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Al Qady, M and Kandil, A (2010) Concept Relation Extraction from Construction Documents Using Natural Language Processing. Journal of Construction Engineering and Management, 136(03), 294–302.

El-adaway, I H and Kandil, A A (2010) Multiagent System for Construction Dispute Resolution (MAS-COR). Journal of Construction Engineering and Management, 136(03), 303–15.

El-Gohary, N M and El-Diraby, T E (2010) Dynamic Knowledge-Based Process Integration Portal for Collaborative Construction. Journal of Construction Engineering and Management, 136(03), 316–28.

Girmscheid, G and Brockmann, C (2010) Inter- and Intraorganizational Trust in International Construction Joint Ventures. Journal of Construction Engineering and Management, 136(03), 353–60.

Kale, S and Arditi, D (2010) Innovation Diffusion Modeling in the Construction Industry. Journal of Construction Engineering and Management, 136(03), 329–40.

Lin, C and Huang, H (2010) Improved Baseline Productivity Analysis Technique. Journal of Construction Engineering and Management, 136(03), 367–76.

Love, P E D, Edwards, D J, Watson, H and Davis, P (2010) Rework in Civil Infrastructure Projects: Determination of Cost Predictors. Journal of Construction Engineering and Management, 136(03), 275–82.

Menassa, C, Peña Mora, F and Pearson, N (2010) Study of Real Options with Exogenous Competitive Entry to Analyze Dispute Resolution Ladder Investments in Architecture, Engineering, and Construction Projects. Journal of Construction Engineering and Management, 136(03), 377–90.

Minchin, R E, Henriquez, N R, King, A M and Lewis, D W (2010) Owners Respond: Preferences for Task Performance, Delivery Systems, and Quality Management. Journal of Construction Engineering and Management, 136(03), 283–93.

Thomas, M U (2010) Models for Managing Contingency Construction Operations. Journal of Construction Engineering and Management, 136(03), 391–8.

Toor, S and Ofori, G (2010) Positive Psychological Capital as a Source of Sustainable Competitive Advantage for Organizations. Journal of Construction Engineering and Management, 136(03), 341–52.

Touran, A (2010) Probabilistic Approach for Budgeting in Portfolio of Projects. Journal of Construction Engineering and Management, 136(03), 361–6.

  • Type: Journal Article
  • Keywords: Project management; Probability; Risk management; Assessment; Construction costs; Mathematical models; Budgets; Cost overrun; Transit projects; Probabilistic risk assessment; Construction budget; Mathematical model; Portfolio budget;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000128
  • Abstract:
    This paper presents a mathematical model for calculating the budgetary impact of increasing the required confidence level in a probabilistic risk assessment for a portfolio of projects. The model provides a rational approach for establishing a probabilistic budget for an individual project in such a way that the budget for a portfolio of projects will meet a required confidence level. The use of probabilistic risk assessment in major infrastructure projects is increasing to cope with major cost overruns and schedule delays. The outcome of the probabilistic risk assessment is often a distribution for project costs. The question is at what level of confidence (i.e., the probability that budget would be sufficient given the cost distribution) should be used for establishing the budget. The proposed method looks at a portfolio of such projects being funded by the same owner. The owner can establish a target probability with respect to its annual budget. The model can help the owner establish confidence level for individual projects and also examine the effect of changing the confidence level of the portfolio budget on the budget and the confidence level of individual projects. The paper is relevant to practitioners because it provides a methodology for establishing confidence levels by the owner agencies in the emerging field of cost risk assessment for infrastructure projects. A numerical example is provided using actual transit project data to demonstrate the model application.