Doctoral Dissertations

Keywords and Phrases

Construction Bidding; Game Theory; Graph Theory; Infrastructure; Machine Learning

Abstract

"Construction and infrastructure bidding is a highly competitive process that entails various uncertainties faced by contractors. Contractors weigh various factors to determine the expected benefits of a construction project and decide their bid value. However, the situation is more complex in multi-stage bidding (MSG), where general contractors must account for the bids of their subcontractors and face a greater threat of the winner’s curse (i.e., situation where the winning contractor underestimates the actual cost of the project). As such, bidding-related complexities, risks, and uncertainties, if uncontrolled, can lead to the rise of claims and disputes between stakeholders. Existing research falls short on the aforementioned bidding-related issues. As such, the goal of this research is to improve decision-making processes in construction and infrastructure bidding with a focus on MSG. The associated four modules that tackle these issues using various approaches, including graph theory, game theory, and machine learning, are as follows: (1) Module 1: investigates the factors that impact the bidding decision-making processes and identifies areas of future research needs; (2) Module 2: derives a novel game-theoretic bid function to be utilized by general contractors to deal with the issue of the winner’s curse in MSG; (3) Module 3: creates a holistic framework that aids both general contractors and subcontractors in MSG to deal with the winner’s curse issue; and (4) Module 4: investigates the main causes related to the bidding stage, which lead to disputes in construction and infrastructure projects, and identifies the key associations among them. Collectively, this dissertation paves the way towards improved and practical bidding models and contributes to the knowledge and effectiveness of bidding practices in the construction and infrastructure industry" -- Abstract, p. iii

Advisor(s)

El-Adaway, Islam H.

Committee Member(s)

Showalter, W. Eric
Coatney, Kalyn
Fitch, Mark W.
Long, Suzanna, 1961-

Department(s)

Civil, Architectural and Environmental Engineering

Degree Name

Ph. D. in Civil Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2024

Pagination

xv, 292 pages

Note about bibliography

Includes_bibliographical_references_(pages 261-291)

Rights

©2024 Muaz Osman Elzubeir Ahmed , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12418

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