Exploring the relationship of supply chain transformational leadership and supply chain innovations performance on MSMEs satisfaction supply chain outcomes
Bibliographic record
Abstract
In a complex digital era, innovative supply chain management is the key to success in overcoming logistical challenges. By implementing the latest technology, adopting innovative strategies, and managing risk well, Micro, Small and Medium Enterprises (MSMEs) can improve supply chain efficiency and effectiveness. The main driver of innovation is leadership in the supply chain. The supply chain network views transformational leadership and innovation as a source of competitive advantage. This study attempts to examine the direct and indirect relationship between supply chain transformational leadership, supply chain innovation performance, and satisfaction with supply chain outcomes. The main objective of this study is to analyze the mediating effect of supply chain innovation performance on the effect of supply chain transformational leadership on supply chain outcomes. The study uses structural equation modeling (SEM) with SmartPLS 3.0 software where primary data are obtained through a survey by distributing questionnaires. Respondents from this study were 507 leaders of MSMEs who were included in the purposive sampling criteria. The results of the instrument scale test used in this study met the standards of validity and reliability analysis. The results of the regression analysis of this study indicate that supply chain transformational leadership had a significant and positive effect on satisfaction of supply chain outcomes. Supply chain transformational leadership also maintained a significant and positive effect on supply chain innovation performance. Moreover, supply chain innovation performance provided a significant and positive effect on supply chain outcomes. There was also a partial support in examining the effect of mediating variables on supply chain innovation performance on the positive effect of chain transformational leadership. The theoretical implication of this research is that the results of this study support previous research studies which state that supply chain transformational leadership had a positive and significant contribution to satisfaction of supply chain performance and encourages the improvement of MSMEs. The practical implication of this research is that MSMEs managers must use transformational leadership to encourage increased performance and innovation because the results of this study have proven that transformational leadership in the supply chain will contribute to increased innovation and performance of MSMEs.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".