Empowerment and Pathways of Digital Economy in Rural Revitalization: A Case Study of Low Urbanization Areas in China
Abstract
:1. Introduction
2. Literature Review
2.1. Empowerment Mechanisms of the Digital Economy
2.2. Influencing Factors of Rural Revitalization
2.3. Relationship Between the Digital Economy and Rural Revitalization
3. Theoretical Foundations and Model Construction
3.1. Theoretical Foundations
3.1.1. Technical-Economic Paradigm Theory
3.1.2. Innovation Diffusion Theory
3.1.3. Complex Systems Theory
3.2. Model Construction
3.2.1. Deconstruction of the Digital Economy
3.2.2. The Digital Economy’s Empowerment of Rural Revitalization
3.2.3. The Complex Mechanism of the Digital Economy Empowering Rural Revitalization from a Complex Systems Perspective
4. Research Design
4.1. Research Method
- ➀
- Variable calibration. Similar to the traditional fuzzy set qualitative comparative analysis method (fsQCA), it is necessary to calibrate the membership of the cause variable and the result variable to between 0 and 1, so as to clearly represent the different states of each condition variable (such as high and low). Usually, after setting the three anchor points of “full membership”, “intersection”, and “full non membership”, the calibration function in fsQCA3.0 software developed by Ragin is directly used for operation. Since the software will default not to analyze the situation that the membership score is exactly 0.5 in subsequent experiments, it will be adjusted by adding 0.001 to retain the case sample.
- ➁
- Construct a truth table. The truth table is used to show all possible combinations of conditions and their corresponding results. In panel-data QCA, it is usually generated by using the “truthTable” function in R studio after setting the threshold. Threshold includes consistency threshold, PRI threshold, and frequency threshold: Consistency is used to explain the interpretation strength of a certain condition combination on the result, and a generally acceptable consistency should be greater than or equal to 0.8; PRI is used to avoid the situation that the existence of a condition combination will lead to results, and the generally acceptable PRI should be greater than or equal to 0.75; frequency is used to avoid contingency or instability caused by too few cases. It can be set as 1 or 2 in small sample studies, but it should be appropriately increased in large sample studies [54].
- ➂
- Simplify the combination of conditions. Analyze the condition combination and results in the truth table, and use the “minimize” function in R studio to Boolean minimize the condition combination to obtain the complex solution, reduced solution and intermediate solution, and obtain all key indicators of each configuration, i.e., consistency, PRI, coverage, and summary consistency. By analyzing the similarities and differences in the conditions in the intermediate solution and the simple solution, the core conditions are determined, and finally the causal path of the core is extracted.
- ➃
- Calculate group consistency and coverage. Further explore the changes of panel-date configurations in time dimension and individual dimension. The consistency and coverage of cases between and within groups are calculated based on the “cluster” function in R studio, and the robustness of the solution is judged by calculating the consistency adjustment distance between and within groups. It is generally believed that if the adjustment distance is less than 0.2, there is no significant difference between the time dimension and the individual dimension. If it is greater than 0.2, the dynamic changes in the configuration in different dimensions can be further studied.
4.2. Sample Selection
4.3. Variable Measurement
4.3.1. Result Variable
4.3.2. Conditional Variables
4.4. Variable Calibration
5. Results and Analysis
5.1. Necessary Condition Analysis
5.2. Configuration Analysis
5.2.1. High-Level Rural Revitalization Configuration
5.2.2. Non-High-Level Rural Revitalization Configuration
5.3. Robustness Test
6. Further Analysis and Discussion
6.1. Analysis of Digital Economy Empowerment Pathways for Rural Revitalization in Cities with Different Innovation Capabilities
6.1.1. Innovation-Leading Cities’ Digital Economy Empowerment Configuration for Rural Revitalization
6.1.2. Innovation-Lagging Cities’ Digital Economy Empowerment Configuration for Rural Revitalization
6.2. Analysis of Digital Economy Empowerment Pathways for Rural Revitalization in Cities with Different Economic Foundations
6.2.1. Configurations for Rural Revitalization in High-Economic-Foundation Cities
6.2.2. Configurations for Rural Revitalization in Low-Economic-Foundation Cities
7. Conclusions
7.1. Research Conclusions
7.2. Policy Suggestions
7.3. Research Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Dimension | Sub-Indicator | Specific Indicator | Data Source |
---|---|---|---|
Industrial Prosperity | Production Level | Grain production capacity (ten thousand tons) | Local Statistical Yearbook |
Agricultural per capita mechanical power (kilowatts) | Local Statistical Yearbook | ||
Production Efficiency | Labor productivity (CNY/person) | China City Statistical Yearbook Yearbook | |
Industrial Chain Extension | Main business income of large-scale agricultural product processing enterprises (CNY billion) | Local Statistical Yearbook | |
Ecological Livability | Ecological Environment | Greening coverage rate (%) | China City Statistical Yearbook |
Comprehensive utilization rate of livestock and poultry manure (%) | Local Statistical Yearbook | ||
Living Environment | Sanitation toilet popularization rate (%) | Local Statistical Yearbook | |
Village life garbage centralized treatment village proportion (%) | Local Statistical Yearbook | ||
Civilized Customs | Cultural Construction | Number of cultural stations (pieces) | Local Statistical Yearbook |
Cable TV comprehensive coverage rate (%) | Local Statistical Yearbook | ||
Educational Construction | Average years of education for rural residents (year) | Local Statistical Yearbook | |
The proportion of full-time teachers at compulsory education schools with a bachelor’s degree or above (%) | Local Statistical Yearbook | ||
Effective Governance | Governance Capability | The proportion of village party secretaries and directors “one shoulder pick” (%) | Local Statistical Yearbook |
Governance Measures | The proportion of administrative villages with planned village construction (%) | Local Statistical Yearbook | |
The proportion of administrative villages carrying out village rectification (%) | Local Statistical Yearbook | ||
Prosperous Life | Income Level | Per capita disposable income of farmers (CNY/person) | Local Statistical Yearbook |
Urban-rural resident income ratio (%) | China City Statistical Yearbook | ||
Rural resident Engel coefficient (%) | Local Statistical Yearbook | ||
Life Management | Village road hardening rate (%) | Local Statistical Yearbook | |
The number of cars per hundred households (vehicles) | Local Statistical Yearbook | ||
The number of health personnel per thousand rural residents (people) | Local Statistical Yearbook |
Variable Name | Calibration | |||
---|---|---|---|---|
Complete Membership | Crossover Point | Non-Membership | ||
Result variable | Level of Rural Revitalization | 0.326 | 0.275 | 0.059 |
Conditional variable | Digital infrastructure | 22.493 | 18.017 | 6.736 |
Digital industrialization | 31,444.400 | 3911.000 | 997.800 | |
Industrial digitalization | 315.175 | 262.606 | 217.669 | |
Digital governance | 4.355 | 2.022 | 0.666 | |
Data elementization | 169.000 | 33.000 | 3.000 |
Conditional Variable | High-Level Rural Revitalization | Non-High-Level Rural Revitalization | ||||||
---|---|---|---|---|---|---|---|---|
Summary Consistency | Summary Coverage | Between-Group Consistency Adjusted Distance | Within-Group Consistency Adjusted Distance | Summary Consistency | Summary Coverage | Between-Group Consistency Adjusted Distance | Within-Group Consistency Adjusted Distance | |
High Digital infrastructure | 0.901 | 0.899 | 0.099 | 0.056 | 0.458 | 0.443 | 0.013 | 0.574 |
Non-High Digital infrastructure | 0.441 | 0.457 | 0.214 | 0.518 | 0.895 | 0.897 | 0.099 | 0.196 |
High Digital industrialization | 0.603 | 0.726 | 0.199 | 0.448 | 0.537 | 0.627 | 0.226 | 0.518 |
Non-High Digital industrialization | 0.690 | 0.607 | 0.113 | 0.378 | 0.765 | 0.651 | 0.119 | 0.322 |
High Industrial digitalization | 0.643 | 0.676 | 0.481 | 0.308 | 0.602 | 0.612 | 0.583 | 0.350 |
Non-High Industrial digitalization | 0.631 | 0.621 | 0.470 | 0.350 | 0.681 | 0.649 | 0.496 | 0.280 |
High Digital governance | 0.633 | 0.671 | 0.107 | 0.350 | 0.628 | 0.643 | 0.125 | 0.350 |
Non-High Digital governance | 0.663 | 0.648 | 0.084 | 0.336 | 0.679 | 0.641 | 0.099 | 0.322 |
High Data elementization | 0.603 | 0.670 | 0.072 | 0.504 | 0.593 | 0.637 | 0.038 | 0.560 |
Non-High Data elementization | 0.673 | 0.631 | 0.026 | 0.420 | 0.693 | 0.628 | 0.020 | 0.420 |
Causal Combination Scenario | Year | ||||||
---|---|---|---|---|---|---|---|
2018 | 2019 | 2020 | 2021 | 2022 | |||
Scenario 1 | High industrial digitalization and high level of rural revitalization | Between-group Consistency | 0.291 | 0.507 | 0.620 | 0.897 | 0.936 |
Between-group Coverage | 0.942 | 0.831 | 0.759 | 0.634 | 0.557 | ||
Scenario 2 | Non-high industrial digitalization and non-high level of rural revitalization | Between-group Consistency | 0.977 | 0.909 | 0.798 | 0.401 | 0.345 |
Between-group Coverage | 0.520 | 0.675 | 0.671 | 0.772 | 0.859 |
Conditional Variable | High-Level Rural Revitalization | Non-High-Level Rural Revitalization | ||||
---|---|---|---|---|---|---|
1 | 2 | 1a | 1b | 2a | 2b | |
Digital infrastructure | ⚫ | ⚫ | × | × | × | × |
Digital industrialization | ⚫ | × | × | |||
Industrial digitalization | ⚫ | ⚫ | ⚫ | |||
Digital governance | ⚫ | ⚫ | ||||
Data elementization | ⚫ | ⚫ | ||||
Consistency | 0.951 | 0.951 | 0.918 | 0.916 | 0.926 | 0.917 |
PRI | 0.891 | 0.893 | 0.795 | 0.782 | 0.808 | 0.813 |
Coverage | 0.576 | 0.572 | 0.412 | 0.360 | 0.405 | 0.461 |
Unique Coverage | 0.100 | 0.034 | 0.031 | 0.019 | 0.033 | 0.128 |
Between-Group Consistency Adjusted Distance | 0.043 | 0.046 | 0.084 | 0.075 | 0.093 | 0.078 |
Within-Group Consistency Adjusted Distance | 0.042 | 0.042 | 0.168 | 0.168 | 0.168 | 0.182 |
Overall Consistency | 0.934 | 0.907 | ||||
Overall PRI | 0.875 | 0.820 | ||||
Overall Coverage | 0.828 | 0.632 |
Classification | High-Level Rural Revitalization | Non-High-Level Rural Revitalization | |
---|---|---|---|
Conditional Variable | 1 | 2 | 1 |
Digital infrastructure | ⚫ | ⚫ | × |
Digital industrialization | ⚫ | × | |
Industrial digitalization | × | × | ⚫ |
Digital governance | ⚫ | ⚫ | |
Data elementization | ⚫ | ⚫ | |
Consistency | 0.982 | 0.984 | 0.939 |
PRI | 0.939 | 0.940 | 0.761 |
Coverage | 0.361 | 0.321 | 0.253 |
Unique Coverage | 0.115 | 0.075 | 0.253 |
Between-Group Consistency Adjusted Distance | 0.014 | 0.012 | 0.061 |
Within-Group Consistency Adjusted Distance | 0.042 | 0.028 | 0.14 |
Overall Consistency | 0.981 | 0.939 | |
Overall PRI | 0.942 | 0.761 | |
Overall Coverage | 0.436 | 0.253 |
Classification | Innovation-Leading Cities’ Rural Revitalization Configuration | Innovation-Lagging Cities’ Rural Revitalization Configuration | ||||
---|---|---|---|---|---|---|
Conditional Variable | 1 | 2 | 3 | 1 | 2a | 2b |
Digital infrastructure | ⚫ | ⚫ | ⚫ | ⚫ | ⚫ | ⚫ |
Digital industrialization | ⚫ | ⚫ | × | × | ||
Industrial digitalization | × | × | × | × | ||
Digital governance | × | × | ⚫ | |||
Data elementization | × | × | ⚫ | ⚫ | ⚫ | |
Consistency | 0.974 | 0.977 | 0.975 | 0.960 | 0.976 | 0.976 |
PRI | 0.925 | 0.927 | 0.909 | 0.907 | 0.940 | 0.938 |
Coverage | 0.349 | 0.357 | 0.228 | 0.522 | 0.438 | 0.422 |
Unique Coverage | 0.087 | 0.095 | 0.060 | 0.154 | 0.069 | 0.053 |
Between-Group Consistency Adjusted Distance | 0.041 | 0.026 | 0.029 | 0.032 | 0.014 | 0.026 |
Within-Group Consistency Adjusted Distance | 0.090 | 0.080 | 0.070 | 0.050 | 0.040 | 0.040 |
Overall Consistency | 0.973 | 0.953 | ||||
Overall PRI | 0.933 | 0.902 | ||||
Overall Coverage | 0.504 | 0.645 |
Classification | High Economic Foundation Cities’ Rural Revitalization Configuration | Low Economic Foundation Cities’ Rural Revitalization Configuration | |||||
---|---|---|---|---|---|---|---|
Conditional Variable | 1 | 2 | 3 | 4 | 1 | 2 | 3 |
Digital infrastructure | ⚫ | ⚫ | ⚫ | ⚫ | ⚫ | ⚫ | ⚫ |
Digital industrialization | ⚫ | × | × | ||||
Industrial digitalization | × | × | ⚫ | × | |||
Digital governance | × | ⚫ | × | ⚫ | |||
Data elementization | × | ⚫ | ⚫ | ⚫ | |||
Consistency | 0.971 | 0.950 | 0.983 | 0.965 | 0.961 | 0.967 | 0.978 |
PRI | 0.909 | 0.897 | 0.943 | 0.883 | 0.913 | 0.909 | 0.939 |
Coverage | 0.361 | 0.598 | 0.301 | 0.313 | 0.577 | 0.467 | 0.473 |
Unique Coverage | 0.043 | 0.187 | 0.032 | 0.013 | 0.121 | 0.037 | 0.037 |
Between-Group Consistency Adjusted Distance | 0.032 | 0.046 | 0.017 | 0.041 | 0.035 | 0.023 | 0.017 |
Within-Group Consistency Adjusted Distance | 0.070 | 0.070 | 0.050 | 0.060 | 0.050 | 0.050 | 0.040 |
Overall Consistency | 0.947 | 0.955 | |||||
Overall PRI | 0.895 | 0.904 | |||||
Overall Coverage | 0.723 | 0.710 |
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Shen, J.; Zhao, H.; Xiao, F. Empowerment and Pathways of Digital Economy in Rural Revitalization: A Case Study of Low Urbanization Areas in China. Sustainability 2025, 17, 2797. https://doi.org/10.3390/su17072797
Shen J, Zhao H, Xiao F. Empowerment and Pathways of Digital Economy in Rural Revitalization: A Case Study of Low Urbanization Areas in China. Sustainability. 2025; 17(7):2797. https://doi.org/10.3390/su17072797
Chicago/Turabian StyleShen, Junxin, Huizi Zhao, and Fanghao Xiao. 2025. "Empowerment and Pathways of Digital Economy in Rural Revitalization: A Case Study of Low Urbanization Areas in China" Sustainability 17, no. 7: 2797. https://doi.org/10.3390/su17072797
APA StyleShen, J., Zhao, H., & Xiao, F. (2025). Empowerment and Pathways of Digital Economy in Rural Revitalization: A Case Study of Low Urbanization Areas in China. Sustainability, 17(7), 2797. https://doi.org/10.3390/su17072797