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An, X, Li, H, Zuo, J, Ojuri, O, Wang, Z and Ding, J (2018) Identification and Prevention of Unbalanced Bids Using the Unascertained Model. Journal of Construction Engineering and Management, 144(11).

Charkhakan, M H and Heravi, G (2018) Risk Manageability Assessment to Improve Risk Response Plan: Case Study of Construction Projects in Iran. Journal of Construction Engineering and Management, 144(11).

Devine, R D, Barbachyn, S M, Thrall, A P and Kurama, Y C (2018) Effect of Tripping Prefabricated Rebar Assemblies on Bar Spacing. Journal of Construction Engineering and Management, 144(11).

ElMousalami, H H, Elyamany, A H and Ibrahim, A H (2018) Predicting Conceptual Cost for Field Canal Improvement Projects. Journal of Construction Engineering and Management, 144(11).

Gupta, M, Hasan, A, Jain, A K and Jha, K N (2018) Site Amenities and Workers’ Welfare Factors Affecting Workforce Productivity in Indian Construction Projects. Journal of Construction Engineering and Management, 144(11).

Orgut, R E, Zhu, J, Batouli, M, Mostafavi, A and Jaselskis, E J (2018) Metrics That Matter: Core Predictive and Diagnostic Metrics for Improved Project Controls and Analytics. Journal of Construction Engineering and Management, 144(11).

  • Type: Journal Article
  • Keywords: Project control metrics; Cost and schedule; Performance assessment; Forecasting;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001538
  • Abstract:
    Project progress and performance assessment is critically important to the successful delivery of capital facility projects. However, there is no standardized approach for the selection and use of project control metrics, making it difficult to analyze project progress and performance for transforming data into meaningful insights. This research identified core predictive and diagnostic metrics that may provide actionable insights into a project’s actual progress, performance, and forecast at completion. The methodology used for identifying these metrics included a literature review, surveys, expert evaluation utilizing the Delphi method, and statistical validation. The researchers analyzed 44 surveys and collected multiple rounds of responses from 16 subject matter experts to validate the findings. Results indicated there are 20 core metrics, seven validation metrics, seven innovative metrics, and 14 other significant metrics, which can be used for multiple project types, sizes, and contracting strategies. Statistical analyses of the survey data were used to further validate the core metrics and demonstrated that use of more core metrics corresponded with project cost performance and using more diagnostic metrics in projects led to better schedule performance.

Sackey, S and Kim, B (2018) Environmental and Economic Performance of Asphalt Shingle and Clay Tile Roofing Sheets Using Life Cycle Assessment Approach and TOPSIS. Journal of Construction Engineering and Management, 144(11).

Wang, Z, Hu, H and Gong, J (2018) Modeling Worker Competence to Advance Precast Production Scheduling Optimization. Journal of Construction Engineering and Management, 144(11).

Xu, J, Jin, R, Piroozfar, P, Wang, Y, Kang, B, Ma, L, Wanatowski, D and Yang, T (2018) Constructing a BIM Climate–Based Framework: Regional Case Study in China. Journal of Construction Engineering and Management, 144(11).

Yang, F, Li, X, Song, Z, Li, Y and Zhu, Y (2018) Job Burnout of Construction Project Managers: Considering the Role of Organizational Justice. Journal of Construction Engineering and Management, 144(11).