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    Uncertainties Prevailing in Construction Bid Documents and Their Impact on Project Pricing through the Analysis of Prebid Requests for Information

    Source: Journal of Management in Engineering:;2023:;Volume ( 039 ):;issue: 006::page 04023040-1
    Author:
    Rabin Shrestha
    ,
    Taewoo Ko
    ,
    JeeHee Lee
    DOI: 10.1061/JMENEA.MEENG-5475
    Publisher: ASCE
    Abstract: Construction bid documents may contain uncertain or incomplete information that can affect project pricing as well as project performance, if not addressed prior to bidding. To resolve the uncertainties and clarify project requirements, the risk and uncertainties prevailing in the document should be identified at an early stage of the project life cycle. In this study, pre-bid request for information (RFI) is utilized as a key clue to quantify project ambiguities and uncertainties of a bid document, as pre-bid RFI is generated by bidders when any ambiguous or incomplete information is encountered in the bid document. Despite the significance of pre-bid RFI in quantifying project uncertainty, studies considering pre-bid RFI to identify project uncertainty are limited. Driven by document-based analysis, this study aims to investigate what uncertainties are frequently encountered in bid documents and how they affect project pricing. To achieve the research goal, this study will (1) identify the prevailing risks/uncertainties in the bid document; (2) determine the most common risks/uncertainties and their impacts on bid price; and (3) verify the significance of pre-bid RFIs in bid uncertainty prediction models. To achieve these objectives, public project data from US state Departments of Transportation (DOTs) were collected and used for frequency analysis, correlation testing, and machine learning-based prediction models. The results of uncertainty prediction models showed that uncertainties driven by pre-bid RFI analysis can improve the project risk prediction up to 15%, verifying the significance of RFIs in the bid price prediction model. This study will contribute to the construction management body of knowledge by clarifying the likelihood of errors and uncertainties that should be checked before bidding, thereby proactively preventing future design changes, claims, and dispute risks.
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      Uncertainties Prevailing in Construction Bid Documents and Their Impact on Project Pricing through the Analysis of Prebid Requests for Information

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4293976
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    contributor authorRabin Shrestha
    contributor authorTaewoo Ko
    contributor authorJeeHee Lee
    date accessioned2023-11-27T23:56:50Z
    date available2023-11-27T23:56:50Z
    date issued8/23/2023 12:00:00 AM
    date issued2023-08-23
    identifier otherJMENEA.MEENG-5475.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293976
    description abstractConstruction bid documents may contain uncertain or incomplete information that can affect project pricing as well as project performance, if not addressed prior to bidding. To resolve the uncertainties and clarify project requirements, the risk and uncertainties prevailing in the document should be identified at an early stage of the project life cycle. In this study, pre-bid request for information (RFI) is utilized as a key clue to quantify project ambiguities and uncertainties of a bid document, as pre-bid RFI is generated by bidders when any ambiguous or incomplete information is encountered in the bid document. Despite the significance of pre-bid RFI in quantifying project uncertainty, studies considering pre-bid RFI to identify project uncertainty are limited. Driven by document-based analysis, this study aims to investigate what uncertainties are frequently encountered in bid documents and how they affect project pricing. To achieve the research goal, this study will (1) identify the prevailing risks/uncertainties in the bid document; (2) determine the most common risks/uncertainties and their impacts on bid price; and (3) verify the significance of pre-bid RFIs in bid uncertainty prediction models. To achieve these objectives, public project data from US state Departments of Transportation (DOTs) were collected and used for frequency analysis, correlation testing, and machine learning-based prediction models. The results of uncertainty prediction models showed that uncertainties driven by pre-bid RFI analysis can improve the project risk prediction up to 15%, verifying the significance of RFIs in the bid price prediction model. This study will contribute to the construction management body of knowledge by clarifying the likelihood of errors and uncertainties that should be checked before bidding, thereby proactively preventing future design changes, claims, and dispute risks.
    publisherASCE
    titleUncertainties Prevailing in Construction Bid Documents and Their Impact on Project Pricing through the Analysis of Prebid Requests for Information
    typeJournal Article
    journal volume39
    journal issue6
    journal titleJournal of Management in Engineering
    identifier doi10.1061/JMENEA.MEENG-5475
    journal fristpage04023040-1
    journal lastpage04023040-13
    page13
    treeJournal of Management in Engineering:;2023:;Volume ( 039 ):;issue: 006
    contenttypeFulltext
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