Social and Environmental Accounting Reporting and Financial Performances in Ghana
Bibliographic record
Abstract
The paper seeks to ascertain the effects of social and environmental accounting disclosure on the financial performance of companies registered on the Ghana Stock Exchange over the period of three years from 2015 to 2017. The study similarly seeks to determine the extents of social and environmental accounting issues reported and finally document the extent to which companies included SEAR issues in their corporate strategy plan in Ghana. The study used secondary data from a published corporate annual statements of all the registered companies on the Ghana Stock Exchange. A regression model and t-test were used to ascertain the effects of social and environmental accounting reporting on firm’s financial performance. However, questionnaires and content analysis were also used in company reports as a system to measure the degree and nature of corporate social accounting reporting as maintained by the number of words disclosed over the three periods. Results shows that there is a positive correlation between CSR score measuring the social and environmental accounting practices and the company's financial performance registered on the Ghana Stock Exchange. Thus, the effects are insignificant. However, the findings show that companies in Ghana are now hugging social and environmental accounting reporting practices since the course of adoption of SEAR was above 60% from 2015 to 2017. The positive correlation between social and environmental accounting and reporting and companies financial performance specify reliable step pace for top managers in companies grasp and embrace social and environmental accounting reporting practices in Ghana, West African countries and all developing Africa countries. The study backs to the literature and information of corporate social and environmental accounting in West Africa and all developing Africa countries. Besides, it also may be terrific to corporate institutions for comprehension of the social responsibilities be obliged to their stakeholders and community in general.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".