The Impact of Industrial Robot Applications on Global Value Chains Division Position

Authors

  • Kaiqing Wang

DOI:

https://doi.org/10.54097/pkke7302

Keywords:

Global Value Chains; GVC division position; Industrial robots; GVC resilience.

Abstract

This paper surveys the GVC division position across forty-five countries and fourteen manufacturing sub-sectors during the period from 1999 to 2018 to illustrate the impact of applications of industrial robots on the GVC position. The study proves that an increasing level of utilization of industrial robots significantly improves the GVC division position in the manufacturing sector. By automating repetitive and precision tasks, robots enhance efficiency and productivity, therefore allowing deeper specialization in specific stages of the manufacturing process. This technological progress allows for a more connected global production network and hence better integration into GVC. The study also evaluates the spillover effects across value chains and the moderating impact of industrial agglomeration on smart manufacturing.The empirical results show that the application of industrial robots enhances productivity and encourages innovation in related sectors, thereby driving downstream industry growth and promoting industry specialization.Despite the improvement in GVC division positions, robots also contribute to making global value chains more diversified and resilient. Flexible and adaptive manufacturing systems can adapt to disruptions, such as pandemics and geopolitical tensions, ensuring continuity in production and increasing stability and competitiveness in smart manufacturing systems.

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References

[1] Koopman R, Powers W, Wang Z, et al. Give credit where credit is due: Tracing value added in global production chains[R]. National Bureau of Economic Research, 2010.

[2] Wang Z, Wei S J, Zhu K. Quantifying international production sharing at the bilateral and sector levels[R]. National Bureau of Economic Research, 2013.

[3] Antràs P, Chor D, Fally T, et al. Measuring the upstreamness of production and trade flows[J]. American Economic Review, 2012, 102(3): 412-416.

[4] Wang Z, Wei S J, Yu X, et al. Measures of participation in global value chains and global business cycles[R]. National Bureau of Economic Research, 2017.

[5] Graetz G, Michaels G. Robots at work[J]. Review of Economics and Statistics, 2018, 100(5): 753-768.

[6] Acemoglu D, Restrepo P. The race between man and machine: Implications of technology for growth, factor shares, and employment [J]. American economic review, 2018, 108(6): 1488-1542.

[7] Frey C B, Osborne M A. Technology at work v2. 0: The future is not what it used to be[J]. Citi GPS: Global Perspectives & Solutions, 2016.

[8] Zheng Lili, Liu Dongsheng. How Does Industrial Intelligence Affect the Participation of Manufacturing Industry in International Division of Labor - Based on the Global Value Chain Perspective[J]. Journal of Guangdong University of Finance and Economics, 2022, 37(4): 18-29.

[9] Huang, L., Lin, Z., & Wang, X. (2023). The application of industrial robots and the restructuring of global value chains: A perspective based on the bargaining power of export products. China Industrial Economics, (2), 74-92.

[10] Pasquali G, Krishnan A, Alford M. Multichain strategies and economic upgrading in global value chains: Evidence from Kenyan horticulture[J]. World Development, 2021, 146: 105598.

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Published

15-10-2024

How to Cite

Wang, K. (2024). The Impact of Industrial Robot Applications on Global Value Chains Division Position. Highlights in Business, Economics and Management, 41, 497-505. https://doi.org/10.54097/pkke7302