方法对比

	Delphi Technology Forecasting	Gompertz Substitution Forecasting
领域	Futures Foresight Studies	Futures Foresight Studies
方法族	Process / pipeline	Process / pipeline
起源年份	1964	1971
提出者	Olaf Helmer, Norman Dalkey, and colleagues at the RAND Corporation	Benjamin Gompertz (curve); growth-curve technology forecasters (Lenz, Martino) and the Fisher-Pry tradition
类型	Iterative anonymous expert-panel pipeline for forecasting technological events	Growth-curve diffusion pipeline for technology adoption and substitution
开创性文献	Glenn, J. C., & Gordon, T. J. (Eds.). (2009). Futures Research Methodology, Version 3.0. The Millennium Project. ISBN: 9780981894119	Fisher, J. C., & Pry, R. H. (1971). A simple substitution model of technological change. Technological Forecasting and Social Change, 3, 75-88.
别名	Technological Delphi, RAND Delphi Forecasting, Expert Panel Technology Forecasting, Delphi Event Forecasting	Gompertz Diffusion Forecasting, Gompertz Growth-Curve Forecasting, Asymmetric S-Curve Technology Forecasting, Gompertz Adoption Model
相关	3	3
摘要	Delphi technology forecasting is the original and best-known application of the Delphi method: using iterative, anonymous rounds of expert judgment with controlled statistical feedback to forecast the timing and probability of specific technological developments. Developed at the RAND Corporation by Olaf Helmer, Norman Dalkey, and colleagues, the technique was designed to harness expert opinion systematically while suppressing the social pressures of face-to-face committees — dominant personalities, bandwagon effects, and reluctance to abandon a stated position. Rather than asking a panel for a general opinion, technological Delphi asks experts to predict the year by which a well-defined development will occur, or the probability that it will occur by a given date, and then feeds back the panel's median and spread so that experts can reconsider in light of the group. Glenn and Gordon's Futures Research Methodology treats it as a foundational structured-judgment method of the field.	Gompertz substitution forecasting projects the adoption, diffusion, or substitution of a technology by fitting the asymmetric Gompertz growth curve to historical data and extrapolating it toward a saturation ceiling. Like the symmetric logistic used in the Fisher-Pry substitution model, the Gompertz curve captures the characteristic S-shape of technological change — slow initial uptake, rapid mid-life growth, and tapering as the market saturates — but unlike the logistic it is asymmetric, reaching its fastest growth early, at roughly 37 percent of the ceiling rather than at the midpoint. This makes it a natural choice when a new technology accelerates quickly and then approaches its limit gradually. Within the futures and foresight toolkit catalogued by Glenn and Gordon, growth-curve forecasting of this kind is a core quantitative method for anticipating when a technology will mature and when a successor is likely to displace it.