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Record W2076810375 · doi:10.5539/ibr.v7n10p36

Regional Traffic & Medical Services and Cost Efficiency of International Tourist Hotels in Taiwan

2014· article· en· W2076810375 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
Fundersnot available
KeywordsData envelopment analysisTourismBusinessCost efficiencyService (business)Environmental economicsMedical tourismOperations managementTransport engineeringMarketingComputer scienceEconomicsStatisticsGeographyEngineering

Abstract

fetched live from OpenAlex

This study analyzes how regional public transport facilities and medical services affect the efficiency of international tourist hotels (ITHs). First, we adopt data envelopment analysis (DEA) to measure the cost efficiency of international tourist hotels in Taiwan during 1998 to 2009. Next, we use the truncated regression to estimate the effect of traffic convenience and medical services on cost efficiency. The distance to international airports and distance to MRT station have significantly negative effects on cost efficiency of international tourist hotels, while the distance to the freeway exit, distance to bus station, and pick-up service, chain system, and shorter operating year have significantly positive impacts on their cost efficiency. The shorter distance to the hospital and more hospitals in a region significantly improve cost efficiency of ITHs in Taiwan.

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)0.013
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.458
Teacher spread0.333 · 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