Economic and environmental impacts of vertical and horizontal competition and integration
Bibliographic record
Abstract
Abstract We explore the economic and environmental impacts of market structures (competition or integration at vertical and horizontal levels). We consider a bilateral duopoly consisting of two manufacturers and two retailers in which each manufacturer offers a wholesale price contract to the respective retailer. The manufacturers decide on wholesale prices and abatement efforts concerning pollution emissions related to manufacturing processes, whereas the retailers compete in quantities in the consumer market. To understand the comprehensive effects of market structures on economic competitiveness and environmental sustainability, we examine a measure of eco‐friendly social welfare, which is the ratio of social welfare and environmental pollution. Interestingly, we find that the market structures that have been believed to be more efficient are less efficient from a broader perspective: (1) double marginalization can generate higher eco‐friendly social welfare, and (2) horizontal competition between firms can result in lower eco‐friendly social welfare. Although vertical integration and horizontal competition yield greater social welfare by facilitating more production activities, these market structures often fail to induce sufficient abatement efforts to balance the polluting effect of the large volume, resulting in more significant environmental degradation. We also show that, despite the pollution‐curbing effect, higher emission penalties can result in less eco‐friendly social welfare. They can even curtail the abatement efforts of firms under particular circumstances. When products become more substitutable, the eco‐friendly social welfare can decrease depending upon the market structure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".