Investigating the role of leadership, organizational pressure and the work environment on green supply chain performance: Evidence from the Indonesian SMEs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to analyze and examine the effect of leadership on small and medium enterprise (SMEs) green supply chain performance, the effect of organizational pressure on SMEs’ green supply chain performance and the effect of the environment on green supply chain performance of the SMEs. The research method is a quantitative method, data analysis uses structural equation modeling (SEM) with SmartPLS 3.0 software tools. The population of this study is internal auditors who have experience in cyber security and information technology. The sample for this study was 490 respondents of SMEs owners who were determined by the snowball sampling method. The research data was obtained from an online questionnaire which was distributed via social media. The questionnaire was designed using a Likert scale of 1 to 6. The stages of data analysis were validity test, reliability test and significance test. The results indicate that leadership has a positive and significant effect on the performance of the green supply chain of SMEs, organizational pressure has a negative and significant effect on the green supply chain and the environment has a positive and significant effect as well. Improving SMEs' green supply chain performance requires increased leadership, reduced organizational pressure and an improved work environment. This study generates a leadership relationship model on green supply chain performance, organizational pressure on green supply chain performance and environment on green supply chain performance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it