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Record W2803568579 · doi:10.5430/jms.v9n2p69

The Effect of Celebration Marketing and Its Correlation Model

2018· article· en· W2803568579 on OpenAlexvenueno aff
Shwu-Ing Wu

Bibliographic record

VenueJournal of Management and Strategy · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsAttractivenessPsychologyAdvertisingPopulationPhysical attractivenessSocial psychologySociologyBusinessDemography

Abstract

fetched live from OpenAlex

This study explores the effects of Celebration activities, Celebration merchandises, surroundings, and history and culture on the experience attractiveness perceived by tourists, as well as tourists’ attitude and behavioral intention. Tourists who have taken part in any kind of Celebrations were treated as the sample population. The questionnaires were distributed in person upon convenience sampling, and 562 effective samples were retrieved. The results showed that Celebration activities, Celebration merchandises, surroundings, and history and culture have significant positive effects on the experience attractiveness perceived by tourists. Celebrations and culture also have a significant positive effect on tourists’ attitude. However, Celebration merchandises and surroundings have no significant effect on tourists’ attitude. Experience attractiveness has a significant positive effect on attitude and behavioral intention, suggesting that when Celebrations are more attractive to tourists, they feel more delighted, and have stronger behavioral intention.

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)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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 designSimulation or modeling
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
Published2018
Admission routes1
Has abstractyes

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