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The fair allocation of common fixed cost or revenue using DEA concept

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  • M. Khodabakhshi
  • K. Aryavash

Abstract

The common fixed cost or revenue distribution amongst decision making units (briefly, DMUs) in an equitable way is one of the problems that can be solved by data envelopment analysis (DEA) concept. The motivation of this paper is common fixed cost or revenue allocation based on following three principles: First, allocation must be directly proportional to the elements (inputs and outputs) that are directly proportional to imposed common fixed cost or to obtained common fixed revenue. Second, allocation must be inversely proportional to the elements that are inversely proportional to common fixed cost or revenue. Finally, the elements that have no effect on common fixed cost or revenue must have no effect on allocation as well. Copyright Springer Science+Business Media, LLC 2014

Suggested Citation

  • M. Khodabakhshi & K. Aryavash, 2014. "The fair allocation of common fixed cost or revenue using DEA concept," Annals of Operations Research, Springer, vol. 214(1), pages 187-194, March.
  • Handle: RePEc:spr:annopr:v:214:y:2014:i:1:p:187-194:10.1007/s10479-012-1117-2
    DOI: 10.1007/s10479-012-1117-2
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    1. Athanassopoulos, Antreas D., 1995. "Goal programming & data envelopment analysis (GoDEA) for target-based multi-level planning: Allocating central grants to the Greek local authorities," European Journal of Operational Research, Elsevier, vol. 87(3), pages 535-550, December.
    2. Chien-Ming Chen & Joe Zhu, 2011. "Efficient Resource Allocation via Efficiency Bootstraps: An Application to R&D Project Budgeting," Operations Research, INFORMS, vol. 59(3), pages 729-741, June.
    3. Cook, Wade D. & Kress, Moshe, 1999. "Characterizing an equitable allocation of shared costs: A DEA approach," European Journal of Operational Research, Elsevier, vol. 119(3), pages 652-661, December.
    4. Thanassoulis, E., 1996. "A data envelopment analysis approach to clustering operating units for resource allocation purposes," Omega, Elsevier, vol. 24(4), pages 463-476, August.
    5. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    6. Li, Yongjun & Yang, Feng & Liang, Liang & Hua, Zhongsheng, 2009. "Allocating the fixed cost as a complement of other cost inputs: A DEA approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 389-401, August.
    7. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    8. Emrouznejad, A. & De Witte, K., 2010. "COOPER-framework: A Unified Standard Process for Non-parametric Projects," Working Papers 18, Top Institute for Evidence Based Education Research.
    9. Darko Skorin-Kapov, 2001. "On Cost Allocation in Hub-Like Networks," Annals of Operations Research, Springer, vol. 106(1), pages 63-78, September.
    10. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    11. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
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    4. Yongjun Li & Feng Li & Ali Emrouznejad & Liang Liang & Qiwei Xie, 2019. "Allocating the fixed cost: an approach based on data envelopment analysis and cooperative game," Annals of Operations Research, Springer, vol. 274(1), pages 373-394, March.
    5. Benjamin Hampf & Kenneth Løvold Rødseth, 2017. "Optimal profits under environmental regulation: the benefits from emission intensity averaging," Annals of Operations Research, Springer, vol. 255(1), pages 367-390, August.
    6. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal Profits under Environmental Regulation: The Benefits from Emission Intensity Averaging," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 68011, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    9. Feng Li & Qingyuan Zhu & Liang Liang, 2019. "A new data envelopment analysis based approach for fixed cost allocation," Annals of Operations Research, Springer, vol. 274(1), pages 347-372, March.
    10. Adriana Lucía Contreras León & Gloria Isabel Rodriguez Lozano, 2016. "Medición de la eficiencia relativa de fincas ganaderas con servicio de asistencia técnica," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, vol. 25(1), pages 117-128, December.
    11. 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.
    12. 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).
    13. Li, Feng & Zhu, Qingyuan & Chen, Zhi, 2019. "Allocating a fixed cost across the decision making units with two-stage network structures," Omega, Elsevier, vol. 83(C), pages 139-154.
    14. 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.
    15. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    16. 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.
    17. Lanqing Du & Jinwook Lee, 2023. "Workforce pDEI: Productivity Coupled with DEI," Papers 2311.11231, arXiv.org, revised Dec 2023.
    18. I. Contreras & M. A. Hinojosa, 2021. "A note on “The cross-efficiency in the optimistic–pessimistic framework”," Operational Research, Springer, vol. 21(2), pages 1393-1401, June.
    19. An, Qingxian & Tao, Xiangyang & Xiong, Beibei & Chen, Xiaohong, 2022. "Frontier-based incentive mechanisms for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 302(1), pages 294-308.
    20. Youchao Tan & Yang Zhang & Roohollah Khodaverdi, 2017. "Service performance evaluation using data envelopment analysis and balance scorecard approach: an application to automotive industry," Annals of Operations Research, Springer, vol. 248(1), pages 449-470, January.

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