The Effect of Population Socio-Economic Characteristics on Tourism Demand in Serbia: A Survey
Bibliographic record
Abstract
The synthesis of various theoretical concepts and empirical research confirms the significance of leisure time and leisure funds as fundamental factors of tourism demand. It also confirms the fact that the correlation between resources and needs shows that all the person's efforts are directed to coordination between their needs and means and that those tourist needs are manifested through the tourist consumption. Therefore, the study is based on the assumption that socio-economic characteristics of population have a great influence on the decision concerning where and how the vacation will be used.Thus, the aim of the research was to determine whether there is and how important is the influence of socio-economic characteristics of the population as independent variables on the scope and direction of movement of tourist demand in the particular case in practice.Based on the conducted research and analysed results, the authors strived to examine the initial hypotheses, that is to provide a statistical correlation between the dependent and independent variables.The results of research confirm the hypothesis that the socio-economic characteristics of working and living conditions of the population have a great impact on the dynamics and scope of tourism demand.According to the defined aim, the theoretical elaboration of the results dominates the study. During the research and results analysis, the following methods were used: T-test, One-Factor Analysis of Variance, Pearson Correlation Coefficient, Logistic Regression and Multiple Regression.
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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 | 0.001 |
| 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 | 0.001 | 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".