ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Land, Livelihoods and Food Security
This article is part of the Research TopicDigital Agricultural Technologies for Improving Food Security OutcomesView all 11 articles
The Relationship between Livelihood Capital and Herdsmen's Usage of Digital Technology: Evidence from Inner Mongolia, China
Provisionally accepted
Mei Yong
Yunhua Wu*- Inner Mongolia Agricultural University, Hohhot, China
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Digital technology has become a driving force for the development of high-quality agriculture. Existing research mainly focuses on the macro-level factors driving the development of digital technology. In contrast, micro-level investigations considering herdsmen's resource endowments when analyzing the relationship with digital technology remain relatively scarce. Based on survey data from 356 herdsmen in Inner Mongolia, China, this study uses the entropy weight method to calculate the livelihood capital of herdsmen and then uses IV-probit and moderating effect models to analyze the relationship between livelihood capital and herdsmen's usage of digital technology. The results show that the livelihood capital positively impacts herdsmen's use of digital technology at the 1% level of significance and this result is robust. Further analysis of the sub-dimensions reveals that natural, physical, human, and social capital significantly promote herdsmen's digital technology use. In contrast, the impact of financial capital is not significant. Furthermore, technical training and network quality enhance livelihood capital's impact on herdsmen's use of digital technology. Heterogeneity analysis shows that the impact of livelihood capital on the use of digital technology is more pronounced among herdsmen who have a large grassland area, more education, and a greater scale of livestock. Based on our findings, policy recommendations are made for promoting the use of digital technology by enhancing herdsmen's livelihood capital.
Keywords: Livelihood capital, Digital technology, Technical training, Network quality, Moderating effect
Received: 09 Aug 2025; Accepted: 19 Nov 2025.
Copyright: © 2025 Yong and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yunhua Wu, nm_wyh@imau.edu.cn
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