Operationalizing academic entrepreneurship: An organizational-level model of knowledge transfer in Universities

Uglješa Marjanović et al.

International Journal of Entrepreneurship and Innovation2026https://doi.org/10.1177/14657503261438625article
AJG 2ABDC C
Weight
0.50

What the paper says

This study investigates organizational mechanisms that enable academic entrepreneurship and Knowledge Transfer (KT) in universities. As universities increasingly engage in industry collaboration—their “third mission”—KT plays a key role in research commercialization and fostering entrepreneurial ecosystems. Using a grounded theory approach, the study develops a process model emphasizing infrastructure, enabling mechanisms, and valorization. Data were gathered through interviews with university leaders, Knowledge Transfer Office (KTO) staff, and company representatives across Europe. Findings highlight the importance of talent profiles, administrative support, and industry engagement. KTOs emerge as vital connectors between research and market opportunities, supported by leadership, policy, and funding structures. The proposed model explains how universities can systematize KT and entrepreneurship internally. By emphasizing the often-overlooked role of administrative staff and structured organizational processes, the research offers practical and theoretical insights for building more effective university–industry collaborations.

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https://doi.org/https://doi.org/10.1177/14657503261438625

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@article{uglješa2026,
  title        = {{Operationalizing academic entrepreneurship: An organizational-level model of knowledge transfer in Universities}},
  author       = {Uglješa Marjanović et al.},
  journal      = {International Journal of Entrepreneurship and Innovation},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/14657503261438625},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.