全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

中国数字经济核心产业协同演化效应研究——基于改进的CRITIC和灰色关联分析
A Study on the Synergistic Evolution Effects of Core Industries in China’s Digital Economy—Based on an Improved CRITIC and Grey Relational Analysis

DOI: 10.12677/ecl.2025.142524, PP. 304-311

Keywords: 数字经济核心产业,协同演化效应,灰色关联分析,客观赋权法
Core Industries in Digital Economy
, Synergistic Evolution Effects, Grey Relational Analysis, Objective Weighting Method

Full-Text   Cite this paper   Add to My Lib

Abstract:

近年来,随着中国数字经济在技术、市场、运营等方面融合创新不断加强,准确评估数字经济核心产业协同演化效应变化规律,对制定和实施数字经济相关政策至关重要。本文基于2012至2021年中国30个省份的13,200条权威部门统计数据,利用灰色关联分析、熵值赋权法、改进的CRITIC法等方法,构建了量化评估模型,发现了数字经济核心产业协同演化效应自2012年的0.8512波动下降至2021年的0.4590。结果表明,推动产业发展的核心驱动力已经从产业内部向产业外部进行了转移。基于此,本文提出了一系列发展建议,以期为推动中国数字经济核心产业高质量发展提供有益借鉴。
In recent years, as the integration and innovation of China’s digital economy in technology, market, and operations have strengthened, accurately assessing the synergistic evolution of core industries in the digital economy has become crucial for the formulation and implementation of related policies. Based on 13,200 authoritative statistical data points from 30 provinces in China between 2012 and 2021, this paper constructs a quantitative evaluation model using grey relational analysis, the entropy weighting method, and the improved CRITIC method. The analysis reveals that the synergistic evolution effect of core industries in the digital economy fluctuated downward from 0.8512 in 2012 to 0.4590 in 2021. The results indicate that the key driving forces for industrial development have shifted from internal to external industrial factors. Based on these findings, this paper proposes a series of development recommendations, aiming to offer valuable insights for promoting the high-quality development of China’s core digital economy industries.

References

[1]  CAICT (2022) Global Digital Economy White Paper.
[2]  Ding, Z.F. (2020) Research on the Mechanism of Digital Economy Driving High Quality Economic Development: A Theoretical Analysis Framework. Modern Economic Research, 1, 85-92.
[3]  Liu, S.C. (2019) Targeting Path and Policy Supply for the High Quality Development of China’s Digital Economy. Economist, 6, 52-61.
[4]  ITU (2017) ITU Measuring the Information Society Reports 2017. International Telecommunication Union.
[5]  Barefoot, K.D.C. and Jolliff, W. (2018) Defining and Measuring the Digital Economy. US Department of Commerce Bureau of Economic Analysis, Washington DC.
[6]  EC. Digital Economy and Society Index 2017.
http://ec.europa.eu/newsroom/document.cfm?doc_id=43049
[7]  CAICT (2022) Report on the Development of China’s Digital Economy.
[8]  Bruno, G., Diglio, A., Piccolo, C. and Pipicelli, E. (2023) A Reduced Composite Indicator for Digital Divide Measurement at the Regional Level: An Application to the Digital Economy and Society Index (DESI). Technological Forecasting and Social Change, 190, Article 122461.
https://doi.org/10.1016/j.techfore.2023.122461
[9]  Imran, M., Liu, X., Wang, R., Saud, S., Zhao, Y. and Khan, M.J. (2022) The Influence of Digital Economy and Society Index on Sustainable Development Indicators: The Case of European Union. Sustainability, 14, Article 11130.
https://doi.org/10.3390/su141811130
[10]  Du, M., Huang, Y., Dong, H., Zhou, X. and Wang, Y. (2022) The Measurement, Sources of Variation, and Factors Influencing the Coupled and Coordinated Development of Rural Revitalization and Digital Economy in China. PLOS ONE, 17, e0277910.
https://doi.org/10.1371/journal.pone.0277910
[11]  Wang, L., Chen, Y., Ramsey, T.S. and Hewings, G.J.D. (2021) Will Researching Digital Technology Really Empower Green Development? Technology in Society, 66, Article 101638.
https://doi.org/10.1016/j.techsoc.2021.101638
[12]  Zhou, F., Wen, H. and Lee, C. (2022) Broadband Infrastructure and Export Growth. Telecommunications Policy, 46, Article 102347.
https://doi.org/10.1016/j.telpol.2022.102347
[13]  Ma, D. and Zhu, Q. (2022) Innovation in Emerging Economies: Research on the Digital Economy Driving High-Quality Green Development. Journal of Business Research, 145, 801-813.
https://doi.org/10.1016/j.jbusres.2022.03.041
[14]  Wang, L. (2022) Evaluation of High-Quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm. International Transactions on Electrical Energy Systems, 2022, Article ID: 6327347.
https://doi.org/10.1155/2022/6327347
[15]  白列湖. 协同论与管理协同理论[J]. 甘肃社会科学, 2007(5): 228-230.
[16]  韩峰, 李玉双. 产业集聚、公共服务供给与城市规模扩张[J]. 经济研究, 2019(11): 149-164.
[17]  詹姝珂, 王仁曾, 刘耀彬. 金融科技与绿色金融协同对产业结构升级的影响——基于异质性环境规制视角[J]. 中国人口∙资源与环境, 2023, 33(11): 152-162.
[18]  孙燕, 吴莉莉, 金晓斌, 等. 长三角区域一体化对城市群土地利用效率的空间协同效应[J]. 地理研究, 2024, 43(8): 2104-2120.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133