Bibliographic record
Abstract
Purpose As pressure for companies to improve their environmental performance has intensified in recent years, research attention has shifted away from establishing a link between environmental practices and performance towards consideration of other factors that might facilitate performance improvements. The purpose of this paper is to: first, to investigate whether internal support processes interact with pollution prevention by positively moderating the relationship between pollution prevention and environmental performance; and, second, to assess whether the relationship between pollution prevention and cost performance is mediated by environmental performance. Design/methodology/approach It uses a cross-sectional survey of 1,200 UK-based food processing firms to gather information on environmental practices and performance. Regression analysis was conducted on a sample of 149 responding firms to assess the hypothesised relationships. Findings Support was found for two of the four moderated relationships hypothesised namely, suggesting that internal support processes support the environmental performance of some pollution prevention practices. Strong support for a mediated relationship between pollution prevention, environmental performance and cost performance was provided by the results. Originality/value This study provides an original contribution to the literature on the performance outcomes of environmental practices by considering a number indirect relationships between environmental practices and performance. This has implications for the interpretation of the relationship between environmental practices and performance.
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 | 0.002 | 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".