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基于有序Logistic回归的农村院落建设影响因素研究 被引量:1

Factors Influencing Rural Courtyard Construction Based on Ordinal Logistic Regression
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摘要 农村院落建设是家庭外部因素和内部因素综合作用的结果。基于430份山东省农村院落调查问卷,以容积率作为因变量,综合采用文献分析、农民访谈和有序Logistic回归模型研究农村院落建设的影响因素。结果表明:被调查农村院落容积率在0.16~2.0,平均为0.73。院落所在村庄的经济水平、区位条件2个外部因素,家庭总人口、房屋建筑造价、非农收入比重、耕地面积和户主文化水平5个内部因素影响显著。提出引导非农家庭退出院落、入住城镇社区和新型农村社区,农业兼业型家庭优化院落建设、发展农家乐,老年家庭入住养老院,退出、闲置院落改造、复垦等院落分类利用与管理建议,从而引导农村院落建设、提高院落和土地利用效率,并为农村建设和土地管理提供参考。 Rural courtyard construction is the combined result of both family external factors and internalfactors.Based on 430 rural courtyard questionnaires conducted in Shandong Province,with plot ratio as the de-pendent index,the paper,through literature analysis,farmers interviewsand ordinal Logistic regression model,studied the factors which influence rural courtyard construction.The results showed that surveyed yard plot ratiowas between 0.16 and 2.0,with an average of 0.73.2 external factors,namely economic level and geographicalposition of the village,and5 external factors:family population,housing construction costs,proportion of non-ag-ricultural income,the cultivated land area and householder’s education background,had significant impact onrural courtyard plot ratio.The paper provided some suggestions on classification use and management of ruralcourtyards including non-agricultural tendency families moving to the urbanization community, agriculturalfamilies and multiple occupations families optimizing courtyard construction,developing rural home inns,aged families living in nursing homes,and renovating or reclaiming exited and idle courtyards.It is also believed nec-essary to guide rural courtyard construction,improve the efficiency of courtyard and land use.These suggestionscan serve as references for the new rural construction and land management.
出处 《农林经济管理学报》 2017年第6期776-782,共7页 Journal of Agro-Forestry Economics and Management
基金 山东省自然科学基金(ZR2013DM006) 山东农业大学现代农业发展研究院第三批研究课题(14xsk2-03)
关键词 院落建设 容积率 有序Logistic回归 影响因素 rural courtyard construction plot ratio influence factor ordinal logistic regression
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