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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.

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.

  • Type: Journal Article
  • Keywords: Risk management; Fuzzy sets; China; Governments; Private sector; Quantitative risk allocation; PPP projects; Fuzzy set; Fuzzy synthetic evaluation; China;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000189
  • Abstract:
    Equitable allocation of risks between the government and the private sector in concession agreement is essential to the success of public-private partnership (PPP) projects. The decision-making process, based on the established risk allocation principles expressed in linguistic terms, requires qualitative judgment and experiential knowledge of construction experts. However, it is subjective, partial, and implicit in actual application. This paper aims to develop a fuzzy synthetic evaluation model for determining an equitable risk allocation between the government and the private sector. By doing so, it assists the PPP project practitioners to transform the risk allocation principles in linguistic terms into a more usable and systematic quantitative-based analysis using fuzzy set. Twenty-three principles and influencing factors for risk allocation were identified through a comprehensive literature review. Nine critical risk allocation criteria (RACs) that evaluate the risk carrying capability of project participants were further identified, validated, and compiled based on the experts’ knowledge via face-to-face interviews. On the other hand, the weighting for each critical risk allocation criterion was determined through a two-round Delphi questionnaire survey. A set of knowledge-based fuzzy inference rules was then established to set up the membership function for the nine RACs. Based on the research findings, a fuzzy synthetic evaluation model was finally established to determine an equitable risk allocation between the government and the private sector.

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.