Firm Performance and Corporate Social Environmental Initiatives in the Wake of a Health Pandemic
Bibliographic record
Abstract
The study re-examines the relationship between firm share price performance and Corporate Social Environmental Reporting (CSER) initiatives in the wake of a global health pandemic. A comparative analysis was done between the contributions made by listed and non-listed firms in Nigeria towards the pandemic. A comparative analysis of the share price (SP) of listed companies was carried out before the announcement of the pandemic, after the announcement of the pandemic and COVID -19 contributions. A panel regression analysis was conducted. It involved a sample of 70 listed firms in the Nigerian Stock Exchange over a five-year period (2013-2017). The comparative analysis of contributions revealed that listed firms though fewer in number made significantly more contributions than unlisted firms. The study found significant drop in SP after the announcement of a pandemic by the World Health Organisation (WHO). The study also found that SP performance and firm size has a positive and significant relationship with CSER initiatives. The analysis of contributors from listed and non- listed firms in Nigeria towards COVID-19 reveal that only corporate organizations with adequate resource slack can make significant contributions to curtail the spread of the epidemic. The study recommends that corporate organizations should pursue financial capacity in other to make significant CSER investments and expect a change in societal demands and stakeholder expectations in the no distant future.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".