Study and Countermeasures of Industrial Risks in Rural Revitalization Under the Ocean Model

Yun JI, Yongping XIE, Jian CHAI

Journal of Systems Science and Information ›› 2025, Vol. 13 ›› Issue (3) : 399-421.

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中国科学院数学与系统科学研究院期刊网
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Journal of Systems Science and Information ›› 2025, Vol. 13 ›› Issue (3) : 399-421. DOI: 10.12012/JSSI-2024-0035

Study and Countermeasures of Industrial Risks in Rural Revitalization Under the Ocean Model

  • Yun JI1(Email), Yongping XIE1(Email), Jian CHAI1(Email)
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Abstract

Developing rural revitalization industries is crucial for consolidating and expanding the achievements of poverty alleviation and establishing a solid material foundation for comprehensive rural revitalization. The "New Community Factory" in the Qinba Mountain area of Shaanxi Province, as a typical model for industrial revitalization, contributes to the high-quality development of rural areas. This article is based on the ocean model theory and conducts a comprehensive assessment and prevention of industrial risks in the "New Community Factory" model. The results indicate that the industrial risks faced by the "New Community Factory" throughout its development process fall into the category of "medium risk". Among them, the policy risk and environmental risk were highest during the period from 2014 to 2016, the economic risk was highest during the period from 2017 to 2019, and the scale risk and development risk were highest during the period from 2020 to 2022. To address prominent risks such as environmental risk and economic risk, it is urgent for the government to implement special financial policies, strengthen talent cultivation and guidance, support independent brand innovation, and improve the internal and external environment to promote the gathering and development of rural revitalization industries. This article not only enriches and expands the research scope of the ocean model but also has theoretical and practical significance for improving the risk assessment system of rural revitalization industries.

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ocean model / rural revitalization / industrial risk / risk assessment

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Yun JI, Yongping XIE, Jian CHAI. Study and Countermeasures of Industrial Risks in Rural Revitalization Under the Ocean Model. Journal of Systems Science and Information, 2025, 13(3): 399-421 https://doi.org/10.12012/JSSI-2024-0035

References

1
Yang Z L, Qi M, Huang L C, et al. Risk assessment and early warning method for emerging industries from the perspective of "distance" and "speed" — A case study in spacecraft manufacturing industry. Management Review, 2021, 33(7): 43-53.
2
Li S C, Wu J, Xu Z H, et al. Unascertained measure model of water and mud inrush risk evaluation in karst tunnels and its engineering application. KSCE Journal of Civil Engineering, 2017, 21(4): 1170-1182.
3
Fu Y, Zhang J Z, Zhou C. A mean-variance model based study of the optimal investment strategy and risk measure of P2P deb. Management Review, 2017, 29(7): 19-28.
4
Wang K P, Guo X F, Che Y. Research on risk identification and competitive intelligence early warning of strategic emerging industries based on big data thinking. Information Studies: Theory & Application, 2021, 44(5): 92-99.
5
Tian J, Zeng S P. Research on planning method of urban fringe based on social ecosystem balance: A case study of rizhao city. Modern Urban Research, 2018(12): 111-118.
6
Wang L, Liu X, Jia Y J. A study on the dynamic market risk measurement of ETF based on the jump diffusion process. Management Review, 2017, 29(3): 12-26.
7
Zhang Y, Zhou Y H. The Impact of digital finance development on the operational risks of rural financial institutions: A study based on the moderating effect of financial supervision intensity. Chinese Rural Economy, 2022(4): 64-82.
8
Zhang Y L, Ren S C, Li Q Y, et al. Research on the formation mechanism of moral hazard in targeted poverty alleviation and its avoidance in rural revitalization. Management Review, 2024, 36(3): 237-245.
9
Suo L S, Yao J M, Zhou J H. Optimization of rural terminal logistics resources integration under service integrator mode by introducing integration risk. Operations Research and Management Science, 2021, 30(2): 61-67.
10
Zhuang T Y, Li G J, Luo J C. Is there a neighborhood effect in rural households' decision-making on digital finance use? Chinese Rural Economy, 2024(8): 125-144.
11
Boehlje D, Lins A. Risks and risk management in an industrialized agriculture. Agricultural Finance Review, 1998(58): 1-16.
12
Zhao P, Long Z M, Wang C. Risk factors, types and policy implications of large-scale poverty returning: Research based on the survey in southwest minority areas. Journal of Management World, 2022, 38(11): 146-158.
13
Williams J R, Llewelyn R V, Barnaby G A. Risk analysis of tillage alternatives with government programs. American Journal of Agricultural Economics, 1990, 72(1): 172-181.
14
Zuo Z Y, Li Z. Risk preference, policy intervention and adoption of site-specific nutrient management technology: Based on investigation of agricultural non-point source pollution control project funded by loans from world bank. Journal of Agro-Forestry Economics and Management, 2022, 21(1): 10-19.
15
Hou J. The right thesis of environmental governance in contemporary China. Chinese Journal of Environmental Management, 2021, 13(1): 162-169.
16
Guo J, Zhang X R, Kong X Z. The convergence of primary, secondary and tertiary industries and farmers'income generation: One case study of convergence of primary, secondary and tertiary industries in rural areas of henan province. Issues in Agricultural Economy, 2019(3): 135-144.
17
Zhang A M, Cheng X E, Wu W H, et al. Risks and responses to OFDI in China's forestry industry. Macroeconomic Management, 2022(4): 83-90.
18
Jiang H C, Zhang J. Discovering systemic risks of China's listed banks by CoVaR approach in the digital economy era. Mathematics, 2020, 8(2): 180.
19
Li C X, Li Y P. Bottleneck of rural property rights financing and its path choice in the context of agricultural supply-side structural reform. Agricultural Economy, 2020(11): 103-105.
20
Yang X, Hu A J. Empirical study on the development level of county circular economy based on advantageous characteristic industries--taking hanzhong city of shaanxi province as an example. Agricultural Economy, 2018(6): 68-72.
21
Barlett P F. Motivations of part-time farmers. Multiple Job-Holding Among Farm Families, 1991: 45S70.
22
Du Y. Risk diversification and non-farm labor supply — Empirical evidence from rural poor areas. Journal of Quantitative & Technological Economics, 2001(1): 46-50.
23
Li M. J. Ethical response to the development risk of artificial intelligence from the perspective of theoretical level. Exploration and Free Views, 2021(8): 167-176.
24
Wang S Y. A new methodology for studying complex systems. The International Workshop on Complexity Science, 2004.
25
Chin T, Wang S, Rowley C. Polychronic knowledge creation in cross-border business models: A sea-like heuristic metaphor. Journal of Knowledge Management, 2021, 25(1): 1-22.
26
Tan D J, Shi Y, Qian Z. A digital-driven OCEAN model of polychronic knowledge creation: Concept, connotation and theory validation. Management Review, 2022, 34(2): 126-141.
27
Nonaka I, Toyama R. The knowledge-creating theory revisited: Knowledge creation as a synthesizing process. Knowledge Management Research & Practice, 2003, 1(1): 2-10.
28
Osterwalder A, Pigneur Y. Business model generation: A handbook for visionaries, game changers and challenges. Hoboken, NJ: John Wiley and Son, 2010.
29
Xu F Z, Xi W, Xu Y H. Governance mechanisms and their roles in facilitating Chinese rural areas' common prosperity: A case study of two villages. Journal of Management World, 2021, 37(12): 134-151.
30
Yin R K. Case study research: Design and methods. SAGE, 2003.
31
Charmaz K C. Constructing grounded theory: A practical guide through qualitative analysis. London: Sage Publications, 2006.
32
Mao B H, et al. A method of combination weighting for multiple attribute decision making based on interval estimation. Systems Engineering — Theory & Practice, 2007, 27(6): 86-92.
33
Zhang X M, Liu J, Yi P T, et al. New method of weighting based on timing gain excitation and application. Operations Research and Management Science, 2024, 33(3): 89-95.
34
Hu J, Bao F. Airport operational efficiency evaluation based on combined weighting-TOPSIS model. Journal of System Simulation, 2023, 35(12): 2570-2581.
35
Sun H M, Xie Q H, Wu B. Research on AI industry risk in China-U.S. and European and Countermeasures for China. Science and Technology Management Research, 2021, 41(17): 170-178.
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