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Record W4405673748 · doi:10.20431/2349-0349.1211002

Adapting to Change: A Case Study of New Era Art Resort and Spa's Business Evolution and Resilience Strategies During the Covid-19 Pandemic

2024· article· en· W4405673748 on OpenAlexaboutno aff
Tsai-Yu Lai, Li-Shiue Gau

Bibliographic record

VenueInternational Journal of Managerial Studies and Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Resilience (materials science)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)HistoryPolitical scienceGeographyVirologyMedicine

Abstract

fetched live from OpenAlex

This case study focuses on the New Era Art Resort & Spa Park, established in 1987 in the Puli basin of central Taiwan.Conveniently located along the route to the renowned Sun Moon Lake, the park boasts a unique ambiance enriched by the authentic outdoor works of celebrated Taiwanese sculptor Lin Yuan, presented in an Art Brut style.By effectively leveraging these artistic resources, the New Era Art Resort & Spa has successfully attracted visitors in the tourism and hospitality sectors.Spanning 6.6 hectares, the sculpture park has developed a multifaceted business model that includes innovative dining options, conference and wedding facilities, vacation cabins, a spa, a beer plaza, and shops offering local specialties and souvenirs.Additionally, the blooming Tung flowers enhance the park's appeal, making it a significant attraction.The park's operations primarily utilize cottages constructed from Canadian fir, which are complemented by stone carvings, local gourmet food, health products, and unique offerings such as kiln-baked pizza.The diverse entertainment services create a comprehensive leisure and vacation experience that caters to a variety of visitor needs.Together with the rich local tourism

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.202
GPT teacher head0.490
Teacher spread0.288 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Managerial Studies and ResearchSame topicDiverse Aspects of Tourism ResearchFrench-language works237,207