Removing the impact of environment with units-invariant efficient frontier analysis: An illustrative case study with intertemporal panel data

The four-stage methodology consists of a units-invariant efficient frontier analysis followed by Tobit regression, adjustment of data, and a repeat of the efficient frontier analysis. The outlined methodology is an improvement over existing similar approaches because the playing field can be levelled by adjusting data based on input as well as output slacks for managers who may have been advantaged or disadvantaged by their environments. The accompanying case study investigates the influence of the general level of interest rates on bank efficiency using intertemporal panel data spanning 8 years and two countries. Key findings support the assertion that changes in interest rates can distort measurement of bank efficiency.     

Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks

In measuring the overall efficiency of a set of decision making units (DMUs) in a time span covering multiple periods, the conventional approach is to use the aggregate data of the multiple periods via a data envelopment analysis (DEA) technique, ignoring the specific situation of each period. This paper proposes using a relational network model to take the operations of individual periods into account in measuring efficiencies. The overall and period efficiencies of a DMU can be calculated at the same time. Notably, the overall efficiency is a weighted average of the period efficiencies, and the weights are the most favorable ones for the DMU being evaluated. This model, together with two existing ones, is applied to measure the efficiency of 22 Taiwanese commercial banks for the period of 2009–2011. The three-year multi-period analysis shows that the proposed model is more discriminative than the existing ones in ranking the performance of the banks. The period efficiencies for the three years increased steadily, indicating that the performances of the Taiwanese banks examined in this work were improving over this period.     

Microfinance institutions and efficiency

Microfinance Institutions (MFIs) are special financial institutions. They have both a social nature and a for-profit nature. Their performance has been traditionally measured by means of financial ratios. The paper goes beyond simple financial ratios using a data envelopment analysis (DEA) approach to measure the efficiency of MFIs.     

Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach

In recent years the European airline industry has undergone critical restructuring. It has evolved from a highly regulated market predominantly operated by national airlines to a dynamic, liberalized industry where airline firms compete freely on prices, routes, and frequencies. Although several studies have analyzed performance issues for European airlines using a variety of efficiency measurement methods, virtually none of them has considered two-stage alternatives – not only in this particular European context but in the airline industry in general. We extend the aims of previous contributions by considering a network Data Envelopment Analysis (network DEA) approach which comprises two sub-technologies that can share part of the inputs. Results show that, in general, most of the inefficiencies are generated in the first stage of the analysis. However, when considering different types of carriers several differences emerge – most of the low-cost carriers’ inefficiencies are confined to the first stage. Results also show a dynamic component, since performance differed across types of airlines during the decade 2000–2010.     

Risk management and managerial efficiency in Chinese banks: A network DEA framework

Risk management in Chinese banks has traditionally been the Cinderella of its internal functions. Political stricture and developmental imperative have often overridden standard practice of risk management resulting in large non-performing loan (NPL) ratios. The training and practice of risk managers remain second class compared with foreign banks operating in China. This paper surveys Chinese bank risk managers and constructs metrics of risk management practice and risk management organisation. The metrics are used as intermediate inputs in a Network DEA framework to produce a measure of income efficiency. A statistical test is carried out to assess the importance of the risk metrics in evaluating bank income efficiency.     

A survey on bank branch efficiency and performance research with data envelopment analysis

The banking industry has been the object of DEA analyses by a significant number of researchers and probably is the most heavily studied of all business sectors. Various DEA models have been applied in performance assessing problems, and the banks' complex production processes have further motivated the extension and improvement of DEA techniques. This paper surveys 80 published DEA applications in 24 countries/areas that specifically focus on bank branches. Key issues related to the design of DEA models in these studies are discussed. Much advice is included on how to design future experiments and studies in this domain. A number of areas where further research could be fruitful are suggested.     

The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output

The paper analyses technical efficiency of the Japanese banks from 2000 to 2007. The estimation technique is based on the Russell directional distance function that takes into consideration not only desirable outputs but also an undesirable output that is represented by non-performing loans (NPLs). The results indicate that NPLs remain a significant burden as for banks' performance. We show that banks' inputs have to be utilised more efficiently, particularly labour and premises. We also argue that a further restructuring process is needed in the segment of Regional Banks. We conclude that the Japanese banking system is still far away from being fully consolidated and restructured.     

Two-stage evaluation of bank branch efficiency using data envelopment analysis

There are two key motivations for this paper: (1) the need to respond to the often observed rejections of efficiency studies’ results by management as they claim that a single-perspective evaluation cannot fully reflect the operating units’ multi-function nature; and (2) a detailed bank branch performance assessment that is acceptable to both line managers and senior executives is still needed. In this context, a two-stage Data Envelopment Analysis approach is developed for simultaneously benchmarking the performance of operating units along different dimensions (for line managers) and a modified Slacks-Based Measure model is applied for the first time to aggregate the obtained efficiency scores from stage one and generate a composite performance index for each unit. This approach is illustrated by using the data from a major Canadian bank with 816 branches operating across the nation. Three important branch performance dimensions are evaluated: Production, Profitability, and Intermediation. This approach improves the reality of the performance assessment method and enables branch managers to clearly identify the strengths and weaknesses in their operations. Branch scale efficiency and the impacts of geographic location and market size on branch performance are also investigated. This multi-dimensional performance evaluation approach may improve management acceptance of the practical applications of DEA in real businesses.     

Opening the black box: Uncovering the leader trait paradigm through machine learning

Understanding the traits that define a leader is a perennial quest. An ongoing debate surrounds the complexity required to unravel the leader trait paradigm. With the advancement of machine learning, scholars are now better equipped to model leadership as an outcome of complex patterns in traits. However, interpreting those models is often harder. In this paper, we guide researchers in the application of machine learning techniques to uncover complex relationships. Specifically, we demonstrate how applying machine learning can help to assess the complexity of a relationship and show techniques that help interpret the outcomes of “black box” machine learning algorithms. While demonstrating techniques to uncover complex relationships, we are using the Big Five Inventory and need for cognition to predict leadership role occupancy. Among our sample (n = 3385), we find that the leader trait paradigm can benefit from modeling complexity beyond linear effects and generate several interpretable results.     

Assessment of airport performance using the SBM-NDEA model

This paper presents a slacks-based measure network data envelopment analysis (SBM-NDEA) model of performance measurement under series productions with quasi-fixed inputs of runway, terminal and apron areas as well as free linking capacity provisions. Airport operations efficiency is decomposed into production and service efficiency. Service efficiency can then be further decomposed into airside and landside aspects. Our empirical findings suggest that efficiency in airport production may not guarantee efficiency in the service process of domestic airports in Taiwan, and vice versa. This study also estimates the input excess and output shortfalls with respect to production and service processes, respectively.     

Measuring and explaining the cost efficiency of municipal solid waste collection and processing services

This paper proposes an adjusted version of the popular efficiency measurement technique data envelopment analysis (DEA) that makes it possible (1) to evaluate the cost efficiency of municipalities in the collection and processing of multiple household waste fractions, (2) robustifying the cost efficiency evaluations for the impact of measurement errors in the data or municipalities with outlying and atypical performances (if present in the sample set), and (3) to correct the evaluations for differences in the operating environments of municipalities (e.g., factors such as demography and median income of the municipality population). The paper illustrates the usefulness of the methodology by carrying out and analyzing a cost efficiency evaluation using data on 293 municipalities in Flanders, Belgium, for the year 2008.     

A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach

The current paper proposes a slack-based version of the Super SBM, which is an alternative super-efficiency model for the SBM proposed by Tone. Our two-stage approach provides the same super-efficiency score as that obtained by the Super SBM model when the evaluated DMU is efficient and yields the same efficiency score as that obtained by the SBM model when the evaluated DMU is inefficient. The projection identified by the Super SBM model may not be strongly Pareto efficient; however, the projection identified from our approach is strongly Pareto efficient.     

Non-radial profit performance: An application to Taiwanese banks

This research modifies the directional Russell measure (DRM) of Fukuyama and Weber (2009) [1] to decompose the Nerlovian profit efficiency in Chambers et al. (1998) [2] so as to obtain a generalized measure that completely excludes technical inefficiency from allocative inefficiency. Based on such a decomposition, we further develop a new slack-based and profit-oriented productivity indicator, combining the Nerlovian profit measure with the conventional Luenberger productivity indicator (LPI), in order to provide a full picture of the sources of productivity change. Productivity change, based on the profit boundary, is decomposed into four components: the change in technical efficiency; the change in allocative efficiency; the shift of technology; and the price effect from outputs and inputs. This decomposition provides a more complete picture of the sources of productivity change. The above indicator is used herein to measure the productivity change of Taiwanese banks in terms of profit.     

An empirical study of transformational leadership,team performance and service quality in retail banks

The discipline of operations management (OM) has long been offering differing quantitative techniques for improving the efficiency of banking operations. However, there has been a trend in recent years that operations and services of the banking industry are becoming more diverse and unstructured, rendering many traditional OM quantitative techniques less effective in performance improvement. By integrating the literature on banking operations, service quality, leadership style and work teams, we argue that leadership style and team performance are crucial concerns determining the service quality performance of today's banking operations in a team setting. Using data collected from 192 employees from 32 operational teams (a leader and five members in each team) in 15 retail banks in Macau, China, we investigated whether the five dimensions of transformational leadership have an impact on team performance with respect to team cohesion, team leader job satisfaction and team competence; and whether the dimensions of team performance have an impact on such service quality dimensions as reliability and responsiveness. We found that one of the dimensions of transformational leadership and two of the dimensions of team performance have a significant impact on service quality. We discuss the implications of the findings for research and practise.     

Labor-use efficiency in Indian banking: A branch-level analysis

This paper uses data envelopment analysis to measure labor-use efficiency of individual branches of a large public sector bank with a sizable network of branches across India. We find considerable variation in the average levels of efficiency of bank branches across the four metropolitan regions considered in this study. In this context, we introduce the concept of area or spatial efficiency for each region relative to the nation as a whole. Our findings suggest that the policies, procedures, and incentives handed down from the corporate level cannot fully neutralize the detrimental influence of the local work culture across different regions. Most of the potential reduction in labor cost appears to be coming from possible downsizing in the clerical and subordinate staff. Our analysis identifies branches that operate at very low levels of labor-use efficiency and possible candidates for increased supervision and control.     

How to better identify the true managerial performance: State of the art using DEA

Our motivation is to detail a potential improvement on the three-stage analysis published by Fried et al. [Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis 2002;17:157–74] that can distinguish true performers from those that may be advantaged by favourable environments or measurement errors. The method starts with data envelopment analysis (DEA), and continues with stochastic frontier analysis to explain the variation in organisational performance in terms of the operating environment, statistical noise and managerial efficiency. It concludes with DEA again using adjusted data to reveal a measure of performance based on management efficiency only. Our proposed contributions include (i) a comprehensive approach where total input and output slacks are identified simultaneously for non-radial inefficiencies before levelling the playing field, (ii) identifying percent adjustments attributable to the environment and statistical noise, and (iii) using a fully units-invariant DEA model.     

Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks

The great majority of applications of the popular frontier technique data envelopment analysis (DEA) do not test for the association of efficiency estimates with key performance indicators used by industry observers. Nevertheless, identifying efficiency estimates’ associations with commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring. Thus, the current paper investigates to what extent bank DEA super-efficiency estimates are associated with key financial ratios. A low correlation may present an opportunity to address inefficiencies that were not obvious in financial ratio analysis, thus enabling an update of inferences drawn from ratios. Regressing ratios on efficiency estimates may also help predict financial ratios. Where an input–output specification is comprised of key financial ratios, DEA can also be used to objectively identify benchmarks for ratio analysis based on actual observed data collected from peers. Nine super-efficiency DEA formulations across two profitability models are systematically tested. The slacks-based measure of DEA with a parsimonious profitability efficiency model emerges as the most significant combination explaining the variation in the two industry ratios, post-tax profit/average total assets and return on average equity.     

Slack free MEA and RDM with comprehensive efficiency measures

This paper extends two directional distance function models, the Multi-directional Efficiency Analysis (MEA) Model and the Range Directional Model (RDM), in order to account for any type of technical inefficiency, i.e. both directional and non-directional inefficiencies. We first focus on the variable returns to scale (VRS) case, because both VRS-MEA and RDM are translation invariant models, which mean that both models are able to deal with negative data. Our main result is the definition of a new comprehensive efficiency measure which is units invariant and translation invariant and covers both models. Secondly, we introduce the RDM model under constant returns to scale (CRS) together with a new comprehensive efficiency measure.     

Efficiency analysis of university departments: An empirical study

Universities play an important role in the development of a country in this age of the knowledge economy. As government subsidies to universities have been reducing in recent years, the more efficient use of resources becomes an important issue for university administrators. This paper applies data envelopment analysis (DEA) to assess the relative efficiency of the academic departments at National Cheng Kung University in Taiwan. The outputs considered are total credit-hours, publications, and external grants; and the inputs utilized by the departments are personnel, operating expenses, and floor space. An assurance region is constructed by the top administrators of the university to confine the flexibility in selecting the virtual multipliers in DEA. Four groups of departments of similar characteristics are categorized via an efficiency decomposition and cluster analysis. The aggregate efficiency indicates whether the resources have been utilized efficiently by a department and the efficiency decomposition helps identify the weak areas where more effort should be devoted so that the efficiency of the department can be improved.     

An illustration of dynamic network DEA in commercial banking including robustness tests

The main motivation of this article is to illustrate dynamic network data envelopment analysis (DN-DEA) in commercial banking with emphasis on testing robustness. To this end, sixteen foreign banks in China are benchmarked against thirty-two domestic banks for the post-2007 period that follows major reforms. When network and dynamic dimensions are brought together, a more comprehensive analysis of the period 2008–2010 is enabled where divisional and between-period interactions are reflected in efficiency estimates. Weighted, variable returns-to-scale, non-oriented dynamic network slacks-based measure is used within the framework of the intermediation approach to bank behavior. A bank network (i.e., a decision-making unit, DMU) is conceptualized as comprised of two divisions or sub-DMUs, namely, interest-bearing operations and non-interest operations linked by number of referrals. Undesirable outputs from sub-DMUs 1 and 2 (non-performing loans, and proportion of fruitless referrals, respectively) are treated as carry-overs that impact the efficiency of the following periods. Under robustness testing, the illustrative application discusses discrimination by efficiency estimates, dimensionality of the performance model, stability of estimates through re-sampling (leave-one-out method), and sensitivity of results to divisional weights and returns-to-scale assumptions. The results based on Chinese commercial banks are illustrative in nature because of simulated data used on two of the variables.