The Test of Corporate Governance System in the Electric Utilities Industry
Bibliographic record
Abstract
The main purpose of this study is to test whether corporate governance is a system or not. Seven hypotheses are formed to reach this objective. The existence of significant relationships among three dimenisons (principles, processes and business results) is the main theme in these hypotheses. Regression analysis and reliability analysis are used in the study. 74 world’s biggest companies in electric utilities industry are used in the sample of the study. Corporate governance, sustainability and corporate social responsibility reports of these 74 companies are coded with 34 variables in the corporate governance system. It is found that there is a significant and strong relationship among three dimensions. Corporate governance is a construct of our study and principles, processes and business results are dimensions that explain this construct. The seventh hypothesis is formed to test whether corporate governance is constituted from these three dimensions or not. Cronbach alpha of these three dimensions (principles, processes and business results) is 91%. In other words, it is found that these three dimensions explain the construct (corporate governance system) of our study. Stakeholder governance model is used to test the hypotheses of the study. In sum, this study showed us that stakeholder governance model works in electric utilities industry and that there is an integrity among the variables and elements of corporate governance system.
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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".