KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A Bayesian Network-based Decision Framework for Selecting Project Delivery Methods in Highway Construction

    Thumbnail
    View/Open
    Available after: 2020-05-31 (3.322Mb)
    Issue Date
    2018-05-31
    Author
    Bypaneni, Sai Pavan Kumar
    Publisher
    University of Kansas
    Format
    208 pages
    Type
    Dissertation
    Degree Level
    Ph.D.
    Discipline
    Civil, Environmental & Architectural Engineering
    Rights
    Copyright held by the author.
    Metadata
    Show full item record
    Abstract
    Transportation agencies currently have several options in delivering their highway construction projects. Selecting an appropriate project delivery method (PDM) is a complex decision-making process. Researchers and transportation industry practitioners have been striving to discover the knowledge and methodologies to enhance the project delivery decision. However, through conducting an extensive literature review of existing methodologies, it is found that quantitative approaches, implementing probabilistic comparisons, to project delivery decisions are not fully addressed or understood. To fill this gap, this research aims at developing a decision framework by implementing Bayesian Network (BN), an advanced statistical tool, for selecting an appropriate PDM in highway construction industry. The BN-based decision framework incorporates the decision driving factors such as project attributes, risk profiles, project complexity, cost, and time. In developing the BN-based decision framework, this dissertation employed several research methodologies and techniques, including content analysis, questionnaire, case studies, cluster analysis, ANOVA, correlation and reliability analysis, and cross-validation techniques. The dissertation follows a four-journal paper format. The first paper explores the impact of project size on highway design-bid-build (D-B-B) and design-build (D-B) projects. The second paper identifies and evaluates the risks involved in highway project delivery methods: D-B-B, D-B, and construction manager/general contractor (CM/GC). Building upon the findings and results from the first two papers, the third paper determines the probabilistic dependence between the decision factors and develops a theoretical decision framework using BNs for selecting an appropriate PDM. The fourth paper focuses on demonstrating the practical application of the proposed BN-based decision framework using case studies. Also, the final paper presents a k-fold (cross-validation) technique to test and verify the accuracy of the proposed BN-based decision framework. This dissertation contributes to the theoretical body of knowledge by introducing a new quantitative approach using BNs for PDM selection. The findings from this study indicate that implementing BNs facilitate the owner/decision maker in a better understanding of probabilistic comparison and selection of an appropriate PDM for highway construction projects. State transportation agency officials can utilize these findings as a supplemental tool for their project delivery decisions.
    URI
    http://hdl.handle.net/1808/27817
    Collections
    • Engineering Dissertations and Theses [1055]
    • Dissertations [4473]

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps