A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China

There are two typical subprocesses in bank production—deposit generation and loan generation. Aiming to open the black box of input-output production of banks and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM). Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples. Applying it to measure the efficiency of Chinese commercial banks from 2008 to 2012, this paper explores the characteristics of overall and divisional efficiency, as well as the determinants of them. Some interesting results are discovered. The polarization of efficiency occurs in the bank level and deposit generation, yet does not in the loan generation. Five hypotheses work as expected in the bank level, but not all of them are supported in the stage level. Our results extend and complement some earlier empirical publications in the bank level

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

A material balance approach for modelling banks’ production process with non-performing loans

The aim of this to study is to examine how non-performing loans on the balance sheets of Japanese banks affect their performance by adopting a material balance principle. The paper outlines how the material balance conditions can be applied when modelling banks’ production process in the presence of non-performing loans. The paper utilizes the generalized weak G-disposability principle which accounts for the heterogeneity among banks’ input quality. We test how an input-oriented model (non-performing loans are treated as an input), the weak disposability assumption and the adopted material balance approach, affect banks’ performance levels. We apply our test on a sample of Japanese banks over the period 2013 to 2019. Our findings indicate that the input-oriented model and the material balance estimator even if they present similar distributions, they account differently the effect of non-performing loans’ fluctuations over the examined period. In addition, the results under the weak disposability assumption are found to be different compared to the material balance measures and less sensitive to banks’ non-performing loans variation levels. We also provide evidence that the generalized weak G-disposability assumption captures better banks’ performance fluctuations that has been caused by the restructuring of the Japanese banking industry

Energy Efficiency in Transportation along with the Belt and Road Countries

China’s huge investment in the “belt and road initiative” (BRI) may have helped improve the economic level of participating countries, but it may also be accompanied by a substantial increase in greenhouse gas (GHG) emissions. The BRI corridors aim to bring regional stability and prosperity. In such efforts, energy efficiency due to increased transport has been overlooked in the recent literature. This paper employed a data envelopment analysis of the slack-based measurement (SBM) for bad output to assess the transport energy efficiency of 19 countries under the BRI economic corridors. By using the most cited transport-related input variables, such as vehicles, labor, motor oil, jet fuel, and natural gas, this study first analyzes the transport energy efficiency by first assuming the output variables individually and then takes two years as a pre- and post-BRI case by considering the aggregated output model. The results show an increase in economic activity but a decline in transport energy efficiency in terms of consumption and emissions

Bank efficiency and non-performing loans: Evidence from Turkey

This study analyses technical and allocative efficiencies in Turkish banks from December 2002 to December 2017, under the assumption of constant returns to scale. We apply a modified version of the Data Envelopment Analysis (DEA) approach introduced by Aparico et al. (2015), which employs a directional distance model to provide estimates of efficiency, with a focus on Non-Performing Loans (NPLs) as an undesirable output. In addition, we examine the determinants of efficiency by applying quantile regressions to panel data. The results obtained support the thesis that NPLs exert a negative impact in terms of technical efficiency, which confirms the “bad management” hypothesis in the banking sector. We also find that the level of efficiency of Turkish banks differs, depending on the ownership structure in place

A novel multilevel network slacks-based measure with an application in electric utility companies

In this paper, we developed an alternative Network Slacks-Based Data Envelopment Analysis Measure (NSBM) wherein the overall efficiency is expressed as a weighted average of the efficiencies of the individual processes. The advantage of this new model is that both overall efficiency and multi-divisional efficiencies have been calculated with a unified framework. The major merits of the proposed model are its ability to provide appropriate measure of efficiency, obtaining weight of processes from model, simultaneous assessment of intermediate variables considering them as both input and output. Finally, an application in electric power companies shows the practicality of the proposed model

A unified framework for nonperforming loan modeling in bank production: An application of data envelopment analysis

The aim of this paper is to conduct a comparative analysis of three environmental approaches in the context of a bank production framework, considering the presence of nonperforming loans (NPLs). Specifically, we examine banks' inefficiency levels using the "by-production technology," "joint-weak disposable technology," and "material balanced technology." To ensure comparability within a directional slack inefficiency framework, we propose a two-step procedure. The study is based on a sample of 379 prominent banks operating in the United States from 2003 to 2017. Our findings reveal that the material balance and by-production technologies result in estimated inefficiency measures with higher sensitivity compared to the estimator utilizing the joint-weak disposable technology. Additionally, we identify distinct properties among the estimators, emphasizing their unique characteristics for modeling nonperforming loans. Finally, our paper sheds light on the differences between the three estimators in relation to banks' inefficiency levels, considering the incorporation of nonperforming loans in the production process

The governance-production nexus of eco-efficiency in Chinese resource-based cities:A two-stage network DEA approach

For decades, resource-based cities in China have significantly contributed to China's socio-economic development. The heavy resource dependence of resource-based cities inevitably leads to a series of environmental problems. Mitigating environmental impacts in an unthinking manner might be disruptive for economic development. Improving eco-efficiency has been a crucial solution for protecting the environment while mitigating its negative economic impact. However, the method commonly used to evaluate the eco-efficiency – that is, the black-box data envelopment analysis (DEA) – cannot examine the inefficiencies of the internal structure, and as a result, the underlying management defects are unclear. To open the black box, this study presents a two-stage network DEA framework incorporating government and industrial sectors and measures the eco-efficiency of 84 resource-based cities during the post-financial crisis period (2007–2015). The results indicate that the average eco-efficiency of China's resource-based cities shows a promising increase, and there is a positive relationship between governance efficiency and production efficiency. The decreasing trend of governance efficiency in the Central, Western, and Northeast regions after 2014 shows the low quality of the government sector in the usage of fiscal income. Proactive disclosure of how the government sector conducts public business and spends taxpayers' money should be made to increase transparency, attract more entrepreneurial resources to carry out production activities, and further improve sustainability. The two-stage network DEA framework helps obtain more insights into the internal management defects of the government and industrial sectors and enhance their cooperation to improve the eco-efficiency precisely

Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping:a case of Mozambican banks

Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed