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  • A dynamic network DEA model with undesirable outputs
    • Hirofumi Fukuyama (Fukuoka University) and William L. Weber (Southeast Missouri State University)
      This paper integrates a network production technology within a dynamic framework with the theory used to measure the performance of Japanese Shinkin banks. The network technology assumes two stages where an intermediate output is produced in a first stage and then subsequently used to produce final outputs in the second stage. Final outputs consist of both desirable and undesirable outputs. Production in the first stage of the current period depends on the previous period¡Çs production undesirable outputs. Shinkin banks use labor, physical capital, and financial equity capital to produce the intermediate output of deposits in the first stage. In the second stage, deposits are used to produce a portfolio of loans and securities investments. The undesirable output of the second stage is non-performing loans. Those non-performing loans become an undesirable input in the next period¡Çs first stage of production and thus require more desirable inputs, such as equity capital, to offset their effects. The dynamic framework allows bank managers to maximize production possibilities over several periods. Thus, if a bad economy exists, bank managers might choose to forego some current lending opportunities in order to reduce non-performing loans and simultaneously reallocate resources to future periods when the economy might be expected to improve. Data on 270 Japanese Shinkin banks that operated during 2002 to 2009 are used to estimate the model. The directional distance function is used to measure bank performance and it is estimated using DEA (data envelopment analysis).

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  • A DEA Model with Identical Weight Assignment Based on Multiple Perspectives
    • Xiaopeng Yang (Osaka University) and Hiroshi Morita (Osaka University)
      As a powerful tool for evaluating the efficiencies of decision making units (DMUs), one key function of data envelopment analysis (DEA) is to allow individual DMUs to select the optimal variable weights that are the most advantageous in the process of calculating their efficiency scores. For a complicated banking system with various financial attributes, there are usually different classifications of inputs and outputs from the perspectives of different stakeholders. In order to obtain the highest efficiency score, different perspectives tend to select different weight assignment schemes, even in evaluating the same bank. If we select a weight assignment to cater to one stakeholder, other stakeholders may feel dissatisfied. Thus, there is the need to seek an identical set of weights that can balance multiple perspectives (Pareto optimality) based on their market statuses in order to rank the efficiency scores of DMUs in the case of multiple perspectives. In the present paper, we propose a new DEA model incorporating Nash bargaining game (NBG) theory, which focuses on seeking an identical weight assignment scheme to cater to multiple perspectives.
  • On the non-oriented epsilon-based measure of efficiency in DEA
    • ÅẬ·°(À¯ºö¸¦µæÂç³Ø±¡Âç³Ø)¡¢Åû°æÈþ¼ù(ÅÅÎÏÃæ±û¸¦µæ½ê)
      In this paper, we present the non-oriented (i.e. both input- and output-oriented) version of the epsilon- based measure of efficiency (EBM) in DEA and point to a strange property of the model that the constant returns-to scale model and the variable returns-to-scale model yield the same efficiency score. We clarify this phenomenon and demonstrate how to get rid of such inconvenience. The unique features of this paper are (1) unification of radial and non-radial models in a single framework called EBM and (2) extension to the non-oriented case which is suitable for measuring both input-side and output-side inefficiencies simultaneously.
      In DEA, we have two typical measures of technical efficiency with different characteristics: radial and non-radial. Historically, the radial measure, represented by the CCR model, was the first DEA model, whereas the non-radial model, represented by the SBM model was a latecomer. For instance, in the input-oriented case, the CCR deals mainly with proportionate reduction of input resources that can produce the current outputs. In contrast, the non-radial models put aside the assumption of proportionate contraction in inputs and aim at obtaining maximum rates of reduction in inputs that may discard varying proportions of original input resources.
      The main shortcoming of the CCR model is the neglect of non-radial slacks in reporting of the efficiency score. So, if these slacks have an important role in evaluating managerial efficiency, the radial approaches may mislead the decision when we utilize the efficiency score as the only index for evaluating performance of DMUs.
      Since models such as SBM capture the non-radial slacks directly, the optimal efficiency value accounts for the non-radial slacks which are not considered in the radial models. The SBM-projection to the efficient frontier is defined by subtracting or adding the slacks. Thus, the projected DMU may lose the proportionality in the original data. If the loss of the original proportionality is inappropriate for the analysis, then this becomes a shortcoming for non-radial models.
      In Tone and Tsutsui [1], we proposed an epsilon-based measure of efficiency (EBM) in DEA as a third pole of technical efficiency. This model integrates radial and non-radial models in a unified framework through a newly defined affinity index between inputs/outputs. A new principal component analysis (PCA) is applied to determine the epsilon (the radial vs. non-radial ratio) and the weights for input/output items. In the EJOR paper, we mainly presented input/output oriented EBM models. In this paper we observe the non-oriented version of this model and show that the variable returns-to-scale case yields the same score as the constant returns-to-scale case. To prevent such inconvenience we need to add some other constraints on the model. These include constraints on the radial reduction rate of inputs or the radial expansion rate of outputs. We discuss this subject in this paper.
      Reference: [1] Tone K. and Tsutsui M. An epsilon-based measure of efficiency in DEA: A third pole of technical efficiency, European Journal of Operational Research, 207 (2010) 1554-1563.

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