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Aramali, V, Gibson, G E, El Asmar, M and Sanboskani, H (2023) Novel earned value management system maturity framework and its relation to project performance. Journal of Construction Engineering and Management, 149(06).

Arora, J, Kar, S and Jha, K N (2023) Assessment of the significance of identified attributes affecting the rebar-fixing productivity using multiple regression. Journal of Construction Engineering and Management, 149(06).

Asadi, R, Rotimi, J O B and Wilkinson, S (2023) Analyzing underlying factors of rework in generating contractual claims in construction projects. Journal of Construction Engineering and Management, 149(06).

Hsu, C L, Wang, J T and Huang, Y H (2023) A functional element-naming approach for BIM elements in building envelope systems. Journal of Construction Engineering and Management, 149(06).

Karamoozian, A, Wu, D and Luo, C (2023) Green supplier selection in the construction industry using a novel fuzzy decision-making approach. Journal of Construction Engineering and Management, 149(06).

Long, W, Wang, X, Liang, Y and Ye, K (2023) Characteristics of collusive practices in bidding: Mixed methods study in China. Journal of Construction Engineering and Management, 149(06).

Nguyen, T Q, Yeoh, J K W and Angelia, N (2023) Predicting percent plan complete through time series analysis. Journal of Construction Engineering and Management, 149(06).

  • Type: Journal Article
  • Keywords: construction delay; percent plan complete; prediction; reason for noncompletion; time series
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-12867
  • Abstract:
    The percent plan complete (PPC) is a crucial performance metric for a last planner system (LPS). The high positive correlations of the PPC with time and cost performance enable a project team to obtain long-term projections from microachievements. Because predicting PPCs is helpful for project control, this study aimed to investigate the temporal nature of PPCs and develop a time series modeling framework for PPC forecasting based on historical PPCs and the reasons for noncompletion (RNCs). This study found that, although PPCs and RNCs are captured weekly, their impacts on future performance can spread over a longer time span, and future PPCs can be predicted based on historical values. A minimum data time frame of 18 weeks was proposed in the context of the case project. Historical RNCs also impact PPC forecasting. The inclusion of key RNCs can help improve the forecasting accuracy. The findings from this study provide an insight to the hidden temporal nature of the PPC metric resulting from the practical implementation of the LPS. This model can be used as a prediction tool, allowing project teams to anticipate project outcomes and design suitable execution strategies.

Rathnayake, A and Middleton, C (2023) Systematic review of the literature on construction productivity. Journal of Construction Engineering and Management, 149(06).

Tao, Y, Hu, H, Xu, F and Zhang, Z (2023) Ergonomic risk assessment of construction workers and projects based on fuzzy Bayesian network and D-S evidence theory. Journal of Construction Engineering and Management, 149(06).

Tarekegn Gurmu, A (2023) Preconstruction phase management practices enhancing labor productivity in multistory building projects. Journal of Construction Engineering and Management, 149(06).

Tatari, A (2023) Simulating cost risks for prefabricated construction in developing countries using Bayesian networks. Journal of Construction Engineering and Management, 149(06).

Wang, Y, Chen, L and Zhuang, J (2023) Pricing of credit default swaps from the perspective of credit enhancement in PPP projects. Journal of Construction Engineering and Management, 149(06).

Zhang, W, Zhang, H and Yu, L (2023) Collaborative planning for stacking and installation of prefabricated building components regarding crane-collision avoidance. Journal of Construction Engineering and Management, 149(06).