Emrouznejad, A. and M. Marra (2014) Ordered Weighted Averaging Operators 1988–2014: A Citation-Based Literature Survey, International Journal of Intelligent Systems, 29 (11): 994–1014. DOI 10.1002/int.21673

Emrouznejad, A. and M. Marra (2014) Ordered Weighted Averaging Operators 1988–2014: A Citation-Based Literature Survey, International Journal of Intelligent Systems, 29 (11): 994–1014. DOI 10.1002/int.21673.

This study surveys the Ordered Weighted Averaging (OWA) operator literature using a citation network analysis. The main goals are the historical reconstruction of scientific development of the OWA field, the identification of the dominant direction of knowledge accumulation that emerged since the publication of the first OWA paper and to discover the most active lines of research. The results suggest, as expected, that Yager (1988) [Yager, Ronald R. On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 18(1), 183–190.] is the most influential paper and the starting point of all other research using OWA. Starting from his contribution other lines of research developed and we describe them.

 

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Hanen, H., A. Emrouznejad, M. N. Ouertani (2014), Technical efficiency determinants within a dual banking system: a DEA-bootstrap approach, International Journal of Applied Decision Sciences, 7 (4): 382 – 404.

Hanen, H., A. Emrouznejad, M. N. Ouertani (2014), Technical efficiency determinants within a dual banking system: a DEA-bootstrap approach, International Journal of Applied Decision Sciences, 7 (4): 382 – 404.

The purpose of this study is to provide a comparative analysis of the efficiency of the Islamic banking sector in Gulf Cooperation Council (GCC) countries. To this end, we employ a semi-parametric two-stage methodology, where we derive technical efficiency scores via a Data Envelopment Analysis in the first stage. Then scores obtained are regressed on a series of determinants of bank efficiency using a double bootstrapping procedure. Our findings indicate that during the eight years of study, conventional banks largely outperform Islamic banks with an average technical efficiency score of 81% compared to 95.57%. However, it’s clear that since 2008 conventional banks efficiency was in a downward trend while the efficiency of their Islamic counterparts were in an upward trend since 2009. This indicates that Islamic banks have succeeded to maintain a level of effectiveness during the dark period of the subprime crisis after certainly, coming under their secondary effects during 2008-2009.  An investigation of the determinants of bank’s efficiency show that bank size have a significant positive impact on, only Islamic bank’s efficiency, while z-score is related negatively to efficiency of both departments showing that a higher (lower) distance from insolvency reduces (increases) banks’ efficiency. In other words, a stable and reliable system is crucial to foster the efficiency of GCC banks. Finally, for the whole sample, the analysis demonstrates the strong link of macroeconomic indicators with efficiency for GCC banks. But, surprisingly, there is no significant relationship in the case of Islamic banks.

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Hanafizadeh P., H. R. Khedmatgozar, A. Emrouznejad, M. Derakhshan (2014), Neural Network DEA for Measuring the Efficiency of Mutual Funds, International Journal of Applied Decision Sciences, 7 (3): 255-269.

Hanafizadeh P., H. R. Khedmatgozar, A. Emrouznejad, M. Derakhshan (2014), Neural Network DEA for Measuring the Efficiency of Mutual Funds, International Journal of Applied Decision Sciences, 7 (3): 255-269.

Efficiency in the Mutual Fund (MF), is one of the issues that is attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF‘s efficiency in short–term periods, investors need a method that not only having high accuracy, but also high speed. Data Envelopment Analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-propagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large set of MFs.

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Arabi, B., S. Munisamy, A. Emrouznejad and F. Shadman (2014), “Power Industry Restructuring and Eco-Efficiency Changes: A New Slacks-Based Model in Malmquist-Luenberger Index Measurement,” Energy Policy, 68: 132–145.

Arabi, B., S. Munisamy, A. Emrouznejad and F. Shadman (2014), “Power Industry Restructuring and Eco-Efficiency Changes: A New Slacks-Based Model in Malmquist-Luenberger Index Measurement,” Energy Policy, 68: 132–145.

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003–2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis.

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Ghasemi, M. R., J. Ignatius; A. Emrouznejad (2014) “A bi-objective weighted model for improving the discrimination power in MCDEA”, European Journal of Operational Research, 233 (3): 640–650.

Ghasemi, M. R., J. Ignatius; A. Emrouznejad (2014) “A bi-objective weighted model for improving the discrimination power in MCDEA”, European Journal of Operational Research, 233 (3): 640–650.

Lack of discrimination power and poor weight dispersion remain major contention issues in Data Envelopment Analysis (DEA) models, which have also hampered the developments in the multiobjective DEA domain. Since the initial multi- criteria DEA (MCDEA) model of Li and Reeves ( 1999), only one other research by Bal, Örkcü and Çelebio?lu ( 2010) attempted to solve the MCDEA framework through two goal programming approaches, i.e. GPDEA-CCR and GPDEA-BCC. It was claimed that both models improved upon the discrimination power of DEA by balancing the distribution of input-output weights. It was also claimed that both GPDEA models are major improvements to the original MCDEA of Li and Reeves (1999). In this research we first checked the validity of GPDEA models and found that they do not improve the discrimination power as it has been claimed, we further propose an alternative solution to the formulation using bi-objective linear programming. It is shown that the proposed bi-objective multiple criteria DEA(BiO-MCDEA) performs better than the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 26 European Union member countries is further used to describe the efficacy of our approach.

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Bahari A., A. Emrouznejad (2014) “Influential DMUs and outlier detection in Data Envelopment Analysis with an Application to Health Care”. Annals of Operations Research, 223 (1):95-108.

Bahari A., A. Emrouznejad (2014) “Influential DMUs and outlier detection in Data Envelopment Analysis with an Application to Health Care”. Annals of Operations Research, 223 (1):95-108.

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric Data Envelopment Analysis (DEA) models as developed by Yang et al. (2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection.

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Emrouznejad, A. (2014) “Advances in Data Envelopment Analysis”. Annals of Operations Research, 214 (1): 1-4.

Emrouznejad, A. (2014) “Advances in Data Envelopment Analysis”. Annals of Operations Research, 214 (1): 1-4.

Since its introduction in 1978, Data Envelopment Analysis (DEA) has become one of the preeminent non-parametric methods for measuring efficiency and productivity of decision making units. Charnes, Cooper, and Rhodes (1978) provided the original DEA constant returns to scale (CRS) model, later extended to variable returns to scale (VRS) by Banker Charnes, and Cooper (1984).  These ‘standard’ models are known by the acronyms CCR and BCC, respectively, and are now employed routinely in areas that range from assessment of public sectors, such as hospitals and health care systems, schools, and universities, to private sectors such as banks and financial institutions (Emrouznejad, et al, 2008, 2011). The main objective of this volume is to publish original studies that are beyond the two standard CCR and BCC models with both theoretical and practical applications using advanced models in Data Envelopment Analysis.

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Hatami-Marbini, A., A. Emrouznejad, P. J. Agrell (2014) Interval data without sign restrictions in DEA, Applied Mathematical Modelling, 38: 2028–2036.

Hatami-Marbini, A., A. Emrouznejad, P. J. Agrell (2014) Interval data without sign restrictions in DEA, Applied Mathematical Modelling, 38: 2028–2036.

Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches.

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Banker R., A., Emrouznejad, F. Vargas, P. Flores (2014), Sustainable Development and Performance Measurement: Proceedings of the International DEA Workshop, September 17-19, 2014, Hermosillo, Sonora, Mexico, ISBN: 978 1 85449 482 5.

Banker R., A., Emrouznejad, F. Vargas, P. Flores (2014), Sustainable Development and Performance Measurement: Proceedings of the International DEA Workshop, September 17-19, 2014, Hermosillo, Sonora, Mexico, ISBN: 978 1 85449 482 5.

Title: Sustainable Development and Performance Measurement

Subtitle (series): Proceedings of the International DEA Workshop

Venue: September 17-19, 2014, Hermosillo, Sonora, Mexico

Edited by: Rajiv Banker, Ali Emrouznejad, Francisco Vargas and Pedro Flores

Date of Publication: November 2014

Number of Page: 100pp

ISBN: 978 1 85449 482 5

DOI: 10.13140/RG.2.1.1387.2169

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Emrouznejad, A., R. Banker, S. Munisamy, B. Arabi (2014), Theory and Applications of Data Envelopment Analysis, Proceedings of the 12th International Conference of DEA, April 2014, University of Malaya, Kuala Lumpur, Malaysia, ISBN: 978 1 85449 487 0.

Emrouznejad, A.,  R. Banker, S. Munisamy, B. Arabi (2014), Theory and Applications of Data Envelopment Analysis,  Proceedings of the 12th International Conference of DEA, April 2014, University of Malaya, Kuala Lumpur, Malaysia, ISBN: 978 1 85449 487 0.

Title: Recent Developments in Data Envelopment Analysis and its Applications

Subtitle (series): Proceedings of the 12th International Conference on Data Envelopment Analysis

Venue: DEA2014, April 2014, Kuala Lumpur, Malaysia

Edited by: Ali Emrouznejad, Rajiv Banker, Susila M. Doraisamy and Behrouz Arabi

Date of Publication: November 2014

Number of Page: 416pp

ISBN: 978 1 85449 487 0

DOI: 10.13140/RG.2.1.1649.3608

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