An integrated management systems approach to corporate sustainability
Bibliographic record
Abstract
Purpose This paper seeks to describe an integrated management systems (IMS) approach for the integration of corporate sustainability into business processes. Design/methodology/approach An extensive review of published literature was conducted. Building on existing research, the paper presents an original framework for structuring the integration of corporate sustainability with existing business infrastructure. The framework is supported by a detailed set of diagnostic questions to help guide the process. Both the framework and the diagnostic questions are based on the “Plan‐Do‐Check‐Act” cycle of continuous improvement. Findings The paper highlights the need for a systematic means to integrate sustainability into business processes. Building on that point, the paper illustrates how an IMS approach can be used to structure the entire process of managing, measuring, and assessing progress towards corporate sustainability. Practical implications The paper should be of interest to both practitioners and researchers. The framework and diagnostic questions will help guide decision makers through the process of building sustainability into their core business infrastructure. Since the framework and diagnostic questions provide the flexibility to accommodate specific organizational contexts, it is anticipated that they will have wide applicability. Originality/value The paper makes several contributions. The framework provides a systematic approach to corporate sustainability that has not been elaborated on in previous publications. The unique set of diagnostic questions provides a means to evaluate the extent to which corporate sustainability has been integrated into an organization.
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 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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".