VOLUNTARY ACTION OF A FIRM ON ENVIROMENT MANAGEMENT: AN EMPIRICAL ASSESSMENT ON SRI LANKAN FOOD PROCESSING FIRMS’ RESPONSE TO THE PRIVATE AND REGULATORY INCENTIVES
Bibliographic record
Abstract
The effect of a set of private/market (i.e. financial implications, internal efficiency, market response) and public/non-market (i.e. government regulation, judiciary/legal system) incentives for a firm to act voluntarily on environmental quality is examined. It uses the levels of adoption of five solid waste management practices [SWMPs], namely: (1) 3R system; (2) Composting; (3) Good manufacturing practices; (4) Biogas unit, and (5) ISO 14000 by food processing sector in Sri Lanka in response to the prevalence of each incentive at the firm as the case. The data collected from 325 firms through in-depth interviews and site inspections and supported by a validated structured questionnaire were analyzed using the principles of Structural Equation Modeling. The “Analysis of Moment Structures” (AMOS) software was used to establish the relationships between the levels of adoption of SWMPs and the strength of each incentive. The results show that firms‟ response to environment is relatively low, i.e. 49.2% did not adopt a single practice, while only 28%, 12%, 7.4%, 3.1% and 0.3%, respectively, have adopted 1, 2, 3, 4 or all practices. Firms tend to adopt a higher number of SWMPs as the relative strength of an each incentive perceived by the decision maker of firm gets increases. Firms put a higher weight on the impact on regulation and legal system than the private incentives and the firm size has a substantial impact on its response to the environment. The results highlight the importance of bringing the current public regulatory regimes in developing countries like Sri Lanka towards co-regulation, which is practiced by developed countries like Australia and Canada to facilitate businesses to come up with own solutions for environmental and food quality, as the outcome of this analysis points out that firms‟ compliance to the recommended SWMP was not triggered satisfactorily by the private/voluntary action.
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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 | 0.008 | 0.019 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".