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物流金融人才培养效率及其影响因素分析——以广州商学院为例 被引量:1

Analysis of Efficiency of Logistics Finance Talent Training and Its Influencing Factors:In the Case of Guangzhou College of Commerce
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摘要 采用DEA方法测算了2004-2017年广州商学院物流专业的人才培养效率,运用相关分析确定人才培养效率的影响因素,并通过ANN神经网络模型对物流金融人才培养效率的影响因素进行重要性分析。结果显示:除2015年、2016年及2017年三年教学资金得到充分有效利用外,其余年份都存在教学资金投入的冗余,说明人才培养效率与办学时间之间存在较强的正关系,办学时间越长,教学资金利用就越合理,人才培养效率就越高;师资力量、教师年龄结构、科研投入水平、教学环境、教学管理、培养模式、学生课外投入、师生比例、生源质量9个影响因素对人才培养效率的影响比较显著,其中教师年龄结构与人才培养效率之间存在负相关;按照对人才培养效率的重要性程度,其影响因素排序依次为培养模式、师生比例、科研投入水平、师资力量、教学管理水平、教学环境、教师年龄结构、学生课外投入、生源质量,并提出了提升人才培养效率的相关建议。 This paper uses the DEA method to calculate the talent training efficiency of the logistics major students in GuangzhouCollege of Commerce from 2004 to 2017, determines the influencing factors through relevance analysis, and analyzes their importancethrough the ANN model. The results show that, except for the years 2015, 2016 and 2017 when the teaching funds were fully and effectivelyutilized, there is redundancy in teaching fund investment in all the other years, indicating a strong positive relationship between talenttraining efficiency and school running time: the longer the latter is, the more rational the use of the teaching funds is and the more efficient thetalent training will be. The nine influencing factors, including teacher resources, teacher age structure, scientific research investment level,teaching environment, teaching management, training mode, students' extra- curricular investment, teacher- student ratio, and studentquality have significant impact on the efficiency of talent training. A negative correlation exists between the age structure of the teachers andthe efficiency of the talent training. According to their importance to the talent training efficiency, the influencing factors are ranked in thedescending order as follows: training mode, teacher- student ratio, scientific research investment level, teacher resources, teachingmanagement level, teaching environment, teacher age structure, students' extra- curricular investment and student quality. At the end,relevant suggestions are put forward to improve the efficiency of the talent training.
作者 詹荣富 Zhan Rongfu(Guangzhou College of Commerce,Guangzhou 510520,China)
机构地区 广州商学院
出处 《物流技术》 2018年第10期142-147,共6页 Logistics Technology
基金 广东省教育厅2015年教学质量工程"基于互联网+金融+物流要素禀赋的物流教学改革研究-以广东自贸区为背景"(GDJG2015001)
关键词 物流人才 人才培养效率 影响因素 DEA 神经网络 logistics talents talent training efficiency influencing factor DEA: neural network
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