The Influence of Accounting Information Systems (AIS) on Performance of Small and Medium Enterprises (SMEs) in Iraq
Bibliographic record
Abstract
The objective of this paper is to investigate the influence use of Accounting Information System (AIS) performance in Small and Medium Enterprises (SMEs) in Iraq. The study discusses and explores the effects of the use of AIS on the performance of SMEs. The result of this study is expected to help the owners and manager of SMEs to understand the importance of the use of AIS to achieve performance. The use of AIS is influenced by several characteristics enjoyed by the accounting information such as: reliability, relevance, and timeliness that effect on SMEs' performance. The result of this study and modern literature shows that AIS characteristics enjoyed by the accounting information such as: reliability, relevance, and timeliness have significant effects on the use of AIS and SMEs ' performance. Prior researches have shown that is crucial for SMEs to use AIS to ensure business continuity and survival in the increasingly competitive environment and to enhance their business operations capability and efficiency. The study is one of few that shed light on how the use of AIS affects the performance of SMEs. In this study, the authors propose that dimensions of using AIS are important for improve the performance of SMEs.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| 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".