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Record W2157689408 · doi:10.5539/mas.v2n5p145

Study on the Service Quality Evaluation and Improvement for Medium and Small Sized Hotels

2008· article· en· W2157689408 on OpenAlexvenueno aff
Fan Chen

Bibliographic record

VenueModern Applied Science · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessService qualityMarketingTourismService (business)Hotel industrySERVQUALQuality (philosophy)Hospitality industry

Abstract

fetched live from OpenAlex

The tourism industry is in the important state in the national economy, and the hotel industry is the important part of the tourism industry, and the medium and small sized hotels occupy certain market share because of the numerous quantity. Because the service qualities of medium and small sized hotels are different, so the service quality of the hotel is the nuclear content of hotel management. At present, the supply exceeds the demand in the global hotel market, and the competitions among hotels are very intense, and who can supply excellent service for customers, who can obtain predominance in the market and attract more customers and get good benefits, and so the service quality is the life of hotel. In China hotel industry, especially for medium and small sized hotels, their management methods are draggled and there service qualities are relatively low, so many problems exist in this industry. As viewed from customers, this article discusses the satisfactory degree measurement about medium and small sized hotels based on the SERVQUAL method put forward by Parsuraman and the domestic scholars’ opinions about hotel service research, and analyzes the service quality problem of medium and small sized hotels and puts forward the project of improvement.

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)0.005
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.139
GPT teacher head0.322
Teacher spread0.183 · 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 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

Citations8
Published2008
Admission routes1
Has abstractyes

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