Investigating the role of supply chain management on sustainable performance and dynamic capabilities: An empirical study on logistic organization
Bibliographic record
Abstract
This research aims to investigate the effect of supply chain management (SCM) on sustainability performance (SP), the effect of dynamic capabilities (DC) on sustainability performance and finally the effect of SCM on DC. The study uses a quantitative method with a questionnaire approach to investigate the relationship between endogenous and exogenous variables using the Likert scale. The respondents for this research were 680 logistics company owners in Indonesia determined using a simple random sampling method. The results show that SCM had a positive and significant relationship with SP. DC also had a positive and significant relationship with SP and recommends that company owners create policies to increase dynamic capabilities to improve company performance. Finally, DC in our survey had a positive and significant relationship to SP and strengthened the findings of previous findings. Moreover, SCM had a positive and significant relationship with DC, which recommends company owners make policies to improve SCM to increase DC. This research provides input to organizational owners to implement supply chain management, and dynamic capabilities to improve company performance and 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".