• DocumentCode
    578372
  • Title

    A new DEA model on science and technology resources of industrial enterprises

  • Author

    Li-na Yuan ; Li-Na Tian

  • Author_Institution
    Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
  • Volume
    3
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    986
  • Lastpage
    990
  • Abstract
    The science and technology resources play a key role in the development of society and economy. DEA (data envelopment analysis) can be used to gauge overall efficiency. DEA is an empirical method which is used to evaluate the relative effectiveness of decision-making units (DMUs). The DEA has long been applied to assess operational performance in public and private sectors and a two-stage DEA method has been developed. Relative to the traditional DEA approach, two-stage DEA method has the advantage that it can not only provide the overall efficiency values of the evaluated objects, but also the values of each stage. Using the two-stage method, DEA model, this paper gives an analysis of the science and technology resources efficiency of industrial enterprises and its influencing factor. The results reflected the independence of input element and the concentration of output element.
  • Keywords
    data envelopment analysis; decision making; enterprise resource planning; DEA model; DMU; data envelopment analysis; decision-making units; industrial enterprises; operational performance; private sectors; public sectors; science and technology resource efficiency; two-stage DEA method; Abstracts; Analytical models; Atmospheric measurements; Computational modeling; Educational institutions; Indexes; Particle measurements; Data envelopment analysis (DEA); Efficiency evaluation; Industrial enterprises; Science and technology resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4673-1484-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2012.6359488
  • Filename
    6359488