Effect of Product Development and Standard Product to Performance of Ecotourism: Case of Ranong Province, Thailand
Bibliographic record
Abstract
This world is marvelous place full of mystifying places and spectacular experiences only waiting for travel around and exploration. Ecotourism builds cultural and environmental awareness and recognition of such places. Therefore, the current research has investigated the relationship between historical places, natural environment, cultural values, ecotourists satisfaction, and ecotourism performance. Ecotourists satisfaction has direct impact on ecotourism performance. According to the current research, historical places, natural environment, and cultural values particularly in Ranong, a province of Thailand, play significant role for the ecotourist satisfaction and attraction. Hence a survey was conducted to obtain primary data to know ecotourists’ satisfaction level and how it impacts on ecotourism performance. In the survey 850 ecotourists were considered as the respondents of the current research. Hence, after collection of primary data from the respondents, a statistical software name Partial Least Square (PLS) was used to analyze the data for the achievement of end results of the current research. Moreover, the current research helps concerned authorities of Ranong that how they can utilize and earn more profit from ecotourism and make their natural areas recipient of well-being of their people.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".