Why Don’t They Travel? The Role of Constraints and Motivation for Non-Participation in Tourism
Bibliographic record
Abstract
Between one-quarter and one-third of the population in developed economies do not travel, but our understanding of this group is rather limited. Studies looking at constraints and motivation often treat non-travelers as an homogeneous group compared to a spectrum of traveler types. Non-travel is also often implied as being a deficit rather than a voluntary decision. A mixed-method approach is applied in this study to explicitly explore the variety within non-travelers in general and voluntary non-travelers in particular. Qualitative interviews with non-travelers were used to gain a more in-depth understanding of the underlying reasons for non-travel. Non-travelers were then segmented based on constraints and motivation in a large-scale survey representative for Germany. The resulting non-traveler typology clearly shows distinct non-travelers types. By adding a pro non-travel preference instead of using deficit-oriented arguments, voluntary types of non-travelers were identified. This implies that non-travel is not necessarily something people want to overcome.
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 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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".