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中国农学通报 ›› 2021, Vol. 37 ›› Issue (2): 134-139.doi: 10.11924/j.issn.1000-6850.casb20200200155

• 工程·机械·水利·装备 • 上一篇    下一篇

基于数据包络分析的农机维修企业技术效率研究

王扬光(), 田金明, 陶琎, 董洁芳   

  1. 农业农村部农业机械试验鉴定总站,北京 100122
  • 收稿日期:2020-02-29 修回日期:2020-04-28 出版日期:2021-01-15 发布日期:2021-01-14
  • 作者简介:王扬光,男,1982年出生,山东济宁人,高级工程师,硕士,研究方向为农机化人才培训,农机维修质量监管、农机合作社发展指导等。通信地址:100122 北京市朝阳区东三环南路96号农丰大厦 农业农村部农业机械试验鉴定总站,E-mail:wygcau@163.com
  • 基金资助:
    科学技术部“农机装备试验验证方法与技术研究”(2017YFD0700301);农业农村部农业机械试验鉴定总站“农机合作社规范化建设研究”(KJ2017002)

Analysis of Technical Efficiency of Agricultural Machinery Repairing Enterprises Based on DEA Model

Wang Yangguang(), Tian Jinming, Tao Jin, Dong Jiefang   

  1. China Agricultural Machinery Testing Center, Beijing 100122
  • Received:2020-02-29 Revised:2020-04-28 Online:2021-01-15 Published:2021-01-14

摘要:

为综合评价农机维修企业运营情况,用数据包络分析(DEA)法和文本聚类法对调研的116个农机维修企业进行分类统计和技术效率分析。结果表明:农机维修企业技术效率处于较低水平,平均生产技术效率为0.642,纯技术效率和规模效率分别为0.736、0.880。不同类型农机维修企业效率不同,以组建方式分,品牌三包型技术效率最高、社区便利型次之、自我保障型最低;以业务等级分,企业的业务等级越高,技术效率也越高。为提高企业技术效率,从加强从业人员培训、拓展业务范围、争取资金投入等方面提出对策建议。

关键词: 农机维修企业, 品牌三包, 数据包络分析, 文本聚类, 技术效率

Abstract:

To comprehensively evaluate the operation of agricultural machinery repairing enterprises, the paper studied technical efficiency of 116 agricultural machinery repairing enterprises with the DEA and text clustering method. Results show that the efficiency of China’s agricultural machinery repairing enterprises is relatively low with an average rate of 0.642, and the pure technical efficiency and scale efficiency is 0.736 and 0.880, respectively. The efficiency is different among different enterprise types. From the aspect of forming type,the brand three-package type has the highest technical efficiency, the community convenience type is the next, and the self-guarantee type is the lowest. From the aspect of ability grade of enterprise, the higher the ability grade, the higher the technical efficiency is. To improve the technical efficiency of agricultural machinery enterprises, the paper proposes suggestions as strengthening employee training, expanding business scope, and striving for capital investment.

Key words: agricultural machinery repairing enterprises, brand three-package, DEA, text clustering, technical efficiency

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