Effective Factors of Service Marketing Mix on Tourist Satisfaction: A Case Study
Bibliographic record
Abstract
The core goal of the study is to examine the relationship between the service marketing mix and tourist satisfaction. The study also attempted to measures the impact of each element of service marketing on tourist satisfaction at Ahsan Manzil in Bangladesh. In order to attain the goal of the research, a good number of extant literature was reviewed and a structured questionnaire was developed to meet the research gap. Based on the studied variables non probabilistic convenience sampling method used to collect data from a sample of 250 respondents who visited the place and seven causal hypothesize was developed. Statistical measurement techniques employed for the study are descriptive, correlation, regression, ANOVA used and cronbach alpha measured the internal consistency of variables. Data analysis executed by using SPSS 20.0. The findings of the study revealed a positive linear relationship of all variables with tourist satisfaction except promotional activities. The novelty of the paper is that it exhibited the consequences of tourists’ satisfaction and dissatisfaction to guide decision-makers and to keep the specific focus on promotional activities.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".