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Record W3009538836 · doi:10.5539/ibr.v13n4p1

The Satisfaction Study of People with Disabilities Regarding the Restaurant with Barrier-Free Environment in Taiwan Tourism Area

2020· article· en· W3009538836 on OpenAlexvenueno aff
Chia-Hsin Cheng

Bibliographic record

VenueInternational Business Research · 2020
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsTourismBusinessMarketingService (business)Service qualityQuality (philosophy)AdvertisingGeography

Abstract

fetched live from OpenAlex

The number of people with disabilities (PWDs) is expected to increase over years due to the increase of human lifespan and accidents. However, the PWDs as a result of some social factors, such as environment inaccessibility, insufficient job opportunity, inadequate education aids, etc. are excluded from participating their leisure activities or dining out in the society. This study aims to investigate and evaluate the design of barrier-free environment of restaurants in Taiwan famous tourism areas via the restaurant customer satisfaction of PWDs regarding the barrier-free facility and service quality. The results show that the qualified percentage of barrier-free physical environment design is only 44%, and PWDs are not satisfied with the barrier-free physical environment including the space allotted in parking lots, restroom accessibility for PWDs, as well as the slipperiness of floors. The regression analysis shows the barrier-free physical environment and service quality aspect with respect to post-purchase intentions reach statistical significance indicating the environment design for the PWDs is critical to the restaurant management especially in a tourism area.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.058
GPT teacher head0.338
Teacher spread0.281 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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