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Record W2095177558 · doi:10.1080/10548408.2010.526897

Determining the Factors Affecting the Memorable Nature of Travel Experiences

2010· article· en· W2095177558 on OpenAlexaff
Jong‐Hyeong Kim

Bibliographic record

VenueJournal of Travel & Tourism Marketing · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAnticipation (artificial intelligence)RecallExperiential learningPsychologyAutobiographical memoryTourismStructural equation modelingSocial psychologyCognitive psychologyHistoryPedagogyComputer science

Abstract

fetched live from OpenAlex

This study investigates the effects of travel experiences on the autobiographical memory. A structural equation modeling analysis reveals that the experiential factors of involvement, hedonic activity, and local culture positively affected the autobiographical memory of recollection and vividness of past experiences. Specifically, the experiential factors of involvement and refreshing experiences are found to increase an individual's ability to recollect past travel experiences and retrieve the experiences vividly. Alternatively, the experience of local culture enhances the recollection of past travel experiences, albeit not as vividly. The findings of the present study suggest that marketing efforts used at the anticipation stage of travel experiences are necessary to provide memorable travel experiences. The theoretical and managerial implications of the results obtained are discussed in detail.

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)0.024
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.317
Teacher spread0.298 · 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

Citations313
Published2010
Admission routes1
Has abstractyes

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