What makes an entrepreneurial university? Institutional moderators of ecosystem impacts in a developing country.
Published In: Science & Public Policy (SPP), 2024, v. 51, n. 1. P. 108 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Schaeffer, Paola Rücker; Fischer, Bruno Brandão; Queiroz, Sérgio; Moraes, Gustavo Hermínio Salati Marcondes de 3 of 3
Abstract
Entrepreneurial universities have become a key concept in debates concerning regional economic development. Yet, we still fall short of having a clear comprehension of the enablers of such localized impacts arising from academic activity. Such conditions are particularly critical for the context of developing countries, which have mostly mimicked initiatives taking place in the context of developed markets. To address these issues, we analyze the impacts generated by research-intensive universities on local innovation ecosystems. We apply a combination of econometric and case study methods for the state of São Paulo, Brazil. Results suggest that research-intensive universities, mostly public universities, positively impact their respective innovation ecosystems. Moreover, qualified research funds and the existence of a support structure (incubators and science and technology parks) significantly enhance the impacts generated by research-intensive universities. These findings highlight the relationship between the internal constraints of universities and their capacity to generate impacts on local ecosystems. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Science & Public Policy (SPP). 2024/02, Vol. 51, Issue 1, p108
- Document Type:Article
- Subject Area:Politics and Government
- Publication Date:2024
- ISSN:0302-3427
- DOI:10.1093/scipol/scad062
- Accession Number:175635594
- Copyright Statement:Copyright of Science & Public Policy (SPP) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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