Corporate social responsibility in china: an analysis of domestic and foreign retailers' sustainability dimensions
Bibliographic record
Abstract
Abstract In the past decade, a sizeable body of literature has built up on the concept and characteristics of corporate social responsibility (CSR) in Western countries, where it has also been referred to as sustainability. More recently, attention has grown for CSR in emerging countries. Remarkably, China has hardly been studied so far. This paper aims to help fill this gap by considering, against this background, the CSR notion in China, through an exploration of a small sample of large retailers in China, both Chinese and non‐Chinese companies. The analysis of CSR/sustainability dimensions, as communicated by these large retailers in both the Chinese and the English language, shows substantial differences between the Chinese and international contexts. Interestingly, the largest divergence can be found for international retailers between their Chinese and corporate attention for CSR (so home versus host settings), most notably in the case of Carrefour, and to a lesser extent Wal‐Mart. In the Chinese context, there are differences between the Chinese and international retailers as well (so domestic versus foreign firms), with the former reporting more on economic dimensions, including philanthropy, and the latter more on product responsibility – contentious labour issues and the environment receive relatively limited attention in both groups in China. The paper concludes with a discussion of the implications for research and practice. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".