The Impact of Cultural Heritage on Sustainable Tourism - Case Study of Ferizaj Region
Bibliographic record
Abstract
This study aims to analyze the impact of cultural heritage on sustainable tourism in the Ferizaj Region.Through surveys and data analysis, it seeks to explain how visitors' perceptions and feelings towards cultural heritage influence their decisions to visit the region.The results show that cultural heritage has a positive impact on attracting visitors, especially when it offers an authentic sense of the area's culture and history.However, its influence faces challenges and obstacles such as the lack of sufficient tourist infrastructure and limited information about cultural heritage.The study also highlights that to promote and preserve cultural heritage for sustainable tourism, these challenges must be addressed and measures must be taken to improve infrastructure and provide comprehensive information.The findings of this paper will serve as a good reference point for future research in this field.They will also help local authorities, the tourism industry, and the community create a suitable and attractive environment for visitors, emphasizing the crucial role of cultural heritage in their tourist experience.Practical implications: This shows the positive impact of cultural heritage on sustainable tourism.Access to social networks can offer the potential to attract more visitors.Meanwhile, the information should be authentic and continuous to create a communication with visitors that can create a positive image for the tourist destinations they want to visit.From the practical implications, it is observed that tourist agencies should invest more in the promotion of cultural heritage and cooperation with local authorities to enable good tourist infrastructure which influences the decisions of visitors to visit the region.
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 | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".