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| Analisi di Scenario e Simulazione "What-If"× | Analisi di Sensitività Globale× | |
|---|---|---|
| Campo | Simulazione | Simulazione |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1950s (origins); widely adopted in management since 1970s | 1973–2001 |
| Ideatore≠ | Peter Schwartz (scenario planning formalization), Herman Kahn (RAND Corporation, 1950s–60s) | I.M. Sobol (indices, 2001); Morris (screening, 1991); Cukier et al. (FAST, 1973) |
| Tipo≠ | Structured analytical approach / simulation | Variance-based sensitivity decomposition |
| Fonte seminale≠ | Goodwin, P. & Wright, G. (2014). Decision Analysis for Management Judgment (5th ed.). Wiley. ISBN: 978-1118173671 | Sobol, I.M. (2001). Global Sensitivity Indices for Nonlinear Mathematical Models and Their Monte Carlo Estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280. DOI ↗ |
| Alias | what-if analysis, what-if simulation, stress testing, scenario planning | variance decomposition, Sobol indices, Morris screening, FAST method |
| Correlati≠ | 3 | 4 |
| Sintesi≠ | Scenario analysis is a structured analytical approach that systematically compares system outputs across different combinations of uncertain input values. When paired with a quantitative model, it becomes a simulation — capable of stress-testing assumptions and projecting the range of plausible outcomes. Formalised in strategic planning by Peter Schwartz and Herman Kahn from the 1950s onward, the method is widely used in policy evaluation, business forecasting, financial risk assessment, and scientific model exploration. | Global sensitivity analysis (GSA) is a family of techniques that decompose the variance of a model's output across its input parameters, quantifying how much each input — and each combination of inputs — contributes to the total uncertainty in the result. Sobol's variance-based indices (2001), Morris's one-at-a-time (OAT) screening (1991), and the Fourier Amplitude Sensitivity Test (FAST, first proposed by Cukier et al. in 1973) are the three most widely used approaches. Together they serve as the standard toolkit for identifying which parameters drive model behaviour and which can be safely fixed. |
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