Diagnostic Model for IT Governance Assessment in Federal Public Universities
Objective: to develop and validate a diagnostic model for IT governance assessment in Brazilian federal public universities, considering specific factors of public administration related to performance measurement. Theoretical approach: based on corporate and IT governance theories applied to the pu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Associação Nacional de Pós-Graduação e Pesquisa em Administração (ANPAD)
2025-06-01
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| Series: | RAC: Revista de Administração Contemporânea |
| Subjects: | |
| Online Access: | https://rac.anpad.org.br/index.php/rac/article/view/1693 |
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| Summary: | Objective: to develop and validate a diagnostic model for IT governance assessment in Brazilian federal public universities, considering specific factors of public administration related to performance measurement. Theoretical approach: based on corporate and IT governance theories applied to the public sector, integrated with factors that influence the design of performance measurement systems in public organizations. Methods: qualitative research based on a systematic literature review to identify essential IT governance characteristics and develop a conceptual model, followed by a comparative case study in three federal universities using systematic documentary analysis. Results: the diagnostic model revealed significant differences in IT governance maturity levels among institutions (UTFPR — 76.67%, UFABC — 63.33%, and UFBA — 0%) and identified the universal absence of volunteer practices, highlighting specific needs of the public sector. The assessment, based on public documents, may not fully reflect the actual practices of the institutions. Conclusion: the model proved effective for evaluating IT governance practices in public higher education institutions, emphasizing the importance of contextual adaptation and providing a practical tool for diagnosis and development of IT governance in the sector. |
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| ISSN: | 1415-6555 1982-7849 |