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Abdenour, J I (2021) A cost estimation model for improving the budget estimates of industrial plant construction projects, Unpublished PhD Thesis, , The George Washington University.

  • Type: Thesis
  • Keywords: accuracy; construction cost; construction project; cost estimation; equipment; project cost; site work; stakeholders
  • ISBN/ISSN:
  • URL: https://www.proquest.com/docview/2568678359
  • Abstract:
    It is well established that construction projects do not meet their cost budgets. Part of the problem is because cost budgets are not based on definitive cost estimates that are founded on detailed design and engineering, but rather they are based on preliminary cost estimates prepared when the level of project definition is less than 40% at its best. While the expected accuracy range of preliminary cost estimates is between -20% to +30%, past research found that on average over 85% of estimates come closer to the higher end of accuracy range at 28%. This praxis introduces a multiple linear regression model that utilizes some of the project cost elements to estimate its construction cost. This new hybrid (stochastic/deterministic) cost estimation method improves the preliminary cost estimates of industrial plant construction projects. The new model can estimate construction costs within 15% accuracy, which is comparable to results from definitive cost estimates, yet at less than 40% project definition. While definitive cost estimates require detailed project definition for a full set of 15 cost elements, the new model requires only 3, site works, electrical works and auxiliary equipment works. It can be applied earlier in the life of the project to compute improved preliminary cost estimates, providing the project stakeholders with more accurate cost budgets. The model was developed using 32 definitive cost estimates, for small industrial plant projects under US$50 million, and their actual construction costs. It was tested using 4 different datasets reserved for model validation. It has an R2(adj) and R2 (pred) of 82.34% and 79.41% respectively, and an overall regression p-value of 0.000.

Adoko, M T (2016) Developing a cost overrun predictive model for complex systems development projects, Unpublished PhD Thesis, , The George Washington University.

Alves, L F (2006) Stochastic approach to risk assessment of project finance structures under public private partnerships, Unpublished PhD Thesis, , The George Washington University.

Boyer, E J (2012) Building capacity for cross-sector collaboration: How transportation agencies develop skills and systems to manage public-private partnerships, Unpublished PhD Thesis, , The George Washington University.

Cho, S (2000) Sequential estimation and decision-making in project management: A Bayesian way and heuristic approaches, Unpublished PhD Thesis, , The George Washington University.

Farmer, C M (2018) Constructing program management offices for major defense acquisition programs: Factors to consider, Unpublished PhD Thesis, , The George Washington University.

Griffin, M G (2008) The lived experience of first line managers during planned organizational change: A phenomenological study of one firm in the residential construction industry, Unpublished PhD Thesis, , The George Washington University.

Innocent, M J F, Jr. (2018) Predicting military construction project time outcomes using data analytics, Unpublished PhD Thesis, , The George Washington University.

Kim, E (2000) A study on the effective implementation of earned value management methodology, Unpublished PhD Thesis, , The George Washington University.

Lounsbury, C R (1983) From craft to industry: The building process in North Carolina in the nineteenth century, Unpublished PhD Thesis, , The George Washington University.

Ngamthampunpol, D (2008) An assessment of safety management in the Thai construction industry, Unpublished PhD Thesis, , The George Washington University.

Park, J (2015) Essays on the delivery of public infrastructure projects: Empirical analyses on transportation projects in Florida, Unpublished PhD Thesis, , The George Washington University.

Schulte, W D, Jr. (1999) The effect of international corporate strategies and information and communication technologies on competitive advantage and firm performance: An exploratory study of the international engineering, procurement and construction (IEPC) industry, Unpublished PhD Thesis, , The George Washington University.

Shamma, E M (1988) A dynamic model for the growth of construction firms, Unpublished PhD Thesis, , The George Washington University.

Taku, A M (2021) Predicting modular efficiency in oil and gas capital projects using multi-criteria decision analysis, Unpublished PhD Thesis, , The George Washington University.

Zhou, G (2021) Machine learning-based cost predictive model for better operating expenditure estimations of U.S. light rail transit projects, Unpublished PhD Thesis, , The George Washington University.