Impact of migrant and returning farmer professionalization on food production diversity

Liu, Min; Wang, Zheng; Zhong, Taiyang

doi:10.1016/j.jrurstud.2022.05.020

Cited by 9 publications

(7 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of this study indicated that risk has a vital role in peasant households’ production decisions and is related to peasant households’ choices and levels of inputs and outputs. Because agricultural production is a major source of income for peasant households, it is important for them to recognize and manage production risks [ 62 , 63 , 64 ]. Therefore, a timely approach to optimize the agricultural input and production combination can help peasant households to mitigate the negative effects of risks and to adopt adaptive measures.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Wang

Lin

2022

IJERPH

View full text Add to dashboard Cite

Using typical counties in the Yimeng Mountain area of northern China as an example, this paper analyzed the household and agricultural input characteristics of different types of peasant households using survey data from 262 farm households. The target minimization of the total absolute deviations (MOTAD) model was applied to determine the optimal combinations in the allocation of agricultural input factors and production for different types of at-risk peasant households to obtain the ideal agricultural income. The relevant results are twofold. (1) The agricultural input behaviors of different types of peasant households vary significantly. The highest levels of agricultural land, labor, and yield-increasing and labor-saving inputs included I part-time peasant households (I PTPH), followed by full-time peasant households (FTPH), while the input levels of II part-time peasant households (II PTPH) and non-agricultural peasant households (NAPH) with higher levels of non-agricultural employment gradually decreased. In general, an increase in peasant households’ part-time employment revealed an inverted U-shaped trend in the agricultural input level, with a trajectory of I PTPH > FTPH > II PTPH > NAPH. (2) The current agricultural inputs and production combinations of different types of peasant households have room for improvement. It is necessary to adjust agricultural inputs and optimize production combinations to obtain target incomes. Overall, all types of peasant households must streamline labor inputs and increase capital inputs, except for I PTPH, for which capital inputs should be reduced. Following optimization, economic crops gradually replace grain crops, and the optimal agricultural incomes of peasant households will be improved. The study results provide practical policy insights for reducing agricultural production risks and improving agricultural production incomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Wang

Lin

2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…The scores for diversification are based on the combination of planting and breeding and the abundance of species. The combination of planting and raising helps the farm to recycle materials, while monoculture makes the ecosystem more fragile [11]. For the farm certification scores, we refer to the difficulty of obtaining different certifications to assign values, for example, organic product certification is relatively the most difficult and costly, so is assigned the highest value.…”

Section: Dependent Variablesmentioning

confidence: 99%

“…Also, Damalas and Koutroubas [49] concluded that training could motivate farmers to use pesticides in a safe and correct manner. However, some farmers are not willing to participate in agricultural training because they believe some of the training is not sufficiently integrated with production practices and is not helpful [11,50]. We set the dummy variable Certificate to distinguish whether or not farmers were certified as professional farmers and used the continuous variable NTraining to describe farmers' participation in agricultural production training.…”

Section: Covariatesmentioning

confidence: 99%

“…The third set of variables characterizes the farmer's viewpoint (FV). Different types of farmers have different goals and objectives when it comes to farming [11]. And farmers' perceptions and attitudes towards agriculture could directly influence their decisions.…”

Section: Covariatesmentioning

confidence: 99%

“…Land 2024, 13, 119 2 of 25 The literature on SAPs identifies the factors that influence farmers' decision making [5,6,8] and the intensity of adoption [9,10], for example, the farmers' sociodemographic characteristics, farms' attributes [11], farmers' attitudes and intentions [12,13], and government subsidies and tax incentives [1,2,14]. Additionally, an increasing number of researchers have focused on the spatial effects of farmers' decisions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatial Spillover Effects of “New Farmers” on Diffusion of Sustainable Agricultural Practices: Evidence from China

Liu,

Zhong,

Lyu

2024

Land

Self Cite

View full text Add to dashboard Cite

Sustainable agricultural development has been the policy priority for countries with limited natural resources. New farmers’ emergence and growth have not only helped to address the labor crisis in agriculture to some extent, but they have also improved, integrated, and expanded the agricultural sectors. However, less attention has been paid to the performance of new farmers in adopting sustainable agricultural practices and the related spatial effects. Also, few studies have combined the composite adoption intensity of sustainable agricultural practices with the effects of various specific measures. Therefore, this study constructed the Tobit MLE spatial cross-section regression models to empirically study a sample of 174 farmers. We attempted to analyze the impact of the new farmers group on the diffusion of sustainable agricultural practices as well as farmers’ influence on various sorts of sustainable agricultural practices. The results show that new farmers greatly enhanced the adoption of sustainable agricultural practices, as evidenced by the fact that their adoption level was 69.9% greater than that of traditional farmers. However, they had statistically significant negative spillover effects on their neighboring farmers. For the composite adoption intensity of sustainable agricultural practices, there were also statistically significant negative spillover effects. Additionally, there were notable disparities among the factors influencing farmers’ decisions to adopt various types of sustainable agricultural practices and the spatial effects of those adoptions, particularly in the farm size, the number of plots, and the variety of marketing methods employed by farmers. Therefore, measures need to be proposed to address the barriers to the implementation and diffusion of various types of sustainable agricultural practices. This would increase farmers’ willingness to adopt sustainable agricultural practices and the effectiveness of their motivation to neighboring farmers.

show abstract

Spatial distribution and transformation mechanism of specialized villages in typical agricultural areas: Case study of Henan province, China

Xiao,

Qiao,

Han

et al. 2024

Habitat International

View full text Add to dashboard Cite

Impact of migrant and returning farmer professionalization on food production diversity

Cited by 9 publications

References 64 publications

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Spatial Spillover Effects of “New Farmers” on Diffusion of Sustainable Agricultural Practices: Evidence from China

Spatial distribution and transformation mechanism of specialized villages in typical agricultural areas: Case study of Henan province, China

Contact Info

Product

Resources

About