Open Access
Issue
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
Article Number 09019
Number of page(s) 16
Section Computer-Aided Advanced System and Management
DOI https://doi.org/10.1051/matecconf/202133609019
Published online 15 February 2021
  1. He Canfei, Pan Fenghua, Sun Lei. Geographical concentration of manufacturing industries in China. J. Acta Geographica Sinica, 2007, 62(12), 1253-1264. [Google Scholar]
  2. Fan C.C, Scott A.J. Industrial agglomeration and development: A survey of spatial economic issues in east Asia and a statistical analysis of Chinese regions. J. Economic Geography, 2003, 79(3), 295-319. [Google Scholar]
  3. Zhou Shengqiang, Zhu Weiping. Must industrial agglomeration be able to bring about economic efficiency: Economies of scale and crowding effect. J. Industrial Economics Research, 2013, 3, 12-22. [Google Scholar]
  4. Wang Kai, Yi Jing, Xiao Yan, et al. The correlation between tourism agglomeration and industrial efficiency in China. J. Human geography, 2016, 31(2), 120-127. [Google Scholar]
  5. Shi Yanwen, Li Erling, Li Xiaojian, et al. The agricultural industry cluster innovation network and knowledge flow based on SNA: The cases of Shouguang vegetable cluster and Yanling flower and plant cluster. J. Economic Geography, 2015, 35(8), 114-122. [Google Scholar]
  6. Li Erling, Shi Yanwen, Li Xiaojian. The structure analysis of agricultural innovation system based on agricultural cluster: A case study of flower and plant industrial cluster in Yanling County, Henan Province. J. Economic Geography, 2012, 32(11), 113-119. [Google Scholar]
  7. Liu Chao, Li Dalong. Research on the motivation of financial industry agglomeration evolution based on complexity theory . J. Contemporary Economic Research, 2013, 10, 55-62. [Google Scholar]
  8. Qin Tai, Xu Shen. An empirical analysis of the trend of financial agglomeration. J. Journal of Chongqing University of Science and Technology (Social Science Edition), 2012, 1, 80-83. [Google Scholar]
  9. Marshall A. Principles of Economics, 8th ed; London: Macmillan, 1920; pp. 154-160. [Google Scholar]
  10. Paul Krugman. Geography and Trade; Translated by Zhang Zhaojie, Beijing: Peking University Press, Renmin University Press, 2000 [Google Scholar]
  11. Fan Xiufeng, Kang Xiaoqin. Agglomeration level measurement of manufacturing in Shaanxi Province and its influencing factors empirical analysis. J. Economic Geography, 2013, 33(09), 115-119+160. [Google Scholar]
  12. Pan Wenqing, Liu Qing. The manufacture industries agglomeration and the regional economic growth in China: Based on China’s industrial enterprises database. J. Journal of Tsinghua University (Philosophy and Social Sciences Edition), 2012, 1, 137-147. [Google Scholar]
  13. Wen Dongwei, Xian Guoming. The degree of China’s manufacturing industry agglomeration and its evolution trend: 1998-2009. J. The Journal of World Economy, 2014, 3, 3-31. [Google Scholar]
  14. Yang Shouyun, Zhao Xin, Wang Yiqiao. The Impact of high-tech industry agglomeration on industrial efficiency — An empirical test based on Williamson hypothesis and openness hypothesis. J. Science and Technology Progress and Policy, 2019, 36(20), 69-76. [Google Scholar]
  15. Melitz M.J. The impact of trade on intra-industry reallocations and aggregate industry productivity. J. Econometrica, 2003, 71(6), 1695-1725. [Google Scholar]
  16. Bernard, Andrew, B. Plants and productivity in international trade. J. American Economic Review, 2003, 93(4), 1268-1290. [Google Scholar]
  17. Melitz M.J, Ottaviano G I P. Market size, trade, and productivity. J. Review of Economic Studies, 2008, 75(1), 295-316. [Google Scholar]
  18. Greenaway D, Kneller R. Exporting, productivity, and agglomeration. J. European Economic Review, 2008, 52(5), 0-939. [Google Scholar]
  19. Clerides S.K, Saul L, Tybout J.R. Is learning by exporting important? Microdynamic evidence from Colombia, Mexico, and Morocco*. J. Quarterly Journal of Economics, 1998, 113(3), 903-947. [Google Scholar]
  20. Zhao Tingting, Xu Mengbo. The mechanism and effect of industrial agglomeration affecting regional innovation — An empirical test based on China provincial panel data. J. Scientific Management Research, 2020, 38(01), 83-88. [Google Scholar]
  21. Zhao Qingxia, Xia Chuanxin, Shi Jianjun. Sci-tech talents agglomeration, industry agglomeration, and regional innovation capability: Empirical analysis based on Jing– Jin–Ji Region, Yangtze River Delta, and Pearl River Delta. J. Science and Technology Management Research, 2019, 39(24), 54-62. [Google Scholar]
  22. Dijk M P V, Soltan S. Palestinian clusters: From agglomeration to innovation. J. European Scientific Journal, 2017, 13(13), 323-336. [Google Scholar]
  23. Chen Qiangqiang, Ye Deming. Spatial pattern of animal husbandry industrial agglomeration in Gansu Province. J. Arid Land Geography, 2018, 41(03), 652-660. [Google Scholar]
  24. Chen Qiangqiang, Tang Zhengxing, Li Guoshun. Spatial agglomeration and the driving factors of traditional Chinese medicine industry in Gansu Province. J. Research of Agricultural Modernization, 2017, 38(01), 145-153. [Google Scholar]
  25. Ji Zhenglong, Song Yu. Design and application of central gravity index algorithm for industrial spatial agglomeration: Enterprise micro data verification based on the integration perspective of the Yangtze River Delta. J. Statistics and Information Forum, 2020, 35(03), 38-48. [Google Scholar]
  26. Luo Yinchen, Gu Renxu. The pattern and evolutional trend of Chinese manufacturing’s spatial agglomeration — An empirical analysis based on data from 1980 to 2011. J. Economic Geography, 2014, 34(07), 82-89. [Google Scholar]
  27. He Canfei, Pan Fenghua. The trends of geographical agglomeration of manufacturing sectors in China and the explanations. J. South China Journal of Economics, 2011, 06, 38-52. [Google Scholar]
  28. He Canfei, Xie Xiuzhen. Geographical concentration and provincial specialization of Chinese manufacturing industries. J. Acta Geographica Sinica, 2006, 02, 212-222. [Google Scholar]
  29. Bi Xuecheng, Gu Renxu, Su Qin, Lin Shanquan. The agglomeration of manufacturing industry and the evolution of geographical pattern in Jiangsu Province. J. East China Economic Management, 2018, 32(07), 12-21. [Google Scholar]
  30. Zheng Xiao, Liu Zhenning. Thoughts on the Gini Coefficient and Industrial Agglomeration Development of the Construction Industry in Eight Southeastern Provinces [A]. Scientific Research Publishing, USA. Proceedings of the 2010 International Conference on Information Technology and Scientific Management (Volume 2) [C]. Scientific Research Publishing, USA: 2010: 6. [Google Scholar]
  31. Liu Bingsheng, Xue Bin. Analysis of the three-dimensional system of industry linkages with spatial difference for the Chinese regional construction industry. J. Journal of Chongqing University (Social Science Edition), 2015, 21(01), 16-22. [Google Scholar]
  32. Liu Bingsheng, Chen Xiaohong, Xue Bin, Fang Ning. Research on gradient changes and influential mechanism of development level in Chinese regional construction industry. J. Operations Research and Management Science, 2016, 25(01), 254-261. [Google Scholar]
  33. Ma Hui, Wang Suzhen, Huang Mengjiao. Analysis of factors influencing cooperative innovation in construction industry alliance based on social network analysis: Taking Beijing–Tianjin–Hebei Region as an example. J. Science and Technology Management Research, 2018, 38(15), 170-176. [Google Scholar]
  34. Zhang Mao, Qiao Dongyan, Dai Yongan. A spatial econometric analysis of the construction’s differences in China's provincial regions. J. Scientific Decision Making, 2010, 03, 87-93. [Google Scholar]
  35. Dai Yongan, Chen Cai. Spatial econometric analysis of regional differences in China’s construction industry development. J. Statistics and Information Forum, 2010, 05, 53-58. [Google Scholar]
  36. Bu Weiwei, Zhou Wei, Li Wanting. Correlation analysis of provincial construction industry development based on factor analysis. J. Journal of Civil Engineering and Management, 2019, 36(02), 127-131+145. [Google Scholar]

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