Fit to co-lead? Developing a model of individual antecedents for effective topsharing

Introduction: Topsharing represents a specific form of shared leadership, in which two co-leaders occupy a single leadership position. Although Topsharing has become a popular leadership structure across a variety of organizations, leadership research has rather neglected this topic. In particular, little is known about individual antecedents of successful co-leadership. Building on the KSAO-framework, current research aims to identify knowledge, skills, attitudes/values, and personality attributes relevant for co-leaders. These factors will be integrated into a conceptual model that can be used to evaluate the fit of co-leadership arrangements in a systematic way. Methods: We used a mixed-methods design combining qualitative interviews with an online survey. We conducted 17 interviews with co-leaders (13 female, 4 male, average duration 44 minutes). The interviews are currently being analyzed using theory-based content analysis. To validate the interview data, an online survey with a prospective sample size of 150 leaders will be conducted in April. Results: Preliminary findings suggest that both complementary and supplementary factors play a role. However, complementary factors, that is, both co-leaders having similar individual antecedents, seem to be of greater relevance. Conclusions: By developing a theory-based model of the antecedents for successful Topsharing, the current study contributes to research on shared leadership. Moreover, as a practical contribution, our model can be used as a basis to for selecting and developing co-leaders.

Publication Details

Journal
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Published
2025-09-08
Primary Topic
Geochemistry and Geologic Mapping
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article
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article

Fit to co-lead? Developing a model of individual antecedents for effective topsharing

Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Geochemistry and Geologic Mapping
article

Fit to co-lead? Developing a model of individual antecedents for effective topsharing

article en

Abstract

Introduction: Topsharing represents a specific form of shared leadership, in which two co-leaders occupy a single leadership position. Although Topsharing has become a popular leadership structure across a variety of organizations, leadership research has rather neglected this topic. In particular, little is known about individual antecedents of successful co-leadership. Building on the KSAO-framework, current research aims to identify knowledge, skills, attitudes/values, and personality attributes relevant for co-leaders. These factors will be integrated into a conceptual model that can be used to evaluate the fit of co-leadership arrangements in a systematic way. Methods: We used a mixed-methods design combining qualitative interviews with an online survey. We conducted 17 interviews with co-leaders (13 female, 4 male, average duration 44 minutes). The interviews are currently being analyzed using theory-based content analysis. To validate the interview data, an online survey with a prospective sample size of 150 leaders will be conducted in April. Results: Preliminary findings suggest that both complementary and supplementary factors play a role. However, complementary factors, that is, both co-leaders having similar individual antecedents, seem to be of greater relevance. Conclusions: By developing a theory-based model of the antecedents for successful Topsharing, the current study contributes to research on shared leadership. Moreover, as a practical contribution, our model can be used as a basis to for selecting and developing co-leaders.

Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Openalex Percentile: Top 27%
Geochemistry and Geologic Mapping
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Fit to co-lead? Developing a model of individual antecedents for effective topsharing · Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) (2025) | TGRS Research Map | TGRS