Development Strategy of Movie and TV Theme Park Based on Tourism Experience: A Case Study of ChangChun Movie Wonderland
Bibliographic record
Abstract
AS the main form of the theme park, the movie and TV theme park attracts so much public attention.The development of movie and TV theme park has played an active role in promoting local tourism development and improving infrastructure construction. However, since the short history of movie and TV theme park in China, coupled with the unreasonable operation and management and so on, most of movie and TV theme park have fell. We can see that the sustainable and stable development of movie and TV theme park is worrisome. For such situation, this article analyzes primarily from the perspective of tourism experience. In experience, tourists are expecting to seek a more unique and profound tourism experience, not limited to sight seeing.The quality of tourism experience is not only an important measure of tourist satisfaction index, but also represents the development competence of movie and TV theme park. Therefore, it is necessary to analyze the movie and TV theme park from the perspective of the tourist experience to attain the better development. This article is divided into four parts. Firstly it introduces the development status of movie and TV theme park, domestic and foreign scholars' studies about movie and TV theme park and the necessity of studying from the perspective of the tourist experience.The second part introduces Changchun Movie Wonderland, including its basic information and operating condition;the third part is the empirical analysis. This article takes Changchun Movie Wonderland as an empirical research object from the perspective of tourism experience through questionnaires, tourists' travel network and interviews, using SPSS and EXCEL statistical software for sample analysis, reliability analysis, extraction of 14 factors IPA analysis. By analyzing we come to the conclusion that affecting tourism' experience factors are mainly high ticket,not sufficient time for traveling, low participation index and so on; The forth part is some advice on the basis of the Changchun Movie Wonderland's analysis. The recommendations are as follows: First, to strengthen the planning and management. Second, to build brand experience. Third, to make rational ticket price from the perspective of the tourist experience. Fourth, to do experiential marketing.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".