The effect of main characteristics of accounting information on supply chain performance, empirical study in Saudi Arabia
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
The study explored the influence of the main dimensions of accounting information (AI) relevance and reliability on supply chain performance (supply chain exchange information, supply chain collaboration, supply chain integration) at Noon e-commerce companies in Saudi Arabia. The researcher followed the descriptive analytical approach to describe the study variables based on previous studies and explore the study gap. The study adopted a questionnaire, of which 170 were collected. The data was analyzed using partial least squares (PLS) through structural equation modeling (SEM). The results indicated a positive effect of the relevance and reliability of AI on the dimensions of SC performance (SC exchange information, SC collaboration, SC integration), there is a positive effect of the reliability of AI on the dimensions of supply chain performance (SC exchange information, SC integration) and a negative effect of the reliability of AI on the SC collaboration parties. These results clarified the value and benefit of accounting information in improving supply chain performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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