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不同地形地区农村土地流转意愿的影响因素研究——基于中国安徽省和青海省的问卷调查数据。

A study on the influencing factors of rural land transfer willingness in different terrain areas--Based on the questionnaire survey data of Anhui Province and Qinghai Province, China.

机构信息

School of Urban Design, Wuhan University, Wuhan, Hubei Province, China.

出版信息

PLoS One. 2024 Jun 7;19(6):e0303078. doi: 10.1371/journal.pone.0303078. eCollection 2024.

DOI:10.1371/journal.pone.0303078
PMID:38848438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11161119/
Abstract

This study delves into the factors influencing the willingness of rural land transfers in different terrain areas, aiming to promote the improvement of land transfer institutions and accelerate the process of scale farming. Based on rural survey data from Anhui and Qinghai provinces in China, this research uses geographical detector and Binary Logistic Model to explore the differential factors affecting the willingness of farmers to participate in land contract transfer in the first and third terrain areas of China. The study examines four dimensions, including individual characteristics, family endowments, social support strategies, and geographical environment. The findings reveal the following: (1) By comparing the mean values, standard deviations, and coefficients of variation of the data from both provinces, it is evident that the indicators of individual characteristics, family endowments, social support strategies, and geographical environment differ significantly between the two provinces. This indicates substantial disparities in the basic attributes of farmers and their living environments. (2) The single-factor explanatory power significantly influencing farmers' willingness to engage in land transfer varies considerably and is statistically significant at the 1% level. The types of interaction between two factors mainly include dual-factor enhancement, nonlinear enhancement, single-factor nonlinear attenuation, and nonlinear attenuation. (3) There are commonalities and differences in the factors that significantly influence farmers' willingness to participate in land transfer in the two provinces. Common factors influencing farmers' land transfer willingness in both provinces include: the educational level of household heads, the health status of household heads, the number of family laborers, the arable land area, the differentiation of agricultural management objectives, the proportion of agricultural operating income, labor service economy, and relocation policies. Factors showing different influences include: the age of household heads, school-age children, the number of family members engaged in different occupations, the proportion of income from off-farm employment, minimum guarantee policies credit support, location distance, and terrain undulation. Therefore, in formulating land transfer policies, the government should prioritize significant driving factors influencing farmers' decision-making behavior in different regions. It is essential to develop and implement land transfer policies tailored to local conditions with the primary goal of safeguarding the rights and interests of the principal stakeholders, thus achieving sustainable land utilization.

摘要

本研究深入探讨了不同地形地区农村土地流转意愿的影响因素,旨在促进土地流转制度的完善,加速规模经营进程。基于中国安徽和青海两省的农村调查数据,运用地理探测器和二元 Logistic 模型,探讨了中国第一、第三地形区农民参与土地承包经营权流转意愿的差异化影响因素。研究从个体特征、家庭禀赋、社会支持策略和地理环境四个维度进行了考察。研究结果表明:(1)通过比较两省数据的均值、标准差和变异系数,可以发现两省农民个体特征、家庭禀赋、社会支持策略和地理环境等指标存在显著差异,这表明两省农民的基本属性和生活环境存在较大差异。(2)单一因素对农民流转意愿的解释力影响显著且在 1%水平上显著,主要类型包括双因子增强、非线性增强、单因子非线性衰减和非线性衰减。(3)两省影响农民流转意愿的因素既有共性又存在差异,共性因素包括户主受教育程度、户主健康状况、家庭劳动力数量、耕地面积、农业经营目标分化、农业经营收入比例、劳务经济、搬迁政策;差异性因素包括户主年龄、学龄儿童、家庭从事不同职业人数、外出从业收入比例、最低生活保障政策、信贷支持、区位距离、地形起伏。因此,在制定土地流转政策时,政府应优先考虑影响不同地区农民决策行为的显著驱动因素,有针对性地制定和实施符合当地实际的土地流转政策,以维护主要利益相关者的权益为根本目标,实现土地的可持续利用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/fd0828c5624f/pone.0303078.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/2682134788e6/pone.0303078.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/be2837a91824/pone.0303078.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/fd0828c5624f/pone.0303078.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/2682134788e6/pone.0303078.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/be2837a91824/pone.0303078.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c97/11161119/fd0828c5624f/pone.0303078.g003.jpg

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