Effects of Environmental Management Standards on Business Performance in India
Bibliographic record
Abstract
Purpose of this study was to test the effects of perceived importance of environmental management on business performance while controlling for firm size and cost of implementation of the environmental management standards. The term environmental management refers to a business process that ensures an environmentally friendly manufacturing process; i.e., one that complies with the Environmental Management Standards (ISO 14001), whereas business performance relates to firm’s profitability, international trade, “green” (environmentally friendly) image and competitive advantage. Using survey method and multiple regression analysis, results of this study indicated that (1) environmental management was significantly positively related to profitability and international trade; (2) firm size was significantly positively related to competitive advantage and (3) cost was significantly negatively related to competitive advantage. The implication for managers is that they can use the findings to formulate strategies to differentiate and position their firms as green, and thus can target green consumers and attract potential investors interested in investing in green firms. This study contributes to literature by operationalizing the environmental management scale, testing it for its reliability and validity and applying it in the emerging market of India whose managers’ attitudes toward environment are somewhat different from developed countries.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".