俄罗斯联邦小企业使用云技术的风险

IF 2.2 3区 工程技术 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Jasss-The Journal of Artificial Societies and Social Simulation Pub Date : 2022-01-01 DOI:10.18254/s207751800019437-9
K. Fedorchuk
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引用次数: 0

摘要

目前,中小企业是俄罗斯经济发展的重要组成部分。中小企业在所有企业中占有相当大的份额。中小企业必须在其活动的各个领域顺应现代趋势,以保持在市场上的竞争力。目前国际和俄罗斯市场的趋势是商业的数字化,这属于创新的范畴。为了节省资源,中小企业被迫使用云解决方案,但云解决方案的使用给企业带来了一定的风险。本文讨论了中小企业在使用这些技术时面临的主要风险。
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Risks of using cloud technologies in small business in the Russian Federation
Currently, small and medium-sized businesses are an important element in the development of the Russian economy. Small and medium business occupies a significant share among all enterprises. SMEs must comply with modern trends in all areas of their activities in order to maintain competitiveness in the market. The current trend in the international and Russian market is the digitalization of business, which belongs to the category of innovation. To save resources, SMEs are forced to use cloud solutions, but their use creates certain risks for the business. The article discusses the main risks faced by SMEs when using such technologies.
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来源期刊
CiteScore
7.40
自引率
9.50%
发文量
16
审稿时长
21 weeks
期刊介绍: The Journal of Artificial Societies and Social Simulation is an interdisciplinary journal for the exploration and understanding of social processes by means of computer simulation. Since its first issue in 1998, it has been a world-wide leading reference for readers interested in social simulation and the application of computer simulation in the social sciences. Original research papers and critical reviews on all aspects of social simulation and agent societies that fall within the journal"s objective to further the exploration and understanding of social processes by means of computer simulation are welcome.
期刊最新文献
Social Identity and Organizational Control: Results of an Agent-Based Simulation Unpacking a Black Box: A Conceptual Anatomy Framework for Agent-Based Social Simulation Models Conditions and Effects of Norm Internalization A Methodology to Develop Agent-Based Models for Policy Support Via Qualitative Inquiry Using Machine Learning for Agent Specifications in Agent-Based Models and Simulations: A Critical Review and Guidelines
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