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Evolution and influencing factors of the green development spatial association network in the Guangdong-Hong Kong-Macao Greater Bay Area

    Zhijun Feng Affiliation
    ; Zinan Chen Affiliation
    ; Hechang Cai Affiliation
    ; Zaoli Yang Affiliation

Abstract

Accurately grasping the structural characteristics and influencing factors of green development spatial association are significant for green coordinated development and ecological civilization construction in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This study evaluates the GBA’s green development performance from 2015 to 2019 based on duality theory, and uses social network analysis to explore the structural characteristics and evolution of the green development spatial association network, and then uses the exponential random graph model to reveal the influencing factors of network formation. we find that: (1) the GBA’s green development is steady. Its spatial association network became increasingly complex, and tends to be tight. (2) As important hubs, Guangzhou, Shenzhen, and Hong Kong have the dominant positions in the GBA’s green development spatial association network. Huizhou, Jiangmen, Zhaoqing, and Macao are at the edge of the network, and their interoperability with other cities is relatively weak. (3) Four subgroups exist in the GBA during different periods, with obvious gradient characteristics between them, and the multilevel transmission mechanism of the green development network gradually forms. (4) Economic development and urbanization level, ecological environment endowment, and geographical, institutional, and industrial proximity all have significant impacts on the formation of the GBA’s green development spatial association network.


First published online 23 March 2022

Keyword : Guangdong-Hong Kong-Macao Greater Bay Area, green development, spatial association network, social network analysis, duality theory, exponential random graph model

How to Cite
Feng, Z., Chen, Z., Cai, H., & Yang, Z. (2022). Evolution and influencing factors of the green development spatial association network in the Guangdong-Hong Kong-Macao Greater Bay Area. Technological and Economic Development of Economy, 28(3), 716–742. https://doi.org/10.3846/tede.2022.16618
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References

Aplin, L. M., Farine, D. R., Morand-Ferron, J., Cockburn, A., Thornton, A., & Sheldon, B. C. (2015). Experimentally induced innovations lead to persistent culture via conformity in wild birds. Nature, 518, 538–541. https://doi.org/10.1038/nature13998

Chen, Z., Sarkar, A., Rahman, A., Li, X., & Xia, X. (2022). Exploring the drivers of green agricultural development (GAD) in China: A spatial association network structure approaches Author links open overlay panel. Land Use Policy, 112, 105827. https://doi.org/10.1016/j.landusepol.2021.105827

Chiou, T. Y., Chan, H. K., Lettice, F, & Chung, S. H. (2011). The influence of greening the suppliers and green innovation on environmental performance and competitive Advantage in Taiwan. Transportation Research Part E: Logistics and Transportation Review, 47(6), 822–836. https://doi.org/10.1016/j.tre.2011.05.016

Chong, Z., & Pan, S. (2020). Understanding the structure and determinants of city network through intra-firm service relationships: The case of GBA. Cities, 103, 102738. https://doi.org/10.1016/j.cities.2020.102738

Copeland, B. R., & Scott, T. M. (1994). North-south trade and the environment. Quarterly Journal of Economics, 109(3), 755–787. https://doi.org/10.2307/2118421

Cui, H., & Lui, Z. (2021). Spatial-Temporal pattern and influencing factors of the urban green development efficiency in Jing-Jin-Ji region of China. Polish Journal of Environmental Studies, 30(2), 1079–1093. https://doi.org/10.15244/pjoes/124758

Ding, L., Shao, Z., Zhang, H., Xu, C., & Wu, D. (2016). A Comprehensive evaluation of urban sustainable development in China Based on the TOPSIS-Entropy method. Sustainability, 8(8), 746. https://doi.org/10.3390/su8080746

Fan, J., & Xiao, Z. (2021). Analysis of spatial association network of China’s green innovation. Journal of Cleaner Production, 299, 126815. https://doi.org/10.1016/j.jclepro.2021.126815

Feng, C., Wang, M., Liu, G., & Huang, J. (2017). Green development performance and its influencing factors: A global perspective. Journal of Cleaner Production, 144, 323–333. https://doi.org/10.1016/j.jclepro.2017.01.005

Feng, Z., & Chen, W. (2018). Environmental regulation, green innovation, and industrial green development: An empirical analysis based on the spatial Durbin model. Sustainability, 10(1), 223. https://doi.org/10.3390/su10010223

Gao, L., & Xu, F. (2007). A preliminary study on the duality theory of systematics: A theoretical framework. System Engineering Theory and Practice, 27, 95–96.

Glazyrina, I. P., & Zabelina, I. A. (2018). Spatial heterogeneity of Russia in the light of the concept of a green economy: The social context. Geography and Natural Resources, 39, 103–110. https://doi.org/10.1134/S1875372818020026

Guo, Y., Tong, L., & Mei, L. (2020). The effect of industrial agglomeration on green development efficiency in Northeast China since the revitalization. Journal of Cleaner Production, 258, 120584. https://doi.org/10.1016/j.jclepro.2020.120584

Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., & Morris, M. (2008). statnet: Software tools for the representation, visualization, analysis and simulation of network data. Journal of Statistical Software, 24, 1–11. https://doi.org/10.18637/jss.v024.i01

He, Y., Wei, Z., Liu, G., & Zhou, P. (2020). Spatial network analysis of carbon emissions from the electricity sector in China. Journal of Cleaner Production, 262, 121193. https://doi.org/10.1016/j.jclepro.2020.121193

Huang, H., Mo, R., & Chen, X. (2021). New patterns in China’s regional green development: An interval Malmquist–Luenberger productivity analysis. Structural Change and Economic Dynamics, 58, 161–173. https://doi.org/10.1016/j.strueco.2021.05.011

Huang, M., & Li, S. (2020). The analysis of the impact of the Belt and Road initiative on the green development of participating countries. Science of The Total Environment, 722, 137869. https://doi.org/10.1016/j.scitotenv.2020.137869

Jia, J., Zhao, L., Gao, X., & Cao, N. (2021). The spatial correlation network structure and its influencing factors of inclusive green growth efficiency in the Bohai Rim. Geography and Geo-Information Science, 37(5), 46–54.

Kim, S. E., Kim, H., & Chae, Y. (2014). A new approach to measuring green growth: application to the OECD and Korea. Futures, 63, 37–48. https://doi.org/10.1016/j.futures.2014.08.002

King, S., Lusher, D., Hopkins, J., & Simpson, G. W. (2020). Industrial symbiosis in Australia: The social relations of making contact in a matchmaking marketplace for SMEs. Journal of Cleaner Production, 270, 122146. https://doi.org/10.1016/j.jclepro.2020.122146

Kortelainen, M. (2008). Dynamic environmental performance analysis: A Malmquist index approach. Ecological Economics, 64(4), 701–715. https://doi.org/10.1016/j.ecolecon.2007.08.001

Lee, J., Om, K., Choi, M., Song, C., & Kim, K. (2014). Scientists and engineers in convergence technologies in Korea: Where are they going and how do they collaborate? Technological and Economic Development of Economy, 20(3), 434–456. https://doi.org/10.3846/20294913.2014.880388

Li, Y., Chen, Y., & Li, Q. (2020). Assessment analysis of green development level based on S-type cloud model of Beijing-Tianjin-Hebei, China. Renewable and Sustainable Energy Reviews, 133, 110245. https://doi.org/10.1016/j.rser.2020.110245

Li, Z., Jia, R., & Gan, S. (2018). Evolution of condensed subgroup of political participation based on mobile phone. Multimedia Tools and Applications, 77, 4271–4282. https://doi.org/10.1007/s11042-017-4735-5

Liu, B., Luo C., Meng, F., & Jiang, H. (2021a). Modelling venture capital networks in hospitality and tourism entrepreneurial equity financing: An exponential random graph models approach. International Journal of Hospitality Management, 95, 102936. https://doi.org/10.1016/j.ijhm.2021.102936

Liu, K., Qiao, Y., & Zhou, Q. (2021b). Analysis of China’s industrial green development efficiency and driving factors: Research Based on MGWR. International Journal of Environmental Research and Public Health, 18(8), 3960. https://doi.org/10.3390/ijerph18083960

Liu, P., Rong, L., & Teng, F. (2019). The evaluation of ecosystem health based on hybrid TODIM method for Chinese case. Technological and Economic Development of Economy, 25(3), 542–570. https://doi.org/10.3846/tede.2019.8021

Liu, S., & Xiao, Q. (2021). An empirical analysis on spatial association investigation of industrial carbon emissions using SNA-ICE model. Energy, 224, 120183. https://doi.org/10.1016/j.energy.2021.120183

Liu, W., Song, Y., & Bi, K. (2021c). Exploring the patent collaboration network of China’s wind energy industry: A study based on patent data from CNIPA. Renewable and Sustainable Energy Reviews, 144, 110989. https://doi.org/10.1016/j.rser.2021.110989

Liu, X., & Yu, H. (2020). Spatial association and spillover effects of China’s inter-provincial green development. Journal of Jiangxi University of Finance and Economics, 3, 14–24.

Liu, Y., Wang, Y., & Li, H. (2020). Enlightenment of the development of world-class bay area industry to the construction of Guangdong-Hong Kong-Macao Greater Bay Area. Bulletin of the Chinese Academy of Sciences, 35(3), 312–321.

Marra, A., Antonelli, P., & Pozzi, C. (2017). Emerging green-tech specializations and clusters – a network analysis on technological innovation at the metropolitan level. Renewable and Sustainable Energy Reviews, 67, 1037–1046. https://doi.org/10.1016/j.rser.2016.09.086

Nabiafjadi, S., Sharifzadeh, M., & Ahmadvand, M. (2021). Social network analysis for identifying actors engaged in water governance: An endorheic basin case in the Middle East. Journal of Environmental Management, 288, 112376. https://doi.org/10.1016/j.jenvman.2021.112376

Pearce, D., Markandya, A., & Barbier, E. (1989). Blueprint for a green economy. Earthscan Publications Ltd.

Qiu, S., Wang, Z., & Liu, S. (2021). The policy outcomes of low-carbon city construction on urban green development: Evidence from a quasi-natural experiment conducted in China. Sustainable Cities and Society, 66, 102699. https://doi.org/10.1016/j.scs.2020.102699

Reardon, J. (2007). Comments on “Green economics: Setting the scene. Aims, context, and philosophical underpinnings of the distinctive new solutions offered by green economics”. International Journal of Green Economics, 1(3–4), 532–538. https://doi.org/10.1504/IJGE.2007.013076

Si, L., Wang, J., Yang, S., Yang, Y., & Zhang, J. (2021). Urban green development towards sustainability in northwest China: Efficiency assessment, spatial-temporal differentiation characters, and influencing factors. Complexity, 2021, 6630904. https://doi.org/10.1155/2021/6630904

Sun, C., Tong, Y., & Zou, W. (2018). The evolution and a temporal-spatial difference analysis of green development in China. Sustainable Cities and Society, 41, 52–61. https://doi.org/10.1016/j.scs.2018.05.006

United Nations Economic and Social Commission for Asia and the Pacific. (2006). State of the environment in Asia and the Pacific 2005. UNESCAP. United Nations publication.

Wang, K., & Zhang, F. (2021). Investigating the spatial heterogeneity and correlation network of green innovation efficiency in China. Sustainability, 13(3), 1104. https://doi.org/10.3390/su13031104

Wang, P., & You, J. (2016). Research on the evaluation of China’s environmental regulation effect: Based on a spatial perspective of industrial green development. Comparison of Economic and Social Systems, 5, 25–42.

Wang, Y., Li, Y., Zhu, Z., & Dong, J. (2021). Evaluation of green growth efficiency of oil and gas resource-based cities in China. Clean Technologies and Environmental Policy, 23(4), 1785–1795. https://doi.org/10.1007/s10098-021-02060-9

Wendling, Z., Emerson, J. W., Sherbinin, A. D., & Esty, D. C. (2020). Environmental performance index 2020. New Haven.

Weng, Q., Qin, Q., & Li, L. (2020). A comprehensive evaluation paradigm for regional green development based on “Five-Circle Model”: A case study from Beijing-Tianjin-Hebei. Journal of Cleaner Production, 277, 124076. https://doi.org/10.1016/j.jclepro.2020.124076

Wu, M., Wu, J., & Zang, C. (2021). A comprehensive evaluation of the eco-carrying capacity and green economy in the Guangdong-Hong Kong-Macao Greater Bay Area, China. China Journal of Cleaner Production, 281, 124945. https://doi.org/10.1016/j.jclepro.2020.124945

Xiang, Y., Wang, S., Zhang, Y., & Dai, Z. (2021). Green development efficiency measurement and influencing factors of the paper industry in the Yangtze River Economic Belt. Water, 13(9), 1286. https://doi.org/10.3390/w13091286

Xu, D., & Ma, L. (2020). Restrictive factors and promoting approaches on collaborative ecological environment governance in the Guangdong-Hong Kong-Macao Greater Bay Area. Geographical Research, 39(9), 2165–2175.

Xu, N., Xi, R., Shi, H., & Zhang, Y. (2019). The status, pressure and countermeasures of ecological environmental protection in the GBA. Environmental Protection, 47, 11–14.

Yoeruek, B. K., & Zaim, O. (2005). Productivity growth in OECD countries: A comparison with Malmquist indices. Journal of Comparative Economics, 33(2), 401–420. https://doi.org/10.1016/j.jce.2005.03.011

Zhang, T., & Wu, J. (2021). Spatial network structure and influence mechanism of green development efficiency of Chinese cultural industry. Scientia Geographica Sinica, 41(4), 580–587.

Zhang, X., & Guo, S. (2020). The spatial association and influencing factors of China’s industrial technological innovation efficiency. Studies in Science of Science, 3, 525–535.

Zhang, Y., Song, Y., & Zou, H. (2020). Transformation of pollution control and green development: Evidence from China’s chemical industry. Journal of Environmental Manage, 275, 111246. https://doi.org/10.1016/j.jenvman.2020.111246

Zhao, T., & Yang, Z. (2017). Towards green growth and management: relative efficiency and gaps of Chinese cities. Renewable and Sustainable Energy Reviews, 80, 481–494. https://doi.org/10.1016/j.rser.2017.05.142

Zhou, L., Zhou, C., Che, L., & Wang, B. (2020). Spatio-temporal evolution and influencing factors of urban green development efficiency in China. Journal of Geographical Sciences, 30, 724–742. https://doi.org/10.1007/s11442-020-1752-5