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The Impact of Digital Transformation of Power Grid Enterprises on Business Value Model

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Application of Intelligent Systems in Multi-modal Information Analytics (ICMMIA 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 136))

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Abstract

With the continuous acceleration of the information process, the transformation of power grid enterprises, as the pillar of national economic development, is the general trend. Taking the digital power industry as an example, this paper analyzes it. Firstly, the problems and current situation faced by China’s power grid enterprises are studied theoretically, and the corresponding countermeasures and suggestions are put forward according to these situations. Secondly, the relevant conclusions are given according to the current problems and what adjustments need to be made in the future. Finally, through case analysis, the significance and practical value of the above strategies for promoting national and socio-economic development are verified, so as to provide reference for further carrying out the transformation of power enterprises and institutions in the digital era in the future.

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Authors and Affiliations

  1. State Grid Jiangsu Electric Power Co., Ltd., Economic and Technological Research Institute, Nanjing, 210000, Jiangsu, China

    Mingxia Zhu, Zhenjian Xie & Zhe Wang

Authors
  1. Mingxia Zhu
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  2. Zhenjian Xie
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  3. Zhe Wang
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Corresponding author

Correspondence to Zhe Wang .

Editor information

Editors and Affiliations

  1. School of Business Administration, Oakland University, Rochester, MI, USA

    Vijayan Sugumaran

  2. Amrita School of Engineering, Chennai, Tamil Nadu, India

    A. G. Sreedevi

  3. Shanghai Polytechnic University, Shanghai, China

    Zheng Xu

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Zhu, M., Xie, Z., Wang, Z. (2022). The Impact of Digital Transformation of Power Grid Enterprises on Business Value Model. In: Sugumaran, V., Sreedevi, A.G., Xu, Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-031-05237-8_4

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