Change Orders: Automating Comparative Data Analysis and Controlling Impacts in Public Projects
Publication: Journal of Construction Engineering and Management
Volume 145, Issue 11
Abstract
Change orders grant public-project owners exceptional flexibility to alleviate construction problems and respond promptly to project needs. Recently, in the Middle East, change orders have become common, leading to significant major problems and disputes. The negative impacts of this phenomenon on project cost and time create a critical need for systems that enable public agencies to identify the technical causes of change orders and investigate their impacts in order to prepare relevant response strategies. This study presents the development of a model for change-order data analysis that is capable of quantifying the impact of change orders on project cost and time. The model incorporates newly developed elements that enable (1) identifying the leading technical causes of change orders by project type and instigator; (2) quantifying the influence of project type and size on change-order cost and duration; and (3) automating the development of periodic reports that can be used to mitigate the negative impacts of change orders. To illustrate the viability of the developed model, a computerized system was developed and populated with data collected from 38 public projects that included 67 change orders. The leading technical causes of change orders identified through record analysis were poor definition of work scope, lack of coordination with authorities, and unplanned interruptions. An inverse exponential relationship is observed between the project size and both the percent time change and percent cost change of change orders. In projects that experienced scope-of-work changes, the percent time and cost changes were substantially higher compared with projects without scope-of-work changes. The paper’s primary contributions to the overall body of knowledge are (1) the development of a standard model to facilitate and automate the comparative analysis of change-order data across public-project types and sizes; and (2) the empirical demonstration of its viability for the analysis of change-order data.
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Data Availability Statement
All data generated or analyzed during the study are included in the published paper.
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Published In
Journal of Construction Engineering and Management
Volume 145 • Issue 11 • November 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Jul 16, 2018
Accepted: Feb 26, 2019
Published online: Aug 24, 2019
Published in print: Nov 1, 2019
Discussion open until: Jan 24, 2020
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