DB on the practitioners' perceptions of a design-build method, where DST-DB recorded significantly higher usability, likelihood, precision, confidence, and satisfaction rate than the conventional approach (multicriteria decision analysis) of decision-making in the construction industry. There have been many other decision support studies over the years, but the current study served as one of the first decision support studies for design-build construction projects in the construction industry, which offered appreciative insights into the importance of adopting CSFs and DBDs in decision support tools (DST-DB). (C) 2022 American Society of Civil Engineers.
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页数:14
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