Political Economy of ASEAN Open Skies Policy: Business Preferences, Competition and Commitment to Economic Integration
Bibliographic record
Abstract
Despite significant growth of the domestic airline industry, Indonesia was hesitant to ratify the ASEAN Open Skies Policy (OSP) until 2016. One of the recent findings exposed the increasing concern over foreign–domestic airline competition with too little attention in exploring airline aspirations and the potential interplay between the airline preferences and the state interest. This study empirically investigates the dynamics of domestic resistance to the implementation of OSP, and to what extent the interplay of Indonesian airlines’ business preferences, ASEAN contexts and state interests have contributed to the OSP ratification postponement. Taking some lessons from the OSP ratification, we argue that the efforts towards advancing ASEAN economic integration through the open skies are contested domestically when business preferences showed mixed reactions. There has been little agreement on how the OSP could benefit the domestic airlines following their own business strategy. In the meantime, state principles indicated certain priorities for domestic interests, while ASEAN contexts allowed a member state to practice a negotiated move. The study was conducted using a qualitative method, with semi-structured interviews involving three Indonesian airlines (state and privately owned, full service and budget airlines), government officials, a civil society element and the Indonesian national air carriers association. JEL Classification: F0, F5
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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 | 0.002 | 0.003 |
| 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 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".