A Comparative Study of the Hotel Industry: Revenue Management Strategy in Canada and the United States
Bibliographic record
Abstract
As a result of the perfect storm of 2008-2009 (an intensely competitive environment and extremely harsh economic conditions), hotel properties around the world are more dependent upon revenue management strategies today. Furthermore, hotel revenue management has become a core strategic element for both domestic and international major brand name hotels within today's worldwide lodging industry. Accordingly, this study examined any potential linkage between revenue management resources, management approach, working knowledge of the external environment, and overall revenue management performance of international hotel properties. In this context, revenue management resources speak to management information systems, technology, and human capital. Furthermore, management's approach to how the external environment is taken into consideration is also addressed. Consequently, this study identifies which specific outside variables management considers relevant to the revenue management decision-making process. As such, this study contributes to the discipline of revenue management by addressing the following: (a) How are revenue management decisions for hotel properties influenced by external factors if at all? (b) How significant are internal resources, such as human capital and technology, to the success of hotel revenue management programs and systems as well as overall firm performance in a cross-border, premier international tourist destination? The results of this study help to augment and expand revenue management theory as well as provide hotel managers with a deeper understanding as to how revenue management decisions are influenced by external environmental factors as well as the importance of internal resources on hotel revenue management performance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".