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A data envelopment analysis approach to clustering operating units for resource allocation purposes

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  • Thanassoulis, E.

Abstract

Bodies such as those funding education or health services normally make use of marginal resource levels (e.g. the level of funding per pupil) to allocate resources to operating units. It is typically desired that marginal resource levels should encourage the operating units to use resources as efficiently as possible. This paper develops a method for simultaneously clustering operating units and determining a different set of marginal resource levels for resourcing the units of each cluster, consistent with the foregoing aim. The user controls the number of clusters created, striking a balance between the multiplicity of sets of marginal resource levels estimated and the strength of the incentive offered to operating units to use a resource efficiently. The clusters identified can prove useful in themselves in that operating units sharing similar environmental conditions and/or value systems are identified.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jomega:v:24:y:1996:i:4:p:463-476
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    Cited by:

    1. Sakouvogui Kekoura & Shaik Saleem & Addey Kwame Asiam, 2020. "Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector," Open Economics, De Gruyter, vol. 3(1), pages 50-69, January.
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    3. Afsharian, Mohsen & Bogetoft, Peter, 2023. "Limiting flexibility in nonparametric efficiency evaluations: An ex post k-centroid clustering approach," European Journal of Operational Research, Elsevier, vol. 311(2), pages 633-647.
    4. Giokas, Dimitris I., 2001. "Greek hospitals: how well their resources are used," Omega, Elsevier, vol. 29(1), pages 73-83, February.
    5. repec:lan:wpaper:1031 is not listed on IDEAS
    6. Thanassoulis, Emmanuel, 2000. "The use of data envelopment analysis in the regulation of UK water utilities: Water distribution," European Journal of Operational Research, Elsevier, vol. 126(2), pages 436-453, October.
    7. repec:lan:wpaper:1046 is not listed on IDEAS
    8. 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.
    9. Heris Golpira, 2016. "A Hybrid Clustering Method Using Balanced Scorecard and Data Envelopment Analysis," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 2(1), pages 15-22, April 10..
    10. Romano, Teresa & Cambini, Carlo & Fumagalli, Elena & Rondi, Laura, 2022. "Setting network tariffs with heterogeneous firms: The case of natural gas distribution," European Journal of Operational Research, Elsevier, vol. 297(1), pages 280-290.
    11. E Thanassoulis & M Kortelainen & G Johnes & J Johnes, 2011. "Costs and efficiency of higher education institutions in England: a DEA analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1282-1297, July.
    12. Ross, Anthony D., 2000. "Performance-based strategic resource allocation in supply networks," International Journal of Production Economics, Elsevier, vol. 63(3), pages 255-266, January.
    13. Amin, Gholam R. & Emrouznejad, Ali & Rezaei, S., 2011. "Some clarifications on the DEA clustering approach," European Journal of Operational Research, Elsevier, vol. 215(2), pages 498-501, December.
    14. Aleskerov, Fuad & Ersel, Hasan & Yolalan, Reha, 2003. "Personnel allocation among bank branches using a two-stage multi-criterial approach," European Journal of Operational Research, Elsevier, vol. 148(1), pages 116-125, July.
    15. Ray R. Hashemi & Louis A. Le Blanc, 2000. "Resource Allocation through Negotiation and Compromise: A Database Approach," Group Decision and Negotiation, Springer, vol. 9(4), pages 325-345, July.
    16. Yu, Ming-Miin & Chern, Ching-Chin & Hsiao, Bo, 2013. "Human resource rightsizing using centralized data envelopment analysis: Evidence from Taiwan's Airports," Omega, Elsevier, vol. 41(1), pages 119-130.
    17. Ming-Miin Yu & Chih-Ku Fan, 2006. "Measuring the Cost Effectiveness of Multimode Bus Transit in the Presence of Accident Risks," Transportation Planning and Technology, Taylor & Francis Journals, vol. 29(5), pages 383-407, July.
    18. Afsharian, Mohsen & Ahn, Heinz & Thanassoulis, Emmanuel, 2019. "A frontier-based system of incentives for units in organisations with varying degrees of decentralisation," European Journal of Operational Research, Elsevier, vol. 275(1), pages 224-237.
    19. Ming-Miin Yu, 2008. "Measuring the efficiency and return to scale status of multi-mode bus transit - evidence from Taiwan's bus system," Applied Economics Letters, Taylor & Francis Journals, vol. 15(8), pages 647-653.
    20. Wu, Jie & Liang, Liang & Yang, Feng, 2009. "Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method," European Journal of Operational Research, Elsevier, vol. 197(2), pages 722-730, September.
    21. Beasley, J. E., 2003. "Allocating fixed costs and resources via data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 198-216, May.
    22. repec:lan:wpaper:1109 is not listed on IDEAS
    23. Paradi, Joseph C. & Zhu, Haiyan & Edelstein, Barak, 2012. "Identifying managerial groups in a large Canadian bank branch network with a DEA approach," European Journal of Operational Research, Elsevier, vol. 219(1), pages 178-187.
    24. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.

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