Vesali Mahmoud, N (2016) A comprehensive decision support framework in the front-end phase of major transportation projects. PhD thesis, Florida International University, USA.
Abstract
Identifying the best project alternative is a critical challenge facing major transportation projects (MTPs) at the front-end phase. The increasing complexity and dynamism of MTPs have imposed substantial uncertainties and subjectivities in the decision-making process. Despite the efforts made in previous studies, a stochastic framework to facilitate the comprehensive assessment is still missing. In this research, a stochastic decision support framework has been developed to cope with the considerable uncertainties in MTPs. The features of the proposed decision support framework are achieved by using the Bayesian belief network modeling technique to provide a comprehensive registry of the relevant decision factors, establish the interrelationships between these decision factors, and consequently quantify uncertainties of decision indicators. The calculated probabilities for decision indicators have been interpreted to a satisfaction level of stakeholders based on their constraints as a multi-criteria decision model. A Monte Carlo simulation has been conducted to simulate a real condition using the decision indicators probability as input. Finally, MTP alternatives prioritized according to the anticipated satisfactory gained among various stakeholders. The created framework is used in a preliminary alternative assessment for case study related to Detroit River International Crossing project. The case study investigates the decision-making of key stakeholders related to prioritization of alternative projects for a new access between Detroit, US and Winsdor, Canada. The project team verified applicability of the model. The developed framework and the case study highlight the significance of identification of a stochastic project alternative assessment method. The proposed framework provides decision-makers with a decision support tool to facilitate front-end phase of MTPs.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Bayraktar, M E and Jin, X |
| Uncontrolled Keywords: | complexity; decision support; project team; stakeholders; Canada; probability; case study; Monte Carlo simulation; simulation |
| Index terms: | decision-making, complexity, decision support, bayesian belief network, transportation project, subjectivity, project team, modelling, case study, satisfaction, Canada, decision-making process, Monte Carlo simulation |
| Subjects: | project delivery, modelling and simulation, data collection methods, systems engineering, infrastructure and transport systems, decision analysis, probabilistic model, analytical methods, human factors and perception, Geography |
| Topics: | Digital Applications, Research Practice, Risk Management, Engineering Principles, Geographical Context, Project Management |
| Descriptive scope: | 4 PCEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here