Leveraging good university governance to enhance HEI's performance through the lens of ethical work climate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the role of management control systems (MCS) in enhancing the performance of Higher Education Institutions (HEIs) in Indonesia, focusing on the interaction between enabling and coercive control systems within the framework of ethical work climate (EWC) and good university governance (GUG). The research highlights the importance of creating a positive ethical work environment to improve the effectiveness of MCS and governance practices. A survey was conducted with lecturers and administrative staff from private universities across Indonesia, with data analyzed using Structural Equation Modelling (SEM) to test the relationships between EWC, MCS, GUG, and HEI performance. The findings reveal that both Enabling and Coercive Control Systems positively influence HEI performance and contribute to the improvement of GUG. Additionally, a positive EWC strengthens the effectiveness of both control systems, fostering trust, transparency, and employee engagement. The study provides theoretical insights into how MCS and ethical climates shape governance and performance in higher education, with practical implications for HEIs administrators to optimize MCS, balance control systems, and cultivate an ethical work environment to enhance institutional success. Future research could further explore the impact of leadership styles and external factors on the effectiveness of these systems in different higher education contexts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it