TY - JOUR
T1 - Variability, Sensitivity, and Econometric Analyses of Field Density in Pay for Performance Data for Hot-Mix Asphalt in Illinois
AU - Sayeh, Watheq
AU - Al-Qadi, Imad L.
N1 - This publication is based on the results from an Illinois Center for Transportation Project, R27-189: Evaluation of Data Trends and Variability in the Quality Control for Performance (QCP) and Pay for Performance (PFP) Programs. The project was conducted in cooperation with the Illinois Department of Transportation and the Illinois Asphalt Pavement Association. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Illinois Department of Transportation (Grant No. R27-189). The help of Jose J. Rivera-Perez, Seunggu Kang, and Javier J. Garcia Mainieri is appreciated. The input of Jim Trepanier, Kevin Burke III, Brian Hill, Dennis Dvorak, Tom Zehr, and other members of the project’s Technical Review Panel is greatly appreciated. The input from Hasan Ozer and Adam Hand is acknowledged.
This publication is based on the results from an Illinois Center for Transportation Project, R27-189: Evaluation of Data Trends and Variability in the Quality Control for Performance (QCP) and Pay for Performance (PFP) Programs. The project was conducted in cooperation with the Illinois Department of Transportation and the Illinois Asphalt Pavement Association. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Illinois Department of Transportation (Grant No. R27-189). The help of Jose J. Rivera-Perez, Seunggu Kang, and Javier J. Garcia Mainieri is appreciated. The input of Jim Trepanier, Kevin Burke III, Brian Hill, Dennis Dvorak, Tom Zehr, and other members of the project's Technical Review Panel is greatly appreciated. The input from Hasan Ozer and Adam Hand is acknowledged.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Pay for Performance (PFP) is a statistical-based quality assurance specification used to evaluate asphalt concrete construction for projects having mix quantities greater than 7,260 t (8,000 US tons). The contractor pay is adjusted based on mix field density, air voids, and voids in mineral aggregate. In this study, data were analyzed from the 2015 to 2017 highway construction seasons in Illinois to determine variability trends. Density was the major factor driving contractor pay disincentives in PFP, followed by air voids. To identify the impact of construction field density consistency on the final pay factor, a sensitivity analysis was performed to determine the changes in the contractor pay with respect to variability, which is measured by standard deviation. In addition, an econometric analysis based on sensitivity analysis using linear regression was conducted. The results showed that a 1% reduction in density standard deviation led to a 0.066 increase in density pay factor. Based on the 79 projects analyzed, if the density standard deviation had been reduced from 1.67 to 1.0, the average increase in pay per project would be $38,000.
AB - Pay for Performance (PFP) is a statistical-based quality assurance specification used to evaluate asphalt concrete construction for projects having mix quantities greater than 7,260 t (8,000 US tons). The contractor pay is adjusted based on mix field density, air voids, and voids in mineral aggregate. In this study, data were analyzed from the 2015 to 2017 highway construction seasons in Illinois to determine variability trends. Density was the major factor driving contractor pay disincentives in PFP, followed by air voids. To identify the impact of construction field density consistency on the final pay factor, a sensitivity analysis was performed to determine the changes in the contractor pay with respect to variability, which is measured by standard deviation. In addition, an econometric analysis based on sensitivity analysis using linear regression was conducted. The results showed that a 1% reduction in density standard deviation led to a 0.066 increase in density pay factor. Based on the 79 projects analyzed, if the density standard deviation had been reduced from 1.67 to 1.0, the average increase in pay per project would be $38,000.
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U2 - 10.1061/JPEODX.PVENG-997
DO - 10.1061/JPEODX.PVENG-997
M3 - Article
AN - SCOPUS:85141810523
SN - 2573-5438
VL - 149
JO - Journal of Transportation Engineering Part B: Pavements
JF - Journal of Transportation Engineering Part B: Pavements
IS - 1
M1 - 04022064
ER -