Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 12 results ...

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.

  • Type: Journal Article
  • Keywords: Monte Carlo method; Design/build; Selection; Quantitative analysis; Bids; Construction industry; Monte Carlo method; Design/build; Selection; Quantitative analysis;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000194
  • Abstract:
    The use of design/build (DB) contracting by transportation agencies has been steadily increasing as a project delivery system for large complex highway projects. However, moving to DB from traditional design-bid-build procurement can be a challenge. One significant barrier is gaining acceptance of a best-value selection process in which technical aspects of a proposal are considered separately and then combined with price to determine the winning proposal. These technical aspects mostly consist of qualitative criteria, thus making room for human errors or biases. Any perceived presence of bias or influence in the selection process can lead to public mistrust and protests by bidders. It is important that a rigorous quantitative mathematical analysis of the evaluation process be conducted to determine whether bias exists and to eliminate it. The paper discusses two potential sources of bias—evaluators and weighting model—in the DB selection process and presents mathematical models to detect and remove biases should they exist. A score normalization model deals with biases from the evaluators; then a graphical weight-space volume model and a Monte Carlo statistical sampling model are developed to remove biases from the weighting model. The models are then tested and demonstrated using results from the DB bridge replacement project for the collapsed Mississippi River bridge of Interstate 35W in Minneapolis.

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.

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.