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.
► 80 published DEA applications in 24 countries/areas on bank branches are surveyed. ► Key issues related to the DEA models used in these studies are discussed. ► Advices are provided on how to design future studies in this domain. ► Suggestions are made on the areas that might be worth further research.
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.
This paper offers a methodology to estimate an unconditional probability density function (PDF) for the stock price of an initial public offering (IPO), at a short-term post-IPO horizon. The ...resultant PDF is unique to the IPO of interest (IPOI) and serves to model the short-term post-market uncertainty associated with its price. Such a methodology is unprecedented in the IPO risk literature since the
ex ante
quantification of the short-term uncertainty associated with the stock price of a newly public firm was viewed as burdened by the lack of sufficient accounting and market history at the IPO stage. This gap is addressed here through recognizing that common in most IPO cases are the scarcity of hard data and abundance of soft data (strong prior belief), and that one can combine Bayesian inference and Data Envelopment Analysis (DEA) to develop a unique risk quantification setting that befits and serves these two characteristics of IPOs. In this setting, DEA serves to quantify the prior belief, to be subsequently updated in the Bayesian phase. This paper remains the first of its kind which unravels the IPO risk analysis from such perspective. It develops an iterative process that uses DEA to design a multi-dimensional similarity metric to find the ‘comparables’ to IPOI, and thereof the closest comparable to it, whereupon Bayesian inference is employed to utilize the information available from these comparables to sequentially update and revise the IPOI’s prior PDF. The validity of the proposed risk methodology was examined by backtesting analyses.
•This study focuses on the determination of the technological returns to scale.•This problem is a key factor in calculating the efficiency scores.•We propose the Angles method using a data mining ...structure for this problem.•For the validation of the Angles method, we examine 6 one input/one output cases.•Also, we test the proposed method using real world data of a major Canadian Bank.
In this paper, we consider one of the most critical problems for setting up a data envelopment analysis model: the identification of suitable returns to scale (RTS) for the data. We refer to it as the technological returns to scale (TRTS) to completely separate the technology's RTS from the DMU's RTS. The only existing objective approaches for the TRTS identification are statistically based. While they are supported by strong theories, they might be problematic in practice. In this paper, we introduce a novel and objective non-statistical method for the identification of the data's TRTS. Our proposed approach is called the Angles method since it utilizes the angles between the hyperplanes to calculate the gap between the constant and variable TRTS assumptions. The gap is calculated for both the increasing and the decreasing sections of the frontier. The larger such gap is, the more the TRTS approaches the increasing and/or decreasing assumptions. The novelty of the Angles method is that it determines the TRTS by using only the dataset without any statistical assumptions. Moreover, the introduced gap in the Angles method represents the rate of increase or decrease of the TRTS. For the validation test of the proposed method, we examine 6 one input/one output cases. Also, we test the method using real world data of a major Canadian Bank.
In two recent papers, Lozano and Villa Centralized resource allocation using data envelopment analysis. Journal of Productivity Analysis 2004;22:143–61. 1 and Lozano et al. Centralized target setting ...for regional recycling operations using DEA. OMEGA 2004;32:101–10. 2 introduce the concept of “centralized” data envelopment analysis (DEA) models, which aim at optimizing the combined resource consumption by all units in an organization rather than considering the consumption by each unit separately. This is particularly relevant for situations where some variables are controlled by a central authority (e.g. Head Office) rather than individual unit managers. In this paper we reconsider one of the centralized models proposed by the above-mentioned authors and suggest modifying it to only consider adjustments of previously inefficient units. We show how this new model formulation relate to a standard DEA model, namely as the analysis of the mean inefficient point. We also provide a procedure that can be used to generate alternative optimal solutions, enabling a decision maker to search through alternate solution possibilities in order to select the preferred one. We then extend the model to incorporate non-transferable as well as strictly non-discretionary variables and illustrate the models using an empirical example of a public service organization.
In this paper, we focus on evaluating the performance of the commercial branches of a large Canadian bank using data envelopment analysis. Two production models are considered in this country-wide ...evaluation. One model, looking directly at resource usage, is most useful to the branch manager. The other model, incorporating financial results, is more geared towards senior management. We introduce non-discretionary factors to reflect specific aspects of the environment a branch is operating in, such as risk and economic growth rate of the region. Both input and output multipliers are constrained by incorporating market prices as well as managerial preferences, in order to get effectiveness measures. The cost-minimisation study led to valuable results pertaining to the performance of individual branches. Notable is the methodology introduced here that shows how to present graphical and numeric outcomes to managers. Gap maps, pie charts and target tables are produced for each branch to provide performance goals for the managers. Useful information has also been obtained at the district level. Output oriented models were analysed to reflect the Bank's recent emphasis towards growth in some areas.
•Data envelopment analysis can used to assess relative financial risk tolerance.•Risk tolerance is a multidimensional concept.•Risk is characterized by 4 elements: attitude, propensity, capacity, and ...knowledge.•Women may perceive risk differently than men.
Typical questionnaires administered by financial advisors to assess financial risk tolerance mostly contain stereotypes of people, have seemingly unscientific scoring approaches and often treat risk as a one-dimensional concept. In this work, a mathematical tool was developed to assess relative risk tolerance using Data Envelopment Analysis (DEA). At its core, it is a novel questionnaire that characterizes risk by its four distinct elements: propensity, attitude, capacity, and knowledge. Over 180 individuals were surveyed and their responses were analyzed using the Slacks-based measure type of DEA efficiency model. Results show that the multidimensionality of risk must be considered for complete assessment of risk tolerance. This approach also provides insight into the relationship between risk, its elements and other variables. Specifically, the perception of risk varies by gender as men are generally less risk averse than women. In fact, risk attitude and knowledge scores are consistently lower for women, while there is no statistical difference in their risk capacity and propensity compared to men. The tool can also serve as a “risk calculator” for an appropriate and defensible method to meet legal compliance requirements, known as the “Know Your Client” rule, that exist for Canadian financial institutions and their advisors.
This paper presents a framework where data envelopment analysis (DEA) is used to measure
overall efficiency and show how to apply this framework to assess
effectiveness for more general behavioral ...goals. The relationships between various cone-ratio DEA models and models to measure overall efficiency are clarified. Specifically it is shown that as multiplier cones tighten, the cone-ratio DEA models converge to measures of overall efficiency. Furthermore, it is argued that multiplier cone and cone-ratio model selection must be consistent with the behavioral goals assigned or assumed for purposes of analysis. Consistent with this reasoning, two new models are introduced to measure effectiveness when value measures are represented by separable or linked cones, where the latter can be used to analyze profit-maximizing effectiveness.
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