Sustainability‐oriented Innovation: A Systematic Review
Bibliographic record
Abstract
This paper is intended as a contribution to the ongoing conceptual development of sustainability‐oriented innovation (SOI) and provides initial guidance on becoming and being sustainable. The authors organize and integrate the diverse body of empirical literature relating to SOI and, in doing so, develop a synthesized conceptual framework onto which SOI practices and processes can be mapped. Sustainability‐oriented innovation involves making intentional changes to an organization's philosophy and values, as well as to its products, processes or practices to serve the specific purpose of creating and realizing social and environmental value in addition to economic returns. A critical reading of previous literature relating to environmental management and sustainability reveals how little attention has been paid to SOI, and what exists is only partial. In a review of 100 scholarly articles and 27 grey sources drawn from the period of the three Earth Summits (1992, 2002 and 2012), the authors address four specific deficiencies that have given rise to these limitations: the meaning of SOI; how it has been conceptualized; its treatment as a dichotomous phenomenon; and a general failure to reflect more contemporary practices. The authors adopt a framework synthesis approach involving first constructing an initial architecture of the landscape grounded in previous studies, which is subsequently iteratively tested, shaped, refined and reinforced into a model of SOI with data drawn from included studies: so advancing theoretical development in the field of SOI.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".