Abstracts – Browse Results
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Abbiasov, T (2021) Essays in Urban Economics, Unpublished PhD Thesis, , Columbia University.
Asgari, S (2016) Modeling construction competitive bidding: An agent-based approach, Unpublished PhD Thesis, , Columbia University.
Chang, H-H (2002) N-dimensional construction management information system (NDCON): System design and performance modeling through the zero -buffered project management philosophy, Unpublished PhD Thesis, , Columbia University.
Chen, S-M (2002) Intelligent scheduling model and multi-dimensional CM information system, Unpublished PhD Thesis, , Columbia University.
Chiara, N (2006) Real option methods for improving economic risk management in infrastructure project finance, Unpublished PhD Thesis, , Columbia University.
Fitch, G J (2019) System dynamics models for the valuation of real options in infrastructure investments, Unpublished PhD Thesis, , Columbia University.
- Type: Thesis
- Keywords: best value; complexity; procurement method; real options; utilities; design-build-finance-operate; innovation; lifecycle; project delivery; project finance; public-private partnership; risk analysis; simulation; best practice; delivery method; stakeholder
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2315243344
- Abstract:
As public utilities and government owners face increased budget constraints and greater expectations, alternative project delivery methods will increasingly be used to fast track projects, reduce costs, promote innovation and ensure proper performance for various types of facilities and infrastructure systems. The goals of public utility owners along with economic and financial considerations suggest why some project delivery methods have been selected over other project delivery methods. In response, the first phase of this doctoral research presents a model for selecting the optimum project delivery method that considers economic sustainability as well as other goals of multiple project stakeholders. This first phase of research contributes to the existing body of knowledge and benefits industry practitioners by identifying best practices that improve the project delivery selection process while enhancing risk mitigation efforts. The procurement selection process uses multiple-criteria decision-making and financial risk analysis to select the most economically sustainable delivery method given each project's unique characteristics. A present value analysis establishes a range of values that considers variables that will potentially impact lifecycle costs. The selection of the procurement process is based on best value where financial risks to the concerned government and other project stakeholders are mitigated through service fee agreements and project finance structures, which are both dynamic and provide for real options. The second phase of this research presents an innovative approach for the valuation of the types of real options on project finance structures which are specifically procured through a design-build-finance-operate project delivery method (also known as a public-private partnership) (P3). This second phase of research includes an investigation into systems engineering and System Dynamics (SD) simulation modeling. An SD model is used for the valuation of real options attached to a P3 project's finance structure. The valuation of these real options is based on the simulation results related to infrastructure performance. The significance of this research is made greater considering that P3s are increasingly being pursued because of their ability to alleviate pressure on government budgets, promote innovation and implement new technologies. These types of contracts, however, tend to be long-term and often need to account for future yet-to-be-seen variables that potentially impact the feasibility of this procurement method. This is especially true when the P3 project exists within a portfolio of competing assets across infrastructure systems. This second phase of research presents An SD model that is used to analyze the complexity of an infrastructure asset procured through a P3 within such a portfolio. An illustrative case demonstrates how discrete and continuous events potentially impact the successful procurement of infrastructure within a portfolio of competing assets comprising a regional transportation system. This second phase of research contributes to the existing body of knowledge by demonstrating how An SD model can simulate the real-world causal relationships that impact the procurement of infrastructure through P3s. The SD model is used for the valuation of real options to promote public initiatives, encourage private participation and enhance economic sustainability of P3 as a viable procurement strategy. The third and final phase of this doctoral research considers the increasing complexity of infrastructure procurement as individual assets are increasingly viewed as being part of a larger network of interdependent systems. In response, the objective of this final phase is to present a methodology to simulate the behavior of assets that span across different types of infrastructure systems. This investigation presents a method for analyzing investments that traverses across different infrastructure systems with individual assets procured through a variety of project delivery methods. This third investigation also utilizes An SD simulation model. In the final phase of this doctoral research, however, the SD model captures the causal relationships between competing assets where simulation results elucidate the compounding effects of multiple investments that traverse across two or more infrastructure systems. By doing so, this research contributes to the existing body of knowledge and demonstrates how SD models are effectively used to value real options that are termed exotic. These exotic types of real options occur within a portfolio of competing infrastructure assets where the valuation of each real option must consider the compounding effects of competing alternatives as well as the value of the underlying asset. This research presents a methodology for the valuation of multiple types of exotic options in real investments that traverse across various types of infrastructure systems. This method can also be applied to the valuation of other types of exotic options in various industries including research and development pursuits.
Gerstenberger, A J (2021) Modeling the likelihood of construction incidents using public data, Unpublished PhD Thesis, , Teachers College, Columbia University.
Gocmen, F C (2014) Infrastructure scaling and pricing, Unpublished PhD Thesis, , Columbia University.
He, Y (2006) Earthquake loss and risk estimation of buildings by Monte Carlo simulation, Unpublished PhD Thesis, , Columbia University.
Hogan, D B (1998) Modeling construction cost performance: A comprehensive approach using statistical, artificial neural network and simulation methods, Unpublished PhD Thesis, , Columbia University.
Kokkaew, N (2010) Risk flexibility analysis in infrastructure project finance, Unpublished PhD Thesis, , Columbia University.
Li, W (1995) Benefit and cost analysis: Three-dimensional computer models with integrated databases in the management of construction, Unpublished PhD Thesis, , Columbia University.
Lu, Z (2018) Feasibility assessment framework for financing public-private partnership infrastructure projects through asset-backed security, Unpublished PhD Thesis, , Columbia University.
Silver, M L (1981) Craft production: Work and alienation in the construction industry, Unpublished PhD Thesis, , Columbia University.
Song, X (2013) The application of insurance as a risk management tool for alternative dispute resolution (ADR) implementation in construction disputes, Unpublished PhD Thesis, , Columbia University.
Sturts, C S (2001) Value-bidding: An integrative approach utilizing conjoint analysis and classical bidding theory, Unpublished PhD Thesis, , Columbia University.
Subsomboon, K (2004) A procurement and material management (PMM) system based on the fully integrated and automated project process (FIAPP), Unpublished PhD Thesis, , Columbia University.
Sun, W (2023) A self-localized smart hardhat system for construction 4.0, Unpublished PhD Thesis, , Columbia University.
Tavakolan, M (2011) Development of construction projects scheduling with evolutionary algorithms, Unpublished PhD Thesis, , Columbia University.
Teferra, K (2012) Developments in the theory and applications of the variability response function concept, Unpublished PhD Thesis, , Columbia University.
Ucbenli, C (2010) A bargaining mechanism with incomplete information and its application in trilateral BOT negotiations, Unpublished PhD Thesis, , Columbia University.
Unsal, H I (2010) Modeling the hold-up problem and absorptive capacity of project networks, Unpublished PhD Thesis, , Columbia University.
Wang, W (2010) Multivariate stochastic copula-based deterioration models in infrastructure economic risk management, Unpublished PhD Thesis, , Columbia University.