SARS: lessons in strategic planning for hoteliers and destination marketers
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 The purpose of this paper is to review the impact that the 2003 SARS epidemic had on tourism and summarize the lessons that were learned from this crisis. To offer both practical and strategic tips for hoteliers and destination marketers in the Niagara region should a similar crisis affect this region. Design/methodology/approach Findings were derived from the analysis of both secondary and primary data. The popular press and academic journals as well as reports, briefs, and presentations were analyzed. A questionnaire was designed to investigate the impact of SARS, management during the crisis, recovery strategies, and formal planning. Findings Provides information on how industry dealt with a major, extended crisis. Recognizes the importance of an integrated strategy for dealing with a crisis. Research limitations/implications The paper concentrates on the effects of an epidemic in two large North American cities. The strategic and practical tips may not be suitable in other jurisdictions. Practical implications This paper provides information on how the tourism industry can prepare itself for a crisis or disaster and describes how all stakeholders must work together to better deal with the effects of a crisis. Originality/value This paper summarizes the effects that SARS had on the tourism industry and offers practical and strategic tips for preparing for and managing crises.
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 | 0.002 | 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