Coupling Coordination Analysis between Circular Economy and Green Supply Chain: A Case Study of China’s Eastern Economic Belt
DOI: https://doi.org/10.62381/ACS.AEMS2025.07
Author(s)
Wenjie Cheng*
Affiliation(s)
Capital University of Economics and Business, Beijing, China
*Corresponding Author
Abstract
Against the backdrop of prominent environmental issues, sustainable economic development is faced with higher demands, urgently requiring the promotion of green transformation. This study constructs a circular economy and green supply chain system with 17 indicators. It measures the coupling coordination degree of 10 eastern provinces and municipalities from 2010 to 2022 by the entropy-weight method, TOPSIS, and the coupling coordination degree model. The results show that the coupling coordination level is generally in the transitional coordination stage and shows a growth trend. There are differences in development among the provinces. Provinces with significant resources and industrial advantages, such as Shandong and Hebei, have a higher level of coordination. Certain provinces, such as Hainan, started late but have gradually improved under policy and market-driven conditions. Functionally adjusted regions have insufficient incentives for transformation, such as Beijing. This study provides a data-driven reference for promoting the optimization of China's green transformation.
Keywords
Eastern Economic Belt; Circular Economy; Green Supply Chain; Coupling Coordination Degree Model
References
[1] Sun, Y., Zhu, S., Wang, D. et al. (2024) Global supply chains amplify economic costs of future extreme heat risk. Nature, 627: 797–804.
[2] Reh, L. (2013) Process engineering in circular economy. Particuology, 11: 119–133.
[3] Murray, A., Skene, K., & Haynes, K. (2017) The Circular Economy: An Interdisciplinary Exploration of the Concept and Application in a Global Context. Journal of Business Ethics, 140: 369–380.
[4] Lahane, S., Kant, R., & Shankar, R. (2020) Circular supply chain management: A state-of-art review and future opportunities. Journal of Cleaner Production, 258: 120859.
[5] Li, Y., Li, Y., Zhou, Y., Shi, Y., & Zhu, X. (2012) Investigation of a coupling model of coordination between urbanization and the environment. Journal of Environmental Management, 98: 127–133.
[6] Sui, G., Wang, H., Cai, S., & Cui, W. (2023) Coupling coordination analysis of resources, economy, and ecology in the Yellow River Basin. Ecological Indicators, 156: 111133.
[7] Genovese, A., Acquaye, A. A., Figueroa, A., & Koh, S. C. L. (2017) Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega, 66(Part B): 344–357.
[8] National Bureau of Statistics of China. (2021) How are economic zones divided?. NBS of the PRC. https://www.stats.gov.cn/zt_18555/zthd/lhfw/2021/rdwt/202302/t20230214_1903926.html.
[9] NetEase. (2024) "Eastern 10 Provinces: Top 10 Provinces in China, Half of the Nation's GDP." NetEase Hao. https://www.163.com/dy/article/IPTOEJU1055633IB.html.
[10] Shandong Circular Economy Association. (2023) Ten Major Events of Shandong Circular Economy in 2023. Shandong Circular Economy Association Website. http://www.sdcyc.com.
[11] Circular Economy in Textiles and Apparel: Processing, Manufacturing, and Design, Elsevier (2018), pp. 77-93.
[12] Patwa, N., Sivarajah, U., Seetharaman, A., Sarkar, S., Maiti, K., & Hingorani, K. (2021) Towards a circular economy: An emerging economies context. Journal of Business Research, 122: 725–735.
[13] Huang, S., Tan, H. (2025) Evaluating the effects of green supply chain, digital technologies, and energy prices on renewable energy innovations: A way forward for an emerging economy. Energy Economics, 141: 108038.
[14] Kumar, R., Bilga, P. S., Singh, S. (2017) Multi objective optimization using different methods of assigning weights to energy consumption responses, surface roughness and material removal rate during rough turning operation. Journal of Cleaner Production, 164: 45–57.
[15] Taheriyoun, M., Karamouz, M., & Baghvand, A. (2010) Development of an entropy-based fuzzy eutrophication index for reservoir water quality evaluation. Iranian Journal of Environmental Health, Science and Engineering, 7(1): 1–7.
[16] Hwang, C.L. and Yoon, K. (1981) Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, New York.
[17] Lai Z, Ge D, Xia H, Yue Y, Wang Z (2020) Coupling coordination between environment, economy and tourism: A case study of China. PLOS ONE 15(2): e0228426. https://doi.org/10.1371/journal.pone.0228426.
[18] Lin, S. G., Lu, R. C., Ye, Z. D., et al. (2022) Spatial evolution and coupling coordination of territorial space functions in China-Vietnam border area. Chinese Land Science, 36(9): 90–101.