面向未来产业的技术预测分析——理论、方法与实践路径

Analysis of Technology Forecasting for Future Industries: Theory, Methodology, and Practical Pathways

摘要:

未来产业前瞻布局对培育新质生产力、塑造竞争新优势和建设现代化产业体系具有重要意义。技术预测是识别技术演化规律、研判科技发展方向和支撑科技战略制定的重要工具，但现有研究在理论基础、方法体系与实践路径之间仍缺乏系统整合，难以为不同预测目标下的方法选择与流程设计提供统一指导。基于此，本文旨在构建面向未来产业的技术预测整合框架。研究采用系统文献综述法，从内在机理、方法模型和实践流程三个维度梳理国内外相关研究，整合技术生命周期、技术融合与技术轨道跃迁等理论，归纳定性方法以及统计方法、机器学习方法、图理论方法等定量方法，并构建涵盖目标设计、理论和方法选择、数据准备、数据分析与验证输出五个环节的预测流程。在此基础上，本文形成了技术预测“理论—方法—流程”整合性分析框架，揭示了理论基础、方法模型与实践路径之间的协同逻辑，厘清了各流程环节的核心要素及其内在关联。研究弥补了既有综述在系统整合与流程指导方面的不足，为提升未来技术预测过程的连贯性与科学性提供了系统化指导，也为优化国家及企业科技创新战略、前瞻布局未来产业发展方向提供了重要参考。

Abstract:

The forward-looking deployment of future industries is of great significance for fostering new quality productive forces, shaping new competitive advantages, and building a modern industrial system. Technology forecasting is an important tool for identifying the patterns of technological evolution, judging the directions of scientific and technological development, and supporting the formulation of science and technology strategies. However, existing studies lack systematic integration among theoretical foundations, methodological systems, and practical procedures. Unified guidance for method selection and process design under different forecasting objectives is still insufficient. Therefore, an integrated framework of technology forecasting for future industries was constructed. A systematic literature review was conducted. Relevant studies in China and abroad were reviewed from three dimensions, namely internal mechanisms, method models, and practical procedures. The theories of technology life cycle, technology convergence, and technological trajectory transition were integrated. Qualitative methods and quantitative methods, including statistical methods, machine learning methods, and graph-theoretic methods, were summarized. A forecasting process covering five stages, namely objective design, theory and method selection, data preparation, data analysis, and validation and output, was also constructed. An integrated analytical framework of “theory-method-process” for technology forecasting is constructed. The collaborative logic among theoretical foundations, methodological models, and practical pathways is revealed. The key elements of each stage and their internal relationships are clarified. The gap in existing review studies in terms of systematic integration and process guidance is filled. Systematic guidance is provided for improving the coherence and scientificity of the forecasting process. Important references are also provided for optimizing national and enterprise science and technology innovation strategies and for the forward-looking deployment of future industries.