Abstracts – Browse Results
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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J I (2021) A cost estimation model for improving the budget estimates of industrial plant construction projects, Unpublished PhD Thesis, , The George Washington University.
Adoko, M T (2016) Developing a cost overrun predictive model for complex systems development projects, Unpublished PhD Thesis, , The George Washington University.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L F (2006) Stochastic approach to risk assessment of project finance structures under public private partnerships, Unpublished PhD Thesis, , The George Washington University.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collaboration: How transportation agencies develop skills and systems to manage public-private partnerships, Unpublished PhD Thesis, , The George Washington University.
Cho, S (2000) Sequential estimation and decision-making in project management: A Bayesian way and heuristic approaches, Unpublished PhD Thesis, , The George Washington University.
Farmer, C M (2018) Constructing program management offices for major defense acquisition programs: Factors to consider, Unpublished PhD Thesis, , The George Washington University.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during planned organizational change: A phenomenological study of one firm in the residential construction industry, Unpublished PhD Thesis, , The George Washington University.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 (2018) Predicting military construction project time outcomes using data analytics, Unpublished PhD Thesis, , The George Washington University.
Kim, E (2000) A study on the effective implementation of earned value management methodology, Unpublished PhD Thesis, , The George Washington University.
Lounsbury, C R (1983) From craft to industry: The building process in North Carolina in the nineteenth century, Unpublished PhD Thesis, , The George Washington University.
Ngamthampunpol, D (2008) An assessment of safety management in the Thai construction industry, Unpublished PhD Thesis, , The George Washington University.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Essays on the delivery of public infrastructure projects: Empirical analyses on transportation projects in Florida, Unpublished PhD Thesis, , The George Washington University.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.
- Type: Thesis
- Keywords: accuracy; funding; service delivery; United States; statistical analysis
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2468704153
- Abstract:
Inaccurate forecasts of operating expenditures during the planning phase for new Light Rail Transit (LRT) projects in the United States underestimated future costs by up to 45% (Pickrell, 1989). When operating expenditures exceeded projected levels, local transit agencies often reduced public transit services to operate within their respective annual budgets. Therefore, it is imperative for transit agencies to produce reasonably accurate planning estimates to secure sufficient funding to support future operations, maintenance, and service delivery associated with LRT systems. The research aimed to develop a more accurate LRT operating expenditure predictive model to be used during the planning stage. Traditional statistical analysis and various machine learning-based algorithms were utilized with input from 22 LRT systems in the United States spanning between 2008 to 2018 from various U.S. governmental public databases. This praxis extended the current state of practice that relied primarily on sum of unit-cost estimates (also known as the unit-cost method) which generally failed to produce accurate forecasts due to lack of engineering details at the planning stage. Existing research attempted to develop regression-based methodologies using system-based attributes but did not substantially increase prediction accuracy from using the unit-cost method. The research improved current practices and research by having developed a more accurate and replicable machine learning-based predictive model using available geographic, socio-economic and LRT system-related variables.