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Record W2015498984 · doi:10.1504/ijor.2010.032109

The impact of fare pricing cooperation in airline revenue management

2010· article· en· W2015498984 on OpenAlex
Syed Asif Raza, Ali Akgündüz

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 Journal of Operational Research · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDuopolyRevenue managementMicroeconomicsRevenueNash equilibriumCompetition (biology)Game theoryRevenue sharingPaymentEconomicsBusinessOperations researchFinanceMathematics

Abstract

fetched live from OpenAlex

This article addresses an airline revenue management strategy to jointly determine both the seat allocation and the fare price for a single leg flight in a duopoly market. Two game theoretic scenarios: non-cooperative and cooperative are considered. In non-cooperative game setting, existence of pure strategy Nash Equilibrium for the perfect competition between two airlines is shown. In cooperative scenario, two bargain games that differ in availability of side payment (SP) option while sharing of the gain of cooperation are studied. Numerical study based on a series of statistical comparisons shows that cooperation with the SP options results superior payoffs to both airlines compared to cooperation with no SP options. A regression analysis is used to analyse the impact of various market factors on payoffs.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.390
Teacher spread0.342 · 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