Abstract
Leader behavior is essential for creating inclusive organizations. The disruptive context of the COVID-19 pandemic forced many people to work remotely and leaders to cope with the disruption of their teams' workflows and work arrangements. However, fixed sets of leader behavior as well as stable and shared physical contexts are implicit assumptions in current knowledge and theorizing on inclusive leadership. Therefore, in this study, we first synthesize inclusive leadership literature with leader adaptability and context-sensitive leadership studies. Next, drawing on 47 interviews with leaders and their followers, we unravel how the enactment of aspired inclusive leadership behaviors was hampered due to the pandemic-related disruption, and explain how leaders adjusted their inclusive behaviors in response to these difficulties. From these findings, we develop a model that suggests rather than a static set of inclusive leader behaviors, inclusive leadership is enacted through the continuous adjustment on leaders' perceptions of the context and followers' feelings of inclusion.
| Original language | English |
|---|---|
| Pages (from-to) | 1315-1343 |
| Number of pages | 29 |
| Journal | Journal of Organizational Behavior |
| Volume | 45 |
| Issue number | 9 |
| Early online date | 2 Jan 2024 |
| DOIs | |
| Publication status | Published - Nov 2024 |
Bibliographical note
Publisher Copyright:© 2023 The Authors. Journal of Organizational Behavior published by John Wiley & Sons Ltd.
Funding
The authors would like to thank Ayfer Veli Korkmaz, the guest editors, specifically Dr. Andri Georgiadou, and the anonymous reviewers for their comments on the earlier versions of the manuscript. We would like to thank the participants, as well as Catarina Ripamonti, Elodie Schulte, Josephine zu Stolberg, and Diede Visser for their assistance with the fieldwork.
| Funders | Funder number |
|---|---|
| Ayfer Veli Korkmaz |
Keywords
- diversity
- individual differences (personality, values, traits)
- leadership
- qualitative data analysis