Applying just‐in‐time principles in the delivery and management of airport terminal buildings
Bibliographic record
Abstract
Purpose This study aims to examine how the just‐in‐time (JIT) principles can be adopted for the air travel industry with specific emphasis on the management and operations of terminal buildings in airports. Design/methodology/approach Three methods were adopted for the empirical part of this study. These included the observational walk‐through, interviews and survey questionnaires conducted in the Changi International Airport in Singapore. The evaluation for JIT application, as part of a larger study, includes the points of arrival and departure, the check‐in hall, immigration area, transit mall, gate lounges, food and beverage outlets, retail shops as well as other management initiatives that strive for continuous improvement. This paper focuses only on the check‐in hall. Findings Japanese businesses have been able to compete successfully in the world market in recent decades because of their total dedication to quality and productivity issues. This has been made possible in part by the guiding principles of the JIT concept which many Japanese businesses subscribed to. The JIT principles include waste elimination, pull production system, uninterrupted work flow, total quality control, top management commitment, employee involvement, long term working relationships with suppliers and continuous improvement. The JIT concept was specifically examined in this study in the context of the Changi International Airport through its planning processes and existing operations. The study was able to highlight the strengths as well as areas for potential improvements in the airport through the application of the seven JIT principles. Practical implications Beyond Japanese businesses, the JIT concept was also found to have benefited organizations in a wide range of industries including those relating to the built environment. The study covers major processes and procedures typical of the spatial management and operations of major airport terminal buildings which holds promising lessons for airport management worldwide. Originality/value The analysis shows significant potential in applying JIT principles for managing airport operations within the confines of the physical airport terminal buildings. It recommends that designers, project managers and asset managers should progress beyond the traditional “design follows functions” approach to adopt the more integrative “design follows JIT‐driven functions” approach.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".