The Diffusion of Balanced Scorecard from the Perspective of Adopters: Evidence from Australia
Bibliographic record
Abstract
© 2018 Academic Research Centre of Canada The purpose of this paper is to explore the shortcomings of the Balanced Scorecard (BSC) as a performance measurement tool, and to examine the extent of association between its diffusion and the characteristics of its adopters in practice. This study uses a survey approach and targets registered members of Chartered Institute of Management Accountants (CIMA) in Australia. The results show that ignoring the risks, environmental and sustainability factors as well as neglecting the concerns/rights of relevant stakeholders are the key shortcomings of the BSC in practice. The findings further confirm that it is vital to distinguish between the diffusion of the BSC as a practice (one single tool) and as a process (a chain of different activities). Because some attributes of adopters are only associated with the initial decisions to adopt (or not) the BSC (as a practice) but not with the sequential implementation stages of its adoption (as a process) and vice versa.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".