Social Responsibility and Its Effect on the Companies’ Success According to Users Opinions in Jordan
Bibliographic record
Abstract
The main purpose of this study is to examine the impact of social responsibility on the companies’ success according to users’ opinions, the study applies the qualitative method to collect the data through semi-structure interview to extract the users perception about how social responsibility effect on companies’ success, the researcher identified several criteria to understand the concept of "social responsibility’’ and used several variables (ten variable) as a proxy to measure companies’ success, the paper indicate that all accounting information users agree on the importance of social responsibility to help them in the judging the companies’ success and there is a strong effect of social responsibility on the companies’ success which in turn affect users’ decisions, such as investors. The public image of the organization will be better when playing a social role, and reduce the government’s actions and laws, one of the most important results obtained from the respondents’ views is that CSR announcements provide new information to the market and allow the users to change or modify their decisions, also we find that two groups’ investors and accountants have a very diverse view on CSR application. The findings of the study have important implications concerning users of financial statements. In particular, investors and creditors (the supplier of capital) the study confirms that the importance of social responsibility and the main role of social responsibility in decision making process. It is believed that there is no Jordanian study to date examining the impact of the social responsibility on the companies’ success according users perspective. Also this considers the first study that used the qualitative method for data collection semi-structure interview, therefore, this study significantly contributes to the limited literature on the perceived the effect of social responsibility on the firm’s success. The difficulty of applying such studies depending on interviewing in developing countries, such as Jordan.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".