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基于林农意愿的公益林管护人员选拔方式的研究--以外河家庭管护林场为例 被引量:5

Selection Method for Management Personnel on Non-Commercial Forest Based on Forestry Farmers' Willingness: Take the Waihe Family Protection Forest Farm as an Example
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摘要 以对韩家园外河家庭管护林场198位林农进行问卷调查的数据为依据,运用Multinomial Logit模型对管护人员选拔意愿进行实证分析。结果表明:户主年龄、受教育水平、家庭年均总收入、劳动力比例、家庭是否有人担任专业管护人员、林农对管护效果的满意度评价以及林农参与管护的意愿对管护人员选拔方式具有显著影响。因此,提出提高林农与职工的认知水平、加强林农参与公益林管护工作、推行差别化管护政策等建议。 Background The relevant literature about non-commercial forest in the past 6 years showed that foreign scholars'studies mainly focused on present situation and resources utilization;and that domestic scholars'studies mainly focused on management efficiency,management performance,management fee,compensation mechanism,etc.Some scholars explored participatory management in the applications of non-commercial forest.Up to September 2016,scholars had done a lot of researches on forestry farmers'willingness,but few researches focused on selection of management personnel.Therefore,this paper would build a Multinomial logistic regression model to discuss factors determine the selection of management personnel and put forward pertinent suggestions.Methods This paper take Waihe family protection forest farm as the research object,and choose the forestry farmers as the samples(including 21 professional management personnels and more than 200 general management personnels)based on the principle of typical sampling and random sampling.Excluding the questionnaires of missing important information,198 valid questionnaires were taken back,the valid recovery rate is as high as 90%.This paper applied Multinomial logistic regression analysis to study the selection method of management personnel on non-commercial forest based on the willingness of forestry farmers.Results In this paper,the selection method of management personnel is divided into 3 ways:the way 1is to hire workers and farmers in proportion,the way 2 is rotation mode,and the way 3 is to match jobs and salaries.The results of Multinomial logistic regression analysis show that 7 factors would influence the selection method of management personnel remarkably,especially the factor as the age of household head has a significant effect on way 2 at the 10%level and the factor as educational level has a significant effect on way 1 at the 1%level.The factors of household income level and whether there are professional management personnel have a cross impact on the selection of forest management and protection personnel.The level of household income has a important impact on way1 and way 2 at the 5%level and the 10%level respectively.The professional management personnels at home are more willing to choose the way 3,while the others would choose way 1 and way 2 at the 10%level.The proportion of the labor force has a significant impact at the 5%level,that the greater proportion of the labor of the family are more inclined to way 2,and the others would choose the way 3.Most of the forestry farmers are satisfied with the management and protection policy which is prominent on way 2 at the 10%level.And the forestry farmers'participating willingness in management has a significant impact on way1 at the1%level.Conclusions and Discussions The age of household head,the educational level,the household income level,whether there are professional management personnel,the proportion of the labor force,the satisfaction evaluation of management effect and the willingness of participating in management of forestry farmers are the 7factors for influencing selection method of management personnel on non-commercial forest.There are some inherent characteristics in it,so put forward the following suggestions:the first one is to strengthen the propaganda and improve the cognitive level and management skills of forestry farmers;the second one is to strengthen the participation of farmers;the third one is to improve the enthusiasm of forest management and protection personnel.
作者 王菲 马文学
出处 《林业经济问题》 北大核心 2017年第2期13-18,共6页 Issues of Forestry Economics
关键词 公益林管护 林农家庭 MULTINOMIAL logit模型 forest management and protection farmer family Multinomial logistic regression model
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