A Study on the Relationship and Influence Between Motivation and Satisfaction of Ecotourism Visitors Based on IOT
Bibliographic record
Abstract
Background/Objectives: All modern activities have been developed to manage the system fused with IoT Internet of Things. Tourism industry is also developing into a fusion and complex. Currently, the Internet of things is the most active field of use, and the development plan of the Internet of things and ecotourism is being studied very little. ICT convergence industry in other fields is considered to be a field with high potential growth potential from remote systems. The purpose of this study is to empirically verify the relationship and influence between the motivation and satisfaction of eco-tourism tourists.Methods/Statistical analysis: In order to achieve the purpose of this study, literature research and empirical research were conducted in parallel. First, the concept and characteristics of ecotourism were examined based on IoT base through theses, journals, and other related materials, and theoretical considerations such as motivation, satisfaction, revisit intention and recommendation intention of tourist destinations were conducted. The reliability test was conducted to identify internal consistency using SPSS program, and factor analysis was conducted to verify validity.Findings: In order to investigate the relationship between the motivation and satisfaction of visitors to IOT ecotourism, this study was conducted to investigate the relationship between the motivation and satisfaction. First, based on the previous studies, the characteristics and mutual relations are conceptually redefined through theoretical review of ecotourism, tourism motivation, and tourism satisfaction. Second, the relationship between tourism characteristics, tourism motivation, tourism satisfaction, and revisit recommendation intention was empirically verified for tourists visiting IOT eco-tourism sites. Third, it is intended to provide useful Infor-mation for the development and management of ecological tourist destinations and the tourists who visit ecological tourist destinations in the future.Improvements/Applications: Despite the importance of IOT ecotourism, systematic research is insufficient. The reason is that the application of ecotourism is different from case to case, so it is difficult and it is applicable to various fields, so various approaches are possible. This study was conducted to investigate the relationship between the tourist's motives and tourist satisfaction, targeting various ecotourism resources of the Jindo Mystery Sea Road Festival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".