Haidar, A (2011) Analysis and optimization of megaproject performance. Unpublished PhD thesis, University of Florida, USA.
Abstract
Large scale complex projects commonly known as megaprojects suffer from poor managerial performance that results in enormous cost overruns and time extensions. Several researchers of different management fields have attempted to improve megaprojects' time and cost performance. However, the methodologies provided do not constitute tangible solutions that could be used to improve megaprojects' managerial as well as project performance. The research aims to optimize megaproject project performance by providing work practices that are capable of handling megaprojects' managerial difficulties caused by the dynamic and parallel operation of numerous interrelated workgroups. Two methods are provided to achieve megaproject performance optimization. The first method is a decision model that determines the optimal work practices based on predetermined management objectives. The model was developed from case studies that determined the work practices and a survey that evaluated them. The second method is a planning process for optimizing the management organization. The process was developed from the case studies' lessons learned and conclusions drawn from the survey evaluations. The proposed benefits of using the methods include improved megaproject cost, time, and quality performance. Benefits also include improved managerial performance through optimal allocation of duties and responsibilities, streamlined management processes, and better integration and coordination. Most important, the methods provide construction practitioners a decision support system to determine the optimal work practices that suit their capabilities and management objectives.
Item Type: | Thesis (Doctoral) |
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Thesis advisor: | Ellis, R |
Uncontrolled Keywords: | integration; megaproject; performance; project cost; coordination; decision support; optimization; case studies; project performance |
Date Deposited: | 16 Apr 2025 19:29 |
Last Modified: | 16 Apr 2025 19:29 |