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A dynamic and adaptive scenario approach for formulating science & technology policy

机译：制定科技政策的动态自适应情景方法

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摘要

Purpose: Dynamic changes in the world bring challenges for making long-term future-oriented policy and strategy. A number of recent developments like drops in oil prices, increasing global conflicts, mass immigration and economic stagnation have had disruptive effects on long-term policies and strategies. The purpose of this paper is to provide a dynamic and adaptive Foresight approach as required by the fast-changing global landscape. Design/methodology/approach: The scenario approach presented in the paper aims to develop multiple time horizons by bringing together short-term forecasts and long-term exploratory and visionary scenarios. Each time horizon allows for re-considering and dynamically changing drivers and assumptions of scenarios and thus builds not a single linear, but multiple and dynamic pathways into the future. Following the presentation on the background and description of the methodology, the paper illustrates the proposed approach with a case study on science and technology (S&T) development in Russia. Findings: The flexible scenario approach allows developing and strategies with similar adaptability and flexibility. Practical implications: The scenario approach presented in the paper may be applicable for Foresight exercises at all levels of governance, including national, international, regional and corporate. Originality/value: A novel scenario approach is presented for the formulation of S&T policy with an illustrative case study.
机译：目的：世界的动态变化为制定面向未来的长期政策和战略带来了挑战。油价下跌，全球冲突加剧，大规模移民和经济停滞等最近的一些事态发展对长期政策和战略产生了破坏性影响。本文的目的是根据瞬息万变的全球形势提供一种动态且自适应的前瞻性方法。设计/方法/方法：本文中介绍的情景方法旨在通过将短期预测与长期探索性和有远见的情景结合在一起来开发多个时间范围。每个时间范围都允许重新考虑和动态更改场景的假设和假设，因此，它们不会构建单一的线性路径，而是构建通往未来的多种动态路径。在介绍了方法的背景和描述之后，本文以俄罗斯的科学技术发展为例，说明了所提出的方法。调查结果：灵活的方案方法可以使开发和策略具有相似的适应性和灵活性。实际意义：本文中介绍的情景方法可能适用于所有治理级别（包括国家，国际，区域和公司）的前瞻性练习。独创性/价值：通过说明性案例研究，提出了一种新颖的情景方法来制定科技政策。

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  • 来源
    《Foresight》 |2017年第5期|473-490|共18页
  • 作者

    Saritas Ozcan; Dranev Yury; Chulok Alexander A.;

  • 作者单位

    Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics, Moscow, Russian Federation;

    Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics, Moscow, Russian Federation;

    Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics, Moscow, Russian Federation;

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  • 正文语种 eng
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  • 关键词

    Backcasting; Forecasting; Foresight; Russia; Scenario planning; Science and technology policy;

    机译：回播;预测;前瞻性俄国;场景规划;科技政策;

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