1,100
Views
2
CrossRef citations to date
0
Altmetric
Research Article

Integrating farmers’ perception of sustainable agricultural technologies towards the development of sustainable tea production in China

, , , , &
Article: 2303886 | Received 11 Apr 2023, Accepted 08 Jan 2024, Published online: 30 Jan 2024
 

ABSTRACT

Technologies are essential for reducing environmental impact and increasing agricultural productivity. Previous adoption studies indicate several socioeconomic, technological, and institutional variables influencing the adoption of agricultural technologies. With less than a decade to the United Nation's sustainable development agenda for 2030, there are yet reports on farmers' resistance to sustainable agricultural technologies. Using a survey and multistage sampling procedure in selecting the respondents of 405 smallholder Chinese farmers, the study models farmers' adoption intensity of sustainable agricultural technologies and their impact on productivity. A 5-point Likert scale was used to analyse farmers' SAT perception levels. The PSM was used to eliminate a major proportion of bias when estimating a more precise treatment effect or impact of SAT adoption on productivity. The findings showed that farmers have mixed perceptions (positive and negative) about SAT adoption, which is reflected in their adoption decisions. The study found that family members as extension officers positively impacted farmers' adoption behaviour. On the contrary, regular visits by agricultural extension services had no impact on farmers' adoption behaviour, but positive on productivity. The results clearly showed elements of constraints in farmers' decision-making. The ATT results showed a significant and positive impact of SATs' adoption on productivity.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported financially by the Expert Workstation of Yunnan Province (202105AF150045), the Improvement Project of Efficient Production Technology Capacity in Wen County's Characteristic Industries (22CX8NA034) and the Science and Technology Plan Program of Enshi (XYJ2022000099).