Navigating operational excellence: A strategic framework for enhancing sustainable logistics performance at Indonesian International Airport
Bibliographic record
Abstract
Research on measuring airport operational performance has predominantly focused on technical aspects. However, there is still a need for studies to be conducted on measuring sustainable logistics and operational performance at international airports. The objective of this study is to develop a comprehensive measurement system for the Airport Operations Division in Indonesia that incorporates both operational and sustainable logistics performance. This will be achieved by integrating the company's vision, mission, and strategy into various performance measures using the Balanced Scorecard concept. The research methodology employed quantitative research methods, including primary data collection through observation and questionnaires. These questionnaires were developed using a pairwise comparison matrix derived from the Analytical Hierarchy Process (AHP). Data was collected from five international airports in Indonesia. The findings of the study demonstrate that the application of the Balanced Scorecard, coupled with the Objective Matrix method for setting performance targets and enriched with the AHP approach, enables the identification of priorities and assessment of performance. The research emphasizes the significance of considering non-financial aspects when measuring airport performance. This is crucial for supporting strategic decision-making and promoting sustainable performance improvement.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".