Career outcomes of women in the AEC industry: a predictive analysis of gender barriers

Purpose Diversity improves innovation and performance, yet sectors continue to underutilize women's expertise due to structural and cultural barriers. While global studies often describe these challenges, they rarely test their impact on careers. In countries such as Ethiopia, the subject is rarely studied, although its impact is crucial. This research addresses these gaps by examining career development, quantifying clustered barriers and assessing their predictive effects on career disruption and intent-to-leave among 332 professional women in Ethiopia's AEC industry. Design/methodology/approach The study employed a modeling framework using exploratory factor analysis, structural equation modeling, logistic regression and predictive modeling using receiver operating characteristic (ROC) analysis. Six latent constructs (46 items) were identified and analyzed to determine their influence on women's career outcomes. Findings Gender policy and institutional gaps, along with work-life conflict, emerged as the strongest predictors of intent-to-leave and career disruption, affecting nearly half of the participants. Patriarchal norms and social pressure showed a marginally protective effect, suggesting adaptive strategies that challenge dominant constraint narratives, though they also contribute to stagnation. Predictive performance was acceptable, with ROC area-under-curve values of 0.629 for intent to leave and 0.667 for career disruption. The models demonstrated complementary strengths: higher sensitivity for intent-to-leave (77.42%) and higher specificity for career disruption (76.6%). Originality/value By quantifying clustered barriers, this study advances understanding from descriptive categorization to predictive modeling, highlighting institutional neglect as the key driver of disrupted career pathways and providing a transferable background for gendered career analysis and SDG 5(Gender Equality) implementation in the industry.