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Resource allocation for branch network system with considering heterogeneity based on DEA method

Author

Listed:
  • Yingying Shao

    (University of Science and Technology of China)

  • Gongbing Bi

    (University of Science and Technology of China)

  • Feng Yang

    (University of Science and Technology of China)

  • Qiong Xia

    (Hefei University of Technology)

Abstract

In this paper, we proposed a new DEA approach to allocate the resource in branch network system which is not covered by the existing resource allocation works under a centralized decision-making environment. The branch network system is typically appears in multi-national or multi-regional corporations, which has many branches across multiple locations. Given the spatial distribution of the production, we imposed additional restrictions on resource allocation and divided the resource inputs into three groups: fixed inputs, regional inputs that allocated to the branches in the same area and common resource that an additional resource allocated to all the branches. Then, we generalize the model further to accommodate technological heterogeneity due to the difference in the geographical locations of the branches. And the objective of the proposed models is to maximize the gross profits of the entire organization, which is a natural assumption for a for-profit organization. Finally, an example was presented to illustrate the proposed approach with heterogeneous technology is more practically feasible and superior than the prior approach with homogeneous technology.

Suggested Citation

  • Yingying Shao & Gongbing Bi & Feng Yang & Qiong Xia, 2018. "Resource allocation for branch network system with considering heterogeneity based on DEA method," 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. 26(4), pages 1005-1025, December.
  • Handle: RePEc:spr:cejnor:v:26:y:2018:i:4:d:10.1007_s10100-018-0563-6
    DOI: 10.1007/s10100-018-0563-6
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    References listed on IDEAS

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    Cited by:

    1. Contreras, I. & Lozano, S., 2022. "Size efficiency, splits and merger gains, and centralized resource reallocation of Spanish public universities," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Xiong, Xi & Yang, Guo-liang & Zhou, De-qun & Wang, Zi-long, 2022. "How to allocate multi-period research resources? Centralized resource allocation for public universities in China using a parallel DEA-based approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Josef Jablonský & Ali Emrouznejad & Mehdi Toloo, 2018. "Editorial: Special issue on data envelopment analysis," 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. 26(4), pages 809-812, December.
    4. Lozano, Sebastián & Contreras, Ignacio, 2022. "Centralised resource allocation using Lexicographic Goal Programming. Application to the Spanish public university system," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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