Does implementing green operation management affect the Sustainability of port operations in Labuan Bajo?
Bibliographic record
Abstract
Labuan Bajo Seaport's maritime logistics ecosystem serves the marine logistics supply chain as an essential part of economics and social development in the region. It is one of the economic regions that need to be developed where green operations management must be applied to suppress the negative impact of port operations. The research aims to analyze the influence of green marketing, business, and operation management on Sustainability. A cross-sectional study has been conducted in this research with data processing using partial least squares (PLS) path modeling. The population is the stakeholder of Labuan Bajo seaport, and the samples are 100 with a purposive sampling method. Findings show that green marketing has influenced business, operation management, and Sustainability. However, the green industry also influenced green operation management and impacted Sustainability. The study indicates that Sustainability can be achieved when the seaport operates using green principles from planning to monitoring by the involvement of the stakeholder.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".