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基于改进TOPSIS法的P2P网贷平台运营效率评价

刘翱1,2,3,童泽平1,2,邓旭东1,2,刘克4,5,6   

  1. 1.武汉科技大学管理学院,武汉 430065; 2. 武汉科技大学服务科学与工程研究中心,武汉 430065;3. 智能信息处理与实时工业系统湖北省重点实验室, 武汉 430065; 4.中国科学院数学与系统科学研究院, 北京 100190; 5.中国科学院管理决策与信息系统重点实验室, 北京 100190;6. 中国科学院大学,  北京 100049
  • 出版日期:2017-07-25 发布日期:2017-09-30

刘翱,童泽平,邓旭东,刘克. 基于改进TOPSIS法的P2P网贷平台运营效率评价[J]. 系统科学与数学, 2017, 37(7): 1620-1632.

LIU Ao,TONG Zeping,DENG Xudong,LIU Ke . An Improved TOPSIS Evaluation of Peer-To-Peer Lending's Operational Efficiency[J]. Journal of Systems Science and Mathematical Sciences, 2017, 37(7): 1620-1632.

An Improved TOPSIS Evaluation of Peer-To-Peer Lending's Operational Efficiency

LIU Ao 1,2,3 , TONG Zeping 1,2 ,DENG Xudong 1,2 ,LIU Ke 4,5,6   

  1. 1. School of Management, Wuhan University of Science and Technology, Wuhan 430065; 2. Research Center of Service Science and Engineering, Wuhan University of Science and Technology, Wuhan 430065; 3. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430065; 4. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190; 5. Key Laboratory of Management, Decision and Information Systems, Chinese Academy of Sciences, Beijing 100190; 6. University of Chinese Academy of Sciences, Beijing 100049
  • Online:2017-07-25 Published:2017-09-30

近年来, P2P网络借贷发展迅猛, 吸引了来自金融、经济、管理等诸多领域研究人 员越来越多的关注. 如何结合运营数据对P2P网贷平台效率进行综合评价, 这对P2P网贷平台的运营管理和投资者的投资决策有着十分重要的影响, 目前关于这方面的研究相对欠缺. 鉴于此, 文章提出数据驱动赋权的改进TOSPSIS法对P2P网贷平台效率进行综合评价. 首先, 针对TOPSIS 法存在的主观权重问题, 提出数据驱动赋权的数学模型; 其次, 利用教与学优化算法确定最优权重, 以最大化赋权前后数据的一致性和权重的客观性; 最后, 结合网贷之家的运营数据应用改进TOPSIS法对100家P2P网贷平台效率进行综合评价. 结果表明, 基于改进TOPSIS法的评价结果和网贷之家的评价结果具有较高的一致性.

In recent years, P2P (peer-to-peer) lending has emerged and developed rapidly, which has attracted increasing attention from research experts in the fields of finance, economics, management, et al, and then, operational data driven efficiency evaluation of P2P plays a vital role in P2P's operation management and investor's investment decision-making. In this paper, an improved TOPSIS driven by the operational data is presented to evaluate the P2P's operational efficiency. Firstly, a data driven weighting mathematical model is proposed and dedicated to solving the subjective weight problem in TOPSIS; secondly, a teaching-learning-based optimization algorithm is utilized to determine the optimal weight by maximizing the consistency between the origin data and the evaluation result as well as the objectivity of the weight; finally, the improved TOPSIS is employed to evaluate the efficiency of one hundred P2P lending platforms loan platforms, which indicates its the consistency with the evaluation results of http://www.wdzj.com/.

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