Examining XBRL Adoption Process of Four Regulators using the Diffusion of Innovation Theory on Organisational Context: A Malaysian Evidence
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 investigates the organisational factors that influence the XBRL adoption process involving three phases namely, knowledge and persuasion, decision making and, implementation and confirmation phase.This study utilises the Diffusion of Innovation theory and the qualitative approach on four regulators in the financial reporting environment in Malaysia.This study finds that in the knowledge and persuasion phase, management support is the driving factor whilst lack of expertise, skills and knowledge on XBRL are challenges.In the decision-making phase, capability and data assurance are challenges whilst in the implementation and confirmation phase, resource capacity, adoption cost and financial resources are the driving factors to XBRL adoption process.This study finds lack of expertise, skills and knowledge have encouraged the regulators to rely on external sources in development of XBRL.The findings in this study shed some lights on the XBRL adoption process among regulators and contributes to the financial reporting landscape.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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