The behavioral strategies of multiple stakeholders in the NIMBY facility public-private partnership project: a tripartite evolutionary game analysis based on prospect theory
Bibliographic record
Abstract
In this study, evolutionary game method, prospect theory, and system dynamics (SD) method are combined to analyze the key stakeholders’ behaviors in the public-private partnership project of not-in-my-back-yard facility. First, the interaction behavior of the public sector, the private sector, and the public and their equilibrium state was analyzed based on the evolutionary game method and prospect theory. Then, the SD method was used to simulate and analyze the impact of different variables on the behavior of the three stakeholders. The results show that the greater the perceived cost difference between the active and negative behavior among the three stakeholders, the more likely they are to take negative behavior. The private sector tends to act opportunistically under low-risk loss situations. Dynamic rewards are more likely to incentivize the public to supervise than high rewards. Some recommendations to promote active behavioral interactions and cooperation among stakeholders were presented accordingly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".