Tourists’ Perceived Quality on History and Culture of Sheqi Ancient Town: A Moderating Effect of Tourist Motivation
Bibliographic record
Abstract
Perceived quality was identified an important antecedent of tourist satisfaction and destination loyalty, however, few studies examine the factors influencing tourist’s perception on the service quality of a destination. For historic and cultural tourists, tourist experience play an important role during their visits. The main purpose of this study was to investigate whether tourists’ experience influenced perceived quality of the tourist as an antecedent and the moderating effect of tourists’ motivation on the relationship between tourists’ experience and perceived quality within historic and cultural tourism contexts. A survey of 1,389 tourists visited an ancient town in center part of China, Sheqi, was conducted as the basis for analysis. With SPSS 22.0 and data collected in Sheqi Ancient Town, the hypothetical model was tested by the method of hierarchical regression analysis. The empirical results indicated that, firstly, the tourists’ experience positively influenced perceived quality significantly. Secondly, tourist motivation played a significant moderating role on the relationship between tourist’s experience and perceived quality.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".