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Record W2162900963 · doi:10.5539/ibr.v5n4p12

Taking an Expended View of Customer to Construct Hotel Rating System

2012· article· en· W2162900963 on OpenAlexvenueno aff
Jui-Ying Hung, Feng-Li Lin

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
FundersNational Science Council
KeywordsTourismMarketingBusinessService (business)Service qualitySERVQUALCustomer satisfactionChina

Abstract

fetched live from OpenAlex

An attention on leisure consciousness and related activities by Taiwan people also signifies an enhanced standard on service quality and demand satisfaction of tourism and leisure industry, in which a perception of customer satisfaction perceived by consumers in terms of appraisal dimension and measurement was gradually replaced by intangible accommodation experience or personalized service by service personnel from tangible hardware facilities and equipments in the past. Tourism Bureau of Republic of China has recently announced the execution of “hotel rating system” which suspended for nearly twenty, an announcement of this policy has caused considerable echoes and support to scholars from the academy and the industry and consumers with regard to hotel business, the hotel industry in Taiwan will only be able to get connected with international tourism market so as to inspire the global awareness of tourism market in Taiwan through the implementation of “hotel rating system”. The study follows the assessment standards of “star hotel rating system” promoted and implemented by Tourism Bureau, Ministry of Transportation and Communications (MOTC) in 2010, to conduct analysis in terms of SERVQUAL’s five dimensions proposed by Parasuraman, Zeithamel and Berry (1985). According to the research results, the hotel rating system in Taiwan is badly in need of an attention to the establishment and assessment of indicators in terms of “service assurance” and “service empathy” dimensions, the results also indicated that tourists make judgment based on “tangible hardware” along with “intangible service” provided by the hotels, are important determinants to enable a differentiation.

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 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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.154
GPT teacher head0.404
Teacher spread0.250 · 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 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

Citations6
Published2012
Admission routes1
Has abstractyes

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