Research on the Evaluation of Total Factor Productivity of Large Electric Power Enterprises Based on Three-Stage DEA

With the development of the times and changes in the situation, electric power services present new needs and characteristics, large state-owned enterprises in the electric power industry deepen their strategic objectives and put forward major strategic development layouts, this paper proposes a set of indicator system from the perspective of total factor productivity, combined with the company's strategic system, to evaluate the strategy of large power grid enterprises. In this paper, the data of four input-output indicators and three environmental variables of 13 electric power listed enterprises from 2018 to 2022 are selected as research samples in the arithmetic example, and the three-stage DEA method is used to evaluate the efficiency of the grid company, and the results of the research show that: electric power listed companies are generally at a high level of total factor productivity, the number of years of establishment and the gross regional product will reduce the input redundancy, and the government subsidy will increase the input redundancy of enterprises, the efficiency of listed electric power companies is improved after removing the influence of environmental variables, and the efficiency level of enterprises is underestimated. In terms of technology, enterprises can increase investment in technology research and development, and actively introduce and cultivate technical talents; in terms of government subsidies, they can reasonably allocate resources and optimize the direction and strength of investment; in terms of enterprise management, they can reform the enterprise system mechanism to improve enterprise efficiency.

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Published
2024-12-13
DOI
https://doi.org/10.1145/3724154.3724208
Primary Topic
Evaluation and Optimization Models
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article
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Research on the Evaluation of Total Factor Productivity of Large Electric Power Enterprises Based on Three-Stage DEA

Nan Xu, Qiang Lu, Zheng Li, Yuxin Xing
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Evaluation and Optimization Models
article

Research on the Evaluation of Total Factor Productivity of Large Electric Power Enterprises Based on Three-Stage DEA

Nan Xu, Qiang Lu, Zheng Li, Yuxin Xing
article en

Abstract

With the development of the times and changes in the situation, electric power services present new needs and characteristics, large state-owned enterprises in the electric power industry deepen their strategic objectives and put forward major strategic development layouts, this paper proposes a set of indicator system from the perspective of total factor productivity, combined with the company's strategic system, to evaluate the strategy of large power grid enterprises. In this paper, the data of four input-output indicators and three environmental variables of 13 electric power listed enterprises from 2018 to 2022 are selected as research samples in the arithmetic example, and the three-stage DEA method is used to evaluate the efficiency of the grid company, and the results of the research show that: electric power listed companies are generally at a high level of total factor productivity, the number of years of establishment and the gross regional product will reduce the input redundancy, and the government subsidy will increase the input redundancy of enterprises, the efficiency of listed electric power companies is improved after removing the influence of environmental variables, and the efficiency level of enterprises is underestimated. In terms of technology, enterprises can increase investment in technology research and development, and actively introduce and cultivate technical talents; in terms of government subsidies, they can reasonably allocate resources and optimize the direction and strength of investment; in terms of enterprise management, they can reform the enterprise system mechanism to improve enterprise efficiency.

China University of Mining and Technology (CN), Energy Research Institute (CN), Shanghai Electric (China) (CN)
Decent work and economic growth
Openalex Percentile: Top 64%
Evaluation and Optimization Models
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