Σύγκριση μεθόδων

	Fisher-Pry Substitution Model	Emerging Issues Analysis	Trend Impact Analysis
Πεδίο	Futures Foresight Studies	Futures Foresight Studies	Futures Foresight Studies
Οικογένεια	Process / pipeline	Process / pipeline	Process / pipeline
Έτος προέλευσης	1971	2009	1972
Δημιουργός	John C. Fisher & Robert H. Pry (General Electric)	Graham T. T. Molitor; Hawai'i School / Millennium Project	Theodore J. Gordon (The Futures Group / Millennium Project)
Τύπος	Logistic-growth forecasting pipeline for technological substitution	Early-detection pipeline for issues on the S-curve of public attention	Probabilistic trend-extrapolation pipeline perturbed by future events
Θεμελιώδης πηγή	Fisher, J. C., & Pry, R. H. (1971). A simple substitution model of technological change. Technological Forecasting and Social Change, 3, 75-88.	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.
Εναλλακτικές ονομασίες	Fisher-Pry Model, Technological Substitution Model, Logistic Substitution Forecasting, Fisher-Pry Curve	Emerging Issue Analysis, EIA, Issues Emergence Analysis, Weak Signal Scanning	TIA, Trend-Impact Forecasting, Probabilistic Trend Perturbation, Event-Adjusted Trend Extrapolation
Συναφείς	2	3	3
Σύνοψη	The Fisher-Pry Substitution Model, introduced by John Fisher and Robert Pry of General Electric in 1971, is a foundational technique for forecasting technological substitution — the process by which a new technology displaces an older one. Its empirical premise, supported by dozens of historical cases from synthetic to natural materials and from one manufacturing process to another, is that the fractional market share captured by the new technology follows a logistic (S-shaped) growth curve. The model's elegance lies in a transformation: when the takeover ratio f/(1-f), the ratio of the new technology's share to the old's, is plotted on a logarithmic scale against time, the substitution traces a straight line. This linearization makes it easy to fit, interpret, and extrapolate substitutions from sparse early data, which is why the Fisher-Pry curve remains a workhorse of technological forecasting.	Emerging Issues Analysis (EIA) is a horizon-scanning method, associated with Graham Molitor and the Hawai'i School and codified in the Millennium Project's Futures Research Methodology, for detecting issues at the earliest, weakest-signal stage — long before they register as trends or reach public consciousness. Its organizing idea is that issues, like technologies, follow an S-curve of public attention: they begin in obscure, marginal sources, accelerate as advocates and specialists pick them up, and only later become widely recognized trends and finally mainstream concerns. The strategic value of catching an issue on the flat, early part of that curve is enormous, because that is when there is the most time and the most room to respond. EIA therefore deliberately scans the fringe — specialist literature, activist publications, patents, subcultures, marginal voices — to spot the small clouds on the horizon and position them on the issue lifecycle.	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.