Challenges and innovations in hotel operations in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to analyse key challenges Canadian hotels are facing, and to suggest innovative steps to make hotel operations in Canada more successful. Design/methodology/approach The foundation for this paper was laid during a well attended Worldwide Hospitality and Tourism Themes (WHATT) roundtable discussion between industry leaders and hospitality educators in May 2012. The subject of hotel operations is discussed in the context of the theme for the 2012 Canadian WHATT roundtable and the strategic question: “What innovations are needed in the Canadian hotel industry and how might they be implemented to secure the industry's future?” Findings The paper provides valuable information on hotel management and operations, and outlines innovative solutions to key challenges Canadian hotels are facing. Practical implications The paper highlights effective approaches to managing hotel operations. The authors propose segment‐specific, tailor‐made training sessions for the diverse workforce of today. Originality/value The paper draws on the authors' experience and observations to explain how hoteliers can implement innovative change that enables them to achieve greater operational success. As the team of authors represents both academia and the industry, including a former general manager of the largest hotel in Canada, this paper will be of immense value to students, educators, and researchers, as well as industry leaders.
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.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it