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Anastasopoulos, P C, Labi, S, Bhargava, A, Bordat, C and Mannering, F L (2010) Frequency of Change Orders in Highway Construction Using Alternate Count-Data Modeling Methods. Journal of Construction Engineering and Management, 136(08), 886–93.

El Asmar, M, Lotfallah, W, Whited, G and Hanna, A S (2010) Quantitative Methods for Design-Build Team Selection. Journal of Construction Engineering and Management, 136(08), 904–12.

Ji, S, Park, M and Lee, H (2010) Data Preprocessing–Based Parametric Cost Model for Building Projects: Case Studies of Korean Construction Projects. Journal of Construction Engineering and Management, 136(08), 844–53.

Kent, D C and Becerik-Gerber, B (2010) Understanding Construction Industry Experience and Attitudes toward Integrated Project Delivery. Journal of Construction Engineering and Management, 136(08), 815–25.

Kim, B and Reinschmidt, K F (2010) Probabilistic Forecasting of Project Duration Using Kalman Filter and the Earned Value Method. Journal of Construction Engineering and Management, 136(08), 834–43.

Korkmaz, S, Riley, D and Horman, M (2010) Piloting Evaluation Metrics for Sustainable High-Performance Building Project Delivery. Journal of Construction Engineering and Management, 136(08), 877–85.

Lai, A W Y and Pang, P S M (2010) Measuring Performance for Building Maintenance Providers. Journal of Construction Engineering and Management, 136(08), 864–76.

Mostafavi, A and Karamouz, M (2010) Selecting Appropriate Project Delivery System: Fuzzy Approach with Risk Analysis. Journal of Construction Engineering and Management, 136(08), 923–30.

Nguyen, L D and Ibbs, W (2010)  Case Law and Variations in Cumulative Impact Productivity Claims. Journal of Construction Engineering and Management, 136(08), 826–33.

  • Type: Journal Article
  • Keywords: Claims; Contracts; Court decisions; Productivity; Owners; Contractors; Claims; Contracts; Court decisions; Productivity; Owners; Contractors;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000193
  • Abstract:
    Proving and quantifying lost productivity due to cumulative impacts of multiple changes are difficult tasks. This paper presents the most acceptable methods from case law and demonstrates their applications for analyzing the loss of productivity. These methods include earned value analysis, measured mile analysis, and combinations of these two. They are either well established or drawn from recent court and board decisions. A case study is used to illustrate and compare the use of these methods. These methods result in considerably different loss of productivity values though the actual amount (i.e., inefficiency in labor hours) is unique for a particular case and though these methods are often thought to be similar or even the same. How a measured mile analysis and its variants are employed affects the amount of lost productivity estimated. The variants can avoid some drawbacks of measured mile and earned value studies. Nevertheless, which method is more accurate and reliable is difficult to provide for a particular claim. Practitioners should choose between them based on the availability of project records and the nature of changes and cumulative impacts. Practitioners may also employ two or more methods to perform a “sensitivity analysis” of the chosen methods and persuade the other party and/or the jury that their estimate of lost productivity is sufficiently certain.

Xu, Y, Chan, A P C and Yeung, J F Y (2010) Developing a Fuzzy Risk Allocation Model for PPP Projects in China. Journal of Construction Engineering and Management, 136(08), 894–903.

Zheng, S and Tiong, R L K (2010) First Public-Private-Partnership Application in Taiwan’s Wastewater Treatment Sector: Case Study of the Nanzih BOT Wastewater Treatment Project. Journal of Construction Engineering and Management, 136(08), 913–22.

Zou, P X W, Chen, Y and Chan, T (2010) Understanding and Improving Your Risk Management Capability: Assessment Model for Construction Organizations. Journal of Construction Engineering and Management, 136(08), 854–63.