Study on Energy Efficiency of Manufacturing Industry in Shandong Province in the Context of Carbon Neutrality
- DOI
- 10.2991/978-94-6463-368-9_69How to use a DOI?
- Keywords
- Manufacturing industry; energy efficiency; Data Envelopment Analysis (DEA); K-means clustering algorithm
- Abstract
Using the Data Envelopment Analysis (DEA) model, this article establishes an input-output indicator system to study the energy efficiency of 25 subsectors of manufacturing industries in Shandong Province. Subsequently, k-means algorithm is used for cluster analysis to classify the industry into four categories. The article finds that the overall energy use efficiency of manufacturing industries in Shandong Province is not high in 2021. Nearly two-thirds of the manufacturing industries is in the stage of increasing returns to scale, and should increase investment to obtain greater benefits. Most of the manufacturing industries in Shandong Province are of the type of low energy efficiency and low energy consumption. In the future, in order to reduce the amount of energy consumption, realize the efficient use of energy and promote the economic development, the government can take measures to improve the level of technology, optimize the industrial structure and so on.
- Copyright
- © 2024 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 - Jing Xue AU - Fumei Xue AU - Zhen Jiang PY - 2024 DA - 2024/02/14 TI - Study on Energy Efficiency of Manufacturing Industry in Shandong Province in the Context of Carbon Neutrality BT - Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023) PB - Atlantis Press SP - 582 EP - 589 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-368-9_69 DO - 10.2991/978-94-6463-368-9_69 ID - Xue2024 ER -