Exploring the role of supplier integration, customer integration on operational performance by mediating the SMEs supply chain flexibility
Bibliographic record
Abstract
This research investigated the relationship between supplier integration and customer integration on operational performance by mediating supply chain flexibility in SMEs in Indonesia. The method used in this research used quantitative methods using a conceptual framework and analysis of research data was performed using structural equation models (SEM) with SmrtPLS 3.0 software tools. Respondents to this study were 650 SMEs owners in Indonesia who were determined using the simple random sampling method. Data collection in this study was carried out on primary data in the form of respondents' statements obtained from answers to online research questionnaires designed using a Likert scale of 7. The results of this study stated that Supplier Integration had a positive and significant effect on supply chain flexibility. Customer Integration had a positive and significant effect on Supply Chain Flexibility. Supply Chain Flexibility had a positive and significant effect on operational performance. Supplier integration had a positive and significant effect on operational performance. Customer integration had a positive and significant effect on operational performance.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".