Emerging economy sourcing: Implications of supplier social practices for firm performance
Bibliographic record
Abstract
As firms search the world for suppliers that provide the best combination of cost, quality and latest technology, they have been confronted with the challenges of managing the sustainability performance of their global supply chains. Specifically, companies have come under increased scrutiny from various stakeholder groups for the labour and human rights practices of suppliers located in emerging economies. Drawing on the sustainability, supplier relationship management, and stakeholder literature, this research examines the relationship between emerging economy sourcing, the use of purchasing teams, and the impact on enforcement of supplier social practices, and firm financial performance. Using data from a survey and archival sources from a sample of large U.S. firms, findings confirm the mediated role of the use of purchasing teams resulting in better enforcement of supplier social practices and improved firm performance. Findings also provide important implications for supply chain and purchasing executives. While the results of this research demonstrate the performance benefits of sourcing from emerging economies, findings also suggest that organizations should make investments to support capabilities related to enforcement of supplier social practices. Opportunities for future research are also identified.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".