The Impact of the Short Span between COVID-19 Recovery and the Onset of Russia-Ukraine Conflict on the Financial Performance of FTSE 350 Service Firms
Bibliographic record
Abstract
The COVID-19 outbreak and recovery, as well as the Russia-Ukraine conflict, have resulted in several difficulties and risks that affect economies and the businesses functioning within them. Both have fundamentally altered how businesses are run. So far, just a few studies have examined how the conflict between Russia and Ukraine affects both countries, with a particular focus on Russia given the severe international financial sanctions that are now affecting its economy. Thus, this study explored the effect of the short timeframe between COVID-19 recovery and the onset of the Russia-Ukraine war on the financial performance of FTSE 350 service companies. In the study, the financial ratios of the sampled firms were computed for both during COVID-19 recovery (i.e., from the last quarter of 2021 to the end of the 1st quarter of 2022) and during the Russia-Ukraine war (i.e., from the end of the 1st quarter of 2022 to the end of the 1st quarter of 2023). Then, using t-test, the significance level of the differences between these two sets of financial ratios was determined. From the results, it was revealed that the overall performance of the firms improved, with service firms into energy services, real estate, financial services, materials procurement, and staffing/recruitment services being less sensitive to the effect of the Russia-Ukraine war on their financial performance indicators whereas the firms into asset management, investment management, retails, and insurance were more sensitive to the effect of the war as their financial performance were more negatively impacted on by the war. And despite the improved performances of the firms, the differences in their performance compared to the period of COVID-19 recovery were not statistically significant. Hence, the null hypothesis formulated in the study was accepted, implying that there is no significant effect of the short timeframe between the recovery from COVID-19 and the onset of Russia-Ukraine war on the financial performance of FTSE 350 service firms. Keywords: COVID-19 recovery; Russia-Ukraine conflict; Financial performance; FTSE 350 service firms; Financial ratios. DOI: 10.7176/EJBM/15-17-02 Publication date: October 31 st 2023
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".