Deal or no deal on water‐saving program? Exploring the optimal interval for government subsidies and internal incentives
Bibliographic record
Abstract
Water resources can be soon exhausted with the overdeveloped industrialization. High-water-consumption (HWC) industries and their supply chains are trying to reduce water consumption in the production process. These water-saving behaviors and effects may be subsidized by the government to pursue the goal of social welfare maximization (SWM). In this context, to investigate when to bring in government subsidy for any water-saving behaviors and effects to maximize the social welfare, six game-theoretical decision models for the water-saving supply chain under three scenarios are developed, analyzed, and compared, and the corresponding numerical and sensitivity analyses of water-saving case in the papermaking industry are conducted and compared; on this basis, the corresponding policy implications and managerial insights are discussed and summarized in this article. The research results indicate that the supply chain would only have internal incentive to implement water-saving management under low- or medium-cost case, while the government would only have external incentive to subsidize water-saving behaviors and effects under medium-cost case. Besides, the coordination strategy outperforms the equilibrium strategy regarding the water-saving effects, operational performances, social welfare, consumer surplus, and positive externality for the water-saving supply chain under all three scenarios. Furthermore, a kind of niche targeting subsidy policy based on actual water-saving effect that the government only subsidizes the water-saving supply chain operating under coordination strategy with medium water-saving cost structure can achieve social welfare maximization, operational performance improvement, and positive externality enhancement. PRACTITIONER POINTS: The optimal interval for internal incentives of water-saving is explored. The optimal interval for government subsidies of water-saving is investigated. The optimal operational strategy for the water-saving supply chain is examined.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".