विधियों की तुलना करें

	SMIC Prob-Expert	Cross-Impact Balance Analysis
क्षेत्र	Futures Foresight Studies	Futures Foresight Studies
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2006	2006
प्रवर्तक	Michel Godet (LIPSOR)	Wolfgang Weimer-Jehle
प्रकार	Probabilistic cross-impact pipeline for ranking scenario combinations	Semi-quantitative scenario-construction pipeline
मौलिक स्रोत	Godet, M. (2006). Creating Futures: Scenario Planning as a Strategic Management Tool (2nd ed.). Economica. ISBN: 9782717852448	Weimer-Jehle, W. (2006). Cross-impact balances: A system-theoretical approach to cross-impact analysis. Technological Forecasting and Social Change, 73(4), 334-361.
उपनाम	SMIC, Systeme et Matrices d'Impacts Croises, SMIC-PROB-EXPERT, Probabilistic Cross-Impact Method	CIB Analysis, Cross-Impact Balances, Balance Algorithm Scenario Analysis, Qualitative Systems Analysis (Weimer-Jehle)
संबंधित	3	4
सारांश	SMIC Prob-Expert — from the French Systeme et Matrices d'Impacts Croises, Systems and Matrices of Cross-Impacts — is the probabilistic cross-impact method in Michel Godet's la prospective toolkit. It takes a small set of fundamental hypotheses about the future and asks experts for both the simple probability that each hypothesis comes true and the conditional probabilities linking the hypotheses to one another. Because experts' raw estimates are rarely mutually consistent, SMIC's core is a quadratic optimisation that adjusts them minimally into a coherent joint probability distribution over the 2^n possible combinations of the hypotheses. Each combination is an image of the future — a scenario — and the corrected, or net, probabilities rank these images from most to least likely. The method thereby turns scattered expert opinion into a probabilistically weighted set of scenarios, identifying the few core futures that concentrate most of the probability mass.	Cross-Impact Balance (CIB) analysis is a semi-quantitative foresight method that turns a panel of qualitative expert judgments into a small set of internally consistent scenarios. Introduced by Wolfgang Weimer-Jehle in 2006, CIB describes a system as a set of descriptors, each of which can take one of several discrete future states, and asks experts to judge, pairwise, how strongly each state promotes or restricts every other state. These judgments form a cross-impact matrix; a balance algorithm then searches the combinatorial space of state combinations for configurations in which every descriptor's chosen state is the one most strongly supported by all the others. These self-consistent combinations are the scenarios. CIB has become a standard tool for building qualitative socio-technical scenarios, including the shared socio-economic pathways used in climate research.