ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1597571
The Impact of Migrant Work Experience on the Adoption Behavior of Green Production Technologies Among New Professional Farmers: Evidence from Jiangxi and Guangdong Provinces, China
Provisionally accepted
- Xinyang Normal University, Xinyang, China
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Based on the analytical framework of imprinting theory, this study employs survey data from 1,707 new professional farmers in Guangdong and Jiangxi provinces (2019-2021) and econometric methods to empirically examine the impact and mechanisms of migrant work experience on their adoption of green production technologies. The findings reveal three key insights: First, migrant work experience significantly increases the probability of adopting green production technologies. Robustness checks through replacing core explanatory variables and propensity score matching (PSM) confirm the stability of this conclusion, underscoring the critical role of migrant work experience in technological adoption.Second, mechanism analysis demonstrates that migrant work experience enhances farmers' adoption behavior by elevating their technical cognition levels. Such experience not only exposes farmers to advanced external production practices and concepts but also strengthens their cognitive understanding and receptivity to new technologies, thereby positively facilitating green technology adoption. Third, heterogeneity analysis reveals differentiated effects: Migrant work experience exhibits stronger promotion effects on the adoption of water-saving technologies compared to energy-saving and environmental protection technologies, a disparity linked to variations in application costs, technical barriers, and learning curves across technology types. Age-specific differences emerge, with migrant work experience exerting a greater influence on middle-aged farmers than on younger counterparts.
Keywords: migrant work experience, green production technology, New professional farmers, Probit model, Propensity Score Matching (PSM) method
Received: 21 Mar 2025; Accepted: 15 May 2025.
Copyright: © 2025 Lei, Zhao, Zhang and Chen. 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: Xiankai Lei, Xinyang Normal University, Xinyang, China
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