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Abbasian-Hosseini, S A, Hsiang, S M, Leming, M L and Liu, M (2014) From Social Network to Data Envelopment Analysis: Identifying Benchmarks at the Site Management Level. Journal of Construction Engineering and Management, 140(08).

Arambula, E and Gharaibeh, N (2014) Methods for Accumulating Construction and Material Quality Test Results and Their Effect on Acceptance Decisions. Journal of Construction Engineering and Management, 140(08).

Hanna, A S, Lotfallah, W, Aoun, D G and Asmar, M E (2014) Mathematical Formulation of the Project Quarterback Rating: New Framework to Assess Construction Project Performance. Journal of Construction Engineering and Management, 140(08).

Kim, T W and Fischer, M (2014) Ontology for Representing Building Users’ Activities in Space-Use Analysis. Journal of Construction Engineering and Management, 140(08).

Lau, S, Lu, M and Poon, C (2014) Formalized Approach to Discretize a Continuous Plant in Construction Simulations. Journal of Construction Engineering and Management, 140(08).

Mello Saraiva Caldeira, L M and Brito, A (2014) Use of Soil-Rock Mixtures in Dam Construction. Journal of Construction Engineering and Management, 140(08).

Naderpajouh, N, Mahdavi, A, Hastak, M and Aldrich, D P (2014) Modeling Social Opposition to Infrastructure Development. Journal of Construction Engineering and Management, 140(08).

Pomares, J C, Irles, R, Segovia, E and Ferrer, B (2014) Acceleration and Deflection Analysis for Class C Edge Protection Systems in Construction Work. Journal of Construction Engineering and Management, 140(08).

Sousa, V, Almeida, N M and Dias, L A (2014) Role of Statistics and Engineering Judgment in Developing Optimized Time-Cost Relationship Models. Journal of Construction Engineering and Management, 140(08).

  • Type: Journal Article
  • Keywords: Construction management; Project management; Scheduling; Construction costs; Statistics; Time factors; Construction project scheduling; Time-cost relationship; Regression; Statistics; Engineering judgment; Cost and schedule;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000874
  • Abstract:
    When estimating the duration of the construction stage during the design stages of construction projects, empirical models are often used as a substitute for more accurate estimates based on detailed scheduling. These models, traditionally designated as time-cost relationships (TCR), derive from regressions relating the duration of concluded construction projects with characteristics that can be easily foreseen during the planning and design stages—both quantitative (e.g., cost, gross floor area, number of floors) and qualitative (e.g., type of contract). This paper reviews the approaches that have been adopted to develop the TCR models and discusses the complementary roles that statistics and engineering judgment can play towards their optimization and enhanced accuracy. This discussion includes the statistical and practical implications of (1) the quantitative independent variables used, (2) the qualitative independent variables used, and (3) the mathematical structure used. The paper aims at demonstrating the importance of sound statistics and highlights some of the most common mistakes. Additionally, it provides illustrative examples to show the complementary role that engineering judgment should have in the process of developing more robust, reliable, and accurate statistical-based TCR.

Xia, B, Skitmore, M, Wu, P and Chen, Q (2014) How Public Owners Communicate the Sustainability Requirements of Green Design-Build Projects. Journal of Construction Engineering and Management, 140(08).

Zhao, X, Hwang, B and Low, S P (2014) Investigating Enterprise Risk Management Maturity in Construction Firms. Journal of Construction Engineering and Management, 140(08).