Do large-scale agricultural entities achieve higher livelihood levels and better environmental outcomes than small households? Evidence from rural China.

There is an ongoing debate about the type or scale of agriculture that should be most encouraged. This study explores the differences in livelihood levels and outcomes between new agricultural business entities (NABEs) and traditional small households. We applied the analytical tools of a sustainable livelihood framework and a multiple linear regression model to describe the determinants of livelihood outcomes of 105 NABEs and 119 traditional small households in two typical areas around the Sichuan Basin in China. The results show that the overall livelihood level of NABEs is 1.40 times higher than traditional small households. NABEs with a mixed livelihood strategy of both planting and breeding have the highest livelihood level, followed by planting NABEs and breeding NABEs. About 3.13% of all agricultural entities are at risk of falling into poverty; the greater risk levels are associated with the subsidized households (30.00%), pure farmers (12.50%), and part-time farming households (1.69%). NABEs in the study area are verified to use 2.06 times more pesticide and herbicide inputs compared to traditional small households. Education level, technical training, financial accessibility, and the connection with professional cooperatives are common factors influencing the livelihood levels of the two groups of agricultural entities. Livelihood levels of NABEs are also significantly influenced by the age of NABE leaders, planting area per capita, and agricultural insurance. Based on these results, the study proposes policy interventions that are most appropriate for achieving higher livelihood levels among both NABEs and small households. Although the mixed type of NABEs and non-farming households are recognized as being better agricultural entity types for poverty alleviation, we recommend a balance between fostering NABEs and maintaining traditional small households; guidance related to green agriculture production for NABEs is also urgently needed.

Moderate operation scales of agricultural land under the greenhouse and open-field production modes based on DEA model in mountainous areas of southwest China.

The identification of the moderate scale of agricultural land was recognized as one of the key measures promoting sustainable agriculture development. However, due to the research gap in mountainous areas, new agricultural business entities (NABE) in these areas usually either refer to the plain area or simply pursue large scale, resulting in low production efficiency and even posing a threat to their sustainable survival. In this study, the Data Envelopment Analysis (DEA) model and Tobit regression model tools were employed to quantitatively reveal the moderate scale and key driving factors of agricultural land under the scale operation modes of greenhouse and open-field types. It was based on 154 NABE questionnaires in the mountainous areas around the Sichuan Basin in China, where NABEs are flourishing. The findings show an approximately "inverted U-shaped" curve relationship between NABE's production efficiency and their planting scale. The primary reason for the failure of NABE to achieve an overall high level of production efficiency is scale inefficiency. The optimal scale intervals for the greenhouse and open-field types of scale operation modes are 3.0-4.3 ha and 3.3-5.0 ha, respectively. Business entities' age, land circulation scale, land rent, and agricultural insurance are common factors that influence the scale efficiencies of both the greenhouse and open-field types. Accordingly, policy interventions regarding the guidance of moderate-scale operation of agricultural land are proposed for achieving the dual goal of cultivating NABE and implementing the Rural Revitalization Strategy in mountainous areas of China. While contributing to the knowledge on scale efficiency of agricultural land, this research also enlightens the practice of policy-making targeted to the sustainable development of agricultural industry led by NABE worldwide.

Defining Household Typologies Based on Cropland Use Behaviors for Rural Human-Environment Systems Simulation Research: A Case Study in Southwest China.

The dynamics of rural human-environment systems in developing countries have increasingly been attracting attention. Agent-based modeling (ABM) is a valuable simulation tool for detecting complex feedback loops in rural human-environment systems with a 'bottom-up' approach. However, such models require the prerequisite analysis of household typology to simulate households' decision-making process, where a gap exists between having accurate classification criteria and a simplified modeling framework. This study aimed to develop a household typology for two selected counties in southwest China based on multivariate analysis techniques and the classification tree method. Four categories of socioeconomic variables, including labor conditions, resource endowments, economic status, and social connections, were screened as possible factors impacting agriculture practice decisions. The results showed that household diversification in the study area was mainly determined by diversified livelihood strategies of off-farm work, livestock breeding, subsidy dependence, and traditional planting. Five distinct household types were identified: non-farm households, part-time households, livestock breed households, subsidized households, and traditional planting households. The household types were associated with specific cropland use behaviors, and their decision-making behaviors were verified with bounded rationality theory (where the maximization of profits is the primary goal). The quantitative classification criteria obtained in this study were clear and could be easily identified and used by ABMs. Our study provides a basis for further simulation of the complicated rural human-environment systems in southwest China.