Customers matter: How do key corporate customers affect the environmental-financial performance relationship?
Bibliographic record
Abstract
This paper examines how the relationship between the supplier's environmental and financial performance may be contingent on its key corporate customers' environmental performance (EP). Drawing on status theory, we theorize that the financial rewards a supplier receives for its environmental improvements depend on both its EP and that of its key customers. An analysis of panel data from U.S. public firms validated our hypotheses. We find a curvilinear relationship between suppliers' EP and financial performance (FP). We also find that the curvature and direction (i.e., increasing or decreasing) of the relationship depend on key customers' EP. Our results contribute to the literature by providing theoretically grounded explanations and empirical evidence that emphasize the importance of key stakeholders in suppliers' EP‒FP relationships. This research is the first large-scale study in the corporate environmental management literature to empirically examine customer influence on profitability. • The EP-FP relationship for a supplier could take a different shape depending on the customers' EP. • FP is concave increasing in EP when the customers have high EP. • FP is convex decreasing in EP when the customers have low EP. • Provide a novel revenue-cost framework for analysing the higher-order effect of EP on FP.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".