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Record W3007315733 · doi:10.1108/ijtc-07-2019-0111

Congestion, popular world heritage tourist attractions and tourism stakeholder responses in Macao

2020· article· en· W3007315733 on OpenAlexaff
Hilary du Cros, Weng Hang Kong

Bibliographic record

VenueInternational Journal of Tourism Cities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTourismVisitor patternStakeholderOriginalityBusinessCompetitor analysisGovernment (linguistics)MarketingWorld heritageData collectionDestination managementValue (mathematics)Public relationsQualitative researchGeographyDestinationsPolitical scienceSociologyComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to offer advice to the Macao Special Administrative Region (SAR) Government regarding the tourist and traffic flow concerning how these contribute to congestion in World Heritage Site (WHS) elements and make recommendations regarding the management of tourist flows and traffic congestion. Design/methodology/approach The research undertaken in this study is partially longitudinal. The case study is also partially ethnographic in that tourist behaviour at key sites has been observed. Concerning the specific methodology applied, data collection techniques are chosen to provide a multiplicity of data sources: on-site observation and semi-structured telephone interviews. Findings The study is found that Macao was at a crossroad. All stakeholders needed to take some responsibility for implementing actions recommended that would ensure that Macao SAR’s World Heritage assets would be used responsibly for future, as well as for present generations. Originality/value The study has shown that better and long-term understanding of congestion is necessary to inform better visitor management decision-making, enhance tourist experience and discover the factors that influence visitor satisfaction. It is also needed to reveal aspects of stakeholder readiness and barriers to action.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.093
GPT teacher head0.352
Teacher spread0.259 · 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.

Study designNot applicable
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

Citations36
Published2020
Admission routes1
Has abstractyes

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