An Exploratory Study of the Level of Sophistication of Management Accounting Practices in Jordan
Bibliographic record
Abstract
Purpose – The research aims to provide a view of the present role of management accounting to identify the extent of usage of management accounting practices (MAPs) and finally to determine the sophistication level of MAPs by employing International Federation of Accountants model (IFAC) in the Jordanian financial sector. Design/methodology/approach – To attain these objectives, the research used the questionnaire method 64 valid questionnaires were returned, giving a 67.3% response rate. Descriptive statistical analysis was used to analyse the responses. Findings – Regarding the life-cycle stages, it was revealed that 67.2% of the respondent companies are located in the first two stages. The research reported that traditional practices are still widespread and highly used, rarely using the more sophisticated or advanced practices, and that there is a diversity of practices used in the financial sector context. In general, the research revealed that budgeting practices and financial measures are heavily used, and there is a lack of usage of decision making practices and strategic analysis practices. Concerning the sophistication level of MAPs, the research revealed that almost all of the Jordanian financial sector companies are located in the first stage by 64.1% and 29.7% of companies in the second stage based on the IFAC model, thus indicating the simplicity of information that they require. This, in turn, reflects the simplicity of practices that are used in the Jordanian financial sector. Originality/value – Provides a broad overview of management accounting practices in the Jordanian financial sector, indicates is a lack of using MAPs in the developing countries, and indicates the improvement which would take place in the Jordanian financial sector in terms of the adoption of more sophisticated or advance MAPs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".