Tourism behaviour: travellers' decisions and actions
Bibliographic record
Abstract
Abstract This book focuses on individuals' and households' thinking and behaviour relating to discretionary travel. Part I (chapters 1-3) covers new theories of tourism behaviour and offers examples of empirical examinations of these theories in three settings: Australia, Hawaii (USA), and Prince Edward Island (Canada). Part II (chapters 4-11) builds and examines a theory comparing leisure traveller plans and behaviour. The eight chapters in part II cover all four possible behaviours: (1) planned and done (deliberate strategies); (2) planned and not done (unrealized strategies); (3) unplanned and done (emergent strategies); and (4) unplanned and not done (unused but possible strategies). The trade-offs made in life among work, leisure, travel and personal maintenance actions and how plans actually relate to deeds are therefore considered. Plans and behaviours for tourist spending, length of stay, attractions, destinations, accommodation and activities are reviewed and how marketing strategies affect consumer plans are investigated. This book is intended for travel and leisure researchers, destination marketing managers and advanced students in tourism and consumer behaviour. The book has a subject index.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".