Technical Papers
Apr 25, 2022

Impact of Polycentric Urban Network on Industrial Structure Upgrades: Evidence from the Yangtze River Economic Belt

Publication: Journal of Urban Planning and Development
Volume 148, Issue 3

Abstract

Polycentric urban networks (PUNs) have been found to be an important factor for urban economic growth. This study is based on a PUN analytical framework and features agglomeration effects and network externalities. We examine the relationship between PUNs and industrial structure upgrading, using a data set of 108 cities in the Yangtze River Economic Belt of China from 2005 to 2017. We find that the PUN is associated with an increase in the industrial structure upgrading index, but small cities benefit less from the network. In reference to spatial political economics, new structural economics, and product space theory, we build an analysis framework to explain the mechanism. The main channel is a positive effect of encouraging the spatial flow of factors, promoting regional integration, and enhancing urban innovativeness. This research has significant policy implications for discovering alternative avenues to reform the manufacturing industry and enhancing regional economic development efficiency from a spatial perspective.

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Acknowledgments

Thanks are given for funding from the Chinese Ministry of Education’s Humanities and Social Science Project (Grant Nos. 20XJC790004 and 21XJC790006). We are also immensely grateful to the anonymous reviewers for their valuable comments and constructive remarks.

References

Agyemang, F. S. K., E. Silva, and M. Poku-Boansi. 2019. “Understanding the urban spatial structure of Sub-Saharan African cities using the case of urban development patterns of a Ghanaian city-region.” Habitat Int. 85: 21–33. https://doi.org/10.1016/j.habitatint.2019.02.001.
Anas, A., R. Arnott, and K. Small. 1998. “Urban spatial structure.” J. Econ. Lit. 36 (3): 1426–1464.
Bartosiewicz, B., and S. Marcińczak. 2020. “Investigating polycentric urban regions: Different measures – Different results.” Cities 105: 102855. https://doi.org/10.1016/j.cities.2020.102855.
Baum-Snow, N. 2007. “Did highways cause suburbanization?” Q. J. Econ. 122 (2): 775–805. https://doi.org/10.1162/qjec.122.2.775.
Burger, M. J., B. de Goei, L. van der Laan, and F. J. M. Huisman. 2011. “Heterogeneous development of metropolitan spatial structure: Evidence from commuting patterns in English and Welsh city-regions, 1981–2001.” Cities 28 (2): 160–170. https://doi.org/10.1016/j.cities.2010.11.006.
Cai, F. 2012. “The coming demographic impact on China’s growth: The age factor in the middle-income trap.” Asian Econ. Pap. 11 (1): 95–111. https://doi.org/10.1162/ASEP_a_00121.
Cai, F. 2020. “The second demographic dividend as a driver of China’s growth.” China World Econ. 28 (5): 26–44. https://doi.org/10.1111/cwe.12350.
Chen, W., O. Golubchikov, and Z. Liu. 2021a. “Measuring polycentric structures of megaregions in China: Linking morphological and functional dimensions.” Environ. Plann. B Urban Anal. City Sci. 48 (8): 2272–2288. https://doi.org/10.1177/2399808320974687.
Chen, X., X. Chen, and M. Song. 2021b. “Polycentric agglomeration, market integration and green economic efficiency.” Struct. Change Econ. Dyn. 59: 185–197. https://doi.org/10.1016/j.strueco.2021.08.016.
Chenery, H. B., S. Robinson, and M. Syrquin. 1986. Industrialization and growth: A comparative study. New York: Published for the World Bank by Oxford University Press.
China State Council. 2020. Major Figures on 2020 Population Census of China, Beijing, China: China Statistical Press. http://www.stats.gov.cn/tjsj/pcsj/.
Davoudi, S. 2003. “Polycentricity in European spatial planning: From an analytical tool to a normative agenda.” Eur. Plann. Stud. 11 (8): 979–999. https://doi.org/10.1080/0965431032000146169.
Department of Urban Society and Economic Statistics National Bureau of Statistics of China. 2006-2018. China City Statistical Year Book. Beijing, China: China Statistical Press.
Derudder, B., X. Liu, M. Wang, W. Zhang, K. Wu, and F. Caset. 2021. “Measuring polycentric urban development: The importance of accurately determining the ‘balance’ between ‘centers.’.” Cities 111: 103009. https://doi.org/10.1016/j.cities.2020.103009.
Fan, F., S. Dai, K. Zhang, and H. Ke. 2021a. “Innovation agglomeration and urban hierarchy: Evidence from Chinese cities.” Appl. Econ. 53 (54): 6300–6318. https://doi.org/10.1080/00036846.2021.1937507.
Fan, W., S. Wang, X. Gu, Z. Zhou, Y. Zhao, and W. Huo. 2021b. “Evolutionary game analysis on industrial pollution control of local government in China.” J. Environ. Manage. 298: 113499. https://doi.org/10.1016/j.jenvman.2021.113499.
Fernández-Maldonado, A. M., A. Romein, O. Verkoren, and R. Parente Paula Pessoa. 2014. “Polycentric structures in Latin American metropolitan areas: Identifying employment sub-centres.” Reg. Stud. 48 (12): 1954–1971. https://doi.org/10.1080/00343404.2013.786827.
Glaeser, E. L., G. A. M. Ponzetto, and Y. Zou. 2016. “Urban networks: Connecting markets, people, and ideas: Urban networks.” Pap. Reg. Sci. 95 (1): 17–59. https://doi.org/10.1111/pirs.12216.
Gonzalez-Navarro, M., and M. A. Turner. 2018. “Subways and urban growth: Evidence from earth.” J. Urban Econ. 108: 85–106. https://doi.org/10.1016/j.jue.2018.09.002.
Hausmann, R., and B. Klinger. 2006. “The evolution of 59 comparative advantage: The impact of the structure of the product space.” CID working paper 106. Cambridge, MA: Harvard Univ.
Hidalgo, C. A., B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The product space conditions the development of nations.” Science 317 (5837): 482–487. https://doi.org/10.1126/science.1144581.
Huang, Y., and R. Liao. 2021. “Polycentric or monocentric, which kind of spatial structure is better for promoting the green economy? Evidence from Chinese urban agglomerations.” Environ. Sci. Pollut. Res. 28 (41): 57706–57722. https://doi.org/10.1007/s11356-021-14655-2.
Jiang, Z., W. Zhai, X. Meng, and Y. Long. 2020. “Identifying shrinking cities with NPP-VIIRS nightlight data in China.” J. Urban Plann. Dev. 146 (4): 04020034. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000598.
Johansson, B., and J. M. Quigley. 2003. “Agglomeration and networks in spatial economies.” Pap. Reg. Sci. 83 (1): 165–176. https://doi.org/10.1007/s10110-003-0181-z.
Ju, J., J. Y. Lin, and Y. Wang. 2015. “Endowment structures, industrial dynamics, and economic growth.” J. Monetary Econ. 76: 244–263. https://doi.org/10.1016/j.jmoneco.2015.09.006.
Kloosterman, R. C., and S. Musterd. 2001. “The polycentric urban region: Towards a research agenda.” Urban Stud. 38 (4): 623–633. https://doi.org/10.1080/00420980120035259.
Kou, Z., and X. Liu. 2017. “FIND Report on City and Industrial Innovation in China (2017).” Fudan Institute of Industrial Development, School of Economics, Fudan University. http://www.cbnri.org/news/5389402.html.
Kumar, S., S. Ghosh, and S. Singh. 2021. “Polycentric urban growth and identification of urban hot spots in Faridabad, the million-plus metropolitan city of Haryana, India: A zonal assessment using spatial metrics and GIS.” Environ. Dev. Sustainability 1–41. https://doi.org/10.1007/s10668-021-01782-6.
Kwon, K., and M. Seo. 2018. “Does the polycentric urban region contribute to economic performance? The case of Korea.” Sustainability 10 (11): 4157. https://doi.org/10.3390/su10114157.
Lao, X., T. Y. Shen, Y. Yang, and Y. Zhang. 2016. “A study on the economic network of the urban agglomeration in the middle reaches of the Yangtze River: Based on social network analysis method with gravity model.” [In Chinese.] Urban Dev. Stud. 23 (7): 91–98.
Li, Y., and B. Derudder. 2020. “Dynamics in the polycentric development of Chinese cities, 2001–2016.” Urban Geogr. 1–21. https://doi.org/10.1080/02723638.2020.1847938.
Li, Y., and R. Du. 2022. “Polycentric urban structure and innovation: Evidence from a panel of Chinese cities.” Reg. Stud. 56 (1): 113–127. https://doi.org/10.1080/00343404.2021.1886274.
Lin, J. Y. 2012. “From flying geese to leading dragons: New opportunities and strategies for structural transformation in developing countries.” Global Policy 3 (4): 397–409. https://doi.org/10.1111/j.1758-5899.2012.00172.x.
Lin, J. Y., and Y. Wang. 2020. “Seventy years of economic development: A review from the angle of new structural economics.” China World Econ. 28 (4): 26–50. https://doi.org/10.1111/cwe.12340.
Liu, X., B. Derudder, and K. Wu. 2016. “Measuring polycentric urban development in China: An intercity transportation network perspective.” Reg. Stud. 50 (8): 1302–1315. https://doi.org/10.1080/00343404.2015.1004535.
Liu, X., L. Gong, Y. Gong, and Y. Liu. 2015. “Revealing travel patterns and city structure with taxi trip data.” J. Transp. Geogr. 43: 78–90. https://doi.org/10.1016/j.jtrangeo.2015.01.016.
Liu, W., H. Zhang, and Z. Huang. 2008. “A survey of the progress and regional differences of China’s industrial structure advancement and industrialization.” [In Chinese.] Econ. Perspect. 11: 4–8.
Long, Y., W. Zhai, Y. Shen, and X. Ye. 2018. “Understanding uneven urban expansion with natural cities using open data.” Landscape Urban Plann. 177: 281–293. https://doi.org/10.1016/j.landurbplan.2017.05.008.
Louail, T., M. Lenormand, O. G. Cantu Ros, M. Picornell, R. Herranz, E. Frias-Martinez, J. J. Ramasco, and M. Barthelemy. 2015. “From mobile phone data to the spatial structure of cities.” Sci. Rep. 4 (1): 5276. https://doi.org/10.1038/srep05276.
Lv, Y., Z. Lan, C. Kan, and X. Zheng. 2021a. “Polycentric urban development and its determinants in China: A geospatial big data perspective.” Geog. Anal. 53 (3): 520–542. https://doi.org/10.1111/gean.12236.
Lv, Y., L. Zhou, G. Yao, and X. Zheng. 2021b. “Detecting the true urban polycentric pattern of Chinese cities in morphological dimensions: A multiscale analysis based on geospatial big data.” Cities 116: 103298. https://doi.org/10.1016/j.cities.2021.103298.
Meijers, E. 2007. “Clones or complements? The division of labour between the main cities of the Randstad, the Flemish Diamond and the RheinRuhr Area.” Reg. Stud. 41 (7): 889–900. https://doi.org/10.1080/00343400601120239.
Meijers, E. J. 2008. “Measuring polycentricity and its promises.” European Plann. Stud. 16 (9): 1313–1323. https://doi.org/10.1080/09654310802401805.
Meijers, E. J., and M. J. Burger. 2010. “Spatial structure and productivity in US metropolitan areas.” Environ. Plann. A Econ. Space 42 (6): 1383–1402. https://doi.org/10.1068/a42151.
Meijers, E. J., and M. J. Burger. 2017. “Stretching the concept of ‘borrowed size’.” Urban Stud. 54 (1): 269–291. https://doi.org/10.1177/0042098015597642.
Meijers, E. J., M. J. Burger, and M. M. Hoogerbrugge. 2016. “Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe.” Pap. Reg. Sci. 95 (1): 181–198. https://doi.org/10.1111/pirs.12181.
Musterd, S., and I. van Zelm. 2001. “Polycentricity, households and the identity of places.” Urban Stud. 38 (4): 679–696. https://doi.org/10.1080/00420980120035286.
Ouwehand, W. M., F. G. van Oort, and N. Cortinovis. 2022. “Spatial structure and productivity in European regions.” Reg. Stud. 56 (1): 48–62. https://doi.org/10.1080/00343404.2021.1950912.
Sadewo, E., I. Syabri, A. Antipova, Pradono, and D. Hudalah. 2021. “Using morphological and functional polycentricity analyses to study the Indonesian urban spatial structure: The case of Medan, Jakarta, and Denpasar.” Asian Geogr. 38 (1): 47–71. https://doi.org/10.1080/10225706.2020.1737829.
Song, G. 2021. “Road versus rail: Assessing the implications of transport infrastructure for spatial growth pattern in China’s megaregions.” J. Urban Plann. Dev. 147 (1): 04020050. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000588.
Strambach, S., and B. Klement. 2012. “Cumulative and combinatorial micro-dynamics of knowledge: The role of space and place in knowledge integration.” Eur. Plann. Stud. 20 (11): 1843–1866. https://doi.org/10.1080/09654313.2012.723424.
Su, H., G. Han, L. Li, and H. Qin. 2021. “The impact of macro-scale urban form on land surface temperature: An empirical study based on climate zone, urban size and industrial structure in China.” Sustainable Cities Soc. 74: 103217. https://doi.org/10.1016/j.scs.2021.103217.
Sun, B., S. Han, and W. Li. 2020. “Effects of the polycentric spatial structures of Chinese city regions on CO2 concentrations.” Transp. Res. Part D Transp. Environ. 82: 102333. https://doi.org/10.1016/j.trd.2020.102333.
Wang, M., B. Derudder, and X. Liu. 2019. “Polycentric urban development and economic productivity in China: A multiscalar analysis.” Environ. Plann. A Econ. Space 51 (8): 1622–1643. https://doi.org/10.1177/0308518X19866836.
Wang, X. L., G. Fan, and L. P. Hu. 2018. Marketization Index of China's Provinces: Neri Rep. 2018. Beijing, China: Social Sciences Academic Press.
Wang, T., W. Yue, X. Ye, Y. Liu, and D. Lu. 2020. “Re-evaluating polycentric urban structure: A functional linkage perspective.” Cities 101: 102672. https://doi.org/10.1016/j.cities.2020.102672.
Xiao, W., Y. D. Wei, and H. Li. 2021. “Spatial inequality of job accessibility in Shanghai: A geographical skills mismatch perspective.” Habitat Int. 115: 102401. https://doi.org/10.1016/j.habitatint.2021.102401.
Yang, Z., Y. Chen, G. Guo, Z. Zheng, and Z. Wu. 2021. “Using nighttime light data to identify the structure of polycentric cities and evaluate urban centers.” Sci. Total Environ. 780: 146586. https://doi.org/10.1016/j.scitotenv.2021.146586.
Yue, W., S. Qiu, H. Xu, L. Xu, and L. Zhang. 2019. “Polycentric urban development and urban thermal environment: A case of Hangzhou, China.” Landscape Urban Plann. 189: 58–70. https://doi.org/10.1016/j.landurbplan.2019.04.008.
Zhang, T., B. Sun, and W. Li. 2017. “The economic performance of urban structure: From the perspective of Polycentricity and Monocentricity.” Cities 68: 18–24. https://doi.org/10.1016/j.cities.2017.05.002.
Zhong, C., S. M. Arisona, X. Huang, M. Batty, and G. Schmitt. 2014. “Detecting the dynamics of urban structure through spatial network analysis.” Int. J. Geog. Inf. Sci. 28 (11): 2178–2199. https://doi.org/10.1080/13658816.2014.914521.
Zhu, D., C. Cheng, W. Zhai, Y. Li, S. Li, and B. Chen. 2021. “Multiscale spatial polygonal object granularity factor matching method based on BPNN.” ISPRS Int. J. Geo-Inf. 10 (2): 75. https://doi.org/10.3390/ijgi10020075.

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 148Issue 3September 2022

History

Received: Aug 4, 2021
Accepted: Jan 26, 2022
Published online: Apr 25, 2022
Published in print: Sep 1, 2022
Discussion open until: Sep 25, 2022

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Assistant Professor, Western China Center for Economic Research, Southwestern Univ. of Finance and Economics, Chengdu 611130, P.R. China. ORCID: https://orcid.org/0000-0001-6101-7007. Email: [email protected]
Minghui Liu [email protected]
Assistant Professor, School of Marxism, Sichuan Agricultural Univ., Chengdu 611130, P.R. China. Email: [email protected]
Associate Professor, Western China Center for Economic Research, Southwestern Univ. of Finance and Economics, Chengdu 611130, P.R. China. ORCID: https://orcid.org/0000-0002-7356-569X. Email: [email protected]
Assistant Professor, School of Finance and Economics, Jiangsu Univ., Zhenjiang 212013, P.R. China (corresponding author). ORCID: https://orcid.org/0000-0002-7356-569X. Email: [email protected]

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