Peer effects, attention allocation and farmers' adoption of cleaner production technology: Taking green control techniques as an example

Niu, Ziheng; Chen, Chen; Gao, Yang; Wang, Yaqi; Chen, Yu‐Sheng; Zhao, Kongjia

doi:10.1016/j.jclepro.2022.130700

Cited by 62 publications

(30 citation statements)

References 31 publications

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“…First, this study constructed a comprehensive evaluation index system of farmers' AGP Frontiers in Environmental Science frontiersin.org behavior. In the extant literatures, some scholars discussed farmers' AGP behavior from one or several aspects, such as the application of organic fertilizer (Li and Shen 2021), the adoption of pro-green control technology (Niu et al, 2022;Lou et al, 2021), the adoption of straw return (Mi et al, 2020). The above research cannot fully reflect the characteristics of farmers' AGP behavior.…”

Section: Discussionmentioning

confidence: 99%

“…In previous studies, many scholars pointed out that some demographic and socio-economic factors might be the major reasons that prevented farmers from adopting AGP behavior (Li et al, 2020). In addition to individual endowment (e.g., gender, age, education degree) (Yu et al, 2021), household characteristics (e.g., family income, off-farm income ratio, farm income ratio, e-commerce adoption) Xie and Huang, 2021), farming conditions (e.g., farm size, degree of farmland fragmentation; land transfer) (Qi et al, 2021;Xie and Huang, 2021), farmers' AGP behavior might be affected by social factors (e.g., training, cooperative, social capital, experience sharing, peer effects, supervision, government subsidies, government propaganda, community governance) (Kassie et al, 2013;Xie and Huang, 2021;Thu et al, 2020;Yu et al, 2022;Zhang et al, 2018;Li et al, 2019;Yi et al, 2021;Niu et al, 2022) and market environment (e.g., expected price) (Zhao et al, 2018). In terms of measuring AGP behavior, most of the existing research has extended in two directions.…”

Section: Introductionmentioning

confidence: 99%

“…In terms of measuring AGP behavior, most of the existing research has extended in two directions. On the one hand, some scholars used binary choice variables to characterize farmers' AGP behavior, and then used Logistic and Probit models to explore its influencing factors (Zhang et al, 2018;Cao et al, 2020;Li and Shen, 2021;Niu et al, 2022). On the other hand, some studies have used multiple questions with binary selection variables to ask farmers about their AGP behavior, and used a count dependent variable measuring the number of AGP behavior adopted by farmers.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of environmental literacy on farmers’ agricultural green production behavior: Evidence from rural China

Liu

Yang

et al. 2022

Front. Environ. Sci.

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Agricultural green production has been regarded as an effective way to solve the increasing level of agricultural environmental pollution and the frequent safety crises of agricultural products. As the main decision makers of agricultural production, farmers’ agricultural green production behavior directly determines the process of agricultural green development. However, few studies have explored farmers’ agricultural green production behavior from the perspective of environmental literacy, and the formation mechanism of farmers’ agricultural green production behavior is still unclear. This study aims to clarify the effect of environmental literacy on farmers’ agricultural green production behavior and its impact mechanism. Based on survey data from 830 farmers in China, this study constructs comprehensive index systems to evaluate farmers’ environmental literacy and agricultural green production behavior, and adopts multiple linear regression models and quantile regression model to explore the impact of environmental literacy on this behavior. Meanwhile, the mediation effect model is used to explore the mediation effect of agricultural green production cognition and agricultural green production willingness in the influence of environmental literacy on farmers’ agricultural green production behavior. Three conclusions arise. First, farmers’ environmental literacy and agricultural green production behavior are at the middle level, both of which should be strengthened. Second, environmental literacy has a significant positive impact on farmers’ agricultural green production behavior. Finally, environmental literacy influences farmers’ AGP behavior through the independent and chain mediation effects of AGP cognition and AGP willingness. Environmental literacy has heterogeneity impact on farmers’ agricultural green production behavior under different level of agricultural green production and external environment. This research not only provides theoretical support for the study of farmers’ agricultural green production behavior from the perspective of environmental literacy, it also provides a reference to the relevant government departments so that they can guide farmers to adopt more agricultural green production behavior.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of environmental literacy on farmers’ agricultural green production behavior: Evidence from rural China

Liu

Yang

et al. 2022

Front. Environ. Sci.

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“…It had been confirmed that personal and family characteristics were important factors influencing pesticide safety use among farm households [ 46 , 47 , 48 ], while, to further control for factors that may affect it among farmers, the study selects control variables in terms of both personal and family characteristics. Specifically, for personal characteristics, we introduce gender, age, years of education, whether a village cadre, and physical health status.…”

Section: Methodsmentioning

confidence: 99%

External Supervision, Face Consciousness, and Pesticide Safety Use: Evidence from Sichuan Province, China

Qiao

Luo

Zheng

et al. 2022

IJERPH

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Clarifying the factors influencing the safe use of pesticide is essential for scientific decision making to effectively manage pesticide use and promote sustainable agroecological development. The study aims to explore the factors influencing farmers’ safe use of pesticides from the perspectives of external supervision and face consciousness. Using survey data covering 534 farm households in Sichuan province, this study empirically analyzes the influence mechanisms of external supervision, face consciousness, and their interaction terms on farmers’ safe use of pesticides by employing the binary logit and IV-2SLS model, and further reveals their intergenerational differences on this basis. The results show that external supervision and positive face consciousness have significantly positive effects on pesticide safety use by farmers; market supervision and ability-type face, respectively, play the biggest role among them. Furthermore, there is an interaction effect between external supervision and face consciousness with respect to pesticide safety use. Farmers with different generation farms are influenced differently by external supervision and face consciousness. The behaviors of the new generation farmers to safely use pesticide are principally influenced by government supervision, market supervision, and ability-type face; in contrast, the ones of the older generation farmers are mainly influenced by market supervision, organization supervision, and relationship-type face.

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“…GCT is an environmentally friendly technology widely used in European and American countries, and it is the sinicization of the concept of Integrated Pest Management (IPM) ( Gao et al, 2017 ). GCT emphasizes the comprehensive utilization of ecological regulation, biological control, physical, and chemical inducement, and scientific drug use or their combination to effectively control pests and diseases, ensure ecological environment safety, promote agricultural cost savings and increase income, and minimize farmers’ dependence on chemical inputs ( Yu et al, 2020 ; Niu et al, 2022 ). By the end of 2019, the coverage rate of GCT in China was only 37% ( Ministry of Justice of the People’s Republic of China, 2020 ), and the application level was not high.…”

Section: Introductionmentioning

confidence: 99%

The influence of social capital on farmers’ green control technology adoption behavior

Ren

Zhong

2022

Front. Psychol.

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Relying on social capital to promote farmers’ adoption of green control technology is of great significance for the governance of rural environment and the realization of sustainable agricultural development. Based on the survey data of 754 farmers in Shandong Province, this paper uses the Probit model and the instrumental variable method to empirically analyze the impact of social capital on farmers’ green control technology adoption behavior. The results show that: social capital has a promoting influence on farmers’ green control technology adoption behavior; the influence of the three dimensions of social capital on farmers’ green control technology adoption behavior is in turn social norms, social networks, and social trust; social networks play an enhanced moderating role in the process of social trust and social norms promoting farmers’ green control technology adoption behavior; education level, the number of family labor force and annual family income level have a significant positive impact on farmers’ green control technology adoption behavior, while age has a significant negative impact. Therefore, the government should make full use of social capital to promote farmers to adopt green control technology.

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Peer effects, attention allocation and farmers' adoption of cleaner production technology: Taking green control techniques as an example

Cited by 62 publications

References 31 publications

Impact of environmental literacy on farmers’ agricultural green production behavior: Evidence from rural China

Impact of environmental literacy on farmers’ agricultural green production behavior: Evidence from rural China

External Supervision, Face Consciousness, and Pesticide Safety Use: Evidence from Sichuan Province, China

The influence of social capital on farmers’ green control technology adoption behavior

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