Innovation Application Toward Strategic Development of Pattaya City Administration from Viewpoints of Visitors Visiting Pattaya City, Chonburi Province, Thailand
Bibliographic record
Abstract
This research investigated the application of innovation in the strategic development of Pattaya City administration from the perspective of visitors who visited Pattaya City, Chonburi Province, Thailand in January 2023.The study aimed to explore the level of innovation in Pattaya City administration, its strategic development, and the impact of innovation on strategic development.The research populations comprised of 400 visitors who responded to a questionnaire, and data analysis was conducted using statistical techniques such as frequency, percentage, average, standard deviation, correlation analysis, and multiple regression analysis.The study found that innovation was implemented at a high level in Pattaya City administration, with product innovation, strategic innovation, and process innovation being the most significant areas.Moreover, the strategic development of Pattaya City administration was identified as being at a high level, with strengthening sustainable support for a livable city, promoting the organization's potential towards becoming a regional hub, and developing towards a global tourism economy being key areas.The study also identified several innovation factors that influence Pattaya City's strategic development, including service innovation, process innovation, product innovation, social innovation, strategic innovation, and philosophical innovation.Overall, the study suggests that innovation is a crucial factor in the strategic development of Pattaya City administration.The findings provide valuable insights for policymakers and practitioners to enhance innovation and strategic development in Pattaya City.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".