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Abdelgawad, M and Fayek, A R (2010) Risk Management in the Construction Industry Using Combined Fuzzy FMEA and Fuzzy AHP. Journal of Construction Engineering and Management, 136(09), 1028–36.

Adriaanse, A, Voordijk, H and Dewulf, G (2010) Adoption and Use of Interorganizational ICT in a Construction Project. Journal of Construction Engineering and Management, 136(09), 1003–14.

Bayraktar, M E and Hastak, M (2010) Scoring Approach to Construction Bond Underwriting. Journal of Construction Engineering and Management, 136(09), 957–67.

Hallowell, M R and Gambatese, J A (2010) Population and Initial Validation of a Formal Model for Construction Safety Risk Management. Journal of Construction Engineering and Management, 136(09), 981–90.

Hwang, S (2010) Cross-Validation of Short-Term Productivity Forecasting Methodologies. Journal of Construction Engineering and Management, 136(09), 1037–46.

Hwang, S and Liu, L Y (2010) Contemporaneous Time Series and Forecasting Methodologies for Predicting Short-Term Productivity. Journal of Construction Engineering and Management, 136(09), 1047–55.

Ioannou, P G and Awwad, R E (2010) Below-Average Bidding Method. Journal of Construction Engineering and Management, 136(09), 936–46.

Love, P E D, Mistry, D and Davis, P R (2010) Price Competitive Alliance Projects: Identification of Success Factors for Public Clients. Journal of Construction Engineering and Management, 136(09), 947–56.

Sacks, R, Koskela, L, Dave, B A and Owen, R (2010) Interaction of Lean and Building Information Modeling in Construction. Journal of Construction Engineering and Management, 136(09), 968–80.

Serag, E, Oloufa, A, Malone, L and Radwan, E (2010) Model for Quantifying the Impact of Change Orders on Project Cost for U.S. Roadwork Construction. Journal of Construction Engineering and Management, 136(09), 1015–27.

  • Type: Journal Article
  • Keywords: Change order; Claims; Construction management; Highways and roads; Change orders; Claims; Multiple regression; Heavy construction;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000206
  • Abstract:
    Change orders are very common in almost every construction project nowadays, often resulting in increases of 5–10% in the contract price. Understanding the consequences of such trends, several studies have attempted to quantify the impact of change orders on the project cost. Most of the studies aimed at the quantification of the change orders were sponsored by contractors’ organizations, where statistical models used to quantify the impact of the change orders on the project cost were based on data supplied by the contractors; a situation that can lead to owner-contractor disagreements related to the quantification method used. In addition, most of the studies tackled commercial and electromechanical work, and very rare studies tackled the field of heavy construction; a field that suffers from change orders because of errors and omissions, scope of work changes, or changes because of unforeseen conditions. This study addresses the need for a statistical model to quantify the increase of the contract price due to change orders in heavy construction projects in Florida. The model is based on data collected from 16 Florida DOT projects with contract values that ranged between $10–$25 million, and that encountered an increase in the contract price from 0.01 to 15%. Eleven variables were analyzed to test their impact on the cost of the change orders. The study concluded that most significant variables that impact the value of the change order, which are (1) the timing of the change order and (2) when the reason for issuing the change order is unforeseen conditions. Two regression models are developed and validated as follows: (1) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 0.01 to 5% and (2) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 5 to 15%. Those models will provide the owner with a retrospective or forward pricing of the change orders, and hence, allow the owner to estimate and utilize contingency amounts.

Wong, J M W, Chan, A P C and Chiang, Y H (2010) Modeling Construction Occupational Demand: Case of Hong Kong. Journal of Construction Engineering and Management, 136(09), 991–1002.

Zhao, Z Y, You, W Y and Zuo, J (2010) Application of Innovative Critical Chain Method for Project Planning and Control under Resource Constraints and Uncertainty. Journal of Construction Engineering and Management, 136(09), 1056–60.