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Relationship between DEA models without explicit inputs and DEA-R models

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  • M. Mozaffari
  • J. Gerami
  • J. Jablonsky

Abstract

Data envelopment analysis (DEA) is one of often used modeling tools for efficiency and performance evaluation of decision making units. Ratio DEA (DEA-R) is a group of novel mathematical models that combines standard DEA methodology and ratio analysis. The efficiency score given by standard DEA CCR model is less than or equal to that given by DEA-R model. In case of single input or single output the efficiency scores in CCR and DEA-R models are identical. The paper deals with DEA-R models without explicit inputs, i.e. models where only pure outputs or index data are taken into account. A basic DEA-R model without explicit inputs is formulated and a relation between output-oriented DEA models without explicit inputs and output-oriented DEA-R models is analyzed. Central resource allocation and slack-based measure models within DEA-R framework are examined. Finally they are used for projections of decision making units on the efficient frontier. The results of the proposed models are applied for efficiency evaluation of 15 units (Chinese research institutes) and they are discussed. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • M. Mozaffari & J. Gerami & J. Jablonsky, 2014. "Relationship between DEA models without explicit inputs and DEA-R models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 1-12, March.
  • Handle: RePEc:spr:cejnor:v:22:y:2014:i:1:p:1-12
    DOI: 10.1007/s10100-012-0273-4
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    Cited by:

    1. Mozaffari, Mohammad Reza & Dadkhah, Fatemeh & Jablonsky, Josef & Wanke, Peter Fernandes, 2020. "Finding efficient surfaces in DEA-R models," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    2. Sagarra, Marti & Mar-Molinero, Cecilio & Agasisti, Tommaso, 2017. "Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling," Omega, Elsevier, vol. 67(C), pages 123-133.
    3. Dariush Akbarian, 2021. "Network DEA based on DEA-ratio," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    4. Javad Gerami & Reza Kiani Mavi & Reza Farzipoor Saen & Neda Kiani Mavi, 2023. "A novel network DEA-R model for evaluating hospital services supply chain performance," Annals of Operations Research, Springer, vol. 324(1), pages 1041-1066, May.
    5. Kalundu Kimanzi & Prof. Mirie Mwangi & Dr. Duncan Elly Ochieng & Prof. Josephat Lishenga, 2020. "Moderating Effect of Board Gender Diversity on the Relationship between Financial Structure and Operating Efficiency," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 9(1), pages 1-1.

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