Implementing responsibility centre management in a higher educational institution
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
Purpose The purpose of this study is to examine the design, development and implementation of responsibility centre management at a mid-sized Canadian university, within the context of decentralized decision-making. More specifically our study focused on the design, development and implementation of a revenue and cost allocation process known as transparent activity–based budgeting system (TABBS). Design/methodology/approach The authors conducted this study using a qualitative case study methodology, rooted in grounded theory, as the primary approach to collect and analyse data, and report the findings. Primary data were collected from ten participants using semi-structured interviews. Findings The main takeaways from our research are that (1) such systems take time to design, develop and implement, (2) consultation, communication and information sharing and model adjustment and refinement are important enabling mechanisms, (3) internal and external events posed significant challenges, (4) although such systems are often designed keeping in mind several intended outcomes, there exists the possibility of experiencing some unintended consequences and (5) the juxtaposition of the above has the potential to negatively or positively impact organizational performance. Originality/value The research demonstrates that the design, development and implementation of a complex resource allocation model is an important element of a responsibility-centred approach to planning and decision-making. It highlights the importance and contribution of enabling mechanisms as well as the challenges that large, complex organizations may confront when introducing change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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