Value Engineering Factors with an Impact on Design Management Performance of Construction Projects
Publication: Journal of Management in Engineering
Volume 38, Issue 3
Abstract
Design management is one of the most important construction project stages. Identifying the factors that impact a project’s performance is crucial for the overall success of construction projects. This research contributes to the body of knowledge by examining value engineering elements that might affect design management performance to keep the project team focused on those issues to achieve successful design management performance. As an integrated aspect of lean construction, this would result in a successful project with minimal waste of time, cost, or rework. Based on the assumptions made, these value engineering components were prioritized by their significance. To the best of the authors’ knowledge, this study is the first to quantitatively examine the impact of value engineering parameters on design management performance. After a detailed analysis of the literature and consultation with value engineering experts and design professionals, 22 value engineering design management factors were identified and then grouped into the three categories of designers’ conditions, owner and stakeholders’ conditions, and value engineering conditions. A questionnaire was designed and distributed to construction industry professionals to rank the factors on a five-point Likert scale. One hundred and fifty complete responses were received. The structural equation model (SEM) and the collected data were used to study the relationship and association between these value engineering factors and design management performance. After performing a thorough analysis of the results, the top-ranked group was found to be the owner and stakeholders’ conditions, followed by the group of value engineering conditions and design conditions, respectively. The results of this study will help design professionals consider the value engineering factors during the design stage of a project according to their importance, as suggested by this research.
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Data Availability Statement
All data, models, and codes generated or used during the study are available from the corresponding author by request.
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Journal of Management in Engineering
Volume 38 • Issue 3 • May 2022
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© 2022 American Society of Civil Engineers.
History
Received: Jun 2, 2021
Accepted: Dec 1, 2021
Published online: Feb 25, 2022
Published in print: May 1, 2022
Discussion open until: Jul 25, 2022
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