DOI: 10.7910/dvn/d35vp3
title: Replication Data for: Diagnostic Model for IT Governance Assessment in Federal Public Universities published by RAC-Revista de Administração Contemporânea

description: Research Hypothesis:
It is believed that IT governance (ITG) in federal public universities can be effectively assessed through a diagnostic model based on essential characteristics of ITG and specific public administration factors aimed at performance measurement.

Data Description and Collection:
Data were collected through a systematic document analysis of public documents (PDTIs, PDIs, Management Reports, among others) from three Brazilian federal public universities: UTFPR, UFABC, and UFBA. A checklist with 30 questions grouped by 10 evaluation factors of ITG was used. Responses were categorized as "positive," "negative," or "inconclusive."

Findings:
UTFPR: 76.67% positive responses (higher maturity in ITG);

UFABC: 63.33%;

UFBA: 0% (absence of documentary evidence of ITG practices).

Interpretation and Use:
These data indicate significant differences in the level of ITG maturity among the institutions. The diagnostic model allows for identifying gaps, guiding corrective actions, and serving as a comparative tool for similar institutions. The absence of common volunteering practices in NGOs, for example, may indicate the need to adapt frameworks for the public sector.

Limitations:
Reliance on public documents (may not reflect informal practices).
Small sample size (3 universities).
description: Steps to reproduce
1. Research Design
Type of Study: Qualitative research based on a comparative case study approach.
Objective: Develop and validate a diagnostic model for IT governance (GTI) assessment in Brazilian federal public universities.
Theoretical Foundation: Integrated corporate governance, IT governance theories, and performance measurement systems (PMS) in public administration.

2. Data Sources
Primary Data: Publicly available institutional documents from three federal universities:
UTFPR (Universidade Tecnológica Federal do Paraná)
UFABC (Universidade Federal do ABC)
UFBA (Universidade Federal da Bahia)

Document Types Analyzed:
Institutional Self-Assessment Reports (2023–2024)
IT Master Plans (PDTI, 2021–2023)
Management Reports (2023)
Institutional Development Plans (PDI, 2018–2033)
IT Sector Goal Plans (where available).

3. Data Collection Protocol
Step 1: Identification of Sources:
Official university websites and repositories.

Step 2: Selection Criteria:
Documents explicitly mentioning "IT governance," "strategic alignment," or related terms.
Most recent versions (2018–2024) to ensure relevance.

Step 3: Collection Period:
August to October 2024.

Step 4: Systematic Keyword Search:
Keywords: "governança de TI," "alinhamento estratégico," "PDTI," "compliance," "accountability."
Tools: Manual search with cross-verification by two researchers.

4. Data Analysis Methods
Content Analysis:
Coding Framework: 30 questions grouped into 10 factors (e.g., accountability, stakeholder involvement).

Classification Criteria:
Positive: Explicit mention in documents (e.g., "GTI is prioritized in the PDI").
Negative: Absence or contradictory statements.
Inconclusive: Vague or incomplete references.

Triangulation:
Cross-validation of findings across multiple documents from the same institution.
Independent coding by two researchers to ensure reliability.

Maturity Scale:
Adapted from COBIT 2019 (ISACA):
Level 1 (Initial): 0–20% positive responses.
Level 4 (Managed): 61–80% (e.g., UTFPR at 76.67%).

5. Limitations and Mitigation
Limitations:
Reliance on public documents (may not reflect informal practices).
Small sample size (3 universities).

Mitigation:
Explicit inclusion/exclusion criteria for documents.