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Record W3042571375 · doi:10.1007/978-3-030-53552-0_31

HotelSimu: Simulation-Based Optimization for Hotel Dynamic Pricing

2020· book-chapter· en· W3042571375 on OpenAlexfundno aff
Andrea Mariello, Manuel Dalcastagné, Mauro Brunato

Bibliographic record

VenueLecture notes in computer science · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsnot available
FundersUniversity of IoanninaUniversite AngersNational Research University Higher School of EconomicsUniversità degli Studi di FerraraUniversità degli Studi di UdineUniversità della CalabriaUniversità BocconiConsejo Superior de Investigaciones CientíficasUniversità di BolognaUniversity of HaifaUniversità degli Studi di CagliariCentre National de la Recherche ScientifiqueUniversità degli Studi di Napoli Federico IIChina Scholarship CouncilEcole Nationale de l'Aviation CivileUniversity of TorontoUniversity of New South WalesUniversity of CreteUniversità degli Studi di CamerinoKU LeuvenUniversity of California, DavisFar Eastern Federal UniversityUniversità degli Studi di TrentoBeijing University of TechnologyUniversità degli Studi di Milano-BicoccaSobolev Institute of Mathematics, Siberian Branch, Russian Academy of SciencesUniversitat Pompeu FabraWilfrid Laurier UniversityInstitut national de recherche en informatique et en automatique (INRIA)Aristotle University of ThessalonikiIndian Council of Agricultural ResearchCarnegie Mellon UniversityUniversità Degli Studi di Modena e Reggio EmilaUniversité de LilleBournemouth UniversityUniversity of PittsburghUniversity of WarwickUniversité de LorraineUniversidade de Aveiro
KeywordsComputer scienceMathematical optimizationSet (abstract data type)Revenue managementRevenueParametric statisticsDynamic pricingMonte Carlo methodOperations researchMathematicsFinanceEconomics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2020
Admission routes1
Has abstractno

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