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Airline seat allocation competition

2008· article· en· W2072747920 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Transactions in Operational Research · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsNash equilibriumProfit (economics)RivalryUniquenessMicroeconomicsCompetition (biology)Computer scienceEconomicsDilemmaAir traffic managementOperations researchCost allocationMathematical economicsMathematical optimizationMathematicsAir traffic control

Abstract

fetched live from OpenAlex

Abstract This paper examines the classical seat allocation problem under competition between two airlines with different cost structure. The cost asymmetry that has been ignored in the yield management literature can be caused by either operations or distributions. We investigate the decision problem of two airlines offering two identical fare classes under both the simultaneous and sequential allocations. For both allocation cases, we show the existence, uniqueness and stability of pure‐strategy Nash equilibrium under a reasonable condition on the ratios of relative profit margins of the two fare classes. We find that there will be fewer seats protected for the full‐fare class if the discount seats can be booked first. We found that the asymmetry in costs has two effects on the equilibrium solutions: (a) an airline behaves aggressively for the fare class where it enjoys a cost advantage; (b) an airline tends to balance the trade‐offs internally when it has absolute cost advantage in both fare classes. In deriving the collusive solution for both cases for comparative purposes, we discover new insights by solving the two‐flight, two‐fare seat allocation problem with different cost structures on the two flights. In particular, we show that rivalry in full‐fare seat protection leads to a Prisoners' Dilemma for the carriers. Finally, a numerical example is used to illustrate various analytical results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.117
GPT teacher head0.351
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it