Supply Chain Management Practices and Supply Chain Integration on Organizational Performance: The Mediation Role of Competitive Capabilities
Bibliographic record
Abstract
Purpose- This study's goal is to ascertain how competitive capabilites through supply chain management and supply chain integration affect organizational performance. Design/Methodology/Approach- Structural Equation Modeling, assisted by the Smart PLS program, is the data processing technique utilized in this study to examine the impact of the indicators of each of the aforementioned variables on Batik Micro, Small and Medium Enterprises in the Special Region of Yogyakarta. By distributing questionnaires, the researchers were able to collect data from up to 65 respondents. Findings- The findings of this study demonstrate that supply chain management and supply chain integration have a favorable impact on organizational performance, and that competitive skills can mediate that effect. Research limitations/implications- The study's findings are anticipated to serve as a guide and source of knowledge for business players, particularly Batik Micro, Small, and Medium Enterprises in Special Region of Yogyakarta, who are expected to understand that in order to enhance the performance of their enterprise, attention must be paid to elements that may have an impact. This study demonstrates that competitive competencies, supply chain integration, and supply chain management techniques are all elements that can impact a company's performance. Originality/value- There are still very few studies on supply chains and organizational performance in micro, small, and medium-sized businesses, particularly Batik. In this study, characteristics that are thought to have an impact on the number of Batik Micro, Small, and Medium Enterprises in a Special Region of Yogyakarta are revealed.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".