Business sustainability and corporate social responsibility: case studies of three gas operators in China
Bibliographic record
Abstract
This study investigates the corporate social responsibility (CSR) practices of three gas operators in China and the benefits resulting from these practices. The current paper provides the proposed conceptual framework, literature review of CSR theories and prior research on the experiences of companies operating in various sectors. Data from in-depth case studies of the three gas distributors in Mainland China are collected, analysed and summarised. The three gas distributors proactively developed their respective CSR objectives and engaged in CSR practices in many dimensions that related to employees, consumers, investors, community and the environment. Consequently, the benefits realised for various stakeholders and for the three companies include high-quality products and service offerings, reliable and efficient supply chain, stable cash flow, loyal customer bases, positive social image and reputation, and overall top firm’s performance. On the bases of the literature review and case analysis, implications that focus on two areas are derived and presented in this paper. Governments and other nonprofit organisations such as professional associations and trade unions play their respective roles in CSR. Government authorities can shape the CSR practices of business enterprises by providing a legal framework and related policies to guide company practices.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".