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Value-based DEA models: application-driven developments

Author

Listed:
  • P N de Almeida

    (EXIMIUS Consulting, Coimbra, Portugal)

  • L C Dias

    (INESC Coimbra and Faculty of Economics, University of Coimbra, Coimbra, Portugal)

Abstract

Data envelopment analysis (DEA) is an approach based on linear programming to assess the relative efficiency of peer decision-making units (DMUs). Typically, each DMU is free to choose the weights of the factors used in its evaluation. However, the evaluator's preferences may not warrant so much freedom. Several approaches have been proposed to allow the incorporation of managerial preferences in DEA, but few address the additive DEA model specifically. This paper presents additive DEA models that use multi-criteria decision analysis concepts to incorporate managerial preferences, and presents the corresponding preference elicitation protocols. The models developed allow the incorporation of preferences at different levels: on valuing performance improvements, on introducing weight restrictions, and on finding adequate targets. These were application-driven developments, resulting from discussing modelling options and preliminary results with the top-level management of a retail chain in the context of an assessment of stores’ performance, also described in this paper.

Suggested Citation

  • P N de Almeida & L C Dias, 2012. "Value-based DEA models: application-driven developments," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(1), pages 16-27, January.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:1:p:16-27
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    Citations

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    Cited by:

    1. Venkataraghavan Krishnaswamy & R. P. Sundarraj, 2017. "Organizational implications of a comprehensive approach for cloud-storage sourcing," Information Systems Frontiers, Springer, vol. 19(1), pages 57-73, February.
    2. Henriques, C.O. & Gouveia, C.M. & Tenente, M. & da Silva, P.P., 2022. "Employing Value-Based DEA in the eco-efficiency assessment of the electricity sector," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 826-844.
    3. Henriques, C.O. & Gouveia, M.C., 2022. "Assessing the impact of COVID-19 on the efficiency of Portuguese state-owned enterprise hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Salvatore Ammirato & Gerarda Fattoruso & Antonio Violi, 2022. "Parsimonious AHP-DEA Integrated Approach for Efficiency Evaluation of Production Processes," JRFM, MDPI, vol. 15(7), pages 1-15, June.
    5. Michalis Doumpos & Alexis Guyot & Emilios Galariotis & Constantin Zopounidis, 2020. "Assessing the quality of life in French municipalities: a multidimensional approach," Annals of Operations Research, Springer, vol. 293(2), pages 789-808, October.
    6. Gouveia, M.C. & Henriques, C.O. & Costa, P., 2021. "Evaluating the efficiency of structural funds: An application in the competitiveness of SMEs across different EU beneficiary regions," Omega, Elsevier, vol. 101(C).
    7. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
    8. Labijak-Kowalska, Anna & Kadziński, Miłosz & Dias, Luis C., 2024. "Robustness analysis for imprecise additive value efficiency analysis with an application to evaluation of special economic zones in Poland," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    9. Gouveia, M.C. & Henriques, C.O. & Dias, L.C., 2023. "Eco-efficiency changes of the electricity and gas sectors across 28 European countries: A value-based data envelopment analysis productivity approach," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    10. Santos, Sérgio P. & Belton, Valerie & Howick, Susan & Pilkington, Martin, 2018. "Measuring organisational performance using a mix of OR methods," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 18-30.
    11. Gouveia, M.C. & Dias, L.C. & Antunes, C.H. & Boucinha, J. & Inácio, C.F., 2015. "Benchmarking of maintenance and outage repair in an electricity distribution company using the value-based DEA method," Omega, Elsevier, vol. 53(C), pages 104-114.
    12. Subrata Mitra & Balram Avittathur, 2018. "Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 207-224, September.
    13. Henriques, C.O. & Chavez, J.M. & Gouveia, M.C. & Marcenaro-Gutierrez, O.D., 2022. "Efficiency of secondary schools in Ecuador: A value based DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    14. Wang, H., 2015. "A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator," Energy, Elsevier, vol. 80(C), pages 114-122.
    15. M. C. Gouveia & L. C. Dias & C. H. Antunes & M. A. Mota & E. M. Duarte & E. M. Tenreiro, 2016. "An application of value-based DEA to identify the best practices in primary health care," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 743-767, July.

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