Does the Digital Divide Affect Farmers' Motivation for Agricultural Practices? Evidence from China
College of Vocational and Technical Education, Inner Mongolia Agricultural University, Inner Mongolia 010000, China
College of Vocational and Technical Education, Inner Mongolia Agricultural University, Inner Mongolia 010000, China
College of Economics and Management, Inner Mongolia Agricultural University, Inner Mongolia 010000, China
College of Vocational and Technical Education, Inner Mongolia Agricultural University, Inner Mongolia 010000, China
DOI: https://doi.org/10.36956/rwae.v6i3.1869
Received: 17 March 2025 | Revised: 13 May 2025 | Accepted: 19 May 2025 | Published Online: 15 July 2025
Copyright © 2025 Yi Ding, Yunhui Ai, Fu Zuo, Xiang Liu. Published by Nan Yang Academy of Sciences Pte. Ltd.
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Abstract
This study examines the impact of the three-tier digital divide (access, usage, outcome) on Chinese farmers' agricultural behavioral initiative using 2022 China Family Panel Studies data. Multivariate regression analyses reveal significant negative effects: access divide (β=−2.39, p<0.05), usage divide (β=−3.23, p<0.01), and outcome divide (β=−2.62, p<0.01), with the usage divide showing the strongest inhibitory effect. Endogeneity-adjusted models confirm robustness (access: β=−11,178.4, p<0.1; usage: β=−18,935.8, p<0.01; outcome: β=−6,451.3, p=0.0736). Mechanism analysis identifies class perception, information collection willingness, and risk preference as mediating factors. Heterogeneity analyses demonstrate: 1) Age effects—usage divide uniquely impacts farmers under 45 (β=13,644.7), while all divides affect older groups (p<0.01); 2) Regional disparities—non-eastern regions exhibit stronger negative effects (β=−7,004.3 to −13,736.6, p<0.01) compared to eastern areas; 3) Gender differences—males are more affected by access and usage gaps (β=−7,270.4 to −11,545.6), whereas females show greater susceptibility to usage and outcome divides (β=−17,023.0 to −5,978.7, p<0.05). These findings contribute to digital divide research by empirically validating the outcome divide's behavioral implications and providing policy insights for digital inclusion strategies in rural agriculture.At the same time, these findings also provide some references for further research on the relationship between the digital divide and farmers’ income, regional agricultural economy in developing countries .
Keywords: Access Divide; Usage Divide; Outcome Divide; Information Acquisition Efficiency
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