主办单位:成都体育学院
ISSN 1001-9154 CN 51-1097/G8

成都体育学院学报 ›› 2014, Vol. 40 ›› Issue (2): 26-32.

• 体育人文社会科学 • 上一篇    下一篇

中国各省区竞技体育效率评估的模式研究

李淞淋1,李联堂2   

  1. 1.中国人民大学统计学院,北京 100872;
    2.河南濮阳职业技术学院体育系,河南 濮阳 457000
  • 收稿日期:2014-03-13 修回日期:2014-03-13 出版日期:2014-02-15 发布日期:2014-03-13
  • 作者简介:李淞淋(1988-),女,博士生,研究方向为统计与决策,数量经济学,体育社会学。

Development Modes of Competitive Sports Efficiency in China

LI Song-Lin1, LI Lian-Tang2   

  1. 1. Renmin University of China, Beijing, 100872
    2. Puyang Vocational and Technical College, Puyang Henan, 457000
  • Received:2014-03-13 Revised:2014-03-13 Online:2014-02-15 Published:2014-03-13

摘要: 竞技体育效率研究可用于评估一个国家或地区向体育运动的投资效率,寻找竞技体育效率发展的影响因素,为进一步提高当地的体育水平提供思路。采用包络分析方法和基于面板数据的K-中心函数聚类方法分析中国31个省、市、区在1994-2013年期间的经济、人口和全运会奖牌情况,发现区域竞技体育效率发展趋势明显存在较大差异;结合各省区的实际情况,具体地将31个省(市)具体分为经济主导型高效率组、人口主导型高效率组、经济优势型低效率组、人口优势型低效率组、双优势型低效率组五种竞技体育效率发展模式;研究讨论了每种模式下竞技体育效率上升或下降的原因,为将来提升各省、市、区的竞技体育效率提供建议。

关键词: DEA, K-中心函数聚类方法, 面板数据, 竞技体育效率

Abstract: Studies on competitive sports efficiency can help to evaluate the investment of a country or region in ' competitive sports and figure the related influence factors on the development of competitive sports so as to provide ideas for the further development of sports in this region. Depending on the DEA method and the K-centers functional clustering method, the paper analyzes the situations of economy, population and medals at the National Games in 31 provinces, regions and cities from 1994 to 2013, finding that there exist obvious differences in competitive sports development efficiency between different places. According to the situations of different provinces and regions, the 31 provinces are divided into five different development modes of economic-oriented high efficiency group, population-oriented high efficiency group, low efficiency group with economic advantages, low efficiency group with population advantages, and low efficiency group with both economic and population advantages. The paper further discusses the reasons for the increases and decreases of competitive sports efficiency so as to come up with suggestions for the improvement of competitive sports efficiency in different provinces and regions.

Key words: DEA, k-centers functional clustering method, panel data, competitive sports efficiency

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