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Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach

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Listed:
  • Tao Ding

    (Hefei University of Technology)

  • Ya Chen

    (Hefei University of Technology)

  • Huaqing Wu

    (Hefei University of Technology)

  • Yuqi Wei

    (Hefei University of Technology)

Abstract

Many studies have concentrated on fixed cost and resource allocation issues by using data envelopment analysis (DEA). The existing approaches allocate fixed cost or resource primary based on efficiency principle. They usually assume that all of the DMUs become efficient after fixed cost or resource allocation. However, due to the existing of technology heterogeneity among DMUs, it is impractical for all the DMUs to achieve a common technology level, especially when some DMUs are far from the efficient frontier. In this paper, under the centralized decision environment, we present a new approach to deal with fixed cost and resource allocation problems by considering the factor of technology heterogeneity. Specifically, the concepts of meta-efficiency and group efficiency as well as meta-technology ratio are firstly introduced to reflect the technology level of the DMUs. Then two centralized DEA models considering technology heterogeneity are proposed to allocate fixed cost and resources, respectively. Finally, two numerical examples are presented to illustrate the feasibility and superiority of the proposed approach compared with prior studies.

Suggested Citation

  • Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.
    • Handle: RePEc:spr:annopr:v:268:y:2018:i:1:d:10.1007_s10479-017-2414-6
    DOI: 10.1007/s10479-017-2414-6
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    3. Mohsen Afsharian, 2020. "A metafrontier-based yardstick competition mechanism for incentivising units in centrally managed multi-group organisations," Annals of Operations Research, Springer, vol. 288(2), pages 681-700, May.
    4. Elizabeth Ahikiriza & Jef Meensel & Xavier Gellynck & Ludwig Lauwers, 2021. "Heterogeneity in frontier analysis: does it matter for benchmarking farms?," Journal of Productivity Analysis, Springer, vol. 56(2), pages 69-84, December.
    5. 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.
    6. Li, Yongjun & Lin, Lin & Dai, Qianzhi & Zhang, Linda, 2020. "Allocating common costs of multinational companies based on arm's length principle and Nash non-cooperative game," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1002-1010.
    7. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).
    8. Jiasen Sun & Guo Li, 2022. "Optimizing emission reduction task sharing: technology and performance perspectives," Annals of Operations Research, Springer, vol. 316(1), pages 581-602, September.
    9. Mehdi Soltanifar & Farhad Hosseinzadeh Lotfi & Hamid Sharafi & Sebastián Lozano, 2022. "Resource allocation and target setting: a CSW–DEA based approach," Annals of Operations Research, Springer, vol. 318(1), pages 557-589, November.
    10. Qingxian An & Ping Wang & Honglin Yang & Zongrun Wang, 2021. "Fixed cost allocation in two-stage system using DEA from a noncooperative view," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1077-1102, December.
    11. Yu, Anyu & Zhang, Qin & Yu, Rongjian & Cheng, Yu, 2023. "More is better or in waste? A resource allocation measure of government grants for facilitating firm innovations," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    12. Ding, Tao & Yang, Jie & Wu, Huaqing & Liang, Liang, 2022. "Land use efficiency and technology gaps of urban agglomerations in China: An extended non-radial meta-frontier approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    13. An, Qingxian & Wang, Ping & Emrouznejad, Ali & Hu, Junhua, 2020. "Fixed cost allocation based on the principle of efficiency invariance in two-stage systems," European Journal of Operational Research, Elsevier, vol. 283(2), pages 662-675.
    14. Tao Xu & Jianxin You & Yilei Shao, 2020. "Efficiency of China’s Listed Securities Companies: Estimation through a DEA-Based Method," Mathematics, MDPI, vol. 8(4), pages 1-16, April.

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