Research on the Impacts of Information Capacity on Farmers’ Green Prevention and Control Technology Adoption

Abstract

This study was carried out to reveal the key factors affecting farmers’ green prevention and control technology adoption and to deeply analyse the influence of different generations of farmers’ information capacity on green prevention and control technology adoption. Based on the survey data of 509 farmers in Liaoning Province and the probit model and logit model, this paper conducted an empirical analysis of the farmers’ green prevention and control technology adoption, and analysed the differences in farmers’ adoption of green prevention and control technology from the perspective of intergenerational difference. The research results show as follows: First, information capacity has a significant positive impact on farmers’ green prevention and control technology adoption; Second, the influence of information capacity on the green prevention and control technology adoption of different generations of farmers is different. Information consciousness has more significant influences on farmers in the new and middle-generations; information needs have more significant influences on farmers in the new and old generations; information use only has significant influences on farmers in the middle-generation. Therefore, in order to increase the probability of farmers’ green prevention and control technology adoption, it is necessary to not only pay attention to the influence of farmers’ information capacity, but also fully consider the different stages of the life cycle of different generations of farmers and their own endowment differences.

Impact of consumer information capability on green consumption intention: the role of green trust and media publicity

“…Consequently, hypothesis H1 is supported, affirming a significant positive effect of information capability on consumers’ inclination toward green consumption. The results of the analysis suggest that information capability plays a pivotal role in influencing behavioral changes, particularly within the context of the digital information era ( Wu Q. et al, 2022 ). Consumers possessing a strong information capability exhibit a heightened mastery of green information.…”

“…Therefore, information capability includes not only the acquisition of information, but also the capability to judge and process information, as well as the capability to utilize information. Therefore, building upon prior research ( Wu Q. et al, 2022 ), this paper delineates information capability into three dimensions: information cognitive capability, information acquisition capability, and information sharing capability. Information cognitive capability pertains to consumers’ level of knowledge regarding the functionalities or values associated with green products.…”

Quantifying the Income-Increasing Effect of Digital Agriculture: Take the New Agricultural Tools of Smartphone as an Example

“…The use of new smartphone farming tools plays an important role in breaking the low level of equilibrium, mitigating the information dilemma, and enhancing farmers’ ability to access information. According to search theory, farmers will reduce their search behavior when the cost of searching for information is higher, all other things being equal [ 25 ]. When the cost of searching for information is low, farmers will expand the scope and depth of their search and are more likely to obtain relevant, actionable information, thus optimizing their allocation of resources and increasing their income levels.…”

Is there a “made in Mexico” model for innovation transfer or diffusion among farmers?

“…In another study carried out in China, the authors found an increase in the adoption rate of innovations for precision fertilization when extension services based on information and communication technologies were used (Li et al, 2022); in a study on adoption of irrigation systems in Lebanon, the authors found that an increase in risk perception reduced the adoption of innovations (Sabbagh and Gutierrez, 2022). Another factor is the level of knowledge that the farmer has about a given innovation, which has been positively correlated with the adoption of that innovation (Khan et al, 2022); as well as the farmer's ability to process information, which is correlated to his or her age (Wu et al, 2022), and whether or not they belong to a cooperative (Adebayo et al, 2022).…”