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Record W2141097009 · doi:10.15807/jorsj.53.207

STOCHASTIC COMPARISONS IN REVENUE MANAGEMENT UNDER A DISCRETE CHOICE MODEL OF CONSUMER BEHAVIOR

2010· article· en· W2141097009 on OpenAlexfundno aff
Hideo Miki, De-bi Cao, Yasushi Masuda

Bibliographic record

VenueJournal of the Operations Research Society of Japan · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsnot available
FundersMcGill University
KeywordsIntuitionRevenue managementMonotonic functionConsumer choiceMicroeconomicsRevenueConsumer behaviourDiscrete choiceEconomicsEconometricsMathematical economicsYield managementChoice setBusinessMarketingMathematicsPsychology

Abstract

fetched live from OpenAlex

This study examines the monotonicity properties of expected revenue in a revenue management problem with respect to the consumers' choice behavior and the market size. The consumer behavior is described by a general discrete choice model. The firm decides which subset of fare products to offer at each time period. An example shows that the usual stochastic order relation in consumers' preference over the set of fare products is not sufficient for our naive intuition regarding the monotonicity to hold true. We provide sufficient conditions under which our intuition is valid. These conditions identify desirable changes in consumer behavior for the firm.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.089
GPT teacher head0.353
Teacher spread0.264 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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