Analysis on the economic growth effects of industrial clustering in high-tech manufacturing and knowledge-intensive service industries
Abstract
High-tech manufacturing and knowledge-intensive service industries exert significant spatial spillover effects on economic growth, which arise from their close coupling in innovation-driven development, value chain upgrading, mutual complementarity and synergy, spatial diffusion and spillover, as well as policy guidance and regional competition. First, their collaborative agglomeration enhances regional innovation capacity and industrial competitiveness, directing industrial structures toward higher value-added and more technologically advanced levels. Second, it enables the cross-regional flow and exchange of knowledge, technology, and talent, thereby fostering broader coordinated development and narrowing regional disparities. Empirical evidence indicates that such collaborative agglomeration is substantially more pronounced in the relatively developed central and eastern regions, yet remains comparatively weak in the western region, resulting in a nationwide spatial pattern characterized by the coexistence of “high-high” and “low-low” clusters. Further analysis using the Spatial Durbin Model confirms a significant positive impact of the joint agglomeration of high-tech manufacturing and knowledge-intensive services on regional economic growth, underscoring the vital importance of inter-industry collaboration. Spatial heterogeneity analysis reveals notable discrepancies in industrial agglomeration across regions. Consequently, strengthening the collaborative agglomeration capacity of these two industries is pivotal for establishing a new agglomeration model that aligns with their developmental requirements. Such efforts not only promote knowledge and technology spillovers but also help mitigate resource misallocation caused by congestion, thereby contributing to a reduction in regional development disparities.
References
1. Wei J, Tao Y, Wang L. Research on the Concept and Classification of Knowledge-Intensive Service Industries.China Soft Science. 2007; (1): 33–41.
2. Cao Y, She S. Research on the Conceptual Connotation and Extension of Knowledge-Intensive Service Industries from a Chinese Perspective. Studies in Science of Science. 2008; 1: 103–110.
3. Xiong L, Sun YX, Liu W. Research on the System Model and Operation Mechanism of Collaborative Innovation in Knowledge-Intensive Service Industries (Chinese). Science and Technology Progress and Policy. 2011; 18: 56–59.
4. Zhang X, Du XP, Wang LX. Construction of a Regional Innovation Endogenous System Based on Knowledge-Intensive Service Industries (Chinese).Science and Technology Progress and Policy. 2013; 4: 33–38.
5. Antonietti R, Cainelli G. Spatial agglomeration, technology and outsourcing of knowledge-intensive business services: empirical insights from Italy. International Journal of Services Technology and Management. 2008; 10(2/3/4): 273. doi: 10.1504/ijstm.2008.022123
6. Fang Y, Zhang F, Ruan A, Bi D. Geographical Studies on Knowledge-Intensive Business Services: Progress and Prospects (Chinese). Progress in Geographical Sciences. 2024; 8: 1617–1632.
7. Pereyra C, Antonio J, Lobato JAÁ, Garrocho C. Agglomeration Dynamics of Manufacturing Companies and Knowledge-Intensive Service Companies (KIBS) in the Metropolitan Areas of Toluca and Queretaro. Revista Economía Del Rosario. 2023; 26(2): 1–44. doi: 10.12804/revistas.urosario.edu.co/economia/rer.v26i2
8. Zou DL, Cong HB, Xu M. Comprehensive Measurement of the Spatial Agglomeration of Knowledge-Intensive Service Industries in the Yangtze River Delta (Chinese). In: Proceedings of the Forum on Science and Technology in China; 2015; pp. 54–60.
9. Wan LJ, Yang YL, Yin XG. Research on the Impact of Knowledge-Intensive Service Industry Agglomeration on Economic Growth. Journal of Chongqing University (Social Science Edition). 2016; 2: 32–38.
10. Zhou Y. Spatial Correlation Characteristics and Influencing Factors of the Development of Knowledge-Intensive Business Services in China]. Statistics & Decision. 2024; 16: 156–160.
11. Feng TW, Sun LY, He Z, Xi ZY. Empirical Study on the Relationship between the Scale of China’s High-Tech Manufacturing Industry and R&D Efficiency (Chinese). Studies in Science of Science and Science and Technology Management. 2008; 6: 15–19.
12. Li J, Feng HY. The Economic Growth Effect of the Collaborative Agglomeration of High-Tech Manufacturing and High-Tech Service Industries. Science and Technology Progress and Policy. 2020; 17: 54–62.
13. Dai HS, Bai R, Zheng WJ. Research on the Impact of Business Environment on Enterprise Technological Innovation Efficiency—Taking High-Tech Manufacturing as an Example. Statistical Theory and Practice. 2023; 11: 59–64.
14. Shi YM, Bao XJ. Coupling Entropy Model and Operation Mechanism of High-Tech Service Industry and Equipment Manufacturing Industry. Journal of Changchun University of Technology. 2013; 1: 26–29.
15. Li ZQ, Guo JY. Spatiotemporal Evolution of High-Tech Manufacturing Agglomeration in the Yangtze River Economic Belt. Journal of Hunan Institute of Science and Technology (Natural Science Edition). 2022; 4: 54–60.
16. Shen Q, Pan YX. Explaining and Modeling the Impact of Industrial Co-Agglomeration on Regional Economic Growth in China: Integrated a Quality Concern of Night-Time Light Perspective. Environmental Science and Pollution Research International. 2023; 46: 56786–56811. doi: 10.1007/s11356-023-28709-0
17. Kang P, He F, Liu R. Does High-Tech Industry Agglomeration Promote Its Export Product Upgrading?—Based on the Perspective of Innovation and Openness. Sustainability. 2022; 14(13): 8148. doi: 10.3390/su14138148
18. Cheng P, Ehsan E, Fan BB, Li ZH. 2022. Effect of High-Tech Manufacturing Co-Agglomeration and Producer Service Industry on Regional Innovation Efficiency. Frontiers in Environmental Science. 2022; 10. doi: 10.3389/fenvs.2022.942057
19. Xu D, Yu B. High-Tech Industry Agglomeration and Urban Innovation in the Yangtze River Delta from the Perspective of Spatial Spillover—Mediation Effect of Industrial Structure Optimization and Upgrading and Spatio-Temporal Heterogeneity Analysis. R&D Management. 2023; 2: 15–29.
20. Lü ML, Jin Y. The Impact of Knowledge-Intensive Service Industries on Innovation in China’s Manufacturing Industry—Based on Empirical Analysis of High-Tech Manufacturing (Chinese). Industrial Technology and Economy. 2016; 4: 17–24.
21. Ren H, Zhou SJ, Hu AG. Research on the Collaborative Growth Effect of Knowledge-Intensive Service Industries and High-Tech Manufacturing (Chinese). China Soft Science. 2017; 8: 34–45.
22. Li FZ, Li Q. Innovation-Driven Effect of the Agglomeration of Knowledge-Intensive Service Industries, High-Tech Manufacturing, and Their Collaborative Agglomeration. Science and Technology Progress and Policy. 2019; 17: 57–65.
23. Czarnitzki D, Spielkamp A. Business services in Germany: bridges for innovation. The Service Industries Journal. 2003; 23(2): 1–30. doi: 10.1080/02642060412331300862
24. Moran, P. The interpretation of statistical maps. Journal of the Royal Society of London Series B, 1948;10, :243-251.
25. Barry N. Boots, Arthur Getis.Point Pattern Analysis.SAGE Publications.1988.
26. Wang WC, Sui Y. Spatial Effects of Collaborative Agglomeration of Producer Services and High-Tech Industries on Regional Innovation Efficiency (Chinese). Journal of Management. 2022; 5: 696–704.
27. Shen BZ, Huang LJ. Government Spending Scale, Economic Fluctuations, and Economic Growth—Empirical Analysis Based on Provincial Panel Data (Chinese). Economic Geography. 2012; 1: 18–21.
28. Yu Z, Liu M, Zhao ZQ. Foreign Direct Investment and China’s Economic Growth—An Empirical Study from the Perspective of Financial Development. Academic Exchange. 2009; 3: 132–135.
29. Zhu CL, Shi P, Yue HZ, Han XF. Human Capital, Human Capital Structure, and Regional Economic Growth Efficiency (Chinese). China Soft Science. 2011; (2): 110–119.
30. Liu ZB. From Latecomer to Forerunner: Theoretical Considerations on Implementing an Innovation-Driven Strategy. Industrial Economic Research. 2011; 4: 1–7.
Copyright (c) 2025 Jiayu Ru, Lu Gan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Submit a Paper
