Who Gets Hired and Paid: An Experimental Analysis of Gender Bias in the Construction Workforce

Despite growing attention to diversity in construction, mechanisms driving gender-based disparities in hiring and compensation remain insufficiently examined using experimental methods. Seventy construction workers across 22 US project sites completed a randomized vignette survey with matched applicant profiles. Hiring and salary outcomes were analyzed using mixed-effects logistic and linear regression models. Hiring decisions showed no statistically significant applicant-gender effect ( p = 0.730 ) under structured, qualification-matched conditions. No overall applicant-gender difference was detected in salary recommendations. In contrast, applicant experience and task risk significantly increased salary estimates, indicating that evaluators responded systematically to competence and context cues. Evaluator gender produced a substantial compensation effect: female evaluators recommended approximately $13,000 higher annual salaries than male evaluators ( B = − 13,240 ; p < 0.001 ; d = 0.50 ), persisting after controlling for experience and age ( B = − 10,831 ; p = 0.002 ). The applicant gender × task risk interaction was not statistically significant; further, descriptive patterns suggesting higher male pay for moderate-risk tasks are presented as exploratory. Attitudinal measures revealed large gender differences ( d = 0.73 to 1.16), with male evaluators expressing more traditional views. Overall, structured evaluation attenuated applicant-gender disparities, whereas evaluator identity and attitudinal orientation were strongly associated with compensation norms.