MEASUREMENT OF DIGITAL RURAL DEVELOPMENT LEVEL AND ITS INFLUENCING FACTORS IN THE YANGTZE RIVER DELTA REGION
Keywords:
Data-driven, Digital rural construction, Entropy-weighted TOPSIS method, Obstacle degree modelAbstract
This paper proposes a data-driven method for measuring the level of regional digital rural development. Based on data collection and application across dimensions such as digital infrastructure, digitalization of rural economy, digital governance, and digital rural life, an evaluation index system for digital rural development is constructed. The entropy weight TOPSIS model is applied to measure and evaluate the overall level of digital rural development and its four subsystems, providing targeted policy recommendations. The obstacle degree model is employed to identify key factors constraining the improvement of digital rural development. Taking the Yangtze River Delta region from 2014 to 2023 as a case study, the paper demonstrates the implementation process of the data-driven approach. The research results validate the feasibility of the proposed methodology, offering theoretical and methodological support for digital rural development studies and management, and providing decision-making foundations for enhancing regional digital rural development, promoting high-quality rural development, and achieving common prosperity.References
[1] Cao X, Yan M, Wen J. Exploring the level and influencing factors of digital village development in China: insights and recommendations. Sustainability, 2023, 15(13): 10423. DOI: 10.3390/su151310423.
[2] Zhao Y, Li R. Coupling and Coordination Analysis of Digital Rural Construction from the Perspective of Rural Revitalization: A Case Study from Zhejiang Province of China. Sustainability, 2022, 14: 3638. DOI: 10.3390/su14063638.
[3] Liu H, Zhang Y, Wang S, et al. Comprehensive evaluation of digital village development in the context of rural revitalization: A case study from Jiangxi Province of China. PLOS ONE, 2024, 19(5): e0303847. DOI: 10.1371/journal.pone.0303847.
[4] Xiong C, Wang Y, Wu Z, et al. What drives the development of digital rural life in China? Heliyon, 2024, 10: e39511. DOI: 10.1016/j.heliyon.2024.e39511.
[5] Xing Z, Zhao S, Wang D. Performance and sustainability evaluation of rural digitalization and its driving mechanism: evidence from Hunan province of China. Frontiers in Environmental Science, 2023, 11: 1326592. DOI: 10.3389/fenvs.2023.1326592.
[6] Chen W, Chen H, Yin J, et al. Evaluation of agricultural products e-commerce logistics service capabilities in Heilongjiang Province based on entropy weight TOPSIS method. PLOS ONE, 2025, 20(6): 0325532. DOI: 10.1371/journal.pone.0325532.
[7] Zhu M, Li Y J, Khalid Z, et al. Comprehensive Evaluation and Promotion Strategy of Agricultural Digitalization Level. Sustainability, 2023, 15: 6528. DOI: 10.3390/su15086528.
[8] Sun Y, Zhao Z, Li M. Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China. PLOS ONE, 2022, 17(9): 0273110. DOI: 10.1371/journal.pone.0273110.
[9] Li Y, Chen Y. The spatiotemporal characteristics and obstacle factors of the coupled and coordinated development of agricultural and rural digitalization and food system sustainability in China. Frontiers in Sustainable Food Systems, 2024, 8: 1357752. DOI: 10.3389/fsufs.2024.1357752.
[10] Chang J, Yu J, Liu J, et al. Digital Village Construction and High-Quality Development of Grain Production Under the Background of Population Shrinkage: Evidence from China’s Major Grain-Producing Areas. Agriculture, 2026, 16(4): 470. DOI: 10.3390/agriculture16040470.
[11] Liu S, Zhu S, Hou Z, et al. Digital village construction, human capital and the development of the rural older adult care service industry. Frontiers in Public Health, 2023, 11: 1190757. DOI: 10.3389/fpubh.2023.1190757.
[12] Li W, Guo J, Tang Y, et al. The impact of digital rural construction on agricultural carbon emission intensity. Frontiers in Environmental Science, 2024, 12: 1492454. DOI: 10.3389/fenvs.2024.1492454.
[13] Fan Z, Guo F, Bian C. Digital rural construction, resource mismatch, and rural land use efficiency. Frontiers in Environmental Science, 2025, 13: 1546082. DOI: 10.3389/fenvs.2025.1546082.
[14] Zhao X, Lan F, Zhang L, et al. The impact of digital village construction on poverty vulnerability among rural households. Scientific Reports, 2025, 15(1): 9967. DOI: 10.1038/s41598-025-91928-7.
[15] Bai X, Qiao S, Jiang Y, et al. Digital Rural Construction and Carbon Emission Intensity of Animal Husbandry: Evidence from China. Polish Journal of Environmental Studies, 2025, 34(5): 6079–6090. DOI: 10.15244/pjoes/192369.
[16] Liu M, Liu H. The Influence and Mechanism of Digital Village Construction on the Urban–Rural Income Gap under the Goal of Common Prosperity. Agriculture, 2024, 14(5): 775. DOI: 10.3390/agriculture14050775.
[17] Wang Y, Huang L, Ren Y, et al. Can Digital Rural Construction Improve Household Food Security? Evidence From Rural China. Food and Energy Security, 2026, 15(1): e70205. DOI: 10.1002/fes3.70205.
[18] Chen W, Wang Q, Zhou H. Digital rural construction and farmers’ income growth: Theoretical mechanism and micro experience based on data from China. Sustainability, 2022, 14(18): 11679. DOI: 10.3390/su141811679.
[19] Wang Q, Ning Z, Tan M. A study on the impact of digital infrastructure development on the health of low-income rural residents: based on panel data from 2010 to 2022. Frontiers in Public Health, 2025, 13: 1503522. DOI: 10.3389/fpubh.2025.1503522.