Statistical Analysis of Hot-Mix Asphalt Pay for Performance versus Quality Control for Performance

Jose J. Rivera-Perez, Seunggu Kang, Watheq Sayeh, Javier Garcia-Mainieri, Imad L. Al-Qadi, Hasan Ozer

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Statistical analysis of hot-mix asphalt (HMA) data for quality assurance programs used by the Illinois DOT was conducted. The aim was to quantify the total amount of incentives and disincentives, and distribution of the measured values, variability of HMA test results and identify significant variations between contractor and agency results. Quality control and quality assurance data for construction projects were collected for the 2015-2017 construction seasons and were statistically analyzed using the Mann-Whitney and Levene's tests. The results indicated that during 2015 and 2016, approximately 44% to 55% of the produced HMA tonnage received disincentives, averaging $20,000 per project, based on 710 projects analyzed. More than 80% of the construction projects showed no significant difference between the quality assurance results reported by the district and contractor quality control results. HMA density was the most frequent pay parameter-caused contractor disincentive, and air void content was the second. The bulk specific gravity test results, which contribute to air void and voids in mineral aggregates, were found to be the most variable and, hence, the main cause of differences between IDOT and contractor laboratory data.

Original languageEnglish (US)
Article number04022016
JournalJournal of Transportation Engineering Part B: Pavements
Issue number2
StatePublished - Jun 1 2022


  • Asphalt mixture
  • Hot-mix asphalt (HMA)
  • Pay for performance
  • Quality assurance
  • Quality control
  • Quality management
  • Specifications
  • Statistical quality control

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation


Dive into the research topics of 'Statistical Analysis of Hot-Mix Asphalt Pay for Performance versus Quality Control for Performance'. Together they form a unique fingerprint.

Cite this