A general assumption in public sector research is that public organizations have to be efficient and innovative to overcome challenges such as demographic changes and digitization. This argument has been discussed in light of ambidexterity theory, for example. However, only little public sector research has focused on "how" public organizations reach ambidexterity. We take this question into account and focus on design and leadership conditions that are necessary or sufficient for ambidexterity. More precisely, the main question of this article is: Which combination of leadership and design conditions plays a role for ambidexterity in public organizations? We theoretically rely on the concept of ambidexterity, collected data in Belgian public cultural centers, and analyzed the data via the set-theoretic method Qualitative Comparative Analysis (QCA). We can conclude from our analysis that six different combinations of design and leadership conditions were found to be sufficient for ambidexterity in our dataset. What is more is that public organizations combine design and leadership conditions of both structural and contextual ambidexterity to balance simultaneously exploitation and exploration. Hereby this article provides new theoretical and empirical insights and offers opportunities for further ambidexterity research in public organizations.
机构:
Univ Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, Sweden
Kristiania Univ Coll, Oslo, NorwayUniv Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, Sweden
Magnusson, Johan
Khisro, Jwan
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机构:
Univ Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, SwedenUniv Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, Sweden
Khisro, Jwan
Bjorses, Max
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机构:
CapGemini Sweden, Stockholm, SwedenUniv Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, Sweden
Bjorses, Max
Ivarsson, Aleksander
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机构:
Advectas AB, Gothenburg, SwedenUniv Gothenburg, Swedish Ctr Digital Innovat, Gothenburg, Sweden
机构:
Peking Univ, Sch Govt, Beijing, Peoples R China
Shanghai Jiao Tong Univ, China Inst Urban Governance, Sch Int & Publ Affairs, Shanghai, Peoples R ChinaPeking Univ, Sch Govt, Beijing, Peoples R China
Xiang, Tianyi
Chen, Yifan
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机构:
PKU WUHAN Inst Artificial Intelligence, Urban Governance Lab, Wuhan, Hubei, Peoples R China
Shanghai Jiao Tong Univ, 1954 Huashan Rd, Shanghai 20, Peoples R ChinaPeking Univ, Sch Govt, Beijing, Peoples R China
机构:
Univ Ghent, Fac Econ & Business Adm, Dept Business Informat & Operat Management, Ghent, BelgiumUniv Ghent, Fac Econ & Business Adm, Dept Business Informat & Operat Management, Ghent, Belgium
Helbin, Tomek
[J].
2019 13TH INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN INFORMATION SCIENCE (RCIS),
2019,
: 357
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