Macro Analysis of Benchmarking in Electric Power Enterprises Based on Variance
- DOI
- 10.2991/978-94-6463-042-8_132How to use a DOI?
- Keywords
- variance; benchmarking management; electric power enterprise; development planning
- Abstract
The benchmarking work of State Grid Corporation of China can promote the management level and comprehensive quality of the company, but there are still "shortcomings" and deficiencies. How to find and analyze the shortcomings can provide theoretical basis for decision makers. Based on the basic concept of variance analysis, this paper analyses the degree of difference in the performance and management benchmarking of different companies in different cities by using the analysis of variance from the perspective of horizontal analysis. This method can give the macro-level differences between the same indicators in different cities, and whether the corresponding indicators have the space to increase the size and difficulty. Therefore, it can provide corresponding theoretical basis for decision-makers to formulate short-, medium-, and long-term plans for the development of indicators.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Wenyu Wang AU - Jing-song Xiao AU - Bin Song AU - Linong Wang PY - 2022 DA - 2022/12/29 TI - Macro Analysis of Benchmarking in Electric Power Enterprises Based on Variance BT - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022) PB - Atlantis Press SP - 932 EP - 936 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-042-8_132 DO - 10.2991/978-94-6463-042-8_132 ID - Wang2022 ER -