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Record W2003843914 · doi:10.1108/08876040310482784

Go away! Don’t bother me! I don’t want your money!

2003· article· en· W2003843914 on OpenAlexaboutno aff
Karen Ho, Laurence Jacobs, John Cox

Bibliographic record

VenueJournal of Services Marketing · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsnot available
Fundersnot available
KeywordsReservationRevenueMarketingTest (biology)BusinessSample (material)Quality (philosophy)AdvertisingFinanceLawPolitical science

Abstract

fetched live from OpenAlex

In 1988, 998 letters of reservation inquiries were sent to hotels with 250 rooms or more requesting information about hosting a business reception for 20 couples. The study was designed to test the responsiveness of hotels to reservation inquiries made by letter and whether the hotels would miss the opportunity to maximize their revenues by failing to respond effectively to these reservation inquiries. Recently, 100 letters of similar content were again sent to a random sample of hotels with 250 rooms or more located in the USA, Canada, Mexico, and the Caribbean. The letters of reservation inquiries were sent to test the responsiveness of hotels again and to assess whether the quality of the responses made by the hotels has changed since 1988. The current study found that the responsiveness of hotels to reservation inquiries made by letter has changed little since 1988. Like 1988, many hotels missed the opportunity to maximize their revenues by failing to respond to reservation inquiries made by letter.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.322
Teacher spread0.301 · 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.

Study designObservational
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

Citations5
Published2003
Admission routes1
Has abstractyes

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