Award Date
12-1-2024
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Civil and Environmental Engineering and Construction
First Committee Member
Jeehee Lee
Second Committee Member
Pramen P. Shrestha
Third Committee Member
Jin Ouk Choi
Fourth Committee Member
Jee Woong Park
Fifth Committee Member
Mingon Kang
Number of Pages
129
Abstract
Construction bid documents encompass project specifications, drawings, schedules, and other critical details and are the foundation for project bidding and execution. Accurate bid documents are essential to ensure project bids are competitive, realistic, and aligned with requirements. However, bid documents are susceptible to risks from various sources. Failure to identify and rectify these risks can result in inaccurate cost estimates and higher bids. Therefore, identifying and resolving risks within bidding or contract documents are of utmost importance. While prior research has shed light on potential risk factors within the bid documents, a noticeable gap remains in the literature regarding identifying bid document-related risks through document-based analysis. Moreover, quantifying project cost and schedule variation remains a challenge. This study identifies bid document-related risks by analyzing pre-bid Request for Information (RFI) and quantifies project cost and schedule changes from change order documents. This study has two primary objectives: 1) identifying substantial bid document-related risks and 2) developing an automated model using Natural Language Processing (NLP) to assess cost and schedule changes for new projects. Historical bid and change order documents obtained from the Transportation-related projects of the Oklahoma Department of Transportation (DOT) are used to fulfill these objectives. The findings of this study showed that 'pay item omission' and 'incorrect quantities' are the most significant bid document-related risks for these transportation-related projects. This study enhances our understanding of risk likelihood and the specific risk types before bidding. The study also proposed a prediction model that gives an F1 score of 79% to forecast changes in cost and 72% for predicting schedule changes, achieving an overall prediction accuracy of 75.5% for cost and schedule changes. This result shows that the proposed model adequately forecasts cost and schedule changes from bid and change order documents. Since the model training and validation are carried out using transportation projects from Oklahoma DOT, the findings might not universally apply to all projects and all locations. However, the proposed methodology can be extended to various projects and adapted to suit different contexts with necessary modifications.
Keywords
change order; construction; cost; project; schedule; transportation
Disciplines
Civil Engineering
File Format
File Size
2300 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Shrestha, Rabin, "Prediction Of Cost and Schedule Changes in Transportation Projects Through Historical Bid and Change Order Document Analysis – Using Oklahoma Dot Project Cases." (2024). UNLV Theses, Dissertations, Professional Papers, and Capstones. 5204.
http://dx.doi.org/10.34917/38330416
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
