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基于因子分析和Logistic回归模型的电力普遍服务受助个体主客观诉求影响因素分析
引用本文:赵会茹,霍慧娟,李春杰.基于因子分析和Logistic回归模型的电力普遍服务受助个体主客观诉求影响因素分析[J].陕西电力,2014(8):65-71.
作者姓名:赵会茹  霍慧娟  李春杰
作者单位:华北电力大学经济与管理学院,北京102206
基金项目:国家自然科学基金项目资助(71373076)
摘    要:本文根据"顾客满意度理论",在对云南省150户农民调研的基础上,采用因子分析法和Logistic回归模型,分析了影响电力普遍服务受助个体诉求的主客观因素,并重点分析了主观影响因素的作用机理。结果表明,农户人均年收入、家庭用电量、家电拥有量、通电情况、家庭成员数等客观因素以及收入满意度、家庭负担、文化程度、年龄结构、职业等主观因素对电力普遍服务诉求有显著影响,其中家庭负担过重、对收入不满意、文化程度为初中、从事非农职业和家中有16~40岁人口的农户对电力普遍服务的诉求程度较高。

关 键 词:电力普遍服务  主观因素  因子分析  Logistic回归模型

Analysis of Subjective and Objective Factors Influencing Recipient Demand for Electric Power Universal Service Based on Factor Analysis and Logistic Regression Model
ZHAO Huiru,HUO Huijuan,LI Chunjie.Analysis of Subjective and Objective Factors Influencing Recipient Demand for Electric Power Universal Service Based on Factor Analysis and Logistic Regression Model[J].Shanxi Electric Power,2014(8):65-71.
Authors:ZHAO Huiru  HUO Huijuan  LI Chunjie
Affiliation:(School of Economics and Management, North China Electric Power University, Beijing 102206, China)
Abstract:According to the customer satisfactory theory,based on 150 farmer households investigated in Yunnan Province,the paper uses factor analysis method and logistic regression model to analyze the subjective and objective factors,which influence the recipient demand for electric power universal service (EPUS),and then focuses on the action mechanism of subjective factors.The results show that some objective factors including per capita income,home population,annual electricity consumption and electricity condition,and some subjective factors including income satisfaction,the level of education,age structure,family burden and occupation influence the recipient demand for EPUS significantly.The recipient family,who aren't satisfied with income,have a heavy family burden,belong to the junior middle school level,engaged in non-agricultural occupations,with a population of 16~40 years old,will appeal to EPUS strongly.
Keywords:electric power universal service  subjective factors  factor analysis  logistic regression model
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