DEA Models for Extended Two-Stage Network Structures

Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 208)

Abstract

This chapter discusses DEA modeling technique for a two-stage network process where the inputs of the second stage include both the outputs from the first stage and additional inputs to the second stage. Two models are proposed to evaluate the performance of this type two-stage network structures. One is a non-linear centralized model whose global optimal solutions can be estimated using a heuristic search procedure. The other is a non-cooperative model, in which one of the stages is regarded as the leader and the other is the follower. The newly developed models are illustrated with a case of regional R&D of China.

Keywords

Data envelopment analysis (DEA) Two-stage Game 

Notes

Acknowledgements

This research is supported by National Natural Science Foundation of China under Grants (No. 70901070, 71271196 and 70821001), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 71121061), the National Science Foundation of China for Distinguished Youth Scholars (No. 71225002), the Chinese Universities Scientific Fund (WK2040150005) and the Fund for International Cooperation and Exchange of the National Natural Science Foundation of China (No. 71110107024).

Part of the materials are based upon Li et al. (2012) with permission from Elsevier.

References

  1. Castelli, L., Pesenti, R., & Ukovich, W. (2004). DEA-like models for the efficiency evaluation of hierarchically structured units. European Journal of Operational Research, 154, 465–476.CrossRefGoogle Scholar
  2. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.CrossRefGoogle Scholar
  3. Cook, W. D., Liang, L., & Zhu, J. (2010a). Measuring performance of two-stage network structures by DEA: a review and future perspective. Omega, 38, 423–430.CrossRefGoogle Scholar
  4. Cook, W. D., Zhu, J., Yang, F., & Bi, G. B. (2010b). Network DEA: Additive efficiency decomposition. European Journal of Operational Research, 207, 1122–1129.CrossRefGoogle Scholar
  5. Cooper, W. W., Seiford, L. M., & Zhu, J. (2004). Handbook on data envelopment analysis. Boston: Springer.Google Scholar
  6. Doyle, J., & Green, R. (1994). Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. Journal of the Operational Research Society, 5, 567–578.Google Scholar
  7. Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34, 35–49.CrossRefGoogle Scholar
  8. Huang, Z. M., & Li, S. X. (2001). Co-op advertising models in a manufacturing-retailing supply chain: A game theory approach. European Journal of Operational Research, 135, 527–544.CrossRefGoogle Scholar
  9. Kao, C. (2009a). Efficiency decomposition in network data envelopment analysis: A relational model. European Journal of Operational Research, 192, 949–962.CrossRefGoogle Scholar
  10. Kao, C. (2009b). Efficiency measurement for parallel production systems. European Journal of Operational Research, 196, 1107–1112.CrossRefGoogle Scholar
  11. Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185, 418–429.CrossRefGoogle Scholar
  12. Li, Y., Chen, Y., Liang, L., & Xie, J. (2012). DEA models for extended two-stage network structures. Omega, 40(5), 611–618.CrossRefGoogle Scholar
  13. Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of Operations Research, 145, 35–49.CrossRefGoogle Scholar
  14. Liang, L., Cook, W. D., & Zhu, J. (2008). DEA models for two-stage processes: Game approach and efficiency decomposition. Naval Research Logistics, 55, 643–653.CrossRefGoogle Scholar
  15. Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197, 243–252.CrossRefGoogle Scholar
  16. Zhong, W., Yuan, W., Li, S. X., & Huang, Z. M. (2011). The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data. Omega, 39, 447–455.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Yongjun Li
    • 1
  • Yao Chen
    • 2
  • Liang Liang
    • 1
  • Jianhui Xie
    • 1
  1. 1.School of BusinessUniversity of Science and Technology of ChinaHe FeiP.R. China
  2. 2.Manning School of BusinessUniversity of Massachusetts at LowellLowellUSA

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