Author
Listed:
- Qianwen Yang
(Zhejiang Institute of Administration, Hangzhou 310012, China
These authors contributed equally to this work.)
- Sirui Liu
(Zhejiang Institute of Administration, Hangzhou 310012, China
These authors contributed equally to this work.)
- Yubin Qin
(Zhejiang Institute of Administration, Hangzhou 310012, China)
- Lei Luo
(College of Water Resources and Hydropower, Sichuan Agricultural University, Yaan 625000, China)
Abstract
Environmental pollution and waste caused by traditional citrus farming has become more serious. As the direct subject of agricultural production, we should pay more attention to the green production behavior of farmers. Numerous studies have fully proven that technology training is the important driving factor of farmers’ production behavior, but the question of which main body or organization should carry out the training is the question that still has no definite conclusion, in order to solve this problem. Based on the perspective of the heterogeneity of agricultural technology training organizations, this study conducts a discussion on the indicators of the difference in training organization and technology adoption behavior, and uses the Oprobit and IV-Oprobit models to conduct an empirical analysis on 782 Chinese farmers’ survey data. Finally, we find: (1) Technical training has a positive impact on farmers’ GPT adoption at the 1% level. For each additional training, the probability of adopting five GPT increased by 2.6%; (2) Different training organizations have different impacts on the farmers’ technology adoption. The training of profit-oriented organizations represented by agricultural enterprises has the most obvious promotion effect on GPT adoption by farmers. The overall effect of the training of government agricultural extension departments is better than that of quasi-public welfare organizations such as scientific research institutions; (3) The above effects also have obvious heterogeneity among farmers of different ages, education levels, family social networks, planting scale, family incomes and structure. Based on this, we put forward policy suggestions such as building a diversified agricultural extension training system.
Suggested Citation
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8421-:d:1753418. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.