This study aims to examine how gender shapes family business succession, investigating the systematic exclusion of daughters from leadership pathways. It explores the mechanisms through which women are marginalised despite possessing equal or superior qualifications compared to male successors and challenges the assumption that male succession ensures strategic continuity.
A qualitative study using systematic combining was conducted with seven Portuguese family businesses across diverse sectors. Data were collected through semi-structured interviews with founders and successors and analysed using NVivo, combining theoretically derived and inductively emergent coding categories.
Merit-based selection criteria operate through a “veil of meritocracy,” concealing gendered socialisation patterns that determine early access to education, business exposure and developmental opportunities. Daughter exclusion results from the interplay of parental overprotection, occupational segregation, primogeniture and legitimacy narratives. Contrary to prevailing assumptions, male successors frequently accept leadership out of obligation rather than intrinsic motivation.
Family business owners and advisors should critically reassess succession criteria, recognising that access to education and experience is itself shaped by gendered socialisation. Inclusive, transparent succession planning that engages all potential successors from an early age reduces bias, strengthens governance and enhances organisational resilience. Overlooking capable female candidates narrows the strategic talent pool and heightens long-term succession risk.
This study advances family business literature by revealing succession as a governance vulnerability when qualified daughters are systematically excluded. It exposes how meritocratic rhetoric masks structural gender bias, links daughters' invisibility to early-stage exclusion from knowledge transfer and challenges the strategic optimality of obligatory male succession. These contributions are presented as analytically generalisable insights rather than statistically representative findings.
