Relationships Under Stress: Relational Outsourcing in the U.S. Airline Industry After the 2008 Financial Crisis
Bibliographic record
Abstract
This paper studies how firms restructure their relational contracts in the face of permanent shocks to the value of their relationships. In the context of the U.S. airline industry, we argue that major carriers enter self-enforcing agreements with their outsourced regional partners because a key aspect of airline operations—the exchange of landing slots under adverse weather—is formally noncontractible. We show empirically that major and regional airlines did not terminate their relational contracts after the 2008 crisis but rather, restructured the scope of such contracts in a way that restored their credibility. In particular, we show that a major airline was less likely to continue outsourcing a route to a regional partner after the 2008 crisis the lower the present discounted value of their preexisting relationship and hence, the larger the negative effect of the crisis on the relational contract’s “self-enforcing range.” This paper was accepted by Joshua Gans, business strategy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".