Investigating the Relationship Between ESG Performance and Financial Performance During the COVID-19 Pandemic: Evidence from the Hotel Industry
Bibliographic record
Abstract
The global economy was profoundly impacted by the emergence of the COVID-19 pandemic, with the hotel industry being among the sectors most severely affected. This study explores the relationship between environmental, social, and governance (ESG) performance and financial performance during the pandemic, focusing on 35 of the world’s largest hotel companies. A structured methodology was employed to assess short-term financial resilience using the shock depth (SD) and recovery rate (RR) indicators and long-term performance through the value-added weekly index (VAWI) and K-ratio. The findings of this study indicated that faster recovery was associated with greater capitalization. Furthermore, analysis of ESG scores indicated a median increase from 2019 to 2022, particularly in the figures of the environmental component. Despite these increases, pre-pandemic ESG scores demonstrated limited influence on short-term financial performance, though a correlation was observed between governance scores (as ESG score subscores) and long-term K-ratios. This finding suggests potential trade-offs between improving financial performance and maintaining governance standards in the sense of ESG scores. This study points to the intricate interplay between ESG and financial metrics during systemic crises, providing valuable insights for risk management and strategic planning in the hospitality business. The implications of these findings extend to the enhancement of resilience and the alignment of ESG strategies with financial sustainability.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".