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Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model

Received: 26 April 2018    Accepted:     Published: 27 April 2018
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Abstract

DEA is a systematic method for analyzing the relative effectiveness or benefit of decision- making units based on multi-index inputs and multi-index outputs, while Inverted DEA is a method for evaluating decision-making units based on ineffectiveness. In order to make a more reasonable evaluation of the decision-making unit, we consider using the characteristics of both DEA and Inverted DEA models to make a comprehensive evaluation of decision-making units. After discussing DEA model, Inverted DEA model and the comprehensive evaluation methods such as TOPSIS, a weighted geometric evaluation method was proposed. By using the proposed weighted geometric evaluation method and the other four evaluation methods, we evaluated the performance of 16 logistics enterprises in our country and the evaluation results were compared and sorted. The results show that the weighted geometric evaluation method can provide a new idea for the comprehensive evaluation based on DEA and Inverted DEA models.

Published in American Journal of Applied Mathematics (Volume 6, Issue 2)
DOI 10.11648/j.ajam.20180602.14
Page(s) 48-54
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

DEA, Inverted DEA, TOPSIS, Weighted Geometric Mean, Logistics Evaluation

References
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[2] Shi, Ping, et al. "A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach."Information Technology & Management 16.1(2015):39-49.
[3] Mardani, Abbas, et al. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency." Renewable & Sustainable Energy Reviews 70. In press(2016):In press.
[4] R. Allen, et al. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions."Annals of Operations Research 73.1(1997):13-34.
[5] Andersen, Per, and N. C. Petersen. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis." Management Science39. 10(1993):1261-1264.
[6] Rajiv D. Banker, and Hsihui Chang. "The super-efficiency procedure for outlier identification, not for ranking efficient units." European Journal of Operational Research 175.2(2006):1311-1320.
[7] Yamada, Yoshiyasu, T. Matsui, and M. Sugiyama. "AN INEFFICIENCY MEASUREMENT METHOD FOR MANAGEMENT SYSTEMS." Journal of the Operations Research Society of Japan 37.2(1994):158-168.
[8] Hwang, C. L., and Yoon, K. "Multiple Attribute Decision Making: Methods and Applications." Springer-Verlag, New York.
[9] Tzeng, Gwo Hshiung, and J. J. Huang. "Multiple Attribute Decision Making: Methods and Applications." European Journal of Operational Research 4.4(2011):287-288.
[10] Liu, Wb, et al. "DEA Analysis Based on both Efficient and Anti-Efficient Frontiers." (2007).
[11] Guo, Cun Zhi, et al. "Construction of the Indexes of DEA Used in Comprehensive Evaluation of Sustainable Development." China Population Resources & Environment (2016).
[12] Shen, Wan Fang, et al. "Increasing discrimination of DEA evaluation by utilizing distances to anti-efficient frontiers." Computers & Operations Research 75. C(2016):163-173.
[13] Carayannis, Elias G., E. Grigoroudis, and Y. Goletsis. "A multilevel and multistage efficiency evaluation of innovation systems: A multiobjective DEA approach." Expert Systems with Applications 62(2016):63-80.
[14] Jin, Han Park, Y. K. Ji, and Y. C. Kwun. "Intuitionistic Fuzzy Optimized Weighted Geometric Bonferroni Means and Their Applications in Group Decision Making." Fundamenta Informaticae 144.3-4(2016):363-381.
[15] Emrouznejad, Ali, and G. L. Yang. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016." Socio-Economic Planning Sciences (2017).
[16] Junior, Paulo Rotela, et al. "Entropic Data Envelopment Analysis: A Diversification Approach for Portfolio Optimization." Entropy onl1st.9 (2017).
Cite This Article
  • APA Style

    Zhang Qian, Zhang Bing-jiang. (2018). Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model. American Journal of Applied Mathematics, 6(2), 48-54. https://doi.org/10.11648/j.ajam.20180602.14

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    ACS Style

    Zhang Qian; Zhang Bing-jiang. Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model. Am. J. Appl. Math. 2018, 6(2), 48-54. doi: 10.11648/j.ajam.20180602.14

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    AMA Style

    Zhang Qian, Zhang Bing-jiang. Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model. Am J Appl Math. 2018;6(2):48-54. doi: 10.11648/j.ajam.20180602.14

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  • @article{10.11648/j.ajam.20180602.14,
      author = {Zhang Qian and Zhang Bing-jiang},
      title = {Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model},
      journal = {American Journal of Applied Mathematics},
      volume = {6},
      number = {2},
      pages = {48-54},
      doi = {10.11648/j.ajam.20180602.14},
      url = {https://doi.org/10.11648/j.ajam.20180602.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20180602.14},
      abstract = {DEA is a systematic method for analyzing the relative effectiveness or benefit of decision- making units based on multi-index inputs and multi-index outputs, while Inverted DEA is a method for evaluating decision-making units based on ineffectiveness. In order to make a more reasonable evaluation of the decision-making unit, we consider using the characteristics of both DEA and Inverted DEA models to make a comprehensive evaluation of decision-making units. After discussing DEA model, Inverted DEA model and the comprehensive evaluation methods such as TOPSIS, a weighted geometric evaluation method was proposed. By using the proposed weighted geometric evaluation method and the other four evaluation methods, we evaluated the performance of 16 logistics enterprises in our country and the evaluation results were compared and sorted. The results show that the weighted geometric evaluation method can provide a new idea for the comprehensive evaluation based on DEA and Inverted DEA models.},
     year = {2018}
    }
    

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    T1  - Comprehensive Evaluation of Logistics Enterprise Performance Based on DEA and Inverted DEA Model
    AU  - Zhang Qian
    AU  - Zhang Bing-jiang
    Y1  - 2018/04/27
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    T2  - American Journal of Applied Mathematics
    JF  - American Journal of Applied Mathematics
    JO  - American Journal of Applied Mathematics
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ajam.20180602.14
    AB  - DEA is a systematic method for analyzing the relative effectiveness or benefit of decision- making units based on multi-index inputs and multi-index outputs, while Inverted DEA is a method for evaluating decision-making units based on ineffectiveness. In order to make a more reasonable evaluation of the decision-making unit, we consider using the characteristics of both DEA and Inverted DEA models to make a comprehensive evaluation of decision-making units. After discussing DEA model, Inverted DEA model and the comprehensive evaluation methods such as TOPSIS, a weighted geometric evaluation method was proposed. By using the proposed weighted geometric evaluation method and the other four evaluation methods, we evaluated the performance of 16 logistics enterprises in our country and the evaluation results were compared and sorted. The results show that the weighted geometric evaluation method can provide a new idea for the comprehensive evaluation based on DEA and Inverted DEA models.
    VL  - 6
    IS  - 2
    ER  - 

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Author Information
  • School of Applied Science, Beijing Information Science and Technology University, Beijing, China

  • School of Applied Science, Beijing Information Science and Technology University, Beijing, China

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