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Abouhamad, M and Zayed, T (2019) Risk-Based Asset Management Framework for Subway Systems. Journal of Construction Engineering and Management, 145(11).
Ahn, C R, Lee, S, Sun, C, Jebelli, H, Yang, K and Choi, B (2019) Wearable Sensing Technology Applications in Construction Safety and Health. Journal of Construction Engineering and Management, 145(11).
Alruwaythi, O and Goodrum, P (2019) A Difference in Perspective: Impact of Different Formats of Engineering Information and Spatial Cognition on Craft-Worker Eye-Gaze Patterns. Journal of Construction Engineering and Management, 145(11).
Cheng, M, Chang, Y and Korir, D (2019) Novel Approach to Estimating Schedule to Completion in Construction Projects Using Sequence and Nonsequence Learning. Journal of Construction Engineering and Management, 145(11).
Demirel, H &, Volker, L, Leendertse, W and Hertogh, M (2019) Dealing with Contract Variations in PPPs: Social Mechanisms and Contract Management in Infrastructure Projects. Journal of Construction Engineering and Management, 145(11).
Esmaeeli, A N and Heravi, G (2019) Real Options Approach versus Conventional Approaches to Valuing Highway Projects under Uncertainty. Journal of Construction Engineering and Management, 145(11).
Feng, Y and Trinh, M T (2019) Developing Resilient Safety Culture for Construction Projects. Journal of Construction Engineering and Management, 145(11).
Franco-Duran, D M and Garza, J M d l (2019) Review of Resource-Constrained Scheduling Algorithms. Journal of Construction Engineering and Management, 145(11).
Hamzeh, F R, El Samad, G and Emdanat, S (2019) Advanced Metrics for Construction Planning. Journal of Construction Engineering and Management, 145(11).
Jang, Y, Jeong, I, Cho, Y K and Ahn, Y (2019) Predicting Business Failure of Construction Contractors Using Long Short-Term Memory Recurrent Neural Network. Journal of Construction Engineering and Management, 145(11).
Khalafallah, A and Shalaby, Y (2019) Change Orders: Automating Comparative Data Analysis and Controlling Impacts in Public Projects. Journal of Construction Engineering and Management, 145(11).
- Type: Journal Article
- Keywords: Change order; Cost overrun; Public projects; Schedule creep; Scope-of-work definition; Computerized system;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001700
- 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.
Li, K and Cheung, S O (2019) Unveiling Cognitive Biases in Construction Project Dispute Resolution through the Lenses of Third-Party Neutrals. Journal of Construction Engineering and Management, 145(11).
Prakash, A and Phadtare, M (2019) Exploration of Logic in Project Marketing Using Interpretive Structural Modeling. Journal of Construction Engineering and Management, 145(11).