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Author Wang, T.-Y.; Yang, Y.-H. doi  openurl
  Title A fuzzy model for supplier selection in quantity discount environments Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 10 Pages (down) 12179-12187  
  Keywords Supplier selection; Multi-Objective Linear Programming; Analytical Hierarchy Process; Fuzzy compromise programming  
  Abstract Traditionally, supplier selection should simultaneously take into account numerous heterogeneous criteria, and then is a tedious task for the purchasing decision makers. It becomes especially complicated when quantity discounts are considered at the same time. Under such manner, most studies often formulate such a problem as a Multi-Objective Linear Programming (MOLP) problem, and then scale it down to a Mixed Integer Programming (MIP) problem to handle the inherited multi-objectives simultaneously. However, this approach often neglects to consider scaling and subjective weighting issues. In order to ease the problem mentioned above and to obtain a more reasonable compromise solution for allocating order quantities among suppliers with their quantity discount rate offered, the Analytical Hierarchy Process (AHP) and fuzzy compromise programming are introduced in this study. An illustrated example is presented to demonstrate the proposed model and to illuminate two kinds of attitudes for decision makers. The information from the experiments can be utilized further to explain the suppliers’ possible improvement and to help create win-win policies.  
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  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ WangYang2009 Serial 4698  
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Author Seçme, N.Y.; Bayrakdaroğlu, A.; Kahraman, C. doi  openurl
  Title Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 9 Pages (down) 11699-11709  
  Keywords Performance evaluation; Multi-criteria decision making; Fuzzy; AHP; TOPSIS; Turkish Banking Sector  
  Abstract The performance evaluation of banks has important results for creditors, investors and stakeholders since it determines banks’ capabilities to compete in the sector and has a critical importance for the development of the sector. The aim of this study is to propose a fuzzy multi-criteria decision model to evaluate the performances of banks.The largest five commercial banks of Turkish Banking Sector are examined and these banks are evaluated in terms of several financial and non-financial indicators. Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods are integrated in the proposed model. After the weights for a number of criteria are determined based on the opinions of experts using the FAHP method, these weights are input to the TOPSIS method to rank the banks. The results show that not only financial performance but also non-financial performance should be taken into account in a competitive environment.  
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  Language Summary Language Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ SecmeBayrakdarogluKahraman2009 Serial 4639  
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Author Tsai, M.-C.; Lin, S.-P.; Cheng, C.-C.; Lin, Y.-P. doi  openurl
  Title The consumer loan default predicting model – An application of DEA-DA and neural network Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 9 Pages (down) 11682-11690  
  Keywords Consumer loans; Money attitude; Neural networks; DEA–DA; DEA; Logistic regression  
  Abstract In this paper we construct the consumer loan default predicting model through conducting the empirical analysis on the customers of unsecured consumer loan from a certain financial institution in Taiwan, and adopt the borrower’s demographic variables and money attitude as the real-timeaneous discriminant information. Furthermore, we construct respectively through four predicting methods, such as DA, LR, NN and DEA-DA, to compare the suitability of these four mentioned methods. The results show that DEA-DA and NN are possessed better predicting capability and they are the optimal predicting model that this study longing for. In addition, this study showed that the default loan predicting model will be possessed higher level of predicting capability after added money attitude.  
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  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ TsaiLinChengLin2009 Serial 4676  
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Author Estrada, S.A.; Song, H.S.; Kim, Y.A.; Namn, S.H.; Kang, S.C. doi  openurl
  Title A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 9 Pages (down) 11595-11604  
  Keywords Data Envelopment Analysis (DEA ); Self-Organizing Map; Reinforcement Learning; Proximity-based target selection; Benchmarking  
  Abstract DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually. The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.  
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  Notes Approved  
  Call Number Admin @ admin @ EstradaSongKimNamnKang2009 Serial 4462  
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Author Lin, S.-W.; Shiue, Y.-R.; Chen, S.-C.; Cheng, H.-M. doi  openurl
  Title Applying enhanced data mining approaches in predicting bank performance: A case of Taiwanese commercial banks Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 9 Pages (down) 11543-11551  
  Keywords Bank performance; Data mining; Particle swarm optimization; Parameter optimization; Feature selection  
  Abstract The prediction of bank performance is an important issue. The bad performance of banks may first result in bankruptcy, which is expected to influence the economics of the country eventually. Since the early 1970s, many researchers had already made predictions on such issues. However, until recent years, most of them have used traditional statistics to build the prediction model. Because of the vigorous development of data mining techniques, many researchers have begun to apply those techniques to various fields, including performance prediction systems. However, data mining techniques have the problem of parameter settings. Therefore, this study applies particle swarm optimization (PSO) to obtain suitable parameter settings for support vector machine (SVM) and decision tree (DT), and to select a subset of beneficial features, without reducing the classification accuracy rate. In order to evaluate the proposed approaches, dataset collected from Taiwanese commercial banks are used as source data. The experimental results showed that the proposed approaches could obtain a better parameter setting, reduce unnecessary features, and improve the accuracy of classification significantly.  
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  Notes Approved  
  Call Number Admin @ admin @ LinShiueChenCheng2009 Serial 4555  
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Author Lin, H.-T. doi  openurl
  Title Efficiency measurement and ranking of the tutorial system using IDEA Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 8 Pages (down) 11233-11239  
  Keywords Efficiency; Data Envelopment Analysis (DEA ); Possibility level  
  Abstract This paper considers how to conduct the efficiency measurement and ranking problem of the tutorial system of some higher education institutions (HEIs) in Taiwan more convincingly and persuasively. Measuring the efficiencies of tutors and rewarding the outstanding tutors are conducted once each academic year and have become an important part of the administration practices. The current performance evaluation methods consider only the output factors inhered in vagueness, while the input are neglected. In order to better reflect the actual situations that different tutors consume various amounts of input to produce various amounts of outputs, an IDEA (imprecise data envelopment analysis) model is proposed to measure the efficiencies of tutors under different possibility levels by incorporating the current methods to serve as output factors and additionally considering the input factor. The proposed evaluation approach, which contains efficiency measurement, ranking guide and ties broken rule, can be applied easily to obtain objective and fair results of the addressed problem. A numerical example is used to illustrate the implementation of the proposed approach.  
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  Notes Approved  
  Call Number Admin @ admin @ Lin2009 Serial 4550  
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Author Lee, C.-C. doi  openurl
  Title Analysis of overall technical efficiency, pure technical efficiency and scale efficiency in the medium-sized audit firms Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 8 Pages (down) 11156-11171  
  Keywords Data Envelopment Analysis (DEA ); Medium-sized audit firms; Overall technical efficiency; Pure technical efficiency; Scale efficiency  
  Abstract This study uses the data envelopment analysis (DEA) to evaluate the operational efficiency of 173 medium-sized audit firms in 2005. The empirical result indicates that there are 24 audit firms with the overall technical efficiency value of 1. In terms of overall technical efficiency, pure technical efficiency and scale efficiency, the result shows that the average scale efficiency of all samples is higher than the average pure technical efficiency. Besides, 55 firms of 173 audit firms are in the stage of constant returns to scale, 18 firms are in the stage of increasing returns to scale, 100 of them are in the stage of decreasing returns to scale. Thus, most of medium-sized audit firms are in the stage of decreasing returns to scale. In addition, this paper finds that the larger the scale, the higher the above three efficiency values. The audit firms with higher business revenues have better operational efficiency. The overall technical efficiency and sale efficiency of the audit firms with branches are significantly higher than those without branches. The audit firms with larger number of employees and partners, they perform significantly better overall technical efficiency and sale efficiency. Finally, the audit firms with higher total expenditures also have significantly higher operational efficiency.  
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  Call Number Admin @ admin @ Lee2009a Serial 4541  
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Author Azadeh, A.; Saberi, M.; Gitiforouz, A.; Saberi, Z. doi  openurl
  Title A hybrid simulation-adaptive network based fuzzy inference system for improvement of electricity consumption estimation Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 8 Pages (down) 11108-11117  
  Keywords Hybrid; Adaptive network based fuzzy inference system; Computer simulation; Improvement; Time series; Electricity consumption  
  Abstract This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and complex estimation and forecasting. Computer simulation is developed to generate random variables for monthly electricity consumption. Various structures of ANFIS are examined and the preferred model is selected for estimation by the proposed algorithm. Finally, the preferred ANFIS and time series models are selected by Granger-Newbold test. Monthly electricity consumption in Iran from 1995 to 2005 is considered as the case of this study. The superiority of the proposed algorithm is shown by comparing its results with genetic algorithm (GA) and artificial neural network (ANN). This is the first study that uses a hybrid ANFIS computer simulation for improvement of electricity consumption estimation.  
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  Call Number Admin @ admin @ AzadehSaberiGitiforouzSaberi2009 Serial 4365  
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Author Wu, H.-Y.; Tzeng, G.-H.; Chen, Y.-H. doi  openurl
  Title A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 6 Pages (down) 10135-10147  
  Keywords FMCDM; Balance Scorecard (BSC); Fuzzy Analytic Hierarchy Process (FAHP); TOPSIS; VIKOR  
  Abstract The paper proposed a Fuzzy Multiple Criteria Decision Making (FMCDM) approach for banking performance evaluation. Drawing on the four perspectives of a Balanced Scorecard (BSC), this research first summarized the evaluation indexes synthesized from the literature relating to banking performance. Then, for screening these indexes, 23 indexes fit for banking performance evaluation were selected through expert questionnaires. Furthermore, the relative weights of the chosen evaluation indexes were calculated by Fuzzy Analytic Hierarchy Process (FAHP). And the three MCDM analytical tools of SAW, TOPSIS, and VIKOR were respectively adopted to rank the banking performance and improve the gaps with three banks as an empirical example. The analysis results highlight the critical aspects of evaluation criteria as well as the gaps to improve banking performance for achieving aspired/desired level. It shows that the proposed FMCDM evaluation model of banking performance using the BSC framework can be a useful and effective assessment tool.  
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  Notes Approved  
  Call Number Admin @ admin @ WuTzengChen2009 Serial 4715  
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Author Zerafat Angiz L., M.; Emrouznejad, A.; Mustafa, A.; Rashidi Komijan, A. doi  openurl
  Title Selecting the most preferable alternatives in a group decision making problem using DEA Type
  Year 2009 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 36 Issue 5 Pages (down) 9599-9602  
  Keywords Group decision making; Preferential voting system; Data Envelopment Analysis (DEA ); Most preferable alternative  
  Abstract Group decision making is the study of identifying and selecting alternatives based on the values and preferences of the decision maker. Making a decision implies that there are several alternative choices to be considered. This paper uses the concept of Data Envelopment Analysis to introduce a new mathematical method for selecting the best alternative in a group decision making environment. The introduced model is a multi-objective function which is converted into a multi-objective linear programming model from which the optimal solution is obtained. A numerical example shows how the new model can be applied to rank the alternatives or to choose a subset of the most promising alternatives.  
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  Notes Approved  
  Call Number Admin @ admin @ Zerafat-Angiz-L.EmrouznejadMustafaRashidi-Komijan2009 Serial 4733  
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