Development of a Simulation Model to Predict the Impact of Incentive Contracts on Transportation Construction Project Time Performance PDF Download
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Author: Jae-Ho Pyeon
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
ABSTRACT: Many state highway agencies use incentive contracting methods to improve highway construction project time performance. In general, while reducing project construction time will reduce driver inconveniences caused by construction, few studies have been conducted to evaluate the efficiency of incentive contracting for highway construction projects. Thus, this study focused on developing a model to predict incentive project time performance and to suggest approaches to improve project time performance for Florida Department of Transportation (FDOT) highway construction. A decision-support simulation model using Monte Carlo simulation methods was developed to analyze and improve the efficiency of incentive contracting using key factors in FDOT highway construction projects. The simulation results are presented in the form of probability distributions.
Author: Jae-Ho Pyeon
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
ABSTRACT: Many state highway agencies use incentive contracting methods to improve highway construction project time performance. In general, while reducing project construction time will reduce driver inconveniences caused by construction, few studies have been conducted to evaluate the efficiency of incentive contracting for highway construction projects. Thus, this study focused on developing a model to predict incentive project time performance and to suggest approaches to improve project time performance for Florida Department of Transportation (FDOT) highway construction. A decision-support simulation model using Monte Carlo simulation methods was developed to analyze and improve the efficiency of incentive contracting using key factors in FDOT highway construction projects. The simulation results are presented in the form of probability distributions.
Author: Gary J. Fick
Publisher: Transportation Research Board
ISBN: 0309154782
Category : Business & Economics
Languages : en
Pages : 76
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Book Description
This report will be of interest to state and local highway agency construction managers and contractors with regard to learning about best practices of time-related incentive and disincentive contract provisions and their effect on staffing levels, productivity, project cost, quality, contract administration, and the contractor's operations and innovations. The report also presents a decision process guide to use as a template for crafting the incentive/disincentive provisions.
Author:
Publisher:
ISBN:
Category : Highway research
Languages : en
Pages : 508
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Book Description
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 854
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Book Description
Author: Jin-Fang Shr
Publisher:
ISBN:
Category :
Languages : en
Pages : 204
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Book Description
Currently, most SHAs and contractors use traditional methods. However, more exact time estimates and closer cost predictions are necessary to enable the use of these innovative methods. This research will explore the following topics. For the Florida Department of Transportation (FDOT) (1) how to determine a reasonable range of B in an A + B contract, and (2) how to determine a maximum incentive and maximum days of incentive in an I/D contract. For contractors interested in FDOT projects, (1) what is the best strategy to determine a bid price in an I/D contract, and (2) what is the best strategy to determine a bid price using an A + B + I/D contract. Data from the Florida Department of Transportation (FDOT) are used to verify models to respond to the topics above.
Author: Jae H. Pyeon
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 82
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Book Description
Author: Jae H. Pyeon
Publisher:
ISBN:
Category : Decision support systems
Languages : en
Pages : 82
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Book Description
Author: Sai On Cheung
Publisher: Springer Nature
ISBN: 3031289595
Category : Technology & Engineering
Languages : en
Pages : 297
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Book Description
This book proposes ways to make construction project incentive schemes effective. In this book, construction incentivization is used as a collective term that includes all forms of incentive arrangements aiming to engender extra effort of the contracting parties for the improvement of project performance. This book addresses two questions: i) why so many construction incentive schemes are not delivering the desired outcome? and ii) what will make incentive works under different circumstances? This book contributes to the body of knowledge in construction incentivization by offering conceptualization, showcases and practice suggestions including guidelines for the planning of construction incentive schemes.
Author: Hyung Seok Jeong
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 0
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Book Description
MDT is in the process of modernizing their contract time determination processes by developing user-friendly tools to facilitate the estimation process of project duration and contract time. As part of this modernization effort, a top-down project duration estimation tool was developed in this research project. This tool is particularly useful when there is limited project information available during the early preconstruction stages. This research project involved the development of an Artificial Intelligence (AI) based model that can predict the most probable duration of a construction project using an early cost estimate, major controlling work items, and their estimated quantities as input values. Additionally, a regression model with the same set of input variables was developed as a companion to the AI model. The models were trained and tested using historical project data of more than 1,000 highway projects from 2008 to 2019. To operationalize the models, a user-friendly Microsoft Excel tool named AI-PDET (Artificial Intelligence based Project Duration Estimation Model) was created. AI-PDET can be used throughout the preconstruction phases to quickly determine a reasonable project duration for proper project planning and delivery. Furthermore, it can serve as a reality check tool alongside bottom-up tools during the procurement stage. This report also provides specific guidance on updating the models and the database with new project data in AI-PDET.
Author: Sang Choon Lhee
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
ABSTRACT: Construction projects involve many uncertainties and risks in all phases. As a result, all types of construction projects, including transportation projects, have historically experienced significant cost increases. Project contingencies are important items in the cost estimate for compensating unforeseen risks against underestimating project costs and budget overruns. Generally, a contingency is represented as a fixed percentage of project cost. However, it is not appropriate to apply this deterministic method to all construction projects because it provides an arbitrary percentage value based on only the project costs. The purpose of this study was to develop an artificial neural network model that was able to predict the required contingency amount on transportation construction projects for project owners or sponsors like DOT (Department of Transportation). In order to obtain this ultimate goal, factors that affect the owner's contingency were identified, their weights in contributing to the contingency were discovered, and an appropriate form of the owner's contingency was found with FDOT (Florida Department of Transportation) project data from projects that were completed from 2004 to 2006. The best artificial neural network model to predict the owner's contingency using the NeuroShell Predictor software was discovered and a predictive tool was developed using a Microsoft Excel spreadsheet. The more accurate predictions of the contingency from this study can be used to better manage project contingency requirements and allow for additional projects to be brought online at a faster pace.
