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

Jianling Qi (), Chengda Yang, Juan Xu, Tianhang Yang and Lingjing Zhang
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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

Agriculture, 2025, vol. 15, issue 17, 1-20

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.

Keywords: rural digital intelligence; agricultural eco-efficiency; projection pursuit model; TOE framework; dynamic QCA (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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