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Burleson, R C, Haas, C T, Tucker, R L and Stanley, A (1998) Multiskilled Labor Utilization Strategies in Construction. Journal of Construction Engineering and Management, 124(06), 480–9.

Camfield, F E (1998) Guidelines for Quarrystone Armor Units. Journal of Construction Engineering and Management, 124(06), 465–6.

Diekmann, J E and Featherman, W D (1998) Assessing Cost Uncertainty: Lessons from Environmental Restoration Projects. Journal of Construction Engineering and Management, 124(06), 445–51.

Finke, M R (1998) A Better Way to Estimate and Mitigate Disruption. Journal of Construction Engineering and Management, 124(06), 490–7.

Harper, R S and Koehn, E (1998) Managing Industrial Construction Safety in Southeast Texas. Journal of Construction Engineering and Management, 124(06), 452–7.

Kale, S and Arditi, D (1998) Business Failures: Liabilities of Newness, Adolescence, and Smallness. Journal of Construction Engineering and Management, 124(06), 458–64.

Konchar, M and Sanvido, V (1998) Comparison of U.S. Project Delivery Systems. Journal of Construction Engineering and Management, 124(06), 435–44.

Molenaar, K R and Songer, A D (1998) Model for Public Sector Design-Build Project Selection. Journal of Construction Engineering and Management, 124(06), 467–79.

Sonmez, R and Rowings, J E (1998) Construction Labor Productivity Modeling with Neural Networks. Journal of Construction Engineering and Management, 124(06), 498–504.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1998)124:6(498)
  • Abstract:
    Construction labor productivity is affected by several factors. Modeling of construction labor productivity could be challenging when effects of multiple factors are considered simultaneously. In this paper a methodology based on the regression and neural network modeling techniques is presented for quantitative evaluation of the impact of multiple factors on productivity. The methodology is applied to develop productivity models for concrete pouring, formwork, and concrete finishing tasks, using data compiled from eight building projects. The predictive behaviors of the models are compared with the previous productivity studies. Model results, advantages of the methodology, and study limitations are discussed.