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Multiple Pathways of Rural Digital Intelligence Driving Agricultural Eco-Efficiency: A Dynamic QCA Analysis

Author

Listed:
  • Jianling Qi

    (School of Economics and Management, Yunnan Agricultural University, Kunming 650201, China)

  • Chengda Yang

    (School of Economics and Management, Yunnan Agricultural University, Kunming 650201, China)

  • Juan Xu

    (School of Economics, Guizhou University, Guiyang 550025, China)

  • Tianhang Yang

    (School of Economics and Management, Yunnan Agricultural University, Kunming 650201, China)

  • Lingjing Zhang

    (School of Economics and Management, Yunnan Agricultural University, Kunming 650201, China)

Abstract

The shift toward sustainable and efficient agricultural production has become a global imperative. Rural digital intelligence, which integrates advanced technologies into agricultural practices, emerges as a pivotal driver for advancing green transformation. Based on the technology–organization–environment (TOE) framework, this study explores how rural digital intelligence drives agricultural eco-efficiency. Drawing on panel data from 30 Chinese provinces (2013–2023), this study applies dynamic qualitative comparative analysis (QCA) to unravel the complex causal pathways influencing agricultural eco-efficiency. Key findings demonstrate that (1) no single element of rural digital intelligence suffices to improve agricultural eco-efficiency; the combination of various factors can affect agricultural eco-efficiency. (2) Four distinct pathways achieve high agricultural eco-efficiency, categorized into three archetypes: application-driven pathway, synergy-robust pathway, and policy-driven pathway. (3) Temporal analysis indicates time-dependent effects in these pathways, influenced by fragmented policy implementation and technological constraints. (4) Spatial heterogeneity is pronounced; western China primarily follows the application-driven pathway, while eastern China and central China align with the synergy-robust pathway. This research explores configurational pathways through which rural digital intelligence enhances agricultural eco-efficiency, offering theoretical and empirical foundations for regionally tailored sustainable agricultural policies.

Suggested Citation

  • Jianling Qi & Chengda Yang & Juan Xu & Tianhang Yang & Lingjing Zhang, 2025. "Multiple Pathways of Rural Digital Intelligence Driving Agricultural Eco-Efficiency: A Dynamic QCA Analysis," Agriculture, MDPI, vol. 15(17), pages 1-20, August.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:17:p:1838-:d:1737124
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    References listed on IDEAS

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