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Technical Efficiency Analysis of New Energy Listed Companies Based on DEA

  • Conference paper
Artificial Intelligence and Computational Intelligence (AICI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6319))

  • 1835 Accesses

Abstract

This paper uses the DEA model to analyses the technical efficiency of representative listed companies in China new energy industry representative.Through the analysis and solution for the data on three consecutive years, the results in a certain extent, reflect the development and business efficiency of new energy industry, and provide relevant decision-making information on technical efficiency for new energy industry operation, with strong reliability and practicality.

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References

  1. Wei, Q.L.: Data Envelopment Analysis (DEA). Science Bulletin. 17 (2000)

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Author information

Authors and Affiliations

  1. Department of Economy and Management, North China Electric Power University, Baoding, Hebei Province, 071003, China

    Gao Chong & Zhang Jian-ze

  2. Shunyi Power Supply Company, Beijing Electric Power Corporation, Beijing, 101300, China

    Li Xiao-dong

Authors
  1. Gao Chong
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  2. Zhang Jian-ze
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  3. Li Xiao-dong
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Editor information

Editors and Affiliations

  1. Department of Business Administration, Caritas Francis Hsu College, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

  2. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  3. Department of Computer Science, Nanjing University, 210093, Nanjing, China

    Yang Gao

  4. School of Computer, Nanjing University of Posts and Telecommunications, 210003, Nanjing, China

    Jingsheng Lei

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© 2010 Springer-Verlag Berlin Heidelberg

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Chong, G., Jian-ze, Z., Xiao-dong, L. (2010). Technical Efficiency Analysis of New Energy Listed Companies Based on DEA. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_20

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  • DOI: https://doi.org/10.1007/978-3-642-16530-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16529-0

  • Online ISBN: 978-3-642-16530-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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