single-jc.php

JACIII Vol.27 No.5 pp. 739-747
doi: 10.20965/jaciii.2023.p0739
(2023)

Research Paper:

Industrial Chain Map and Linkage Network Characteristics of Digital Economy

Yanwu Chen ORCID Icon, Haiming Ding, and Jun Ma

Institute of Quantitative Economy, Huaqiao University
No.668 Jimei Avenue, Jimei District, Xiamen 361021, China

Corresponding author

Received:
December 28, 2022
Accepted:
April 8, 2023
Published:
September 20, 2023
Keywords:
digital economy, average propagation length, social network analysis, Weaver–Thomas model, input-output
Abstract

The development of the digital economy in the modern era significantly embodies a country’s comprehensive strength. This paper uses the data from China’s 2012 and 2017 input-output tables to analyze the linkage structure between the digital economy industry and other industries using the average propagation length model and social network analysis. The Weaver–Thomas model was used to obtain the industrial linkage matrix and network characteristics. An industrial chain map of the digital economy was depicted as the core. This paper is of practical significance in depicting the industrial chain structure and network characteristics, understanding the position of digital economy industry in the economic system and promoting the integrated development of the digital economy and traditional manufacturing industries, which allows them to incorporate the new generation of technology and industrial transformation with the digital technology as the core to promote their transformation and upgrading.

The industrial chain map of digital economy industry in 2017

The industrial chain map of digital economy industry in 2017

Cite this article as:
Y. Chen, H. Ding, and J. Ma, “Industrial Chain Map and Linkage Network Characteristics of Digital Economy,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.5, pp. 739-747, 2023.
Data files:
References
  1. [1] W. W. Leontief, “Input-Output Economics,” Oxford University Press, 1966.
  2. [2] E. Dietzenbacher, I. R. Luna, and N. S. Bosma, “Using average propagation lengths to identify production chains in the Andalusian,” Estudios de Economia Aplicada, Vol.23, No.2, pp. 405-422, 2005.
  3. [3] E. Dietzenbacher and I. Romero, “Production chain in an interregional framework: Identification by means of average propagation lengths,” Int. Regional Science Review, Vol.30, Issue 4, 2007.
  4. [4] S. Inomata, “A new measurement for International Fragmentation of the Production Process: An International Input-Output Approach,” Institute of Developing Economies, Article No.175, 2008.
  5. [5] H. Escaith and S. Inomata, “Geometry of Global Value Chains in East Asia: The Role of Industrial Networks and Trade Policies,” D. K. Elms and P. Low (Eds.), “Global Value Chains in a Changing World,” Fung Global Institute (FGI), Nanyang Technological University (NTU), and World Trade Organization (WTO), 2013.
  6. [6] D. L. Fang, C. C. Duan, and B. Chen, “Average propagation length analysis for water-land resource in urban socio-economic system: A nexus perspective,” DEStech Trans. on Environment, Energy and Earth Sciences, 2018.
  7. [7] Y. Li, B. Zhang, B. Wang, and Z. Wang, “Evolutionary trend of the coal industrial chain in China: Evidence from the analysis of I-O and APL model,” Resources, Conservation and Recycling, Vol.145, pp. 399-410, 2019.
  8. [8] X. Liang, X. Yang, F. Yan, and Z. Li, “Exploring global embodied metal flows in international trade based combination of multi-regional input-output analysis and complex network analysis,” Resources Policy, Vol.67, Article No.101661, 2020.
  9. [9] B. Q. Yan, “Take advantage of the digital economy to keep the industrial chain stable,” China Development Observation, Vol.16, No.21, pp. 22-24+32, 2020.
  10. [10] C. M. Liu, X. Yin, and L. S. Wang, “Research on the spatial imbalance and distributional dynamic evolution of digital economy in China,” Forum on Science and Technology in China, Vol.36, No.3, pp. 97-109, 2020.
  11. [11] Y. P. Zhang, C. Dong, and J. Luan, “Mechanism of digital economy promoting high-quality economic development: Based on evidence from the provincial panel data,” J. of University of Jinan (Social Science Edition), Vol.31, No.5, pp. 99-117, 2021.
  12. [12] X. C. Xu and M. H. Zhang, “Research on the scale measurement of China’s digital economy-based on the perspective of international comparison,” China Industrial Economics, Vol.37, pp. 23-41, 2020.
  13. [13] J. H. Wang and C. J. Zhou, “The current situation, characteristics and spillover effect of the development of digital industry in China,” The J. of Quantitative & Technical Economics, Vol.38, No.3, pp. 103-119, 2021.
  14. [14] F. C. Zhu and G. L. Le, “The measurement of the scale of value added in the digital economy,” The World of Survey and Research, Vol.34, No.2, pp. 56-64, 2021.
  15. [15] A. Ghosh, “Input-output approach in an allocation system,” Economica, Vol.25, pp. 58-64, 1958.
  16. [16] K. Barefoot et al., “Defining and Measuring the digital economy,” BEA Working Paper, 2018. http://www.bea.gov/system/files/papers/WP208-4.pdf [Accessed July 30, 2019]
  17. [17] Australian Bureau of Statistics, “Measuring Digital Activities in the Australian Economy,” 2019. https://www.abs.gov.au/websitedbs/D3310114.nsf/ [Accessed July 30, 2019]
  18. [18] Z.-G. Deng and X.-K. Chen, “Analysis on Chinese product sectors’ production chains and their evolution based on APL model,” Mathematics in Practice and Theory, Vol.38, No.1, pp. 53-39, 2008.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024