Tourists Attitude towards Cultural Heritage and Halal Products: A Case Study of Lahore
Bibliographic record
Abstract
The basic purpose of this paper was to assess the tourist’s willingness to pay (WTP) for cultural heritage, their attitude toward cultural heritage, halal products (HPs), and estimate the average spending of the tourists. Moreover, the tourist's satisfaction level towards halal products. It also analyzed buying behavior, the risk associated, and preferences regarding halal food products. The data were collected in the last quarter of 2019 with the help of a well-prepared questionnaire, and respondents were selected through simple random technique. The contingent valuation method was used to estimate the mean of WTP for cultural heritage visits, and the question was in the form of dichotomous choice (yes/no). The results are drawn based on primary data using a survey of 200 tourists. Binary logistic and ordinary least square (OLS) models were applied to estimate the WTP. These statistical analyses have done with the help of MS Excel (socio-economic) and statistical packages for social sciences (SPSS) WTP. The majority of the tourists were WTP and on average USD 900 and USD, 85 were the spending of the international and national tourists respectively. Tourist’s income positively, cost, and distance negatively related to his/her home to cultural heritage were the significant determinants of WTP of the tourists. Results show that tourists preferred halal products having ‘Halal tags’ (65%), environmentally friendly (10%), healthy (13.5%), and alcohol-free (15.5%). Income was the major factor having positive and significant at (1%) impact on WTP. Food authorities should make sure that all tourists get the quality products having information along with ‘halal tag’ and the service provider should have adequate education level so that they can communicate with tourists easily and can provide better services.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".