Critical Assessment of Contract Administration Using Multidimensional Fuzzy Logic Approach
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 2
Abstract
The success of a project depends on the importance of investigating the impact of contract administration implementation parameters such as response time, approval process, resolving issues, coordination, and documentation. To this end, this paper covers the development of a new multidimensional fuzzy model to quantify the performance of construction contract administration (CCA) processes at the project level. The proposed model contains 93 key factors and 11 project management process groups related to contract administration performance. An online questionnaire was used to rate the importance of each factor and group, and 223 responses were collected. The collected data were analyzed for normality, reliability, and intergroup differences. A two-part weighted fuzzy logic model was then developed to measure the CCA performance. The first part represented the group assessment, while the second part assessed the overall performance. The model, which was then implemented in two construction projects in Qatar, illustrated that the proposed model reasonably captured the CCA performance; and thereby a low level of implementing contractual risk management was concluded. The questionnaire results indicated that change control, financial, and claims and disputes resolution management were the top three groups affecting the CCA performance. This study is limited to design-bid-build contracts. Nevertheless, the model might be restudied for other project delivery methods as well.
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Data Availability Statement
All data, models, and code generated or used during the study are available from the corresponding author by request.
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Published In
Journal of Construction Engineering and Management
Volume 147 • Issue 2 • February 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jan 6, 2020
Accepted: Aug 28, 2020
Published online: Nov 24, 2020
Published in print: Feb 1, 2021
Discussion open until: Apr 24, 2021
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