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Record W4413088859 · doi:10.1080/07053436.2025.2524214

Decoding the allure of Nanling National Park: A study on the correlation between environmental responsibility and anticipated tourist behavior from the perspective of scarcity

2025· article· en· W4413088859 on OpenAlexvenueno aff
Gong Wenxin

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)TourismScarcityNatural resource economicsEnvironmental resource managementEnvironmental ethicsPolitical scienceEnvironmental scienceEconomicsComputer scienceLawMarket economy

Abstract

fetched live from OpenAlex

Amid China’s push for ecological civilization and the development of national parks, Guangdong Nanling National Park (proposed) has restricted access since 2018 for reasons of ecological protection. This study examines how the park’s inaccessibility influences tourists’ perceived scarcity and how this scarcity affects their pro-environmental intentions and future travel plans. Using a survey of 310 interested tourists who were unable to visit the park, the findings show that perceived scarcity increases environmental responsibility and future visitation interest. Additionally, destination attachment mediates the relationship between perceived scarcity and these intentions. This study enriches the application of scarcity theory in tourism and environmental psychology, offering destination marketers insights into leveraging scarcity psychology, especially when access restrictions may be lifted, to boost public engagement and sustainable tourism development.

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)0.001
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.399
Teacher spread0.337 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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