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国外技术竞争情报研究现状及前沿趋势分析
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Abstract:
从2000年开始国际社会开始进入了“新中世纪主义”的“弱国时代”，在这一时代特征下，信息战成为当前大国竞争中的主要战争形式。数智赋能下的信息情报作为新型战略资源，在大国博弈中占据了重要的战略制高点。以国家为实施主体的技术竞争情报可以对科研发展态势进行分析，为国家重点领域发展规划和政策制定提供情报支持。研究利用文献计量工具CiteSpace绘制知识图谱，通过关键词聚类和时间线分析，研究热点可以归纳为以技术为监测对象的情报分析工作，以及借助技术的情报分析工作；结合新中世纪时代特点，前沿趋势主要包括从国家和企业两个组织主体出发，以新兴技术为研究对象或者研究方法。由此，研究提出加大自动化监测技术研发投入、提升监测技术自主创新能力、严控信息情报开源范围等建议，为相关情报工作者和技术研究人员提供了必要参考。
Since 2000, the World has entered into an age of weakening states called neomedievalism. Under the characteristics of this era, information warfare has become the main form of warfare in the current competition among major powers. As a new type of strategic resource, information intelligence empowered by digital intelligence occupies an important strategic commanding height in the game of great powers. Competitive technical intelligence with the country as the main body of implementation can analyze the development trend of scientific research and provide intelligence support for the development planning and policy formulation of national key areas. Therefore, the research uses the bibliometric tool CiteSpace to draw a knowledge map. Through keyword clustering and timeline analysis, the research hotspots can be summarized as intelligence analysis work with technology as the monitoring object and intelligence analysis work with the help of technology; combined with the characteristics of the new medieval era, the frontier trends mainly include starting from the two organizational entities of the country and enterprises, and using emerging technologies as the research object or research method. Hence, the study puts forward suggestions such as increasing investment in the research and development of automated monitoring technology, improving the independent innovation ability of monitoring technology, and strictly controlling the scope of information and intelligence open source, which provides necessary reference for relevant intelligence workers and technical researchers.
| [1] | Timothy, R.H., Kong, W.L. and Alexis, D.-H. (2023) U.S.-China Rivalry in a Neomedieval World: Security in an Age of Weakening States. RAND Corporation, Santa Monica, CA. |
| [2] | 赵英. 试论技术竞争情报与科技情报的差异性[J]. 科技情报开发与经济, 2008(24): 96-97. |
| [3] | Lin, F., Evans, R.D., Kharel, R., et al. (2022) Competitor Intelligence and Product Innovation: The Role of Open- Mindedness and Interfunctional Coordination. IEEE Transactions on Engineering Management, 69, 314-328.
https://doi.org/10.1109/TEM.2019.2943359 |
| [4] | Stuart, N.A., Hartfield, G., Schultz, D.M., et al. (2022) The Evolving Role of Humans in Weather Prediction and Communication. Bulletin of the American Meteorological Society, 103, E1720-E1746.
https://doi.org/10.1175/BAMS-D-20-0326.1 |
| [5] | Yin, J. (2023) Crime Prediction Methods Based on Machine Learning: A Survey. Computers, Materials & Continua, 74, 4601-4629. https://doi.org/10.32604/cmc.2023.034190 |
| [6] | Yang, N. (2022) Financial Big Data Management and Control and Artificial Intelligence Analysis Method Based on Data Mining Technology. Wireless Communications and Mobile Computing, 2022, Article ID: 7596094.
https://doi.org/10.1155/2022/7596094 |
| [7] | Shi, D., Zhou, J., Wang, D., et al. (2022) Research Status, Hotspots, and Evolutionary Trends of Intelligent Education from the Perspective of Knowledge Graph. Sustainability, 14, Article No. 10934. https://doi.org/10.3390/su141710934 |
| [8] | Nan, R., Zhu, W. and Xiao, Y. (2022) Knowledge Graph Analysis of Digital Emergency Management Research Based on CiteSpace Visualisation: Comparative Analysis of WOS and CNKI Databases. Discrete Dynamics in Nature & Society, 2022, Article ID: 4604223. https://doi.org/10.1155/2022/4604223 |
| [9] | Mohan, P.V., Dixit, S., Gyaneshwar, A., et al. (2022) Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems and Future Directions. Sensors, 22, Article No. 2194.
https://doi.org/10.3390/s22062194 |
| [10] | Sigov, A., Ratkin, L. and Ivanov, L.A., et al. (2022) Emerging Enabling Technologies for Industry 4.0 and Beyond. Information Systems Frontiers, 1-11. https://doi.org/10.1007/s10796-021-10213-w |
| [11] | Mithas, S., Chen, Z.L., Saldanha, T.J.V., et al. (2022) How Will Artificial Intelligence and Industry 4.0 Emerging Technologies Transform Operations Management? Production and Operations Management, 31, 4475-4487.
https://doi.org/10.1111/poms.13864 |
| [12] | Azzam, M. and Beckmann, R. (2022) How AI Helps to Increase Organizations’ Capacity to Manage Complexity—A Research Perspective and Solution Approach Bridging Different Disciplines. IEEE Transactions on Engineering Management, 1-14. https://doi.org/10.1109/TEM.2022.3179107 |
| [13] | Wang, M.M. and Pan, M.X. (2022) Drivers of Artificial Intelligence and Their Effects on Supply Chain Resilience and Performance: An Empirical Analysis on an Emerging Market. Sustainability, 14, Article No. 16836.
https://doi.org/10.3390/su142416836 |
| [14] | Sun, L. and Wang, Y. (2022) Improving and Evaluating Business Management in the Digital Economy Based on Data Analysis. Security and Communication Networks, 2022, Article ID: 5908877. https://doi.org/10.1155/2022/5908877 |
