Global economic growth has led banks to expand their operations all over the world. The purpose of this research was to understand the efficiency of 18 large bank from all over the world during the period from 2013 to 2017. The performance was estimated by a dynamic slacks-based measure (SBM) model in data envelopment analysis (DEA). This model could be solved using inputs, outputs, and links. The banks variables were considered as follows: Assets, capitalization, and liabilities as inputs; revenue as output; and net interest income as a good link. The final empirical results exhibit the efficiency for each term, and the overall score. The data analysis recommends a feasible solution to refine inefficient terms based on the projections (slacks). This study visually observed the proficiency of the banking industry to equip enterprises with the best choice for their finances.
Electric energy sources are the foundation for supporting for the industrialization and modernization; however, the processes of electricity generation increase CO 2 emissions. This study integrates the Holt-Winters model in number cruncher statistical system (NCSS) to estimate the forecasting data and the undesirable model in data envelopment analysis (DEA) to calculate the efficiency of electricity production in 14 countries all over the world from past to future. The Holt-Winters model is utilized to estimate the future; then, the actual and forecasting data are applied into the undesirable model to compute the performance. From the principle of an undesirable model, the study determines the input and output factors as follows nonrenewable and renewable fuels (inputs), electricity generation (desirable output), and CO 2 emissions (undesirable output). The empirical results exhibit efficient/inefficient terms over the period from 2011-2021 while converting these fuels into electricity energy and CO 2 emissions. The efficiency reveals the environmental effect level from the electricity generation. The analysis scores recommend a direction for improving the inefficient terms via the principle of inputs and undesirable outputs excess and desirable outputs shortfalls in an undesirable model.
Augmentation of electrical equipment is pushing for an increase in energy supply sources all over the world, as electricity consumption (EC) typically rises with growing populations. The value of EC reveals economic development and degree of emissions. Therefore, this research uses the undesirable outputs model in data envelopment analysis (DEA) for estimating relative efficiency of electricity consumption in 42 countries from 2008 to 2017. According to the principle of an undesirable outputs model and studied objectives, variables are selected that included population and EC as inputs, gross domestic product (GDP) as desirable output, and carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) as undesirable outputs. The empirical results indicate that 420 terms of 42 countries during the period of 2008–2017 have 102 efficient and 310 inefficient terms. Moreover, the interplay level between input and output factors every year is presented via scores. The study suggests the effect of EC to human life and propounds the emission status to look for directions to overcome inefficient terms.
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