The hospitality and tourism industry in Canada: innovative solutions for the future
Bibliographic record
Abstract
Purpose This paper aims to provide practical solutions to the strategic question: “The hospitality and tourism industry in Canada: what are the main challenges and solutions?”. It aims to capture the essence of scholarly contributions made by 25 Canadian experts and provide a conclusion to the Worldwide Hospitality Themes ( WHATT ) theme issue (v.9, n.4) dedicated to Canada. Design/methodology/approach The paper draws from key concepts, suggestions and solutions written by 25 Canadian authors in the previous papers of this theme issue. It is worth noting that these authors together have more than 700 years of experience in managing, operating and teaching all aspects of the tourism and hospitality industry. The paper presents nine summaries in the following order: the state of the industry (introductory article); finding innovative solutions for HR challenges (four articles); and new trends and innovation (four articles) Findings In conclusion, 20 recommendations relating to human capital enhancement, as well as general suggestions, are made to embrace useful trends and innovative thinking for future progress in Canada’s hospitality and tourism industry. Practical implications As this paper is a combination of many perspectives from nine co-authored articles, there is no single focus to draw common conclusions. For further information and analysis, it is recommended that the relevant articles from this theme issue be reviewed. Originality/value Readers interested in the Canadian hospitality and tourism industry will find this paper to be of interest.
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 | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".