Theoretical Basis of Digital Transformation of Manufacturing Industry based on the Perspective of Resource Agglomeration


  • Mengyuan Kong



Manufacturing, Digital Transformation, Resource Pooling, Process Mechanisms


Manufacturing industry, as the foundation of a country and the basis of a strong country, is the pillar industry of China's national economy. With the rise of a new round of industrial revolution, the digital economy era, follow the pulse of the times, and actively promote the digital transformation is to realize the transformation and upgrading of the manufacturing industry is the way to go, but also to achieve China's economic development of high quality is an inevitable choice. At present, the foundation of China's manufacturing industry digital transformation is relatively weak, there is a general problem of "do not want to turn, will not turn, cannot turn". In the face of a turn on the death, not turn the dilemma of death, how to effectively and efficiently promote the integration of digital reality, the successful completion of the digital transformation of the current development of the manufacturing industry is a key issue that needs to be resolved. This paper analyzes the process mechanism of digital transformation of manufacturing industry based on the perspective of resource agglomeration, and analyzes the current situation of digital transformation of manufacturing industry and existing problems, and finally proposes relevant policy measures and research outlook. It aims to provide theoretical guidance and policy recommendations for the digital transformation of manufacturing industry.


Wang H J, Song S S. Research on business model innovation of manufacturing platform-based enterprises under the background of the internet--based on the perspective of enterprise value ecosystem construction[J]. Journal of Management, 2019, 32(1): 43-54.

Sharma R, Jabbour C J C, Lopes de Sousa Jabbour A B. Sustainable manufacturing and industry 4.0: what we know and what we don’t[J]. Journal of Enterprise Information Management, 2020, 34(1): 230-266.

Chen Z X, Chi J Y. Manufacturing upgrading and transformation mode, path and management change[J]. Journal of Sun YAT-SEN University (Social Science Edition), 2016, 62(4): 180-191.

Wang N C, Zhou M F, Guo W Q, et al. How does the digital capability of a focal enterprise affect value co-creation and ecological competitive advantage? --An embedded case study of Geely Group[J]. Nankai Management Review, 2024:1-27.

Liu H, Yang J, Wu Y Y. Does the productive service resource agglomeration model affect the return on manufacturing capital? [J]. Business Economics and Management, 2019(7): 75-87.

Zhang Y M, Wu X M, Gao H B. Study on the growth mechanism of international innovation centers under the perspective of resource “agglomeration” and “radiation” --taking Guangdong, Hong Kong and Macao greater bay area as an example[J]. China Industrial Economy, 2022(11): 97-115.

Li H. Digital economy promotes the transformation of enterprises to high-quality development [J]. Journal of Xi'an University of Finance and Economics, 2020, 33(2): 25-29.

Feng W Y. Path and countermeasures for digital transformation of manufacturing industry under the background of digital economy[J]. Contemporary Economic Research, 2021(4): 105-112.

Grabowska S. Smart factories in the age of Industry 4.0[J]. Management Systems in Production Engineering, 2020, 28(2): 90–96.

Jiao Y. Digital economy empowers manufacturing transformation: From value remodeling to value creation[J]. The Economist, 2020(6): 87-94.

Kong C Y, Ding Z F. The inner mechanism and realization path of digital transformation of manufacturing industry [J]. Economic System Reform, 2021(6): 98-105.

Bresciani S, Huarng K H, Malhotra A, Ferraris A. Digital transformation as a springboard for product, process and business model innovation[J]. Journal of Business Research, 2020, 128: 204–210.

Wang Y X, Jiang J. Research on digital transformation path of manufacturing enterprises in the era of digital economy [J]. National Circulation Economy, 2021(28): 135-137.

Wu C Q, Zhang K X, Chen X R. Research on the digital transformation path of traditional manufacturing enterprises--A three-stage evolution model based on structure and actor perspectives [J]. Journal of Shandong University (Philosophy and Social Sciences Edition), 2022(4): 121-135.

Liu J, Qian Y, Cao Y R, et al. Drivers of intelligent manufacturing in China and its regional differences[J]. China Science and Technology Forum, 2022(1): 84-93.

Mohelska H, Sokolova M. Management approaches for Industry 4.0--The organizational culture perspective[J]. Technological and Economic Development of Economy, 2018, 24(6): 2225–2240.

Chirumalla K. Building digitally-enabled process innovation in the process industries: A dynamic capabilities approach[J]. Technovation, 2021, 105: 102256.

Mittal P. Impact of digital capabilities and technology skills on effectiveness of Government in public services. In: 2020 International conference on data analytics for business and industry: way towards a sustainable economy, ICDABI 2020.

Olsen T L, Tomlin B. Industry 4.0: Opportunities and challenges for operations management[J]. Manufacturing & Service Operations Management, 2020, 22(1): 113-122.

Kuo Y H, Kusiak A. From data to big data in production research: The past and future trends[J]. International Journal of Production Research, 2019, 57: 4828-4853.

Duan Y, Edwards J S, Dwivedi Y K. Artificial intelligence for decision making in the era of big data-evolution, challenges and research agenda[J]. International Journal of Information Management, 2019, 48: 63-71.

Hughes L, Dwivedi Y K, Misra S K, et al. Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda[J]. International Journal of Information Management, 2019, 49: 114-129.







How to Cite

Kong, M. (2024). Theoretical Basis of Digital Transformation of Manufacturing Industry based on the Perspective of Resource Agglomeration. Academic Journal of Management and Social Sciences, 7(3), 147-153.