Efficiency factors in OECD banks: A ten-year analysis
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[1] F. Hosseinzadeh Lotfi,et al. Extension of TOPSIS for decision-making problems with interval data: Interval efficiency , 2009, Math. Comput. Model..
[2] Constantin Zopounidis,et al. A multicriteria decision support system for bank rating , 2010, Decis. Support Syst..
[3] J. Powell,et al. Least absolute deviations estimation for the censored regression model , 1984 .
[4] A. Assaf,et al. Bank performance and convergence during the financial crisis: Evidence from the ‘old’ European Union and Eurozone ☆ , 2015 .
[5] Yusuf Tansel Iç,et al. Development of a credit limit allocation model for banks using an integrated Fuzzy TOPSIS and linear programming , 2012, Expert Syst. Appl..
[6] Chenlei Leng,et al. A quantile regression estimator for censored data , 2013, 1302.0181.
[7] Tser-Yieth Chen,et al. A comparison of chance-constrained DEA and stochastic frontier analysis: bank efficiency in Taiwan , 2002, J. Oper. Res. Soc..
[8] Rebel A. Cole,et al. Separating the likelihood and timing of bank failure , 1995 .
[9] B. R. Cobb,et al. Mixture distributions for modelling demand during lead time , 2013, J. Oper. Res. Soc..
[10] Kristiaan Kerstens,et al. Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests , 2011 .
[11] Rebel A. Cole,et al. Predicting Bank Failures: A Comparison of On- and Off-Site Monitoring Systems , 2007 .
[12] A. Micco,et al. Do State-Owned Banks Promote Growth? Cross-Country Evidence for Manufacturing Industries , 2003 .
[13] Carlos Pestana Barros,et al. Productivity and efficiency analysis of Shinkin banks: Evidence from bootstrap and Bayesian approaches , 2011 .
[14] Stephen Portnoy,et al. The jackknife's edge: Inference for censored regression quantiles , 2014, Comput. Stat. Data Anal..
[15] Wen‐Min Lu,et al. The relationship between bank performance and intellectual capital in East Asia , 2013 .
[16] Y. E. Albayrak,et al. A study of bank selection decisions in Turkey using the extented fuzzy AHP method , 2005 .
[17] Allen N. Berger,et al. Competitive viability in banking: Scale, scope, and product mix economies , 1987 .
[18] R. Koenker,et al. Computing regression quantiles , 1987 .
[19] Yusuf Tansel Iç,et al. Development of a quick credibility scoring decision support system using fuzzy TOPSIS , 2010, Expert Syst. Appl..
[20] Cheng-Min Feng,et al. Considering the financial ratios on the performance evaluation of highway bus industry , 2001 .
[21] Te-Won Lee,et al. Independent Component Analysis , 1998, Springer US.
[22] P. Vincke,et al. Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .
[23] Kym Brown,et al. Banking efficiency in China: Application of DEA to pre- and post-deregulation eras: 1993-2000 , 2005 .
[24] Meysam Shaverdi,et al. Combining Fuzzy MCDM with BSC Approach in Performance Evaluation of Iranian Private Banking Sector , 2011, Adv. Fuzzy Syst..
[25] Rolph E. Anderson,et al. Multivariate data analysis (4th ed.): with readings , 1995 .
[26] Jeong Yeon Lee,et al. Bank performance and its determinants in Korea , 2013 .
[27] Irfan Ertugrul,et al. Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods , 2009, Expert Syst. Appl..
[28] Alan Pearman,et al. A Weighted Maximin and Maximax Approach to Multiple Criteria Decision Making , 1977 .
[29] Colin Kirkpatrick,et al. The measurement and determinants of x-inefficiency in commercial banks in Sub-Saharan Africa , 2008 .
[30] S. Greco,et al. Multiple Criteria Hierarchy Process with ELECTRE and PROMETHEE , 2013 .
[31] Anderson Ribeiro Correia,et al. Multicriteria and multivariate analysis for port performance evaluation , 2012 .
[32] Antonio Salmerón,et al. Learning mixtures of truncated basis functions from data , 2014, Int. J. Approx. Reason..
[33] M. Čihák,et al. Determinants of Bank Distress in Europe: Evidence from a New Data Set , 2011 .
[34] J. Powell,et al. Censored regression quantiles , 1986 .
[35] Kristiaan Kerstens,et al. Portfolio Performance Gauging in Discrete Time Using a Luenberger Productivity Indicator , 2009 .
[36] C. Spulbar,et al. Financial Nexus: Efficiency and Soundness in Banking and Capital Markets , 2014 .
[37] Z Yang,et al. Assessing the performance of Canadian bank branches using data envelopment analysis , 2009, J. Oper. Res. Soc..
[38] A. Assaf,et al. Turkish bank efficiency: Bayesian estimation with undesirable outputs , 2013 .
[39] Sophocles N. Brissimis,et al. Technical and allocative efficiency in European banking , 2010, Eur. J. Oper. Res..
[40] Oren Levintal. The Real Effects of Banking Shocks: Evidence from OECD Countries , 2009 .
[41] Rebel A. Cole,et al. A CAMEL Rating's Shelf Life , 1995 .
[42] Allen N. Berger,et al. Efficiency of Financial Institutions: International Survey and Directions for Future Research , 1997 .
[43] Peter Sarlin,et al. Predicting Distress in European Banks , 2013, SSRN Electronic Journal.
[44] Dennis Hilgers,et al. Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA , 2015, Eur. J. Oper. Res..
[45] Yaser E. Hawas,et al. A multi-dimensional framework for evaluating the transit service performance , 2013 .
[46] Pasquale Daponte,et al. Artificial neural networks in measurements , 1998 .
[47] Z. Ying,et al. A simple resampling method by perturbing the minimand , 2001 .
[48] Erik Stafford,et al. New Evidence and Perspectives on Mergers , 2001 .
[49] Peter Wanke,et al. Predicting Efficiency in Angolan Banks: A Two‐Stage TOPSIS and Neural Networks Approach , 2016 .
[50] J. Sturm,et al. What Determines Differences in Foreign Bank Efficiency? Australian Evidence , 2005, SSRN Electronic Journal.
[51] Ksenija Mandic,et al. Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods , 2014 .
[52] P. Molyneux,et al. Determinants of efficiency in South East Asian banking , 2011 .
[53] M. Hemmati,et al. Measuring relative performance of banking industry using a DEA and TOPSIS , 2013 .
[54] Ching-Lai Hwang,et al. Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.
[55] Youxian Sun,et al. Melt index prediction by neural networks based on independent component analysis and multi-scale analysis , 2006, Neurocomputing.
[56] Vadlamani Ravi,et al. Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review , 2007, Eur. J. Oper. Res..
[57] R. Koenker. Censored Quantile Regression Redux , 2008 .
[58] F. Sufian,et al. Determinants of revenue efficiency of Islamic banks: Empirical evidence from the Southeast Asian countries , 2015 .
[59] U. Ramanathan. Aligning supply chain collaboration using Analytic Hierarchy Process , 2013 .
[60] B. Tabachnick,et al. Using Multivariate Statistics , 1983 .
[61] Vadlamani Ravi,et al. Failure prediction of dotcom companies using neural network-genetic programming hybrids , 2010, Inf. Sci..
[62] Shanling Li,et al. Comparative Performance of Chinese Commercial Banks: Analysis, Findings and Policy Implications , 2001 .
[63] S. Ray,et al. Technical Efficiency in Public and Private Sectors in India: Evidence from the Post-Reform Years , 2003 .
[64] Kai Du,et al. Research in International Business and Finance Mergers, Acquisitions, and Bank Efficiency: Cross-country Evidence from Emerging Markets , 2022 .
[65] Oliver Müller,et al. Cross-border bank lending: Empirical evidence on new determinants from OECD banking markets , 2013 .
[66] P. Vincke,et al. Preference ranking organization method for enrichment evaluations , 1985 .
[67] Bruno Biais,et al. Privatisation Versus Regulation in Developing Economies: The Case of West African Banks , 1970 .
[68] J. Cummins,et al. Evidence From the Spanish Insurance Industry By , 2001 .
[69] Han Hong,et al. Three-Step Censored Quantile Regression and Extramarital Affairs , 2002 .
[70] Allen N. Berger,et al. Bank Ownership and Efficiency in China: What Will Happen in the World's Largest Nation? , 2006 .
[71] Kadri Männasoo,et al. Explaining bank distress in Eastern European transition economies. , 2009 .
[72] Antreas D. Athanassopoulos,et al. Nonparametric Frontier Models for Assessing the Market and Cost Efficiency of Large-Scale Bank Branch Networks , 1998 .
[73] Zhiliang Ying,et al. Survival analysis with median regression models , 1995 .
[74] J. Kruskal. Nonmetric multidimensional scaling: A numerical method , 1964 .
[75] Xianggui Qu,et al. Multivariate Data Analysis , 2007, Technometrics.
[76] Larry Jenkins,et al. A multivariate statistical approach to reducing the number of variables in data envelopment analysis , 2003, Eur. J. Oper. Res..
[77] Carlos Pestana Barros,et al. Performance assessment of Nigerian banks pre and post consolidation: evidence from a Bayesian approach , 2012 .
[78] Dmitri A. Rachkovskij,et al. Binding and Normalization of Binary Sparse Distributed Representations by Context-Dependent Thinning , 2001, Neural Computation.
[79] Peter F. Wanke,et al. Financial distress drivers in Brazilian banks: A dynamic slacks approach , 2015, Eur. J. Oper. Res..
[80] Robert Oshinsky,et al. Troubled Banks: Why Don't They All Fail? , 2005 .
[81] I. Dinç,et al. Politicians and Banks: Political Influences on Government-Owned Banks in Emerging Markets , 2005 .
[82] A. Dudek,et al. The fuzzy TOPSIS method and its implementation in the R programme , 2015 .
[83] Morteza Yazdani,et al. A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..
[84] Gwo-Hshiung Tzeng,et al. Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..
[85] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[86] Wen-Min Lu,et al. Does corporate governance play an important role in BHC performance? Evidence from the U.S. , 2012 .
[87] Rachita Gulati,et al. Measuring efficiency, effectiveness and performance of Indian public sector banks , 2009 .
[88] Peter Wanke,et al. Banking efficiency in Brazil , 2014 .
[89] Dwight M. Jaffee,et al. The Structure of Banking Systems in Developed and Transition Economies , 2000 .
[90] Geraldo da Silva e Souza,et al. Evolution of bank efficiency in Brazil: A DEA approach , 2010, Eur. J. Oper. Res..
[91] Bi-Huei Tsai,et al. Predicting Financial Distress Based on the Credit Cycle Index: A Two-Stage Empirical Analysis , 2010 .
[92] K. Schaeck,et al. Distress in European Banks: An Analysis Based on a New Dataset , 2009, SSRN Electronic Journal.
[93] Nicole Adler,et al. Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction , 2010, Eur. J. Oper. Res..
[94] Boaz Golany,et al. Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe , 2001, Eur. J. Oper. Res..
[95] Wan Lung Ng,et al. Production , Manufacturing and Logistics A simple classifier for multiple criteria ABC analysis , 2006 .
[96] A. Bilbao-Terol,et al. Using TOPSIS for assessing the sustainability of government bond funds , 2014 .
[97] Zuzana Fungáčová,et al. Determinants of bank interest margins in Russia: Does bank ownership matter? , 2009 .
[98] C. Barros,et al. A note on productivity change in European cooperative banks: the Luenberger indicator approach , 2010 .
[99] Yan Leng,et al. Integrated weight-based multi-criteria evaluation on transfer in large transport terminals: A case study of the Beijing South Railway Station , 2014 .
[100] C. Barros,et al. An analysis of African airlines efficiency with two-stage TOPSIS and neural networks , 2015 .
[101] Jonathan M. Williams,et al. Rationalizing the value premium in emerging markets , 2014 .
[102] J. Nellis,et al. Does Ownership Affect the Efficiency of African Banks? , 2006 .
[103] Walter Briec,et al. On some semilattice structures for production technologies , 2011, Eur. J. Oper. Res..
[104] Boaz Golany,et al. Including principal component weights to improve discrimination in data envelopment analysis , 2002, J. Oper. Res. Soc..
[105] Štefan Lyócsa,et al. Determinants of Commercial Banks’ Efficiency: Evidence from 11 CEE Countries , 2013 .
[106] Yiwen Bian,et al. A Gram-Schmidt process based approach for improving DEA discrimination in the presence of large dimensionality of data set , 2012, Expert Syst. Appl..
[107] Ability of Accounting and Audit Quality Variables to Predict Bank Failure During the Financial Crisis , 2011 .
[108] C. Hwang,et al. TOPSIS for MODM , 1994 .
[109] Edward I. Altman,et al. FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY , 1968 .
[110] A. George Assaf,et al. Technical efficiency in Saudi banks , 2011, Expert Syst. Appl..
[111] J. Leeuw,et al. Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods , 2009 .
[112] Carlos Pestana Barros,et al. Hotel efficiency: A bootstrapped metafrontier approach , 2010 .
[113] Achim Zeileis,et al. Econometrics in R: Past, Present, and Future , 2008 .
[114] Li Shang,et al. Feature selection in independent component subspace for microarray data classification , 2006, Neurocomputing.
[115] Patrick T. Harker,et al. Measuring aggregate process performance using AHP , 1999, Eur. J. Oper. Res..
[116] E. Gunay. Risk Incorporation and Efficiency in Emerging Market Banks During the Global Crisis: Evidence from Turkey, 2002-2009 , 2012 .
[117] Dimitris Askounis,et al. Multicriteria decision support for global e-government evaluation , 2014 .
[118] A. Maghyereh,et al. Bank distress prediction: Empirical evidence from the Gulf Cooperation Council countries , 2014 .
[119] C. Barros,et al. Analysing the determinants of performance of best and worst European banks: A mixed logit approach , 2007 .
[120] Snigdhansu Chatterjee,et al. Generalized bootstrap for estimators of minimizers of convex functions , 2003 .
[121] M. Balcilar,et al. A Comparative Analysis of Productivity Growth, Catch-Up, and Convergence in Transition Economies , 2005 .
[122] W. Hsu,et al. The sustainability balanced scorecard as a framework for selecting socially responsible investment: an effective MCDM model , 2009, J. Oper. Res. Soc..
[123] E. Oja,et al. Independent Component Analysis , 2013 .
[124] Ioan Nistor,et al. Efficiency assessment of hydroelectric power plants in Canada: A multi criteria decision making approach , 2014 .
[125] Wei Ge,et al. Effects of feature construction on classification performance: An empirical study in bank failure prediction , 2009, Expert Syst. Appl..
[126] E. Altman,et al. ZETATM analysis A new model to identify bankruptcy risk of corporations , 1977 .
[127] Sophocles N. Brissimis,et al. Bank-Specific, Industry-Specific and Macroeconomic Determinants of Bank Profitability , 2008, Social Science Research Network.
[128] Kristiaan Kerstens,et al. The choice of a technical efficiency measure on the free disposal hull reference technology: A comparison using US banking data , 1998, Eur. J. Oper. Res..
[129] S. Managi,et al. The technical efficiency of the Japanese banks : non-radial directional performance measurement with undesirable output , 2012 .
[130] J. Faria,et al. Macroeconomic adjustment under regime change: From social contract to Arab Spring , 2015 .
[131] R. Koenker,et al. Reappraising Medfly Longevity , 2001 .
[132] A. Hatami-Marbini,et al. An Extension of the Electre I Method for Group Decision-Making Under a Fuzzy Environment , 2011 .
[133] Chien‐Chiang Lee,et al. Bank reforms, foreign ownership, and financial stability , 2014 .
[134] Carlos Pestana Barros,et al. An evaluation of European airlines’ operational performance , 2009 .
[135] Robert Deyoung,et al. Management Quality and X-Inefficiency in National Banks , 1998 .
[136] Nguyen Viet Hung,et al. Efficiency and Super-Efficiency of Commercial banks in Vietnam: Performances and Determinants , 2013, Asia Pac. J. Oper. Res..
[137] J. G. Garza-García. Determinants of bank efficiency in Mexico: a two-stage analysis , 2012 .
[138] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[139] Shari Lawrence,et al. The Impact of Mergers and Acquisitions on the Efficiency of the U.S. Banking Industry: Further Evidence , 2008 .
[140] Cengiz Kahraman,et al. Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS , 2009, Expert Syst. Appl..
[141] C. Hwang. Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .
[142] Pierre Dussauge,et al. Alliances versus acquisitions: choosing the right option , 2000 .
[143] Chih-Chou Chiu,et al. Efficiency measurement using independent component analysis and data envelopment analysis , 2011, Eur. J. Oper. Res..
[144] Joseph C. Paradi,et al. Assessing Bank and Bank Branch Performance , 2011 .
[145] Chin-Tsai Lin,et al. Optimal marketing strategy: A decision-making with ANP and TOPSIS , 2010 .