Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model

2016 ◽  
Vol 16 (04) ◽  
pp. 1043-1068 ◽  
Author(s):  
Wei-Hsin Kong ◽  
Tsu-Tan Fu ◽  
Ming-Miin Yu

This paper develops a range directional distance data envelopment analysis (DEA) model to simultaneously deal with the problems of negative data and undesirable outputs in the study of performance measurement with two-stage DEA. We report on the development of this model to handle both positive and negative data in a DEA framework and accommodate the problem of undesirable intermediate outputs in the first stage of operational processes. Unlike previous two-stage DEA models we allow for a nonuniform abatement factor imposing on stage 1’ production technology. Such a model is then applied to evaluate Taiwanese bank efficiencies both at the operational stage and profitability stage in banking activities based on a data set consisting of 35 domestic banks in Taiwan in the period 2007. The results indicate that, by the range directional two-stage data envelopment analysis model, the operational efficiency was smaller than the profitability efficiency. Many banks generated too many performing loans in which independent banks should reduce more performing loans than financial holding company subsidiary banks. Both the ratio of investments to loans and the ratio of nonperforming loans to performing loans did not have significant contributions to the efficiency. This paper is able to provide information for bank operators and researchers on the managerial and strategic implications of how negative data and undesirable outputs affect efficiency and how to measure efficiency appropriately.

2015 ◽  
Vol 25 (14) ◽  
pp. 1540036 ◽  
Author(s):  
Li Fang Fu ◽  
Jun Meng ◽  
Ying Liu

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.


2020 ◽  
Vol 15 (2) ◽  
pp. 165
Author(s):  
Asmina Akter

In this study an Output-oriented DEA (Data Envelopment Analysis) model is used to measure operational efficiency of foreign branches of Bangladeshi banks as financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit. Among 58 Bangladeshi banks there are only three Bangladeshi banks which have in total seven foreign branches in different foreign locations. A branch of bank can’t be separated legally from its parent company and supervised by its home authorities as part of supervision of the banking group as a whole. By employing DEA model and using “Financial Intermediary Approach” this study found that as a financial intermediary organization between savers and borrowers these foreign branches of Bangladeshi banks are performing efficiently over the years. Among three banks Janata Bank Limited and AB Bank limited are performing most efficiently and Sonali Bank Limited is performing less efficiently relative to two other banks in operating their foreign branches as a financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Nafiseh Javaherian ◽  
Ali Hamzehee ◽  
Hossein Sayyadi Tooranloo

Data envelopment analysis (DEA) is a powerful tool for evaluating the efficiency of decision-making units for ranking and comparison purposes and to differentiate efficient and inefficient units. Classic DEA models are ill-suited for the problems where decision-making units consist of multiple stages with intermediate products and those where inputs and outputs are imprecise or nondeterministic, which is not uncommon in the real world. This paper presents a new DEA model for evaluating the efficiency of decision-making units with two-stage structures and triangular intuitionistic fuzzy data. The paper first introduces two-stage DEA models, then explains how these models can be modified with intuitionistic fuzzy coefficients, and finally describes how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. In the end, the proposed method is used to solve an illustrative numerical example.


Author(s):  
Morteza Shafiee

Rapidly changing environment has affected organizations' ability to maintain viability. As a result, various criteria and uncertain situations in a complex environment encounter problems when using the traditional performance evaluation with precise and deterministic data. The purpose of this paper is to propose an applicable model for evaluating the performance of the overall supply chain (SC) network and its members. Performance evaluation methods, which do not include uncertainty, obtain inferior results. To overcome this, rough set theory (RST) was used to deal with such uncertain data and extend rough noncooperative Stackelberg data envelopment analysis (DEA) game to construct a model to evaluate the performance of supply chain under uncertainty. This applies the concept of Stackelberg game/leader–follower in order to develop models for measuring performance. The ranking method of noncooperative two-stage rough DEA model is discussed. While developing the model, which is suitable to evaluate the performance of the supply chain network and its members when it operates in uncertain situations and involves a high degree of vagueness. The application of this paper provides a valuable procedure for performance evaluation in other industries. The proposed model provides useful insights for managers on the measurement of supply chain efficiency in uncertain environment. This paper creates a new perspective into the use of performance evaluation model in order to support managerial decision-making in the dynamic environment and uncertain situations.


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