An Investigation Between Nostalgic Value Resonance and Destination Brand Engagement in Rural Tourism
Bibliographic record
Abstract
The purpose of this study was to examine Destination Brand Self Congruence, Destination Scenery, Nostalgic Value Resonance and Destination Brand Engagement affecting revisitation intention, Recommend Intention.The population of this study are tourists who visit tourist villages in Indonesia.The sample in this study was 400 respondents.This research is quantitative research with a survey method.The data collection tool in this study used a questionnaire.Online questionnaires were distributed to domestic tourists who visited tourism village.Non Probability Sampling approach using purposive sampling with the criteria of namely selecting 400 local tourists who had experience visiting the Keranggan tourism village at least once a year.Data analysis using PLS-SEM.The results of the study show that there is a positive influence between all variables and is mediated by Destination Brand Engagement, so it can be concluded that all hypotheses are supported.This research is original in terms of conceptualization and empirical testing of the relationship between nostalgic value resonance and destination brand engagement in the context of rural tourism in Keranggan.This study is the first to examine the relationship between nostalgic value resonance and destination brand engagement in the rural tourism sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".