Comparison of Chinese Tourists’ Expectations and Perceptions on Seaside Resort Areas’ Service Quality: A Case of Chinese Tourists in Southern Region of Thailand
Bibliographic record
Abstract
The objectives of this study were to analyze the Chinese tourists' expectation and perception gaps of service quality in southern Thailand's seaside resorts, to study the items of service quality that are satisfied by Chinese tourists in southern Thailand's seaside resorts, to study the items of service quality that are dissatisfied by Chinese tourists in southern Thailand's seaside resorts. The researcher used the survey questionnaire to collect data from 400 Chinese tourists who visited seaside resort areas in the southern region of Thailand and used descriptive statistics. The results found that Chinese tourists think some perceptions exceed their expectations, such as supporting online bookings in seaside areas, the staffs provide personalized service, the staffs are respectful, use polite language, smile service towards Chinese tourists, the seaside resorts have technical support. However, Chinese tourists think some perceptions can't reach their expectations, as for the price, it doesn’t have a reasonable price for food items, accommodation, traffic, commodity, and entertainment. As for the staff, it doesn’t have a first-class ability to handle emergencies, they can’t provide fast services. As for the managers of resort areas, it doesn’t have enough legal frameworks in protecting Chinese tourists. The study recommends that the managers of seaside resort areas in southern Thailand need control of the cost of accommodation, food, transportation, commodities to be more rationalized. Additionally, managers should introduce laws and policies to protect the rights and interests of Chinese tourists, improve the ability of staff to handle emergencies and provide fast service for Chinese tourists.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".