The influence of supply chain partners’ integrations on organizational performance: The moderating role of trust
Bibliographic record
Abstract
Supply chain management and integration have become more important business topics mainly addressed within the different businesses industries in order to influence the organizational performance. The current research study aims to investigate this effect by involving some key of supply chain partners on organizational performance. Also, the moderation role of trust as an influential aspect in the business was also studied in this work. To conduct this research and meet the stated research objective, a quantitative research method was used to collect data from food products manufacturers in Jordan due to the main contribution of this sector to the national economy of Jordan. PLS-SEM approach was selected in the phase of analysis and the findings revealed a significant effect of all hypothesized research assumptions and a significant moderating effect of trust on the relationship between supply chain partners’ integration and organizational performance. The research findings also provided expected implications and supported the relevant evidence and literature in this area, as well it would contribute to cover the existing research knowledge gaps by integrating a new model including sets of new variables that have not been examined together within a single conceptual framework.
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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 | 0.006 | 0.023 |
| 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 | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".