The role of supplier-buyer relationship in enhancing business performance through supply chain management practice, total quality management implementation and product innovation
Bibliographic record
Abstract
The Company should collaborate with supply chain members to support business process activities and increase competitiveness. Company collaboration with suppliers is essential in supporting the adoption of supply chain practices and total quality management to pursue product innovation and enhance business performance. This study investigates the role of supplier-buyer relationships in enhancing business performance through supply chain management practice, total quality management, and product innovation. The research surveyed 150 companies implementing total quality management with ISO certification in East Java. Data processing employs partial least squares using SmartPLS software version 4.0. The research found that supplier-buyer relationships positively and significantly influence supply chain practice by 0.800, total quality management by 0.438, and product innovation by 0.293. The company's ability to implement supply chain practices positively affects total quality management by 0.443, product innovation by 0.206, and business performance by 0.263. Total quality management adopted by manufacturing companies by obtaining ISO certification has an impact on increasing product innovation by 0.412 and business performance by 0.276. The company's ability to build a supply chain strategy to produce innovative products affects business performance by 0.446. The research results contribute practically to managers who build coordination with supply chain members, especially purchasing and marketing managers, to be able to read the capabilities and advantages of external partners to be communicated internally in the company—theoretical contribution in enriching supply chain strategy theory in increasing competitiveness.
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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 | 0.005 | 0.011 |
| 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".