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Farmers’ precision pesticide technology adoption and its influencing factors: Evidence from apple production areas in China

Lookup NU author(s): Professor Lynn FrewerORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


The research aimed to understand farmers’ willingness to adopt (WTA) and willingness to pay (WTP) for precision pesticide technologies and analyzed the determinants of farmers’ decision-making. We used a two-stage approach to consider farmers' and, subsequently, their WTP. A survey of 545 apple farmers was administered in Bohai Bay and the Loess Plateau in China. The data were analyzed using the double-hurdle model. The results indicated that 78.72% of respondents were willing to apply precision pesticide technologies provided by service organizations such as cooperatives and dedicated enterprises, and 69.72% were willing to buy the equipment for using precision pesticide technologies. The results of the determinant analysis indicated that farmers’ perceived perceptions, farm scale, cooperative membership, access to digital information, and availability of financial services had significant and positive impacts on farmers’ WTA precision pesticide technologies. Cooperative membership, technical training, and adherence to environmental regulations increased farmers’ WTP for precision pesticide technologies. Moreover, we found nonlinear relationships between age, agricultural experience, and farmers’ WTA and WTP for precision pesticide technology services.

Publication metadata

Author(s): Yue M, Li W, Shan J, Chen J, Chang Q, Jones G, Cao Y, Yang G, Li Z, Frewer LJ

Publication type: Article

Publication status: Published

Journal: Journal of Integrative Agriculture

Year: 2022

Issue: ePub ahead of Print

Online publication date: 10/11/2022

Acceptance date: 27/10/2022

Date deposited: 27/10/2022

ISSN (print): 2095-3119

ISSN (electronic): 2352-3425

Publisher: Elsevier Ltd


DOI: 10.1016/j.jia.2022.11.002


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Funder referenceFunder name
REmote sensing and Decision support for Apple tree Precision management
the Project 2662022JGQD001 supported by the Fundamental Research Funds for the Central Universities
the UK BBSRC-Innovate UK-China Agritech Challenge funded project