China’s Low-carbon Index System — Based on Map Analysis and Factor Analysis of CiteSpace

DOI

10.2991/978-94-6463-102-9_23How to use a DOI?

Keywords

Low-Carbon Economy; Low-Carbon Indicators; CiteSpace; Factor Analysis

Abstract

The low-carbon economy is an important policy for economic development that China is committed to, and it is of very positive significance to analyze its depth. In the context of such an era, China requires vigorous development of a low-carbon economy and strives to achieve the goal of “double carbon”, but to assess whether a country or region is a low-carbon economic development, it is necessary to establish a scientific low-carbon index system (Cong, Yun, Xia, 2014). This paper uses the keyword co-occurrence map and cluster map of CiteSpace to explore the current development status of China's low-carbon index system. Moreover, there is no unity between the low-carbon index system and the national index system in various cities, the system research is not in-depth innovation, and the construction scale of low-carbon cities is not systematic. The factor analysis method is used to conduct empirical analysis, draw conclusions, and according to the conclusions, local governments should strengthen the standardization of the local index system, develop new green enterprises, explore and study new indicators, and provide a certain reference basis.

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.

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TY  - CONF
AU  - Huanyu Zhang
AU  - Chaoren Lin
PY  - 2022
DA  - 2022/12/29
TI  - China’s Low-carbon Index System — Based on Map Analysis and Factor Analysis of CiteSpace
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 196
EP  - 206
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_23
DO  - 10.2991/978-94-6463-102-9_23
ID  - Zhang2022
ER  -