Paid accommodation use of international VFR multi-destination travellers
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the use of paid accommodation by international visitors who also stay with a friend or relative in another destination. Design/methodology/approach This paper conducts analysis of secondary data to look at the proportion of person nights in paid accommodation attributable to visitors who also stay with a friend or relative in another destination, and comparison of different visitor groups and their likelihood to use paid accommodation. Findings Results show that 14.5 per cent of all person nights spent by international visitors to Canada in paid accommodations were attributable to people who also stayed with a friend or relative in another destination. This proportion is higher for destinations outside of the largest cities and varies by source market. Research limitations/implications This paper is limited the structure of the secondary data set, which does not separate visiting friends from visiting relatives, and does not capture host behaviour. Practical implications This paper has implications for destination marketers and tourism businesses as a source for reflection on drivers of their local and international business. Social implications This paper helps position residents in a more central role regarding tourism in their regions and should encourage marketers and service providers to appreciate and engage residents as hosts. Originality/value This paper offers an original position by combining concepts from visiting friends and relatives and multi-destination travel that provides a foundation for further research in this area.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".