The coupling and coordination of digital economy and manufacturing transformation and upgrading for industry 5.0 in Hebei Province
Abstract
In the context of the widespread application of digital technologies such as the Internet, big data, artificial intelligence, and cloud computing, digital transformation in the manufacturing sector has become an important engine to promote high-quality economic development in Hebei Province. This paper aims to objectively analyze the current situation of industrial integration between the Beijing-Tianjin-Hebei digital economy and the manufacturing industry and conduct level measurement so as to promote the in-depth integration and development of the digital economy and manufacturing industry in Hebei Province, so that the manufacturing enterprises in Hebei Province can rebuild their competitive advantages in future development, finally realize digital transformation, and promote the high-quality development of the manufacturing industry in Hebei Province. Therefore, it is very important to carry out empirical research on the integrated development of the digital economy and manufacturing industry in Hebei Province. First of all, this paper constructs the index evaluation system of the digital economy and manufacturing industry, respectively, takes the relevant data of the Beijing-Tianjin-Hebei region in the past five years as data samples, uses the entropy weight-TOPSIS method to measure the level of digital economy development and manufacturing industry transformation, and uses the coupling coordination degree model to measure the level of industrial integration of the two. The final results show that: (1) The development level of the digital economy in Hebei Province fluctuates greatly, and there is still a certain gap with Beijing and Tianjin, but the future development potential of the digital economy is huge. (2) The transformation level of manufacturing industry in Hebei Province shows a trend of fluctuation and rise on the whole, and the development trend is good, and the gap between Hebei Province and developed regions is gradually narrowing. (3) The integration of the digital economy and manufacturing industry in Hebei Province has a good development trend, but there is still a certain gap with Beijing and Tianjin, and there are problems of inadequate, unstable, and unbalanced industrial integration. Finally, based on the research conclusions, suggestions are put forward to promote the coordinated development of the Beijing-Tianjin-Hebei region, improve the level of digital economy and manufacturing integration of industrial convergence development, raise the level of digital infrastructure construction, and raise the level of science and technology innovation. This paper reveals the mechanism of the digital economy affecting the high-quality development of the manufacturing industry, studies the whole process of digitalization, information technology, and intelligence integration into the development of the manufacturing industry, and fully releases the positive effect of the digital economy driving the high-quality development of the manufacturing industry, which has important theoretical and practical significance for promoting the high-quality development of the manufacturing industry and formulating relevant industrial policies.
References
1. Yin S, Zhao Y. Digital green value co-creation behavior, digital green network embedding and digital green innovation performance: moderating effects of digital green network fragmentation. Humanities and Social Sciences Communications. 2024; 11(1). doi: 10.1057/s41599-024-02691-5
2. Yin S, Dong T, Li B, et al. Developing a Conceptual Partner Selection Framework: Digital Green Innovation Management of Prefabricated Construction Enterprises for Sustainable Urban Development. Buildings. 2022; 12(6): 721. doi: 10.3390/buildings12060721
3. Dong T, Yin S, Zhang N. The Interaction Mechanism and Dynamic Evolution of Digital Green Innovation in the Integrated Green Building Supply Chain. Systems. 2023; 11(3): 122. doi: 10.3390/systems11030122
4. Zhao T, Zhang Z, Liang SK. Digital economy, Entrepreneurial Activity and high-quality Development: Empirical evidence from Chinese cities (Chinese). Journal of Management World. 2020; 36(10): 65–76. doi: 10.19744/j.cnki.11-1235/f.2020.0154
5. Zhang J. China Digital Economy Development Report (2022) released by China Academy of Information and Com-munication Technology (Chinese). Scitech in China. 2022; 8: 104.
6. Yang P. The value, development focus and policy supply of digital economy (Chinese). Journal of Xi’an Jiaotong University (Social Sciences). 2020; 2: 57–65+144. doi: 10.15896/j.xjtuskxb.202002007
7. Yin S, Li B. A stochastic differential game of low carbon technology sharing in collaborative innovation system of superior enterprises and inferior enterprises under uncertain environment. Open Mathematics. 2018; 16(1): 607-622. doi: 10.1515/math-2018-0056
8. Cao Z. Research on a new manufacturing model to promote the high-quality development of China’s industry under the background of digital economy (Chinese). Theoretical Investigation. 2018; 2: 99–104. doi: 10.16354/j.cnki.23-1013/d.2018.02.016
9. Yin S, Li B, Zhang X, et al. How to Improve the Quality and Speed of Green New Product Development? Processes. 2019; 7(7): 443. doi: 10.3390/pr7070443
10. Zhou J. Intelligent Manufacturing-the main direction of “Made in China 2025” (Chinese). China Mechanical Engineering. 2015; 26(17): 2273-2284.
11. Li L. The Ministry of Industry and Information Technology issued the Implementation Opinions on Promoting the Quality Improvement of Manufacturing Products and Services (Chinese). Plant Maintenance Engineering. 2019; 19: 4.
12. Conti E, Camillo F, Pencarelli T. The impact of digitalization on marketing activities in manufacturing companies. The TQM Journal. 2023; 35(9): 59-82. doi: 10.1108/tqm-11-2022-0329
13. Zhang L. Digital new business forms boost the transformation and upgrading of traditional industries (Chinese). China’s Foreign Trade. 2021; 4: 24-26.
14. Song H, Wang X, Li Y. Research on the pull and contribution of digital economy development to Hebei economy (Chinese). Statistics and Management. 2021; 36(2): 4–10. doi: 10.16722/j.issn.1674-537x.2021.02.001
15. Colombari R, Geuna A, Helper S, et al. The interplay between data-driven decision-making and digitalization: A firm-level survey of the Italian and U.S. automotive industries. International Journal of Production Economics. 2023; 255: 108718. doi: 10.1016/j.ijpe.2022.108718
16. Yin S, Yuan Y, Han B . Evaluation of the development of digital green innovation in manufacturing industry under the “double carbon” goal: A case study of Beijing-Tianjin-Hebei Province (Chinese). Science and Technology Management Research. 2023; 43(6): 94–104.
17. Li C, Li D, Zhou C. The role of digital economy in driving the transformation and upgrading of manufacturing industry: An analysis from the perspective of industrial chain. Business Research. 2020; 2: 73–82. doi: 10.13902/j.cnki.syyj.2020.02.008
18. Burmaoglu S, Ozdemir Gungor D, Kirbac A, et al. Future research avenues at the nexus of circular economy and digitalization. International Journal of Productivity and Performance Management. 2022; 72(8): 2247–2269. doi: 10.1108/ijppm-01-2021-0026
19. Wang M, Yin S, Lian S. Collaborative elicitation process for sustainable manufacturing: A novel evolution model of green technology innovation path selection of manufacturing enterprises under environmental regulation. PLOS ONE. 2022; 17(6): e0266169. doi: 10.1371/journal.pone.0266169
20. Yin S, Liu L, Mahmood T. New Trends in Sustainable Development for Industry 5.0: Digital Green Innovation Economy. Green and Low-Carbon Economy. 2023. doi: 10.47852/bonviewglce32021584
21. Matt DT, Pedrini G, Bonfanti A, et al. Industrial digitalization. A systematic literature review and research agenda. European Management Journal. 2023; 41(1): 47–78. doi: 10.1016/j.emj.2022.01.001
22. Matthess M, Kunkel S, Dachrodt MF, et al. The impact of digitalization on energy intensity in manufacturing sectors – A panel data analysis for Europe. Journal of Cleaner Production. 2023; 397: 136598. doi: 10.1016/j.jclepro.2023.136598
23. Li C. Preliminary discussion on the connotation of digital economy (Chinese). E-government. 2017; 9: 84–92.
24. Bukht R, Heeks R. Defining, Conceptualising and Measuring the Digital Economy. SSRN Electronic Journal. 2017. doi: 10.2139/ssrn.3431732
25. Chen X, Li Y, Song L, Wang Y. Theoretical system and research prospect of digital economy. Journal of Management World. 2022; 2: 208–224–13–16. doi: 10.19744/j.cnki.11-1235/f.2022.0020
26. Volkova N, Kuzmuk I, Oliinyk N, et al. Development trends of the digital economy: E-business, E-commerce. 2021. Available online: http://paper.ijcsns.org/07_book/202104/20210423.pdf (accessed on 2 February 2024).
27. Batrancea L. The Influence of Liquidity and Solvency on Performance within the Healthcare Industry: Evidence from Publicly Listed Companies. Mathematics. 2021; 9(18): 2231. doi: 10.3390/math9182231
28. Wang SP, Teng TW, Xia QF, Bao H. Spatial and temporal characteristics of the development level of China’s digital economy and its innovation driving mechanism. Economic Geography.2022; 7: 33–43. doi: 10.15957/j.cnki.jjdl.2022.07.004
29. Batrancea L, Rathnaswamy MK, Batrancea I. A Panel Data Analysis on Determinants of Economic Growth in Seven Non-BCBS Countries. Journal of the Knowledge Economy. 2021; 13(2): 1651-1665. doi: 10.1007/s13132-021-00785-y
30. Zhang X, Chen F. Research on the development quality of China’s digital economy and its influencing factors (Chinese). Productivity Research. 2018; 6: 67–71. doi: 10.19374/j.cnki.14-1145/f.2018.06.015
31. Li Z, Liu Y. Research on the Spatial Distribution Pattern and Influencing Factors of Digital Economy Development in China. IEEE Access. 2021; 9: 63094-63106. doi: 10.1109/access.2021.3075249
32. Batrancea LM, Tulai H. Thriving or Surviving in the Energy Industry: Lessons on Energy Production from the European Economies. Energies. 2022; 15(22): 8532. doi: 10.3390/en15228532
33. Batrancea LM. Determinants of Economic Growth across the European Union: A Panel Data Analysis on Small and Medium Enterprises. Sustainability. 2022; 14(8): 4797. doi: 10.3390/su14084797
34. Lv Y, Fan T. Research on the spatial-temporal differentiation and Influencing factors of China’s digital economy development (Chinese). Journal of Chongqing University (Social Sciences Edition). 2023; 29(3): 47-60.
35. Batrancea LM, Rathnaswamy MM, Rus MI, et al. Determinants of Economic Growth for the Last Half of Century: A Panel Data Analysis on 50 Countries. Journal of the Knowledge Economy. 2022; 14(3): 2578-2602. doi: 10.1007/s13132-022-00944-9
36. Li QH. Dynamic mechanism and realization path of high-quality development of manufacturing enterprises in the new era (Chinese). Finance & Economics. 2019; 6: 57–69.
37. Tian Q, Zhang S, Yu H, et al. Exploring the Factors Influencing Business Model Innovation Using Grounded Theory: The Case of a Chinese High-End Equipment Manufacturer. Sustainability. 2019; 11(5): 1455. doi: 10.3390/su11051455
38. Wang F, Shi X. Research on the measurement and influencing factors of the high-quality development level of China’s manufacturing industry. Chinese Soft Science. 2022; 2: 22–31.
39. Wang L, Liu R. Research on the influencing factors of manufacturing industry development under the back–ground of high-quality development (Chinese). Economic Forum. 2021; 10: 34–41.
40. Khin S, Kee DMH. Factors influencing Industry 4.0 adoption. Journal of Manufacturing Technology Management. 2022; 33(3): 448–467. doi: 10.1108/jmtm-03-2021-0111
41. Liere-Netheler K, Packmohr S, Vogelsang K. Drivers of Digital Transformation in Manufacturing. Proceedings of the Annual Hawaii International Conference on System Sciences. 2018. doi: 10.24251/hicss.2018.493
42. Liu F. How Digital Transformation Improves Manufacturing productivity: A triple impact mechanism based on digital transformation (Chinese). Finance & Economics. 2020; 10: 93–107.
43. Wang D, Wu Z. The mechanism and countermeasures of digital economy Promoting the transformation and upgrading of China’s manufacturing industry (Chinese). Changbai Journal. 2020; 6: 92–99. doi: 10.19649/j.cnki.cn22-1009/d.2020.06.013
44. Liu P, Yu X. Digital transformation of manufacturing industry in China: Trends, status and future Policies (Chinese). Journal of the Party School of CPC Hangzhou. 2023; 1: 4–11+2. doi: 10.16072/j.cnki.1243d.2023.01.010
45. Lv X, Wang Y, Liu L, et al. Digital green innovation economy for Industry 5.0. Sustainable Economies. 2024; 2(1): 8. doi: 10.62617/se.v2i1.8
46. Wang R, Chen X. The dynamic mechanism and empirical test of digital economy Boosting the high-quality development of manufacturing industry: An investigation from Zhejiang Province (Chinese). Systems Engineering. 2022; 40(1): 1–13.
47. Batrancea LM, Balcı MA, Akgüller Ö, et al. What Drives Economic Growth across European Countries? A Multimodal Approach. Mathematics. 2022; 10(19): 3660. doi: 10.3390/math10193660
48. Batrancea LM, Balcı MA, Chermezan L, et al. Sources of SMEs Financing and Their Impact on Economic Growth across the European Union: Insights from a Panel Data Study Spanning Sixteen Years. Sustainability. 2022; 14(22): 15318. doi: 10.3390/su142215318
49. Zhou Z. Research on the Path of Digital Economy Empowering the high-quality development of China’s manufacturing industry—Taking the Yangtze River Delta Region as an example (Chinese). China Journal of Commerce. 2023; 16: 63–66. doi: 10.19699/j.cnki.issn2096-0298.2023.16.063
50. Li Y, Han P. Mechanism and path of high-quality development of manufacturing industry in digital economy (Chinese). Macroeconomic Management. 2021; 5: 36–45.
51. Xue W, Zhu B. Analysis and Research on industrial convergence and its effects in the context of digital economy (Chinese). Trade Fair Economy. 2023; 10: 78– 80. doi: 10.19995/j.cnki.CN10-1617/F7.2023.10.078
52. Yin S. Digital economy drives green innovation development of manufacturing industry in Hebei Province: Bot–tlenecks, paths and strategies (Chinese). Technology and Industry Across the Straits. 2023; 36(1): 52– 55.
53. Yin S, Wang Y, Xu J. Developing a Conceptual Partner Matching Framework for Digital Green Innovation of Agricultural High-End Equipment Manufacturing System Toward Agriculture 5.0: A Novel Niche Field Model Combined With Fuzzy VIKOR. Frontiers in Psychology. 2022; 13. doi: 10.3389/fpsyg.2022.924109
54. Dong T, Yin S, Zhang N. New Energy-Driven Construction Industry: Digital Green Innovation Investment Project Selection of Photovoltaic Building Materials Enterprises Using an Integrated Fuzzy Decision Approach. Systems. 2022; 11(1): 11. doi: 10.3390/systems11010011
55. Yin S, Zhang N, Ullah K, et al. Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing. Systems. 2022; 10(3): 72. doi: 10.3390/systems10030072
56. Hou X, Naseem A, Ullah K, et al. Identification and classification of digital green innovation based on interaction Maclaurin symmetric mean operators by using T-spherical fuzzy information. Frontiers in Environmental Science. 2023; 11. doi: 10.3389/fenvs.2023.1164703
57. Wang M, Zhu X, Yin S. Spatial–temporal coupling coordination and interaction between digitalization and traditional industrial upgrading: a case study of the Yellow River Basin. Scientific Reports. 2023; 13(1). doi: 10.1038/s41598-023-44995-7
58. Yang J. Infrastructure level measurement and coupling coordination evaluation of urban agglomeration in the Yangtze River Delta. Journal of Baicheng Normal University. 2022; 2: 47–56.
Copyright (c) 2024 Jianfang Li, Jiachen Wang, Tongtong Sun, Shi Yin
This work is licensed under a Creative Commons Attribution 4.0 International License.
Submit a Paper
