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Digital Agriculture and Urbanization: Mechanism and Empirical Research

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  • Jiang, Song
  • Zhou, Jie
  • Qiu, Shuang

Abstract

Based on theoretical mechanism analysis and provincial panel data of China, this paper empirically examines the impact effect and mechanism of digital agriculture on urbanization from both overall and structural dimensions, and then identifies the weaknesses and restrictive reasons for digital agriculture in promoting urbanization development. The theoretical analysis shows that digital agriculture influences urbanization in four ways, namely the total factor productivity enhancement mechanism, the agricultural labor division acceleration mechanism, the marketization process mechanism, and the human capital mechanism. The empirical test suggests that digital agriculture has significantly promoted urbanization across the sample period, and the effect has shown certain stability, sustainability, and durability. According to the contribution decomposition of digital agriculture sub-indexes, the quality of agricultural operational entities contributes the most to urbanization, followed by digital agricultural infrastructure. However, contrary to expectations, digital agriculture industrialization as measured by “Taobao Village” has the least impact on urbanization. Further mechanism tests indicate that digital agriculture promotes urbanization through the agricultural labor division acceleration mechanism, which is consistent with the theoretical expectation, suggesting that it is the driving force for urbanization. However, the performances of digital agriculture in the human capital mechanism, total factor productivity enhancement mechanism, and marketization process mechanism are inconsistent with the theoretical expectations, which are the main reasons for restricting the role of digital agriculture in promoting urbanization.

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  • Jiang, Song & Zhou, Jie & Qiu, Shuang, 2022. "Digital Agriculture and Urbanization: Mechanism and Empirical Research," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    • Handle: RePEc:eee:tefoso:v:180:y:2022:i:c:s0040162522002505
    DOI: 10.1016/j.techfore.2022.121724
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    6. Fu, Guomin & Zhu, Sijia, 2023. "Innovation, financial risk and natural resources for sustainable development: Fresh evidence from BRICS economies," Resources Policy, Elsevier, vol. 80(C).
    7. Ning Xu & Desen Zhao & Wenjie Zhang & Ming Liu & He Zhang, 2022. "Does Digital Transformation Promote Agricultural Carbon Productivity in China?," Land, MDPI, vol. 11(11), pages 1-19, November.
    8. Lee, Chien-Chiang & Yan, Jingyang & Wang, Fuhao, 2024. "Impact of population aging on food security in the context of artificial intelligence: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    9. Yiru Wang & Honggang Lu & Yuge Chen & Peiwen Yang & Xiangbo Cheng & Fangting Xie, 2023. "The Impact of Farmland Management Rights Mortgage Loan on the Agri-Food Industrial Agglomeration: Case of Hubei Province," Land, MDPI, vol. 12(7), pages 1-17, July.

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