The influencing factors and income effects of green prevention-control technology adoption — An empirical analysis based on the survey data of 792 vegetable growers

To comply with the agricultural production trend of protecting the ecological environment, reducing the application of chemical pesticides, comprehensively developing green agriculture, and helping the rural areas to achieve long-term development, the Chinese government made efforts to promote the application of green prevention-control technology; however, the application level of this technology in China is not high and existing research on the adoption of green prevention-control technology as a method selection by farmers is insufficient. To promote the adoption of green prevention-control technologies by vegetable farmers, achieve green production and quality improvement and income increase, provide policy reference for the effective promotion of green prevention-control technologies in the vegetable planting industry, and enrich the promotion theory of green prevention-control technologies, this study used vegetable growers in Shouguang City, Shandong Province as an example to quantitatively analyze the influencing factors and income effects of vegetable farmers’ adoption of green prevention-control technologies. Based on the micro-data of 792 vegetable farmers, this study characterized the behavior of vegetable farmers in adopting green prevention-control technology according to two aspects, adoption decision and adoption degree, explored the influencing factors affecting the adoption of green prevention-control technology of vegetable farmers using the Heckman correction method model. And the average treatment effect of the adoption of green prevention-control technology of vegetable farmers on their income was analyzed by using an endogenous conversion regression model. The study found that the degree of adoption of green prevention-control technologies by vegetable farmers was insufficient. The numbers of vegetable farmers adopting one and two green prevention-control technologies were the largest, which were 292 households and 216 households, respectively, accounting for 36.87% and 27.27% of the total sample, respectively. The level of awareness of green prevention-control technology of vegetable farmers, the experience of getting quality testing and training, and the active use of the internet in collection of information were significantly positively correlated with the adoption of green prevention-control technologies by vegetable farmers. Factors such as the number of plots owned, the number of information devices significantly negatively correlated with the adoption of green prevention and control technologies among vegetable farmers. Vegetable farmers whose per capita income exceeded the average sample level were more willing to accept green prevention-control technology, and the use of this technology could increase the proportion of the average annual income of vegetable farmers by 7.2%. Therefore, a variety of factors, such as family, information, and government policies, affect the decision-making and adoption degree of green prevention-control technologies by vegetable farmers; moreover, the adoption of green prevention-control technologies has a positive impact on the income of vegetable farmers. Based on this, we should give full play to the increase in the income effect of green prevention-control technology, stimulate the endogenous motivation of vegetable farmers to adopt new technologies, and propose that the government should accelerate the improvement of the promotion mechanism of green prevention-control technology, improve the risk compensation mechanism, give vegetable farmers science and technology policy subsidies, enhance the scientific and technological awareness of vegetable farmers, and actively promote the moderate-scale operation of farmers.