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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.

  • Type: Journal Article
  • Keywords: Costs; Data analysis; Korea, South; Construction management; Cost; Cost model; Cost estimate; Data preprocessing;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000197
  • Abstract:
    For construction to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need reliable estimation strategies. In practice, parametric cost estimation, which utilizes historical cost data, is the most commonly used method in these initial phases. Therefore, compilation of historical data pertaining to appropriate cost variance governing parameters is a prime requirement. However, data mining (data preprocessing) for denoising internal errors or abnormal values must be performed before this compilation. To address this issue, this research proposes a statistical methodology for data preprocessing. Moreover, a statistically preprocessed data–based parametric (SPBP) cost model is developed based on multiple regression equations. Case studies of Korean construction projects verify that the model enhances cost estimate accuracy and reliability than conventional cost models.

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.

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.