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Abstract

In this paper, a new DEA model is presented to solve the problems with undesirable factors and shared factors by linear transformation with parameters based on currently undesirable factors DEA model. Compared to the DEA model with undesirable factors, the new model by this transformation retains the classification invariance.

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References

  1. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units [J]. Eur J Oper Res 2(6):429–444

    Article  Google Scholar 

  2. Charnes A, Cooper WW, Wei QL et al (1989) Cone ratio data envelopment analysis and multi-objective programming [J]. Int J Syst Sci 20(7):1099–1118

    Article  Google Scholar 

  3. Färe REA (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach [J]. Rev Econ Stat 71(1):90–98

    Article  Google Scholar 

  4. Seiford LM, Zhu J (2002) Modeling undesirable factors in efficiency evaluation [J]. Eur J Oper Res 142(1):16–20

    Article  Google Scholar 

  5. Lozano S, Villa G, Adenso-Díaz B (2004) Centralised target setting for regional recycling operations using DEA [J]. Omega 32(2):101–110

    Article  Google Scholar 

  6. Beasley JE (1995) Determining teaching and research efficiencies [J]. J Oper Res Soc 46(4):441–452

    Google Scholar 

  7. Tsai PF, Mar Molinero C (2002) A variable returns to scale data envelopment analysis model for the joint determination of efficiencies with an example of the UK health service [J]. Eur J Oper Res 141(1):21–38

    Article  Google Scholar 

  8. Mar Molinero C, Tsai PF (1997) Some mathematical properties of a DEA model for the joint determination of efficiencies [J]. J Oper Res Soc 48(1):51–56

    Google Scholar 

  9. Cook WD, Hababou M, Tuenter HJH (2000) Multicomponent efficiency measurement and shared inputs in data envelopment analysis: an application to sales and service performance in bank branches [J]. J Prod Anal 14(3):209–224

    Article  Google Scholar 

  10. Cook WD, Hababou M (2001) Sales performance measurement in bank branches [J]. Omega Int J Manag Sci 29(4):299–307

    Article  Google Scholar 

  11. Cook WD, Green RH (2004) Multicomponent efficiency measurement and core business identification in multiplant firms: a DEA model [J]. Eur J Oper Res 157(3):540–551

    Article  Google Scholar 

  12. Jahanshahloo GR, Hadi Vencheh A, Foroughi AA et al (2004) Inputs/outputs estimation in DEA when some factors are undesirable [J]. Appl Math Comput 156(1):19–32

    Article  Google Scholar 

  13. Jahanshahloo GR, Lotfi FH, Shoja N et al (2005) Undesirable inputs and outputs in DEA models [J]. Appl Math Comput 169(2):917–925

    Article  Google Scholar 

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Correspondence to Cheng-chao Qiu .

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Qiu, Cc. (2014). Research on DEA Model with Undesirable Factors and Shared Factors. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40060-5_22

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