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Alhumaidi, H M (2015) Construction Contractors Ranking Method Using Multiple Decision-Makers and Multiattribute Fuzzy Weighted Average. Journal of Construction Engineering and Management, 141(04).

Barry, W, Leite, F and O’Brien, W J (2015) Late Deliverable Risk Catalog: Evaluating the Impacts and Risks of Late Deliverables to Construction Sites. Journal of Construction Engineering and Management, 141(04).

Birgonul, M T, Dikmen, I and Bektas, S (2015) Integrated Approach to Overcome Shortcomings in Current Delay Analysis Practices. Journal of Construction Engineering and Management, 141(04).

Cao, M, Cheng, M and Wu, Y (2015) Hybrid Computational Model for Forecasting Taiwan Construction Cost Index. Journal of Construction Engineering and Management, 141(04).

Dharmapalan, V, Gambatese, J A, Fradella, J and Moghaddam Vahed, A (2015) Quantification and Assessment of Safety Risk in the Design of Multistory Buildings. Journal of Construction Engineering and Management, 141(04).

Liu, J, Love, P E D, Sing, M C P, Carey, B and Matthews, J (2015) Modeling Australia’s Construction Workforce Demand: Empirical Study with a Global Economic Perspective. Journal of Construction Engineering and Management, 141(04).

Vogl, B and Abdel-Wahab, M (2015) Measuring the Construction Industry’s Productivity Performance: Critique of International Productivity Comparisons at Industry Level. Journal of Construction Engineering and Management, 141(04).

Wanberg, J, Javernick-Will, A, Chinowsky, P and Taylor, J E (2015) Spanning Cultural and Geographic Barriers with Knowledge Pipelines in Multinational Communities of Practice. Journal of Construction Engineering and Management, 141(04).

Wauters, M and Vanhoucke, M (2015) Study of the Stability of Earned Value Management Forecasting. Journal of Construction Engineering and Management, 141(04).

  • Type: Journal Article
  • Keywords: Earned value management; Earned schedule; Project management; Forecasting; Simulation; Stability; Cost and schedule;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000947
  • Abstract:
    In this paper, the authors focus on the stability of earned value management (EVM) forecasting methods. The contribution is threefold. First of all, a new criterion to measure stability that does not suffer from the disadvantages of the historically employed concept is proposed. Second, the stability of time and cost forecasting methods is compared and contrasted by means of a computational experiment on a topologically diverse data set. Throughout these experiments, the forecasting accuracy is reported as well, facilitating a trade-off between accuracy and stability. Finally, it is shown show that the novel stability metric can be used in practical environments using two real-life projects. The conclusions of this empirical validation are found to be largely in line with the computational results.