Model Kepemimpinan Generasi Z dalam Menghadapi Ketidaksetaraan Usia di Tempat Kerja Multigenerasi - Jolin Jolin; Maria Agustina Simbolon; Yenny Afriyanti; Sholeha Sholeha; Satriadi Satriadi (Journal of Economics and Management Scienties, 2026)
This article discusses Generation Z leadership models in addressing age inequality in multigenerational workplaces. Demographic shifts in the workforce have led organizations to bring together Baby Boomers, Generation X, Millennials, and Generation Z in the same workspace. This situation can be a strength if managed inclusively, but it can also give rise to stereotypes, communication gaps, limited opportunities, and age-based discrimination. This article employs a qualitative approach using a narrative-conceptual literature review. Data were collected from journal articles, statistical reports, and relevant conceptual studies on Generation Z, inclusive leadership, adaptive leadership, digital leadership, ageism, and multigenerational workforce management. Data were collected from journal articles, statistical reports, and relevant conceptual studies on Generation Z, inclusive leadership, adaptive leadership, digital leadership, ageism, and multigenerational workforce management. The original contribution of this article lies in the development of the IKA-KPK-Based Gen Z Leadership Model as a conceptual framework that explicitly addresses ageism in the context of Indonesian organizations. This model combines seven components: inclusivity, two-way communication, technological adaptation, cross-generational collaboration, mutual learning, equal opportunity, and psychological safety. The findings of this study indicate that the model can help organizations view age not as a basis for superiority, but as a source of complementary experiences, perspectives, and knowledge. This article concludes that Generation Z leadership has the potential to reduce age inequality when implemented through organizational practices that are fair, participatory, competency-based, and open to further empirical validation