预测科技发展,作为数字经济形成的基础

E. Mazilov, D. Alferyev, D. Zaripova
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引用次数: 2

摘要

向下一个技术秩序的过渡,工业生产组织的根本变化导致了新的“知识经济”的形成,它开辟了经济增长的新方向,提高了生产的经济效率,扩大了消费的可能性,创造了新的经济活动领域。目前,俄罗斯在经济增长速度和质量上都明显落后于经济发展的主要国家。主要原因是国家已经形成了以增加燃料和原材料出口为基础的出口原材料的死角经济模式。在这方面,科学地认识在世界分工体系全球转型的背景下形成俄罗斯经济增长的技术基础的组织和方法问题,是俄罗斯经济科学面临的最重要的根本任务之一。有必要认识到,数字经济的形成只有在有一定基础的情况下才有可能,表现在当前国家的科技发展水平上。与此同时,它的预测估计有必要了解需要向哪个方向发展,以便为确保数字经济的更快形成提供条件。本文考虑了科学技术发展建模的理论方面,分析了科学技术特征指标建模领域的现有经验和方法发展,提出了评价的数学模型,以及将所得值解释为经济现象的指标。
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Forecasting scientific and technological development as a basis for the formation of the digital economy
The transition to the next technological order, a radical change in the organization of industrial production leads to the formation of a new "intellectual economy", which opens new directions of economic growth, increases the economic efficiency of production and expands the possibilities of consumption, creating new areas of economic activity. Currently, Russia is significantly inferior to the leading countries of economic development in terms of the rate and quality of economic growth. The main reason is that the country has formed a dead-end export-raw material economic model based on increasing fuel and raw material exports. In this regard, scientific understanding of organizational and methodological problems of forming a technological basis for economic growth of the Russian economy in the context of global transformation of the world system of division of labor is one of the most important fundamental tasks facing Russian economic science. It is necessary to understand that the formation of the digital economy is possible only if there is a certain basis, expressed in the current level of scientific and technological development of the state. At the same time, its forecast estimates are necessary to understand in which direction it is necessary to move in order to provide conditions for ensuring a faster pace of formation of the digital economy. The article considers the theoretical aspects of modeling scientific and technological development, analyzes the existing experience and methodological developments in the field of modeling various indicators that characterize science and technology, offers a mathematical model of evaluation, as well as indicators for interpreting the obtained values into economic phenomena.
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