主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

中国管理科学 ›› 2023, Vol. 31 ›› Issue (11): 349-360.doi: 10.16381/j.cnki.issn1003-207x.2021.2138

• • 上一篇    

面向数据空间体系构建的电力制造业多价值链经营风险识别与管控研究

李明钰1,2,牛东晓1,2(),纪正森1,2,施博文1,2,兰心怡1,张焕粉3   

  1. 1.华北电力大学经济与管理学院, 北京 102206
    2.华北电力大学新能源与低碳发展北京重点实验室, 北京 102206
    3.北京清畅电力技术股份有限公司, 北京 100085
  • 收稿日期:2021-10-20 修回日期:2022-01-20 出版日期:2023-11-15 发布日期:2023-12-05
  • 通讯作者: 牛东晓 E-mail:niudx@126.com
  • 基金资助:
    国家重点研发计划资助项目(2020YFB1707800)

Research on Multi-value Chain Management Risk Identification and Control of Electric Power Manufacturing Industry Oriented to the Construction of Data Space System

Ming-yu LI1,2,Dong-xiao NIU1,2(),Zheng-sen JI1,2,Bo-wen SHI1,2,Xin-yi LAN1,Huan-fen ZHANG3   

  1. 1.School of Economics and Management,North China Electric Power University,Beijing 102206,China
    2.Beijing Key Laboratory of New Energy and Low-Carbon Development,North China Electric Power University,Beijing 102206,China
    3.Beijing Qingchang Power Technology Co. ,Ltd. ,Beijing 100085,China
  • Received:2021-10-20 Revised:2022-01-20 Online:2023-11-15 Published:2023-12-05
  • Contact: Dong-xiao NIU E-mail:niudx@126.com

摘要:

目前,我国电力事业快速发展,智能制造也在不断推进,电力制造行业存在着科技创新不足、竞争能力较弱等问题。对于电力制造企业来说,如何有效识别和控制经营风险,形成新的多价值链风险管理模式,对提高电力制造企业风险管控水平,从而提高经济效益具有重要意义。本文基于数据空间和文本挖掘技术,通过大数据爬虫技术收集电力制造业相关风险政策和新闻报道共16034篇,利用文本挖掘模型进行风险主题的挖掘,识别经营风险关键因素和风险主题;然后利用风险识别结果,从多价值链角度构建电力制造企业全生命周期经营风险安全数据空间;最后,本文利用某电力制造企业近20年生产经营数据进行实例分析,验证风险数据空间构建的有效性。研究结果表明,从多价值链角度对电力制造企业经营风险进行识别具备合理性,电力制造企业全生命周期经营风险安全数据空间的构建能够在各环节实现风险的合理规避和智能管控。

关键词: 数据空间, 文本挖掘, 多价值链, 经营风险, 风险识别与管控

Abstract:

With the rapid development of electric power industry and the continuous advancement of intelligent manufacturing in China, electric power manufacturing companies are facing problems such as insufficient technological innovation and weak competitiveness. For power manufacturing companies, how to effectively identify and control operating risks and form a new multi-value chain risk management model is of great significance to strengthen the level of risk management and control of power manufacturing companies. Based on data space and text mining technology,16,034 related risk policies and news reports of the electric power manufacturing industry are collected through big data crawler technology. The LDA text mining model is used to mine text topics and identify key business risk factors and risk topics. Then the results of risk identification are used to construct a safety data space for the entire life cycle of power manufacturing enterprises from the perspective of multiple value chains. Finally, the production and operation data of a power manufacturing company in the past 20 years are used to conduct a case analysis to verify the effectiveness of risk identification and control. The research results show that it is reasonable to identify the operating risks of power manufacturing companies from the perspective of multiple value chains. The construction of a safe data space for operating risks in the entire life cycle of power manufacturing enterprises can achieve reasonable risk avoidance and intelligent management in all links.

Key words: dataspace, text mining, multiple value chains, business risk, risk identification and control

中图分类号: