Abstract
Although local governments in China are encouraging the development of blockchain technology, the regional clustering of the blockchain industry still shows obvious differentiation. We use blockchain industry-related data during the period 2012–2019 to calculate the blockchain industrial clustering of each province in China. We find that the clustering state of the blockchain industry is quite different from the state of other industries and the situation of economic development in the same region. In less-developed regions, the blockchain industry is more prominent, which may benefit from local government management. We conduct an empirical analysis on the relationship between blockchain industrial clustering and regional government management using the generalized method of moments (GMM) of a dynamic panel. The results show that government management has a positive promoting effect on local blockchain industrial clustering as a whole, among which the promotion from economy, technology, infrastructure and policy is more significant.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Smith, A.: An Inquiry into the Nature and Causes of the Wealth of Nations, Britain (1776)
Marx, D.K.: Germany (1818)
Marshall. Principles of Economics 8th edn, Liberty Fund, Inc. Publishing, Britain (1890)
Poter, M.E.: Clusters and New Ecnomics Competition, no. 11. Harvard Business Review (1998)
Perroux, F.: A New Concept of Development. Routledge Library Editions Publishing, France (1983)
Krugman, P.: Increasing returns and economic geography. J. Politic. Econ. 99(3), 483–499 (1991)
Roelandt, Th.J.A.A., Gilsing, V.A., van Sinderen, J.: New Policies for the New Economy (2003)
Lin, Y.: New structural economics: reconstructing the framework of development economics. Econ. Quart. 1, 1–32 (2010)
Liu, G., Zhang, X., Deng, G.: Factors replacement, economic growth and unbalanced regional development. J. Quant. Tech. Econ. 7, 35–56 (2017)
Lee, J.: The Role of a University in Cluster Formation: Evidence from a National Institute of Science and Technology in Korea, Regional Science and Urban Economics, vol. 86 (2021)
Liu, Z., Zeng, S., Jin, Z., Shi, J.J.: Transport infrastructure and industrial clustering: Evidence from manufacturing industries in China. Transp. Policy 121, 100–112 (2022)
Jiangyong, L., Tao, Z.: Trends and determinants of China’s industrial clustering. J. Urban Econ. 65(2), 167–180 (2009)
Canh, N.P., Schinckus, C., Thanh, S.D.: Do economic openness and institutional quality influence patents? Evidence from GMM systems estimates. Int. Econ. 157, 134–169 (2019)
Steinle, C., Schiele, H.: When do industries cluster? A proposal on how to assess an industry’s propensity to concentrate at a single region or nation. Res. Policy 31(6), 849–858 (2002)
You, S., Zhou, K.Z., Jia, L.: How does human capital foster product innovation? The contingent roles of industry cluster features. J. Bus. Res. 130, 335–347 (2021)
Li, X.: Legal effect of smart contracts based on blockchain. In: Zeng, J.., Jing, W.., Song, X.., Lu, Z.. (eds.) ICPCSEE 2020. CCIS, vol. 1257, pp. 166–186. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-7981-3_12
Huang, J., et al.: Survey on blockchain incentive mechanism. In: Cheng, X., Jing, W., Song, X., Lu, Z. (eds.) ICPCSEE 2019. CCIS, vol. 1058, pp. 386–395. Springer, Singapore (2019). https://doi.org/10.1007/978-981-15-0118-0_30
Li, W., Guo, W.: The competence of volunteer computing for MapReduce big data applications. In: Zhou, Q., Gan, Y., Jing, W., Song, X., Wang, Y., Lu, Z. (eds.) ICPCSEE 2018. CCIS, vol. 901, pp. 8–23. Springer, Singapore (2018). https://doi.org/10.1007/978-981-13-2203-7_2
Wu, H., Li, Q., Li, X.: Research and simulation of mass random data association rules based on fuzzy cluster analysis. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds.) ICPCSEE 2021. CCIS, vol. 1451, pp. 80–89. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-5940-9_6
Song, Y., Wang, J., Yang, S., Zhu, X., Yin, K.: A blockchain-based scheme of data sharing for housing provident fund. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds.) ICPCSEE 2021. CCIS, vol. 1451, pp. 3–14. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-5940-9_1
Mijiyawa, A.G.: Drivers of structural transformation: the case of the manufacturing sector in Africa. World Develop. 99, 141–159 (2017)
Zhang, H., Liu, Z., Zhang, Y.-J.: Assessing the economic and environmental effects of environmental regulation in China: the dynamic and spatial perspectives. J. Clean. Prod. 334 (2022)
Uddin, M.A., Ali, M.H., Masih, M.: Political stability and growth: an application of dynamic GMM and quantile regression. Econ. Model. 64, 610–625 (2017)
Trinugroho, I., Law, S.H., Lee, W.C., Wiwoho, J., Sergi, B.S.: Effect of financial development on innovation: roles of market institutions. Econ. Model. 103 (2021)
Ullah, A., Pinglu, C., Ullah, S., Qaisar, Z.H., Qian, N.: The dynamic nexus of E-Government, and sustainable development: moderating role of multi-dimensional regional integration index in Belt and Road partner countries. Technol. Soc. 68 (2022)
Acknowledgments
This work was supported by The National Key Research and Development Program of China (2020YFB1006104), and the Financial support from the Innovation and Talent Base for Digital Technology and Finance (B21038).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Xu, X., Wu, Z., Qiao, X., Zhang, Y., Guo, H. (2022). The Impact of Policy on the Clustering of the Blockchain Industry. In: Wang, Y., Zhu, G., Han, Q., Zhang, L., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2022. Communications in Computer and Information Science, vol 1629. Springer, Singapore. https://doi.org/10.1007/978-981-19-5209-8_32
Download citation
DOI: https://doi.org/10.1007/978-981-19-5209-8_32
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-5208-1
Online ISBN: 978-981-19-5209-8
eBook Packages: Computer ScienceComputer Science (R0)