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Network Analysis of Actors and Policy Keywords for Sustainable Environmental Governance: Focusing on Chinese Environmental Policy

Author

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  • Dan Zhang

    (School of International Business Management, Woosong University, 171, Dongdaejeon-ro, Dong-gu, Daejeon 34606, Korea
    Dan Zhang and Fan Fan are co-first authors.)

  • Fan Fan

    (School of International Business Management, Woosong University, 171, Dongdaejeon-ro, Dong-gu, Daejeon 34606, Korea
    Dan Zhang and Fan Fan are co-first authors.)

  • Sang Do Park

    (Department of Global Business, Konkuk University, 120, Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea)

Abstract

Environmental issues are viewed as a serious problem with a complex network structure involving various stakeholders. Environmental governance is considered the most reasonable way to promote environmental policy, and it is an important mechanism contributing to the sustainable development of society. Through the network analysis of actor and policy keywords, this study demonstrated whether environmental governance policies are being pursued through the cooperation of various participants in China, the epicenter of global environmental issues. We collected text big data from 2001 to 2018 under the theme of “environmental policy” on the main online portal web in China. Through text mining, key actors and policy keywords were selected according to the timing of environmental policy promotion, and network analysis and core-periphery analysis were conducted based on this actor/keywords data set. The results of this study are as follows. First, China’s environmental policy is a rudimentary governance cooperation structure, and the central and local governments are still the main policy-promoting actors. Second, the fundamental solution of the environmental problem through readjustment of the environment-related system and industrial restructuring has become the keyword for China’s implementation of environmental policy at present. Third, there were certain words, such as social, public, enterprise, and institution, in the aspects of environmental governance, while these words failed to be at the center of multi-dimensional scaling (MDS) analysis for the actors. This result shows that environmental governance and network are still at an early stage and that the Chinese government’s strong power lies in its environmental policy. Based on these results, policy recommendations are presented.

Suggested Citation

  • Dan Zhang & Fan Fan & Sang Do Park, 2019. "Network Analysis of Actors and Policy Keywords for Sustainable Environmental Governance: Focusing on Chinese Environmental Policy," Sustainability, MDPI, vol. 11(15), pages 1-29, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:15:p:4068-:d:252369
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    References listed on IDEAS

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    Cited by:

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    3. Yongliang Yang & Liwen Shen & Yuwen Li & Yi Li, 2022. "The Impact of Environmental Information Disclosure on Environmental Governance Satisfaction," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    4. Sang Do Park, 2022. "Policy Discourse Among the Chinese Public on Initiatives for Cultural and Creative Industries: Text Mining Analysis," SAGE Open, , vol. 12(1), pages 21582440221, March.
    5. Jiangmin Yang & Desheng Xue & Gengzhi Huang, 2020. "The Changing Factors Affecting Local Environmental Governance in China: Evidence from a Study of Prefecture-Level Cities in Guangdong Province," IJERPH, MDPI, vol. 17(10), pages 1-17, May.
    6. Konstantinos G. Papaspyropoulos & Harikleia Liakou & Panayotis Dimopoulos, 2023. "Climate Change in the Biodiversity and Forest Strategies in Greece Using Discourse Analysis and Text Mining: Is an Integration into a Cost-Efficient Natural Resources Policy Feasible?," Sustainability, MDPI, vol. 15(7), pages 1-12, April.
    7. Binbin Yang & Sang-Do Park, 2023. "Who Drives Carbon Neutrality in China? Text Mining and Network Analysis," Sustainability, MDPI, vol. 15(6), pages 1-24, March.
    8. Samuel Zanferdini Oliva & Livia Oliveira-Ciabati & Denise Gazotto Dezembro & Mário Sérgio Adolfi Júnior & Maísa Carvalho Silva & Hugo Cesar Pessotti & Juliana Tarossi Pollettini, 2021. "Text structuring methods based on complex network: a systematic review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1471-1493, February.

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