Factors Influencing the Implementation of Management Accounting Systems in Small and Medium Sized Enterprises in Dubai
Bibliographic record
Abstract
The aim of this study is to examine whether each of the variables (level of competition, age of enterprise, type of sector, quality of ownership, and size of enterprise) has an impact on adopting administrative accounting practices measured by each of (cost systems, budget systems, performance assessment systems) within small and middle sized industrial enterprises in Dubai, in addition to determining whether enterprises are facing difficulties in applying administrative accounting practices. The population of the study represents all small and middle sized industrial enterprises in Dubai. To achieve the study objectives, a questionnaire is designed and distributed on the study sample which consists of (160) accountants and financial mangers working at small and middle sized enterprises in Dubai. The researcher could retrieve (127) responses and (32) responses have been disregarded; thus, the final study sample is represented by (95) responses. For the purpose of the study, the analytical descriptive approach is also employed. Furthermore, to test the study hypothesis, multiple regression model and One Sample T- test are used. The study findings reveal that small and middle sized enterprises in Dubai apply all administrative accounting practices represented by each of (cost systems, budget systems, performance assessment systems). As well, there is an impact of each of the variables (level of competition, age of enterprise, type of sector, quality of ownership, and size of enterprise) on adopting administrative accounting practices measured by each of (cost systems, budget systems, performance assessment systems). Moreover, the study finds that small and middle sized industrial enterprises in Dubai face difficulties in adopting administrative accounting practices but in a slight degree in which that the arithmetical average value is very close to the default average value.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".