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DEA target setting using lexicographic and endogenous directional distance function approaches

Author

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  • Sebastián Lozano

    (University of Seville)

  • Narges Soltani

    (Kharazmi University)

Abstract

Directional Distance Function (DDF) is an approach often used in data envelopment analysis (DEA) due to its clear interpretation and to the flexibility provided by the possibility of choosing the projection direction towards the efficient frontier. In this paper two new DDF approaches are considered. The first one uses an exogenous directional vector and a multi-stage methodology that at each step uses the projection along the input and output dimensions of the directional vector that can be improved. This lexicographic DDF approach also computes a directional efficiency score and a directional inefficiency indicator for each input and output variable. The second approach is a non-linear optimization model that endogenously determines the directional vector so that the smallest improvement required to reach the efficient frontier is computed.

Suggested Citation

  • Sebastián Lozano & Narges Soltani, 2018. "DEA target setting using lexicographic and endogenous directional distance function approaches," Journal of Productivity Analysis, Springer, vol. 50(1), pages 55-70, October.
    • Handle: RePEc:kap:jproda:v:50:y:2018:i:1:d:10.1007_s11123-018-0534-x
    DOI: 10.1007/s11123-018-0534-x
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    References listed on IDEAS

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    Cited by:

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    2. Yu, Ming-Miin & Rakshit, Ipsita, 2024. "How to establish input and output targets for airlines with heterogeneous production technologies: A nash bargaining DEA approach within the meta-frontier framework," Journal of Air Transport Management, Elsevier, vol. 116(C).
    3. Sebastián Lozano & Narges Soltani, 2020. "A modified discrete Raiffa approach for efficiency assessment and target setting," Annals of Operations Research, Springer, vol. 292(1), pages 71-95, September.
    4. Yu, Ming-Miin & Rakshit, Ipsita, 2023. "Target setting for airlines incorporating CO2 emissions: The DEA bargaining approach," Journal of Air Transport Management, Elsevier, vol. 108(C).
    5. Kao, Chiang, 2022. "A maximum slacks-based measure of efficiency for closed series production systems," Omega, Elsevier, vol. 106(C).
    6. Kao, Chiang, 2024. "Maximum slacks-based measure of efficiency in network data envelopment analysis: A case of garment manufacturing," Omega, Elsevier, vol. 123(C).

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