Proposed models to measure the quality of highway projects: Regression analysis vs statistical – fuzzy approach

Quality measurement is the trigger for quality improvement. Indeed, what gets measured gets done. The real scope of quality improvement in construction projects is the difficulty and-maybe-lack of quality measurement methods. The purpose of this paper is to identify the factors influencing the quality performance of highway projects in Egypt. Furthermore, this paper also contributes to develop models to measure the quality level of these projects.

A literature review is conducted to compile a list of factors influencing the quality of highway projects. The resulting list of factors is subjected to a questionnaire survey which was sent to owners, consultants and contractors of highway projects in Egypt. Furthermore, linear regression analysis and statistical fuzzy approaches are adopted for modeling process.

The survey results show that availability of experienced staff in the owner’s and contractor’s teams during the project execution, asphalt quality and type used in the construction process, pavement is not designed according to the regional conditions, and contractor’s labors and equipment capability are among the most important factors influencing quality performance.

The main contribution of this study is to develop models to measure the quality of highway projects in Egypt. The first model is based on the linear regression analysis, while the second one is based on a statistical fuzzy approach which is a hybrid approach from the fuzzy logic and regression analysis. Validation of the models reveals that the linear regression and the statistical fuzzy models can accurately assess expected quality of any future highway projects at confidence levels 68.97 and 87.44 percent, respectively.