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Resource allocation based on cost efficiency

Author

Listed:
  • Akram Dehnokhalaji

    (Aalto University
    Kharazmi University)

  • Mojtaba Ghiyasi

    (University of Southern Denmark
    Shahrood University of Technology)

  • Pekka Korhonen

    (Aalto University)

Abstract

In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi-objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical examples and an empirical illustration are also provided.

Suggested Citation

  • Akram Dehnokhalaji & Mojtaba Ghiyasi & Pekka Korhonen, 2017. "Resource allocation based on cost efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1279-1289, October.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:10:d:10.1057_s41274-016-0020-7
    DOI: 10.1057/s41274-016-0020-7
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    Cited by:

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    3. Edmund Mallinguh & Christopher Wasike & Zeman Zoltan, 2020. "Technology Acquisition and SMEs Performance, the Role of Innovation, Export and the Perception of Owner-Managers," JRFM, MDPI, vol. 13(11), pages 1-19, October.
    4. Mostafa Davtalab-Olyaie & Hadis Mahmudi-Baram & Masoud Asgharian, 2023. "Measuring individual efficiency and unit influence in centrally managed systems," Annals of Operations Research, Springer, vol. 321(1), pages 139-164, February.
    5. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.

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