Alternative Contracting Methods: Modeling and Assessing the Effects of Contract Type on Time-Cost-Change Performance

AbstractAlthough the use of alternative contracting methods (ACMs) has become increasingly common, little is known about their effects on a project’s time-cost-change performance. This study draws from 2,572 project datapoints, addressing this research gap by plotting, analyzing, and validating high...

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Bibliographic Details
Published in:Journal of management in engineering 2021-01, Vol.37 (1)
Main Authors: Choi, Kunhee, Yin, Yangtian, Goehl, Darlene, Jeong, H. David
Format: Article
Language:English
Subjects:
Contingency
Contingency plans
Contraction
Incentives
Performance evaluation
Performance prediction
Prediction models
Risk assessment
Schedules
Technical Papers
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Summary:AbstractAlthough the use of alternative contracting methods (ACMs) has become increasingly common, little is known about their effects on a project’s time-cost-change performance. This study draws from 2,572 project datapoints, addressing this research gap by plotting, analyzing, and validating high confidence performance indicators. The effects of different ACMs on project time, cost, and change performance were all evaluated and time-cost performance prediction models developed and tested. The results reveal that the use of incentives/disincentives is preferable for reducing the duration of a project. Lump-sum contracting is an effective choice for onbudget project delivery, while cost-plus-time bidding is significantly less effective than incentives/disincentives and no-excuse bonus contracting. Notably, the results also convey that ACMs with large project sizes are more prone to schedule delays and cost overruns. The robustness of the predictive models was verified by a predicted error sum of squares validation. The findings of this study will help state transportation agencies make better-informed decisions by providing foresight regarding the pros and cons of ACMs for aspects of project time-cost-change performance. The use of the predictive models will also assist agencies in justifying the probable time-cost impact of project change orders, enabling them to conduct more reliable risk assessments and develop more realistic contingency plans in the project scoping phase.
ISSN:0742-597X
1943-5479
DOI:10.1061/(ASCE)ME.1943-5479.0000863