方法对比

	Relevance Tree Analysis	Trend Impact Analysis
领域	Futures Foresight Studies	Futures Foresight Studies
方法族	Process / pipeline	Process / pipeline
起源年份	1966	1972
提出者	Defense and aerospace planners (Honeywell's PATTERN program); systematized in futures research by Gordon, Helmer and colleagues	Theodore J. Gordon (The Futures Group / Millennium Project)
类型	Normative hierarchical decomposition pipeline for R&D priority-setting	Probabilistic trend-extrapolation pipeline perturbed by future events
开创性文献	Glenn, J. C., & Gordon, T. J. (Eds.). (2009). Futures Research Methodology, Version 3.0. The Millennium Project. ISBN: 9780981894119	Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross-impact matrix method of forecasting. Futures, 1(2), 100-116.
别名	Relevance Tree Method, Relevance Number Analysis, Normative Relevance Tree, PATTERN-Style Relevance Trees	TIA, Trend-Impact Forecasting, Probabilistic Trend Perturbation, Event-Adjusted Trend Extrapolation
相关	3	3
摘要	Relevance tree analysis is a normative forecasting method that decomposes a high-level objective into a hierarchy of sub-objectives, functions, and contributing technologies, and then assigns relevance numbers that quantify how much each branch contributes to its parent. By normalizing these numbers so that the children of every node sum to one and multiplying them down each path, the method produces an overall relevance score for every technology or task at the leaves, which ranks them by their importance to the top objective. Unlike exploratory forecasting, which projects what the future will be, relevance trees work backward from a desired goal — they are 'normative,' starting from where you want to go and identifying what must be developed to get there. Originating in defense and aerospace planning and codified in Glenn and Gordon's Futures Research Methodology, the technique remains a standard tool for research-and-development priority-setting and mission analysis.	Trend impact analysis (TIA) is a forecasting method that marries quantitative extrapolation with expert judgment about disruptive future events. Developed by Theodore Gordon and colleagues at The Futures Group in the early 1970s and later codified in the Millennium Project's Futures Research Methodology, it starts from a 'surprise-free' baseline produced by fitting and projecting a historical time series. It then asks which unprecedented events — events with no historical analog that ordinary extrapolation cannot anticipate — could deflect that trend, and with what probability, magnitude, and timing. Through Monte Carlo simulation those probabilistic impacts perturb the baseline, yielding not a single line but a probability envelope that shows how the trend might bend if the unexpected occurs.