The leadership literature encompasses a bewildering array of leadership styles, with most studies focussing on the nature and consequences of a single leadership style in isolation. This isolationist approach has led researchers to mostly ignore the similarities between supposedly different leadership styles, and few studies have examined these overlaps empirically. To understand the extent of this problem, we use bifactor exploratory structural equation modelling to examine whether 12 dominant leadership measures capture shared variance and whether any variance unique to a particular style is related to theoretically and empirically established covariates. Moreover, we explore what the shared variance of these leadership measures may represent. Across seven samples, five countries, multiple organizational contexts, and 4000 respondents, the 12 leadership measures shared significant amounts of variance and did not systematically capture unique leadership-related variance. Further analyses indicated this shared variance mainly represented the affective quality of the leader–follower relationship. The results reveal an inconvenient truth for leadership researchers who wish to differentiate styles, as the styles have much more in common than differences. Contrasting with previous recommendations to refine styles, we argue that a taxonomic leadership behaviour categories approach to leadership research is the most parsimonious way forward.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)