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Robustness analysis for imprecise additive value efficiency analysis with an application to evaluation of special economic zones in Poland

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  • Labijak-Kowalska, Anna
  • Kadziński, Miłosz
  • Dias, Luis C.

Abstract

We introduce an algorithmic framework for investigating the robustness of efficiency analysis results in the presence of imprecise information about data and preferences. We employ an additive value efficiency model accepting ordinal and interval information about the performances of Decision Making Units and imprecision in the specification of input and output weights and the shapes of marginal value functions. We verify the stability of efficiency measures using a combination of mathematical programming and Monte Carlo simulations. The results capture various certainty levels, emphasizing the necessary, possible, extreme, and expected outcomes and the distribution of outcomes in the space of feasible weights, performances, and marginal functions. The practical usefulness of the proposed framework is demonstrated in a real-world problem concerning the functioning of Special Economic Zones in Poland. We discuss results that increase the discrimination power, indicate overall good performances, and provide hints on the required improvements.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:soceps:v:92:y:2024:i:c:s0038012124000120
    DOI: 10.1016/j.seps.2024.101813
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    1. 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.
    2. Merja Halme & Tarja Joro & Pekka Korhonen & Seppo Salo & Jyrki Wallenius, 1999. "A Value Efficiency Approach to Incorporating Preference Information in Data Envelopment Analysis," Management Science, INFORMS, vol. 45(1), pages 103-115, January.
    3. F. Hosseinzadeh Lotfi & G. R. Jahanshahloo & M. Khodabakhshi & M. Rostamy-Malkhlifeh & Z. Moghaddas & M. Vaez-Ghasemi, 2013. "A Review of Ranking Models in Data Envelopment Analysis," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-20, July.
    4. Kadziński, Miłosz & Tervonen, Tommi, 2013. "Robust multi-criteria ranking with additive value models and holistic pair-wise preference statements," European Journal of Operational Research, Elsevier, vol. 228(1), pages 169-180.
    5. Kadziński, MiŁosz & Greco, Salvatore & SŁowiński, Roman, 2012. "Extreme ranking analysis in robust ordinal regression," Omega, Elsevier, vol. 40(4), pages 488-501.
    6. Pereira, Miguel Alves & Figueira, José Rui & Marques, Rui Cunha, 2020. "Using a Choquet integral-based approach for incorporating decision-maker’s preference judgments in a Data Envelopment Analysis model," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1016-1030.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. M C Gouveia & L C Dias & C H Antunes, 2008. "Additive DEA based on MCDA with imprecise information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 54-63, January.
    9. Anna Labijak-Kowalska & Miłosz Kadziński, 2023. "Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis," Operational Research, Springer, vol. 23(1), pages 1-34, March.
    10. 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.
    11. Kadziński, Miłosz & Labijak, Anna & Napieraj, Małgorzata, 2017. "Integrated framework for robustness analysis using ratio-based efficiency model with application to evaluation of Polish airports," Omega, Elsevier, vol. 67(C), pages 1-18.
    12. Zhu, Joe, 2003. "Imprecise data envelopment analysis (IDEA): A review and improvement with an application," European Journal of Operational Research, Elsevier, vol. 144(3), pages 513-529, February.
    13. Lahdelma, Risto & Salminen, Pekka, 2006. "Stochastic multicriteria acceptability analysis using the data envelopment model," European Journal of Operational Research, Elsevier, vol. 170(1), pages 241-252, April.
    14. Pereira, André Alves & Pereira, Miguel Alves, 2023. "Energy storage strategy analysis based on the Choquet multi-criteria preference aggregation model: The Portuguese case," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    15. Petrović, Marijana & Bojković, Nataša & Stamenković, Mladen & Anić, Ivan, 2018. "Supporting performance appraisal in ELECTRE based stepwise benchmarking model," Omega, Elsevier, vol. 78(C), pages 237-251.
    16. Risto Lahdelma & Pekka Salminen, 2001. "SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making," Operations Research, INFORMS, vol. 49(3), pages 444-454, June.
    17. Ahti Salo & Antti Punkka, 2011. "Ranking Intervals and Dominance Relations for Ratio-Based Efficiency Analysis," Management Science, INFORMS, vol. 57(1), pages 200-214, January.
    18. Kadziński, Miłosz & Stamenković, Mladen & Uniejewski, Maciej, 2022. "Stepwise benchmarking for multiple criteria sorting," Omega, Elsevier, vol. 108(C).
    19. Tarja Joro & Pekka J. Korhonen, 2015. "Extension of Data Envelopment Analysis with Preference Information," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4899-7528-7, April.
    20. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge & Solares, Efrain, 2022. "Handling imperfect information in multiple criteria decision-making through a comprehensive interval outranking approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    21. Alvarez, Pavel Anselmo & Valdez, Cuitláhuac & Dutta, Bapi, 2022. "Analysis of the innovation capacity of Mexican regions with the multiple criteria hierarchy process," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    22. L C Dias & J N Clímaco, 2000. "Additive aggregation with variable interdependent parameters: the VIP analysis software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(9), pages 1070-1082, September.
    23. M C Gouveia & L C Dias & C H Antunes, 2013. "Super-efficiency and stability intervals in additive DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(1), pages 86-96, January.
    24. Salo, Ahti A. & Hamalainen, Raimo P., 1995. "Preference programming through approximate ratio comparisons," European Journal of Operational Research, Elsevier, vol. 82(3), pages 458-475, May.
    25. Cook, Wade D. & Zhu, Joe, 2007. "Classifying inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 180(2), pages 692-699, July.
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