Innovation efficiency evaluation of industrial technology research institute based on three-stage DEA

被引:5
|
作者
Qin, Yidan [1 ]
Zhang, Peng [2 ]
Deng, Xuanhong [3 ]
Liao, Guobo [3 ]
机构
[1] Chongqing Univ, Sch Econ & Business Adm, Chongqing, Peoples R China
[2] Chongqing Univ, Coll Bioengn, Chongqing, Peoples R China
[3] Chongqing Univ, Sch Automat, Chongqing, Peoples R China
基金
中国国家自然科学基金;
关键词
Innovation efficiency; Industrial technology research institute; Three-stage data envelopment analysis; IMAGE STEGANOGRAPHY METHOD; COLLABORATION; SYSTEM;
D O I
10.1016/j.eswa.2023.120004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The industrial technology research institute (ITRI) has become an important platform to promote the transformation of scientific and technological achievements in universities. The influence of environmental factors and random errors is the main problems in the evaluation of ITRI's innovation efficiency, which greatly affects the evaluation results. At present, there are few studies on the ITRI's innovation efficiency, and most existing works do not eliminate environmental and random factors, resulting in biased results. In this paper, for the evaluation of the innovation efficiency of ITRI, the three-stage data envelopment analysis model is utilized. Firstly, in the first stage, based on the original input and output data, the efficiency of each decision making unit is measured by using the input-oriented classic DEA model. Secondly, the stochastic frontier model is constructed in the second stage to eliminate environmental factors and random errors in the original input and output data. Finally, in the third stage, the adjusted input data is brought into the calculation of the first stage to obtain the real innovation efficiency value of ITRI. The extensive experiments are constructed on the relevant indicator data of 80 Chines ITRI, whose results indicate that the evaluation of innovation efficiency is indeed affected by environmental factors and random errors. After eliminating the influences of environmental factors and random error, the innovation efficiency shows a decreasing tendency, which is more in line with Chinese national conditions.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Research on urban innovation efficiency of Guangdong-Hong Kong-Macao Greater Bay Area based on DEA-Malmquist model
    Hu, Shanshan
    Kim, Hyung-Ho
    ANNALS OF OPERATIONS RESEARCH, 2023, 326 (SUPPL 1) : 147 - 147
  • [42] Optimal condition-based renewable warranty policy for products with three-stage failure process
    Wang, Liying
    Yang, Yanmei
    Zhu, Huihui
    Liu, Guoxin
    QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2020, 17 (02): : 216 - 233
  • [43] Subject-independent emotion recognition based on physiological signals: a three-stage decision method
    Chen, Jing
    Hue, Bin
    Wang, Yue
    Moore, Philip
    Dail, Yongqiang
    Feng, Lei
    Dingo, Zhijie
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2017, 17
  • [44] Control and Experiment of an H-Bridge-Based Three-Phase Three-Stage Modular Power Electronic Transformer
    Wang, Xinyu
    Liu, Jinjun
    Ouyang, Shaodi
    Xu, Taotao
    Meng, Fei
    Song, Shuguang
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2016, 31 (03) : 2002 - 2011
  • [45] Scientific and technological innovation efficiency in Chinese provincial higher education institutions: a three-division network DEA approach
    Zhao, Linlin
    Wang, Dawei
    Yang, Feng
    Zha, Yong
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2025, 76 (01) : 111 - 130
  • [46] Innovation efficiency of Chinese provincial high-tech industries based on shared feedback DEA model
    Zhu Y.
    Yang F.
    Jiang L.-J.
    Liu P.
    Kongzhi yu Juece/Control and Decision, 2020, 35 (08): : 1997 - 2005
  • [47] Industrial development environment and innovation efficiency of high-tech industry: analysis based on the framework of innovation systems
    Liu, Zhiying
    Chen, Xiafei
    Chu, Junfei
    Zhu, Qingyuan
    TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2018, 30 (04) : 434 - 446
  • [48] The Three-Stage Strategy of Bi-Level Optimal Energy Management in the Distribution-Home Network Based on Golf Optimization Algorithm
    Goodarzi, Javad
    Askari, Mohammad Tolou
    Amirahmadi, Meysam
    Babaeinik, Majid
    IEEE ACCESS, 2024, 12 : 183973 - 183990
  • [49] Impact of scientific and technological innovation policies on innovation efficiency of high-technology industrial parks - A dual analysis with linear regression and QCA
    Wang, Jinglei
    Ma, Xiao
    Zhao, Yixuan
    Zhao, Jing
    Heydari, Mohammad
    INTERNATIONAL JOURNAL OF INNOVATION STUDIES, 2022, 6 (03) : 169 - 182
  • [50] Multi-Sensor Vibration Signal Based Three-Stage Fault Prediction for Rotating Mechanical Equipment
    Peng, Huaqing
    Li, Heng
    Zhang, Yu
    Wang, Siyuan
    Gu, Kai
    Ren, Mifeng
    ENTROPY, 2022, 24 (02)