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Öğe Data envelopment analysis for scale elasticity measurement in the stochastic case: with an application to Indian banking(Springer Science and Business Media Deutschland GmbH, 2023) Amirteimoori, Alireza; Sahoo, Biresh K.; Mehdizadeh, SaberIn the nonparametric data envelopment analysis literature, scale elasticity is evaluated in two alternative ways: using either the technical efficiency model or the cost efficiency model. This evaluation becomes problematic in several situations, for example (a) when input proportions change in the long run, (b) when inputs are heterogeneous, and (c) when firms face ex-ante price uncertainty in making their production decisions. To address these situations, a scale elasticity evaluation was performed using a value-based cost efficiency model. However, this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data. Therefore, in this study, we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty. An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years (1998–2005) was made to compare inferences about their efficiency and scale properties. The key findings are as follows: First, both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints. However, both models yield the same results at a tolerance level of 0.5, implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks. Second, the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart. Third, public banks exhibit higher efficiency than private and foreign banks. Finally, public and old private banks mostly exhibit either decreasing or constant returns to scale, whereas foreign and new private banks experience either increasing or decreasing returns to scale. Although the application of our proposed stochastic model is illustrative, it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs, which have ample potential for reaping scale and scope benefits. © 2023, The Author(s).Öğe Efficiency analysis and CO2 emission reduction strategies in the US forest sector: a data envelopment analysis approach(Springer, 2024) Amirteimoori, Alireza; Zadmirzaei, Majid; Susaeta, Andres; Amirteimoori, ArashIndustrial economic activities produce pollutants and environmentally sustainable production systems in forestry aim to minimize these undesirable outputs while maintaining high production and economic growth. In this contribution, we assume that in addition to plot-specific inputs and outputs, there are some contextual variables that may be exogenously fixed or may be under the control of the decision-makers. In this sense, we first propose a novel and practical approach to calculate environmental efficiency by reducing undesirable products. Then, we utilize an inverse data envelopment analysis (IDEA) model to effectively manage and reduce CO2 emissions. In doing so, the applied models have been utilized to evaluate the efficiencies of 89 forest plots in the USA. Given our estimations in a real application to the forest plots, the study revealed that the average environmental efficiency score is nearly 0.75 (out of 1). However, there is potential for improvement by adjusting the impacts of contextual factors, which could raise the score to approximately 0.8. Furthermore, the analysis indicates a positive correlation between ownership and environmental efficiency, suggesting that increased ownership leads to higher environmental efficiency. Conversely, temperature exhibits a negative correlation with environmental efficiency. Finally, the results obtained from the IDEA indicate that in order to reduce undesirable outputs by a specific level of 5-10%, it is necessary to decrease other inputs and outputs. This is because, under the assumption of weak disposability, reducing the level of undesirable outputs requires a reduction in certain factors that influence production capacity. In other words, achieving the desired reduction in undesirable outputs inevitably involves diminishing certain aspects of the production process. As the major conclusion, the emergence of IDEA as a powerful tool for sensitivity analysis, along with its flexible nature, offers exciting opportunities for research and practical applications in various fields, including forestry activities. It has the potential to enhance overall environmental efficiency and enable better control over GHG emissions levels.Öğe Efficiency analysis in two-stage data envelopment analysis with shared resources and undesirable outputs: an application in the banking sector(Wiley, 2024) Amirteimoori, AlirezaIn classic and traditional data envelopment analysis (DEA) models, the production process is considered as single stage process and the internal structures have been ignored. In many real-world occasions, however, the processes have two- or multi-stage structures with or without shared resources. Two-stage DEA models deal with the calculation of the technical efficiency of a system, taking into consideration its internal structures. In this contribution, we consider a two-stage production process in which both stages are fed by shared resources, and there are undesirable products from the second stage. In the model we will propose, an optimal split on shared resources is given. To demonstrate the applicability of the proposed approach, data on 40 bank branches in seven years 2014-2020 is presented. In our real application in the banking sector, we find out that the most important sources of inefficiency of bank branches are related to interest revenue and overdue debt (undesirable output). Moreover, we saw that almost all branches were inefficient in the second stage (sale and service section) in all the seven years of evaluation.Öğe A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks(Springer, 2024) Amirteimoori, Alireza; Allahviranloo, Tofigh; Nematizadeh, MaryamIn the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.Öğe Improving decision-making units in performance analysis methods: a data envelopment analysis approach(Springer Heidelberg, 2023) Amirteimoori, Alireza; Allahviranloo, Tofigh; Kordrostami, Sohrab; Bagheri, Seyed FatemehClassifying decision-making units into efficient and inefficient classes is a common procedure in nonparametric data envelopment analysis approach. The inefficient units can be projected onto the production frontier by decreasing their inputs or increasing their outputs. However, if the closer projection point is clarified, the units will achieve their best situation. Previous methods have only focused on one objective, and other features have been ignored. This paper presents an alternative definition for the best projection by considering three main aspects: cost, revenue and closest projection points. The proposed procedure provides the closest possible distance, the lowest cost and the highest revenue, simultaneously. The goal programming has been used in this model. The results of implementing this approach on China's textile industry have shown the model applicability.Öğe An inverse multi-period FDH model with undesirable outputs(Croatian Operational Research Soc, 2023) Asadi, Farzaneh; Kordrostami, Sohrab; Amirteimoori, Alireza; Noveiri, Monireh Jahani SayyadIn some examinations, the changes in performance measures and the efficiency of entities should be addressed over a span of time despite the undesirable outputs and unsatisfactory convexity property. In this study, the performance of processes is analyzed over several periods of time by presenting a multi-period model based on the free disposal hull (FDH) approach, incorporating undesirable outputs. Using the product of availability, performance (efficiency) and quality, the overall equipment effectiveness (OEE) is calculated which shows the level of productivity. After estimating the performance and OEE, an inverse multi-period FDH model is introduced to measure the input changes for the changes made to outputs in different time periods. The proposed approaches are used in the automotive industry to analyze the performance and changes in input measures over multiple periods of time. The results show that the proposed technique is reasonable for assessing the multi-period efficiency, the period and overall OEE of the systems, and the input changes related to several periods while the convexity assumption is violated.Öğe Managerial ability and productivity growth in the European forest sector(Springer, 2023) Amirteimoori, Alireza; Banker, Rajiv D.; Zadmirzaei, Majid; Susaeta, AndresThis paper aims to examine how the data envelopment analysis (DEA) technique can be applied to evaluate managerial ability and productivity growth for 29 European forest sectors over the period 2011-2020. Toward this end, we first applied DEA to evaluate the technical efficiency (TE) from both periodical-frontier and met-frontier perspectives in which results showed that the average TE was 0.645 and the annual operating efficiency of the years studied was reduced by 35%. A modified regression test is secondly developed in order to determine the effect of contextual variables on the log of TE. The findings showed that the regional density, time series and gross domestic product had the highest positive influence on improving the TE results, respectively. In the following, by considering the explanatory variables, a modified DEA-based Malmquist productivity index is used to calculate the productivity growth over the period 2011-2020. The results indicated that there was a decline of 12% for total factor productivity in 2019-2020 compared to 2014-2015 and 7% compared to 2015-2016 which is due to the uniform growth of technological change (TC) and efficiency change recession compared to previous periods. Hence, productivity growth is mainly due to frontier shift (TC).Öğe Marginal rates of technical changes and impact in stochastic data envelopment analysis: An application in power industry(Pergamon-Elsevier Science Ltd, 2024) Amirteimoori, Alireza; Allahviranloo, Tofigh; Khoshandam, LeilaMarginal rates of technical changes and marginal impact are useful tools to calculate the trade-offs between production factors in a production process. In the data envelopment analysis (DEA) framework, the calculation of these trade-offs (marginal rates of technical substitution, marginal rates of transformation, marginal productivity and marginal costs) using the existing deterministic approaches may be sensitive to uncertainty and variability of the input and output data. Therefore, in this contribution, we introduce a stochastic DEA model based on chance constrained programming to develop a measure of the marginal rates of firms facing data uncertainty. In this contribution, chance-constrained programming is used to develop a procedure to calculate these trade-offs. Our proposed stochastic procedure is applied to sample data on 31 power plants. The empirical results on marginal rates obtained from our proposed stochastic programs revealed that the results are different at various tolerance levels of chance constraints.Öğe On the environmental performance analysis: A combined fuzzy data envelopment analysis and artificial intelligence algorithms(Pergamon-Elsevier Science Ltd, 2023) Amirteimoori, Alireza; Allahviranloo, Tofigh; Zadmirzaei, Majid; Hasanzadeh, FahimehGreenhouse gases (GHG) remain in the atmosphere for a very long-time causing alarmingly fast warming worldwide (global warming); especially Carbon dioxide (CO2) emissions have become a worldwide concern because of their harmful effects on the climate, and they are considered as an undesirable product of a lot of production systems. Various models dealing with undesirable outputs for measuring environmental efficiency have been employed to control greenhouse gas emissions via forecasting and/or optimizing their emissions. In this regard, this study proposes a novel modified Fuzzy Undesirable Non-discretionary DEA (FUNDEA) model to Measure environmental efficiency, and combine it with some novel artificial intelligence algorithms (Artificial Neural Network (ANN), Gene Expression Programming (GEP) and Artificial Immune System (AIS)) in order to predict optimal values of inefficient Decision-Making Units (DMUs) for being more efficient and mitigating their Co2 emissions in the uncertain environment for the first time herein. The model is applied to a dataset of 24 Iranian forest management units. Although our findings show that 17 DMUs are inefficient with a weak efficiency dispersion, these inefficient DMUs could improve their efficiency border by following the combined approaches (FUNDEA-ANN, FUNDEA-GEP and FUNDEA-AIS). As a consequence, the applied FUNDEA- artificial intelligent approaches are performed very well in predicting the optimal values of CO2 emissions and, hence increasing the total environmental efficiency.Öğe Performance analysis and managerial ability in the general insurance market: a study of India and Iran(Springer, 2024) Banker, Rajiv. D.; Amirteimoori, Alireza; Allahviranloo, Tofigh; Sinha, Ram PratapManagerial ability and managerial efforts play key role in the performance of business enterprises. However, this indicator is not directly observable. The current paper focuses on estimating managerial ability in the context of the Indian and Iranian general insurance sectors. The study is based on 140 firm-year observations in India and 140 firm-year observations in Iran spread over 7 years (2012-13 to 2018-19). For measuring managerial ability, we have used a three-stage procedure that involves the estimation of insurer-wise efficiency using Data Envelopment analysis (DEA) in the first stage and then regression of the logarithm of technical efficiency on a set of explanatory variables. In the final stage, we have estimated managerial ability from regression residuals (the difference between the observed and fitted values of insurer efficiency). In order to test the validity of the relationship between return on equity and managerial ability we use the general additive model (GAM). Our results confirmed that there is a positive relationship between return on equity and managerial ability. Our findings also revealed that the mean technical and output allocative efficiencies and managerial ability of Iranian markets highly fluctuated with a high variance. In contrast, these indicators did not fluctuate much in India.Öğe Scale elasticity and technical efficiency analysis in the European forest sector: a stochastic value-based approach(Springer, 2023) Amirteimoori, Alireza; Allahviranloo, Tofigh; Zadmirzaei, MajidThis paper is the first to examine both technical efficiency and scale elasticity of the forest sector across different European (EU) regions in an uncertain environment. In doing so, a dataset from 29 EU forest sectors have been collected; where the input and output data have been assumed to be random while their prices (or importance weights) were known. A chance-constrained data envelopment analysis approach was derived from several directional value-based models aimed at evaluating technical efficiency in the first stage. The results indicated that the number of efficient EU forest sectors were reduced substantially with extremely weak efficiency dispersion (about 18%), and the total average technical efficiency scores were moderately reduced by 0.74 as well. However, in the second stage, the findings of the modified cost/revenue-based scale elasticity model interestingly revealed that almost 7% of the EU forest sectors are in increasing returns to scale regions, which means they are still attractive acquisition targets and have the opportunity to increase the level of outputs and shift to the fully efficient border and finally increase their overall efficiency. As the major conclusion, all of our applied stochastic data envelopment analysis models (specially the cost/revenue-based approach) have high discriminating power in order to clearly distinguish the efficiency of the EU forest sector.Öğe Scale elasticity and technical efficiency measures in two-stage network production processes: an application to the insurance sector(Springer, 2024) Amirteimoori, Alireza; Allahviranloo, Tofigh; Arabmaldar, AliasgharIn performance analysis with tools such as data envelopment analysis, calculations of scale properties of the frontier points are studied using both qualitative and quantitative approaches. When the production process is a bit complicated, the calculation needs to be modified. Most existing studies are focused on a single-stage production process under the constant or variable returns to scale specification. However, some processes have two-stage structures, and, in such processes, the concepts of scale elasticity and returns to scale are inextricably related to the conditions of the stages of production. Thus, an evaluation of efficiency, scale elasticity, and returns to scale is sensitive to stages. In this study, we introduced a procedure to calculate technical efficiency and scale elasticity in a two-stage parallel-series production system. Then, our proposed technical efficiency and scale elasticity programs are applied to real data on 20 insurance companies in Iran. After applying our estimations to a real-world insurance industry, we found that, (i) overall, the total inputs of insurers in the life insurance sector should be reduced by 9%. Moreover, the inputs of nonlife insurers should be reduced by 50%. The final output in the investment sector must be increased by 48%. (ii) There are inefficiencies among all insurers in the investment sector, and to improve technical efficiency, the income from investments should be increased significantly. (iii) Finally, the efficiency and elasticity characterizations of insurers are directly subject to stages.Öğe Scale elasticity and technical efficiency measures in two-stage network production processes: an application to the insurance sector (vol 10, 43, 2024)(Springer, 2024) Amirteimoori, Alireza; Allahviranloo, Tofigh; Arabmaldar, Aliasghar[Abstract Not Available]Öğe Stochastic data envelopment analysis in the presence of undesirable outputs(Taylor & Francis Ltd, 2023) Amirteimoori, Alireza; Charles, Vincent; Mehdizadeh, SaberIn contrast to traditional efficiency analysis models in the field of data envelopment analysis (DEA) with undesirable outputs, this paper proposes efficiency models with the joint use of weak and managerial disposability assumptions. First, we develop a deterministic efficiency analysis model to deal with undesirable outputs in a production process. Due to the importance of data variability and uncertainty, the technical efficiency analysis is sensitive to these variations. Using chance-constrained programming theory, we extend our proposed deterministic model to a stochastic production system. To demonstrate the real-world applicability of our proposed models, we employ an empirical application based on actual Iranian gas distribution company data. Although this empirical application is illustrative, our proposed scheme could be used to evaluate the relative efficiency of many real-life production units whose underlying production systems are frequently stochastic.
