A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 285-303.

Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we compare Stochastic-DEA and Fuzzy-DEA models to assess, respectively, how the underlying randomness and fuzziness impact efficiency levels. The proposed models have been demonstrated using an application in Angolan banks. Findings reveal that conclusions with respect to the ranking of DMUs may vary substantially depending upon the type of the model chosen, although efficiency scores are similar to some extent when compared within the ambits of Stochastic-DEA and Fuzzy-DEA models. Additionally, modeling choices on fuzziness, rather than on randomness, appears to be the most critical source for variations in efficiency rankings. Managerial implications for Angolan banks are also explored.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2016065
Classification : 90C05, 62F40, 62U20, 03B52
Mots-clés : Data envelopment analysis, Angola Fuzzy-DEA, Stochastic-DEA, KL-Divergence
Wanke, P. 1 ; Barros, C.P. 1 ; Emrouznejad, A. 1

1
@article{RO_2018__52_1_285_0,
     author = {Wanke, P. and Barros, C.P. and Emrouznejad, A.},
     title = {A comparison between stochastic {DEA} and fuzzy {DEA} approaches: revisiting efficiency in {Angolan} banks},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {285--303},
     publisher = {EDP-Sciences},
     volume = {52},
     number = {1},
     year = {2018},
     doi = {10.1051/ro/2016065},
     mrnumber = {3812481},
     zbl = {1403.90440},
     language = {en},
     url = {http://www.numdam.org/articles/10.1051/ro/2016065/}
}
TY  - JOUR
AU  - Wanke, P.
AU  - Barros, C.P.
AU  - Emrouznejad, A.
TI  - A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks
JO  - RAIRO - Operations Research - Recherche Opérationnelle
PY  - 2018
SP  - 285
EP  - 303
VL  - 52
IS  - 1
PB  - EDP-Sciences
UR  - http://www.numdam.org/articles/10.1051/ro/2016065/
DO  - 10.1051/ro/2016065
LA  - en
ID  - RO_2018__52_1_285_0
ER  - 
%0 Journal Article
%A Wanke, P.
%A Barros, C.P.
%A Emrouznejad, A.
%T A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks
%J RAIRO - Operations Research - Recherche Opérationnelle
%D 2018
%P 285-303
%V 52
%N 1
%I EDP-Sciences
%U http://www.numdam.org/articles/10.1051/ro/2016065/
%R 10.1051/ro/2016065
%G en
%F RO_2018__52_1_285_0
Wanke, P.; Barros, C.P.; Emrouznejad, A. A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 285-303. doi : 10.1051/ro/2016065. http://www.numdam.org/articles/10.1051/ro/2016065/

[1] N. Adler and J. Berechman, Measuring airport quality from the airlines’ viewpoint: an application of data envelopment analysis. Transp. Policy 8 (2001) 171–181 | DOI

[2] H.Y. Aly, R. Grabowski, C. Pasurka and N. Rangan, Technical, scale and allocative efficiencies in U.S. banking: An empirical investigation. The Rev. Econ. Stat. 72 (1990) 211–218 | DOI

[3] A. Amirteimoori and A. Emrouznejad, Flexible measures in production process: A DEA-based approach. RAIRO: OR 45 (2011) 63–74 | DOI | Numdam | MR | Zbl

[4] N.S. Arunraj, S. Mandal and J. Maiti, Modeling uncertainty in risk assessment: An integrated approach with fuzzy set theory and Monte Carlo simulation. Accid. Analysis Prev. 55 (2013) 242–255 | DOI

[5] M. Asmild, P. Bogetoft and J. Leth Hougaard Rationalising inefficiency: Staff utilisation in branches of a large Canadian bank. Omega 41 (2013) 80–87 | DOI

[6] M. Asmild, C.C. Paradi, V. Aggarwall and C. Schaffnit, Combining DEA window analysis with the Malmquist index approach in a study of the Canadian banking industry. J. Prod. Anal. 21 (2011) 67–89 | DOI

[7] A. Assaf, C.P. Barros and A. Ibiwoye, Performance assessment of Nigerian Banks prior and post consolidation: Evidence from a Bayesian approach. The Serv. Industries J. 32 (2010) 215–229 | DOI

[8] J.P. Azam, B. Biais and M. Dia, Privatisation versus Regulation in Developing Economies: The Case of West African Banks. J. Afr Econ. 13 (2004) 361–394 | DOI

[9] R.D. Banker, A. Charnes and W.W. Cooper, Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Sci. 30 (1984) 1078–1092 | DOI | Zbl

[10] R. Banker, Stochastic data envelopment analysis. Carnegie-Mellon University, Pittsburgh (1986)

[11] C.P. Barros, N. Peypoch and J. Williams, A Note on Productivity Change in European Cooperative Banks: The Luenberger Indicator Approach. Int. Rev. Appl. Econ. 24 (2010) 137–147 | DOI

[12] C.P. Barros and Zorro Mendes, Assessing the competition in Angola’s banking industry. Applied Economics (forthcoming) (2016)

[13] C.P. Barros, C. Ferreira and J. Williams, Analysing the Determinants of Performance of Best and Worst European Banks: A Mixed Logit Approach. Journal of Banking and Finance 31 (2007) 2189–2203 | DOI

[14] C.P. Barros, S. Managi and R. Matousek, The Technical Efficiency of the Japanese Banks: Non Radial Directional Performance Measurement with Undesirable Output. Omega 40 (2012) 1–8 | DOI

[15] C.P. Barros, O. Gonçalves and N. Peypoch, French regional public airports technical efficiency. Int. J. Transp. Econ. 39 (2012) 255–274

[16] C.P. Barros, Q.B. Liang and N. Peypoch, Technical Efficiency in the Angolan Banking Sector with the B-Convexity Model. South Afr. J. Econ. 82 (2014) 443–454 | DOI

[17] P.W. Bauer, A.N. Berger and D.B. Humphrey, Efficiency and Productivity Growth in US Banking. In The Measurement of Productive Efficiency: Techniques and Applications, edited by H.O. Fried, C.A.K. Lovell and S.S. Schmidt. Oxford University Press Oxford (1993) 386–413

[18] A.N. Berger, G.A. Hanweck and D.B. Humphrey, Competitive Viability in Banking: Scale, Scope, and Product Mix Economies. J. Monetary Econ. 20 (1987) 501–520 | DOI

[19] A.N. Berger and D.B. Humphrey, Measurement and efficiency issues in commercial banking. In: Output measurement in the service sectors, edited by Z. Griliches. Chicago: University of Chicago Press, Chicago (1992).

[20] A.N. Berger and D.B. Humphrey, Efficiency of financial institutions: international survey and directions for future research. Eur. J. Oper. Res. 98 (1997) 175–212 | DOI | Zbl

[21] A.N. Berger, I. Hasan and M. Zhou, Bank ownership and efficiency in China: what will happen in the world’s largest nation? Journal of Banking and Finance 33 (2009) 113–130 | DOI

[22] L.C. Brandão and J.C.S. Mello, Improvements to Smooth Data Envelopment Analysis. RAIRO: OR 51 (2017) 157–171 | DOI | Numdam | MR | Zbl

[23] F. Brázdik, Stochastic Data Envelopment Analysis: Oriented and Linearized Models, CERGE-EI. Available at: http://home.cerge-ei.cz/brazdik/download/grantmain.pdf (2004)

[24] J.G. Brida, M. Deidda and M. Pulina, Tourism and transport systems in mountain environments: analysis of the economic efficiency of cableways in South Tyrol. J. Transp. Geogr. 36 (2014) 1–11 | DOI

[25] A. Charnes, W.W. Cooper and E. Rhodes, Chance constrained programming. Management Sci. 6 (1959) 73–79 | DOI | MR | Zbl

[26] A. Charnes, W.W. Cooper and E. Rhodes, Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978) 429–444 | DOI | MR | Zbl

[27] T.-Y. Chen, A comparison of chance-constrained DEA and stochastic frontier analysis: bank efficiency in Taiwan. J. Operational Res. Soc. 53 (2002) 492–500 | DOI | Zbl

[28] X. Chen, M. Skully and K. Brown, Banking efficiency in China: Application of DEA to pre- and post-deregulations era: 1993-2000. China Econ. Rev. 16 (2005) 229–245 | DOI

[29] Y.-C. Chen, Y.-H. Chiu, C.-W. Huang and C.-H. Tu, The analysis of bank business performance and market risk – Applying Fuzzy DEA. Econ. Model. 32 (2013) 225–232 | DOI

[30] D.G. Clayton, A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65 (1978) 141–152 | DOI | MR | Zbl

[31] B. Cobb, Mixture distributions for modelling demand during lead time. J. Oper. Res. Soc. 64 (2013) 217–228 | DOI

[32] W.W. Cooper, Z. Huang and S. Li, Satisficing DEA models under chance constraints. Ann. Oper. Res. 66 (1996) 259–279 | DOI | MR | Zbl

[33] W.W. Cooper, K.S. Park and G. Yu, IDEA and AR-IDEA models for dealing with imprecise data in DEA. Management Sci. 45 (1999) 597–607 | DOI | Zbl

[34] W.W. Cooper, H. Deng, Z.M. Huang and S.X. Li, Chance constrained programming approaches to technical efficiencies and inefficiencies in stochastic data envelopment analysis. J. Operational Res. Soc. 53 (2002) 1347–1356 | DOI | Zbl

[35] W.W. Cooper, H. Deng, Z. Huang and S.X. Li, Chance constrained programming approaches to congestion in stochastic data envelopment analysis. Eur. J. Oper. Res. 155 (2004) 487–501 | DOI | MR | Zbl

[36] L. Coroianu, M. Gagolewski and P. Grzegorzewski, Nearest piecewise linear approximation of fuzzy numbers. Fuzzy Sets and Syst. 233 (2013) 26–51 | DOI | MR | Zbl

[37] J. Cubbin and G. Tzanidakis, Regression versus data envelopment analysis for efficiency measurement: an application to the Englandand Wales regulated water industry. Util. Policy 7 (1998) 75–85 | DOI

[38] D.K. Despotis and Y.G. Smirlis, Data envelopment analysis with imprecise data. Eur. J. Oper. Res. 140 (2002) 24–36 | DOI | MR | Zbl

[39] J. Dobri?, and F. Schmid, Nonparametric estimation of the lower tail dependence Î? l in bivariate copulas. J. Appl. Stat. 32 (2005) 387–407 | DOI | MR | Zbl

[40] R.G. Dyson and E.A. Shale, Data envelopment analysis, operational research and uncertainty. J. Oper. Res. Soc. 61 (2010) 25–34 | DOI | Zbl

[41] B.E. El-Demerdash, I.A. El-Khodary and A.A. Tharwat, Developing a Stochastic Input Oriented Data Envelopment Analysis (SIODEA) Model. Int. J. Adv. Comput. Sci. Appl. 4 (2013) 40–44

[42] A. Emrouznejad and M. Tavana, Performance Measurement with Fuzzy Data Envelopment Analysis. Stud. Fuzziness and Soft Comput. 309 (2014) | DOI

[43] L. Fang and H. Li, Multi-criteria decision analysis for efficient location-allocation problem combining DEA and goal programming. RAIRO: OR 49 (2015) 753–772 | DOI | Numdam | MR | Zbl

[44] D. Fantazzini, The effects of misspecified marginals and copulas on computing the value at risk: A monte carlo study. Comput. Stat. Data Anal. 53 (2009) 2168–2188 | DOI | MR | Zbl

[45] C.A. Favero and L. Pepi, Technical efficiency and scale efficiency in Italian banking sector: A non-parametric approach. Appl. Econ. 27 (1995) 385–395 | DOI

[46] C. Figueira, J. Nellis and D. Parker, Does Ownership affect the Efficiency of African Banks? J. Dev. Areas 40 (2006) 38–63 | DOI

[47] M. Fortin and A. Leclerc, Should we Abandon the Intermediation Approach for Analyzing Banking Performance? (Working Paper No.07-01). Departement d’Economique de la Faculte d’administration à l’Universite de Sherbrooke. Available at: http://gredi.recherche.usherbrooke.ca/wpapers/GREDI-0701.pdf (2007)

[48] M.J. Frank, On the simultaneous associativity of F(x, y) and x + y - F(x, y). Aequationes Mathematicae 19 (1979) 194–226 | DOI | MR | Zbl

[49] H. Fukuyama and W.L. Weber, Estimating indirect allocative inefficiency and productivity change. J. Oper. Res. Soc. 60 (2009a) 1594–1608 | DOI | Zbl

[50] H. Fukuyama and W.L. Weber, A directional slacks-based measure of technical inefficiency. Socio-Econ. Plan Sci. 43 (2009b) 274–287 | DOI

[51] H. Fukuyama and L.W. Weber, A slacks-based inefficiency measure for a two-stage system with bad outputs. Omega 38 (2010) 239–410 | DOI

[52] N.S. Gharneh, A. Nabavieh, D. Gholamiangonabadi and M. Alimoradi, Productivity change and its determinants: Application of the Malmquist index with bootstrapping in Iranian steam power plants. Util. Policy 31 (2014) 114–120 | DOI

[53] D. Gstach, Another approach to data envelopment analysis in noisy environments: DEA+. J. Prod. Analysis 9 (1998) 161–176 | DOI

[54] E.J. Gumbel, Bivariate exponential distributions. J. Am. Statistical Assoc. 55 (1960) 698–707 | DOI | MR | Zbl

[55] P. Guo and H. Tanaka, Fuzzy Dea: a perceptual evaluation method. Fuzzy Sets and Syst. 119 (2001) 149–160 | DOI | MR

[56] D. Guyonnet, B.B. Bourgine, D. Dubois, G. Fargier, B. Côme and J.P. Chilès, Hybrid approach for addressing uncertainty in risk assessments. J. Environ. Eng. 129 (2003) 68–78 | DOI

[57] A. Hatami-Marbini, A. Emrouznejad and M. Tavana, A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making. Eur. J. Oper. Res., 214 (2011) 457–472 | DOI | MR | Zbl

[58] A. Hatami-Marbini, S. Saati and M. Tavana, Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach. Int. J. Operations Res. Inf. Syst. 2 (2011) 39–53 | DOI

[59] A. Hatami-Marbini, M. Tavana, S. Saati and P.J. Agrell, Positive and normative use of fuzzy DEA-BCC models: A critical view on NATO enlargement. Int. Trans. Oper. Res. 20 (2013) 1–23 | DOI | Zbl

[60] M. Hemmati, S.A. Dalghandi and H. Nazari, Measuring relative performance of banking industry using a DEA and TOPSIS. Meas. Sci. Lett. 3 (2013) 499–503

[61] D. Holod and H.F. Lewis, Resolving the deposit dilemma: A new DEA bank efficiency model. J. Bank. Finance 35 (2011) 2801–2810 | DOI

[62] B. Hsiao, C.-C. Chern, Y.-H. Chiu and C.-R. Chiu, Using fuzzy super-efficiency slack-based measure data envelopment analysis to evaluate Taiwan’s commercial bank efficiency. Expert Syst. Appl. 38 (2011) 9147–9156 | DOI

[63] Z. Huang and S.X. Li, Stochastic DEA models with different types of input-output disturbances. J. Prod. Analysis 15 (2001) 95–113 | DOI

[64] S.I. Ikhide, Measuring the operational efficiency of commercial banks in Namibia. South Afr. J. Econ. 76 (2008) 586–595 | DOI

[65] G.R. Jahanshahloo, M. Soleimani-Damaneh and E. Nasrabadi, Measure of efficiency in DEA with fuzzy input–output levels: a methodology for assessing, ranking and imposing of weights restrictions. Appl. Math. Comput. 156 (2004) 175–187 | MR | Zbl

[66] G.R. Jahanshahloo, J. Sadeghi and M. Khodabakhshi, Fair ranking of the decision making units using optimistic and pessimistic weights in data envelopment analysis. RAIRO: OR 51 (2017) 253–260 | DOI | Numdam | MR | Zbl

[67] C. Kao and S.T. Liu, Fuzzy efficiency measures in data envelopment analysis. Fuzzy Sets and Syst. 113 (2000a) 427–437 | DOI | Zbl

[68] C. Kao and S.T. Liu, Data envelopment analysis with missing data: an application to University libraries in Taiwan. J. Operational Res. Soc. 51 (2000b) 897–905 | DOI | Zbl

[69] C. Kao and S.T. Liu, Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks. Eur. J. Oper. Res. 196 (2009) 312–322 | DOI | Zbl

[70] C. Kao and S.T. Liu, Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks. Omega 47 (2014) 90–98 | DOI

[71] H.A. Kebede and B. Wassie, How Efficient Are the Ethiopian Microfinance Institutions in Extending Financial Services to the Poor? A Comparison with the Commercial Banks. J. Afr. Econ. 22 (2013) 112–135 | DOI

[72] E. Kentel and M.M. Aral, Probabilistic-fuzzy health risk modeling. Stoch. Environ. Res. Risk Assess. 18 (2004) 324–338 | DOI | Zbl

[73] M. Khodabakhshi and M. Asgharian, An input relaxation measure of efficiency in stochastic data envelopment analysis. Appl. Math. Model. 33 (2008) 2010–2023 | DOI | MR | Zbl

[74] M. Khodabakhshi, Estimating most productive scale size with stochastic data in data envelopment analysis. Econ. Model. 26 (2009) 968–973 | DOI

[75] C.H. Kirkpatrick, V. Murinde and M. Tefula, The Measurement and Determinants of X-inefficiency in Commercial Banks in Africa. Eur. J. Finance 14 (2007) 625–639 | DOI

[76] H. Kiyota, Efficiency of Commercial Banks in Sub-Saharan Africa: A Comparative Analysis of Domestic and Foreign Banks. Proceeding of CSAE Conference 2009: Economic Development in Africa to be held. University of Oxford (2009)

[77] A. Kontolaimou and K. Tsekouras, Are cooperatives the weakest link in European banking? A non-parametric metafrontier approach. Journal of Banking and Finance 34 (2010) 1946–1957 | DOI

[78] S.C. Kumbhakar and D. Wang, Economic reforms, efficiency and productivity in Chinese banking. State University of New York: Binghamton. Working Paper (2005)

[79] K.C. Land, C.A.K. Lovell and S. Thore, Productive efficiency under capitalism and state socialism: The chance constrained programming approach. Public Finance in a World of Transition 47 (1992) 109–121

[80] K.C. Land, C.A.K. Lovell and S. Thore, Chance-constrained Data Envelopment Analysis. Managerial and Decis. Econ. 14 (1993) 541–54 | DOI

[81] H. Langseth, T.D. Nielsen, I. Perez-Bernabe and A. Salmeron, Learning mixtures of truncated basis functions from data. Int. J. Approx. Reason. 55 (2014) 940–956 | DOI | MR | Zbl

[82] S. Lertworasirikul, S.-C. Fang, J.A. Joines and H.L.W. Nutt, Fuzzy data envelopment analysis: a possibility approach. Fuzzy Sets and Syst., 139 (2003) 379–394 | DOI | MR | Zbl

[83] S.X. Li, Stochastic models and variable returns to scales in data envelopment analysis. European J. Operational Res. 104 (1998) 532–548 | DOI | Zbl

[84] Y. Li, The Asian financial crisis and non-performing loans: Evidences from commercial banks in Taiwan. Int. J. Management 20 (2003) 69–74

[85] S.-T. Liu, A fuzzy DEA/AR approach to the selection of flexible manufacturing systems. Computers and Industrial Engineering 54 (2008) 66–76 | DOI

[86] S.M. Miller and A.G. Noulas, The technical efficiency of large bank production. J. Bank Finance 20 (1996) 495–509 | DOI

[87] H. Morita and L.M. Seiford, Characteristics on stochastic DEA efficiency: Reliability and probability being efficient. J. Oper. Res. Soc. Jpn 42 (1999) 389–404 | MR | Zbl

[88] R.B. Nelsen, An introduction to copulas. Springer, New York (1999) | DOI | MR | Zbl

[89] G.J. O’Donnell and G.V.D. Westhnizen, Regional Comparison of banking performance in South Africa. South Afr. J. Econ. 80 (2002) 246–263

[90] C. O’Donnell, D. Rao and G. Battese, Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empir. Econ. 34 (2007) 231–255 | DOI

[91] C.C. Okeahalam, Internationalisation and firm performance: Evidence from estimates of efficiency in banking in Namibia and Tanzania. J. Int. Dev. 20 (2008) 942–964 | DOI

[92] W.O. Olatubi and D.E. Dismukes, A data envelopment analysis of the levels and determinants of coal-fired electric power generation performance. Util. Policy 9 (2000) 47–59 | DOI

[93] O.B. Olesen and N.C. Petersen, Chance constrained efficiency evaluation. Management Sci. 41 (1995) 442–457 | DOI | Zbl

[94] O.B. Olesen and N.C. Petersen, Stochastic Data Envelopment Analysis – A review. Eur. J. Oper. Res. 251 (2016) 2–21 | DOI | MR | Zbl

[95] J. Puri and S.P. Yadav, A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector. Expert Syst. Appl. 40 (2013) 1437–1450 | DOI

[96] J. Puri and S.P. Yadav, A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India. Expert Syst. Appl. 41 (2014) 6419–6432 | DOI

[97] S.C. Ray, Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research. Cambridge University Press, UK (2004) | DOI | MR | Zbl

[98] S. Saati, A. Memariani and G.R. Jahanshahloo, Efficiency analysis and ranking of DMUs with fuzzy data. Fuzzy Optim. Decis. Mak. 1 (2002) 255–267 | DOI | Zbl

[99] R. Schmidt and U. Stadtmuller, Nonparametric estimation of tail dependence. Scand. J. Statistics 33 (2006) 307–335 | DOI | MR | Zbl

[100] C. Sealey and J.T. Lindley, Inputs, outputs and a theory of production and cost at depository financial institution. J. Finance 32 (1977) 1251–1266 | DOI

[101] J.K. Sengupta, Efficiency measurement in stochastic input-output systems. Int. J. Syst. Sci. 13 (1982) 273–287 | DOI | MR | Zbl

[102] J.K. Sengupta, Data envelopment analysis for efficiency measurement in the stochastic case. Comput. Operations Res. 14 (1987) 117–29 | DOI | Zbl

[103] J.K. Sengupta, Measuring efficiency by a fuzzy statistical approach. Fuzzy Sets and Syst. 46 (1992) 73–80 | DOI

[104] H.D. Sherman and F. Gold, Bank branch operating efficiency: Evaluation with data envelopment analysis. J. Bank Finance 9 (1985) 297–316 | DOI

[105] M. Soleimani-Damaneh, G.R. Jahanshahloo and S. Abbasbandy, Computational and theoretical pitfalls in some current performance measurement techniques and a new approach. Appl. Math. Comput. 181 (2006) 1199–1207 | MR | Zbl

[106] R.B. Staub, G.S. Souza and B.M. Tabak, Evolution of bank efficiency in Brazil: A DEA approach. European J. Bank. Finance 202 (2010) 204–213 | Zbl

[107] T. Sueyoshi, Stochastic DEA for restructure strategy: an application to a Japanese petroleum company. Omega 28 (2000) 385–98 | DOI

[108] F. Sufian, The impact of the Asian financial crisis on bank efficiency: The 1997 experience of Malaysia and Thailand. J. Int. Dev. 22(2010) 866–889 | DOI

[109] S. Thore, Chance-constrained activity analysis. Eur. J. Oper. Res. 30 (1987) 267–269 | DOI

[110] A.Y. Vaninsky, Stochastic DEA with a Perfect Object and Its Application to Analysis of Environmental Efficiency. Am. J. Appl. Math. Statistics 1 (2013) 57–63 | DOI

[111] W.-K. Wang, W.-M. Lu and C.-J. Tsai, The relationship between airline performance and corporate governance amongst US Listed companies. J. Air Transp. Management 17 (2011) 148–152 | DOI

[112] Y. Wang and H. Pham, Modeling the dependent competing risks with multiple degradation processes and random shock using time-varying copulas. IEEE Reliab. Soc. 61 (2012) 13–22 | DOI

[113] W.-K. Wang, W.-M. Lu and P.-L. Liu, A fuzzy multi-objective two-stage DEA model for evaluating the performance of US bank holding companies. Expert Syst. Appl. 41 (2014) 4290–4297 | DOI

[114] P. Wanke and C. Barros, Two-stage DEA: An application to major Brazilian banks. Expert Syst. Appl. 41 (2014) 2337–2344 | DOI

[115] P. Wanke, C. Barros and N.P.J. Macanda, Predicting Efficiency in Angolan Banks: A Two-Stage TOPSIS and Neural Networks Approach. South Afr. J. Econ. 84 (2016) 461–483 | DOI

[116] P. Wanke, C.P. Barros and Z. Chen, An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models. Int. J. Production Econ. 169 (2015b) 110–126 | DOI

[117] P. Wanke, C.P. Barros and A. Emrouznejad, Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. Eur. J. Oper. Res. 249 (2016) 378–389 | DOI | Zbl

[118] M. Welde and J. Odeck, The efficiency of Norwegian road toll companies. Util. Policy 19 (2011) 162–171

[119] D. Wu, Z. Yang and L. Liang, Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert Syst. Appl. 31 (2006) 108–115 | DOI

[120] D.D. Wu and C.-G. Lee, Stochastic DEA with ordinal data applied to a multi-attribute pricing problem. Eur. J. Oper. Res. 207 (2010) 1679–1688 | DOI | Zbl

[121] R. Yager, A new methodology for ordinal multiple aspect decisions based on fuzzy sets. Decis. Sci. 12 (1981) 589–600 | DOI

[122] J. Yan, Enjoy the joy of copulas: with a package copula. J. Statistical Softw. 21 (2007) 1–21

[123] P. Yue, Data envelopment analysis and commercial bank performance: A primer with applications to Missouri banks. Federal Reserve Bank of St. Louis 74 (1992) 31–45

[124] L. Zadeh, Fuzzy sets. Information and Control 8 (1965a) 109–141. | DOI | MR

[125] L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility. Information and Control 9 (1965b) 338–353 | Zbl

[126] L. Zadeh, Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Syst. 1 (1978) 3–28 | DOI | MR | Zbl

[127] M. Zerafat Angiz, A. Emrouznejad and A. Mustafa, Fuzzy assessment of performance of a decision making units using DEA: A non-radial approach. Expert Syst. Appl. 37 (2010) 5153–5157 | DOI

[128] H.J. Zimmermann, Description and optimization of fuzzy system. International J. Gen. Syst. 2 (1976) 209–216 | DOI | Zbl

[129] H.J. Zimmermann, Fuzzy Set Theory – and Its Applications, 3rd edn. Kluwer Academic Publishers, Boston (1996) | DOI | MR | Zbl

[130] S.A. Zonouz and S.G. Miremadi, A fuzzy-monte carlo simulation approach for fault tree analysis. Proceeding of the Reliability and Maintainability Symposium, 2006 – RAMS’06. Annual 2006 428–433

Cité par Sources :