方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 政策情景分析× | 随机情景分析× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1967–1990s | 1955–1980s |
| 提出者≠ | Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD | Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition |
| 类型≠ | Qualitative-quantitative hybrid scenario method | Probabilistic scenario enumeration and evaluation |
| 开创性文献≠ | Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146. DOI ↗ | Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374 |
| 别名 | PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis | Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis |
| 相关≠ | 5 | 4 |
| 摘要≠ | Policy Scenario Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health. | Stochastic Scenario Analysis evaluates a system or decision across multiple explicitly defined scenarios, each assigned a probability of occurrence. Unlike deterministic scenario analysis, it propagates uncertainty through probability distributions and computes expected outcomes, variance, and risk metrics across the scenario space, giving decision-makers a structured view of what could happen and how likely each outcome is. |
| ScholarGate数据集 ↗ |
|
|