Amin, G. R., & Emrouznejad, A. (2007). Inverse forecasting: a new approach for predictive modelling. Computers and Industrial Engineering, 53(3), 491–498.
Abstract: In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large uses of linear programming in forecasting models there is no a single application of inverse optimization reported in the forecasting literature when the time series data is available. Thus the goal of this paper is to introduce inverse optimization into forecasting field, and to provide a streamlined approach to time series analysis and forecasting using inverse linear programming. An application has been used to demonstrate the use of inverse forecasting developed in this study.
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Amin, G. R., & Emrouznejad, A. (2007). Inverse Linear Programming in DEA. International Journal of Operations Research, 4(2), 105–109.
Abstract: Despite the large uses of inverse DEA models, there is not any single application of inverse linear programming in DEA when the definition of inverse linear programming is taken under account. Thus the goal of this paper is applying the inverse linear programming into DEA field, and to provide a streamlined approach to DEA and Additive model. Having the entire efficient DMUs in DEA models is an important rule. To speed up the computations of the Additive DEA model this paper uses the inverse linear programming as an alternative procedure. It proposes an alternative inverse notion-based method which is capable to determine all the efficient DMUs of the model.
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Amin, G. R., & Emrouznejad, A. (2007). A note on DEA models in technology selection: an improvement of Karsak and Ahiska’s approach. International Journal of Production Research, 45(10), 2313–2316.
Abstract: This paper introduces a compact form for the maximum value of the non-Archimedean in Data Envelopment Analysis (DEA) models applied for the technology selection, without the need to solve a linear programming (LP). Using this method the computational performance the common weight multi-criteria decision-making (MCDM) DEA model proposed by Karsak and Ahiska (International Journal of Production Research, 2005, 43(8), 1537-1554) is improved. This improvement is significant when computational issues and complexity analysis are a concern.
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Amin, G. R., & Emrouznejad, A. (2006). An extended minimax disparity to determine the OWA Operator weights. Computers and Industrial Engineering, 50(3), 312–316.
Abstract: This paper contributes to extend the minimax disparity to determine the ordered weighted averaging (OWA) model based on linear programming. It introduces the minimax disparity approach between any distinct pairs of the weights and uses the duality of linear programming to prove the feasibility of the extended OWA operator weights model. The paper finishes with an open problem.
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Emrouznejad, A. (2005). Measurement efficiency and productivity in SAS/OR. Computers and Operations Research, 32(7), 1665–1683.
Abstract: This paper explores the use of the optimisation procedures in SAS/OR software with application to the measurement of efficiency and productivity of decision-making units (DMUs) using data envelopment analysis (DEA) techniques. DEA was originally introduced by Charnes et al. [J. Oper. Res. 2 (1978) 429] is a linear programming method for assessing the efficiency and productivity of DMUs. Over the last two decades, DEA has gained considerable attention as a managerial tool for measuring performance of organisations and it has widely been used for assessing the efficiency of public and private sectors such as banks, airlines, hospitals, universities and manufactures. As a result, new applications with more variables and more complicated models are being introduced. Further to successive development of DEA a non-parametric productivity measure, Malmquist index, has been introduced by Fare et al. [J. Prod. Anal. 3 (1992) 85]. Employing Malmquist index, productivity growth can be decomposed into technical change and efficiency change. On the other hand, the SAS is a powerful software and it is capable of running various optimisation problems such as linear programming with all types of constraints. To facilitate the use of DEA and Malmquist index by SAS users, a SAS/MALM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear-programming models based on the selected DEA. An example is given to illustrate how one could use the code to measure the efficiency and productivity of organisations.
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Emrouznejad, A. (2003). An alternative DEA measure: a case of OECD countries. Applied Economics Letters, 10(12), 779–782.
Abstract: Analysis of the production efficiency of industrialized countries, questioning whether certain countries perform better than others in producing more output with the same or less inputs, is an example of the importance of estimating production relationships. In order to estimate efficiency one needs an appropriate model for the two major inputs into production activity, namely labour and capital. A physical asset once installed is capable of contributing several years of output. This implies that investments made in previous years must be taken into account in order to produce a measure of the efficiency and productivity for any given year. The purpose of this article is to introduce a dynamic efficiency model and compare the results with previous work on the analysis of efficiency and productivity of OECD countries. The article proposes that dynamic models capture efficiency better than static models.
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Emrouznejad, A., & Amin, G. R. (2009). DEA models for ratio data: Convexity consideration. Applied Mathematical Modelling, 33(1), 486–498.
Abstract: Data envelopment analysis (DEA) is defined based on observed units and by finding the distance of each unit to the border of estimated production possibility set (PPS). The convexity is one of the underlying assumptions of the PPS. This paper shows some difficulties of using standard DEA models in the presence of input-ratios and/or output-ratios. The paper defines a new convexity assumption when data includes a ratio variable. Then it proposes a series of modified DEA models which are capable to rectify this problem.
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Emrouznejad, A., & Anouze, A. L. (2009). A note on the modeling the efficiency of top Arab banks. Expert Systems with Applications, 36(3, Part 1), 5741–5744.
Abstract: The major aim of this research is benchmarking top Arab banks using Data Envelopment Analysis (DEA) technique and to compare the results with that of published recently in Mostafa (2007a,b) [Mostafa, M. M. (2007a). Modeling the efficiency of top Arab banks: A DEA-neural network approach. Expert Systems with Applications, doi:10.1016/j.eswa.2007.09.001; Mostafa M. M. (2007b), Benchmarking top Arab banks’ efficiency through efficient frontier analysis, Industrial Management & Data Systems, 107(6) 802-823]. Data for 85 Arab banks used to conduct the analysis of relative efficiency. Our findings indicate that (1) the efficiency of Arab banks reported in Mostafa (2007a,b) is incorrect, hence, readers should take extra caution of using such results, (2) the corrected efficiency scores suggest that there is potential for significant improvements in Arab banks. In summary, this study overcomes with some data and methodology issues in measuring efficiency of Arab banks and highlights the importance of encouraging increased efficiency throughout the banking industry in the Arab world using the new results.
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Emrouznejad, A., Green, R. H., & Krivonozhko, V. (2002). Efficiency and Productivity Analysis in the 21st Century. International DEA Symposium 2002, 24-26 June 2002, Moscow (proceedings). Moscow, Russia: Institute for Systems Analysis of Russian Academy of Sciences.
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Emrouznejad, A., Parker, B. R., & Tavares, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences, 42(3), 151–157.
Abstract: Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available. This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007.
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