Quantitative Text Analysis of Circular Economy Policies for Electric Vehicle Batteries in China: Focus on Objectives and Tools

Abstract

Section snippets

Methodology

This study conducted a quantitative analysis on the selected policy texts regarding EV battery CE by combining topic extraction and content analysis.Topic extraction is the process of identifying the underlying topics within a collection of documents using probabilistic models, such as Latent Dirichlet Allocation (LDA) (Blei et al., 2003). It is widely applied in policy text analysis to uncover policy themes and priorities, construct networks that reveal the relationships and evolution of

Policy developmental phases

The development of China’s CE policies for EV battery, based on the distribution of policy quantity and type over time (See Fig. 2), can be divided into three phases: (1) 2012-2014: Exploratory Phase, (2) 2015-2017: Guidance Phase, and (3) 2018-2023: Rapid Development Phase.In 2012, the central policy of “Energy Saving and New Energy Automobile Industry Development Plan (2012-2020)” mentioned EV battery recycling for the first time in China. During 2012-2014, EV battery recycling was only

Policy recommendations

Based on the content analysis results of EV battery CE policies in China, we proposed the following policy recommendations:

Conclusions

Drawing on text mining results from LDA model, we developed a two-dimensional analytical framework on ‘objective’ and ‘tool’ to quantitatively analyze EV battery CE policies at both central and local levels in different phases, using 266 documents from 2012 to 2023. Our analysis reveals that China’s EV battery CE policies have evolved through three phases: Exploratory (2012–2014), Guidance (2015–2017), and Rapid development (2018–2023), with increasing focus on systematic frameworks

Uncited reference

Forward-looking Industry Research Institute, 2024; Green Peace Organization & All-China Environment Federation, 2020; Li et al., 2021; Liu et al., 2023; New energy storage project Management Code, 2021; Regulation 2023/1542, 191 OJ L, 2023; O et al., 2010; Qian, 2024; Zhang et al., 2020; Zhang et al., 2023.

Declaration of Competing Interest

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We thank anonymous reviewers for their valuable suggestions to improve the quality of the paper. This research is funded by the National Natural Science Foundation of China (Grant Number 42371310); the Key program of International Cooperation, Bureau of International Cooperation, Chinese Academy of Sciences (Grant number 131551KYSB20210030)