Moving beyond “the” business case: How to make corporate sustainability work
Bibliographic record
Abstract
Abstract One of the most investigated research topics in the corporate sustainability literature is “the” business case. Long lionized for linking the profit motive to corporate environmental initiatives, the business case for sustainability is now vehemently criticized. These critics generally argue for a return to the state and stronger regulatory frameworks. Others counter that because the private sector's capabilities are uniquely suited to realizing effective sustainability innovations and outcomes, we must not abandon but further develop our business case understanding. In this view, firms' voluntary efforts are key for innovative solutions to sustainability problems. This article overviews and unites these seemingly disparate positions. We move the field forward by placing in context criticisms and also opportunities for more meaningful positive impacts from corporate sustainability. Specifically, we argue that an effective business case orientation requires shifting to a broader “all stakeholders win” approach. This entails impact orientation, collaborative approaches, and economic restraint.
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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 | 0.058 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.017 | 0.058 |
| Scholarly communication | 0.033 | 0.052 |
| Open science | 0.006 | 0.022 |
| Research integrity | 0.018 | 0.015 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".