Financial benefits and risks of dependency in triadic supply chain relationships
Bibliographic record
Abstract
Abstract The economic consequences of interdependent relationships with suppliers and customers have long been of interest to supply chain managers and academics alike. Whereas previous studies have focused on the benefits or risks of embedded relationships that accrue to buying firms, this study simultaneously investigates the effects of a supplier's and a customer's embeddedness, arising from resource dependency, on a focal firm's financial performance in triadic supply chain relationships. Using 1,144 unique focal firm‐years for U.S. firms from Compustat, we find that a supplier's and a customer's dependency both increase the focal firm's performance in terms of return on assets (ROA) and return on sales (ROS) by increasing asset turnover (ATO). As levels of supplier and customer dependency on the focal firm increase, however, the economic benefits of customer dependency diminish beyond a certain point, while those of supplier dependency continue to increase above that threshold. Thus, our findings show the paradoxically differing risks of the supplier's versus the customer's dependency, while establishing the unequivocal economic benefits of supplier and customer relations for focal firms in the middle of concentrated triadic relationships.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".