INNOVATIVE CLASSIFICATION OF METHODS OF THE FUTURE-ORIENTED TECHNOLOGY ANALYSIS
针对传统预测方法在动态环境下失效的问题，提出了一种基于统计方法和人工神经网络的未来导向技术分析方法分类，帮助研究者设计研究流程并选择互补方法。
In the era characterized by significant dynamics of the environment traditional methods of anticipating the future, assuming the immutability of the factors affecting the forecasted phenomenon, may be in the long term ineffective. The modern approach of predicting the future of technology, taking into account the multidimensionality of the environment, is, among other things, the Future-Oriented Technology Analysis (FTA). Designing the FTA research procedure is a complex process, both in organizational and methodological terms. The catalogue of methods that can be used in this process is extensive and constantly open. However, in the source literature the rules for the selection of methods appropriate for the type of research were not specified. The ways of combining methods in the research process were also missing. The main aim of this article was to present the author’s classification of methods of future-oriented technology analysis and indicate the possibilities of its application. In the text, using statistical methods and artificial neural networks, the classification of methods with the potential of exploitation in prospective technology analysis was carried out. Each of the received classes was analysed, the characteristics of particular groups of methods were selected, and authorial names characterizing the given classes were chosen. According to the author, the application of the proposed classification of methods of future-oriented technology analysis facilitates the design of the FTA research process. It will contribute to the systematization and standardization of the manner of selection of research methods. It will also allow for the selection of complementary methods.