Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

2017 ◽  
Vol 9 (1) ◽  
pp. 132 ◽  
Author(s):  
Dinh Xuan Cuong ◽  
Hoang Thi Hien ◽  
Tran Long

The commercial banks (CBs) performance evaluating has been a necessary problem in currently integration trend and usually implemented by a committee of experts under criteria selected. Therefore, it is considered as a Multi - Criteria Decision - Making model (MCDM). Nowadays, there have been many researches proposing various standards and models to evaluate and rank CBs. But in Vietnam, the number of studies related to the Vietnamese banking evaluation model have still been limited. As a result, this study develops a multi-criteria decision model integrating Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The proposed model has evaluated and ranked five Vietnamese commercial banks including CTG, VCB, BIDV, TCB and MB. The paper revealed their ranks. Besides, the results of the research show that the Analytical Hierarchy Process (AHP) model is suitable for applying it to the process evaluating bank performance.


Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay

The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.


2015 ◽  
Vol 220-221 ◽  
pp. 188-193
Author(s):  
Tomasz Giesko

When designing unique optomechatronic systems with the application of innovative solutions, decision making with respect to a number of technical and economic criteria seems to be an essential problem. The multi-criteria decision theory is a process of selecting the best solution to the set of alternatives. The paper presents the application of the TOPSIS method for working towards a solution to decision making in the process of designing a unique measurement vision system. The set of alternatives for the vision system has been considered with regard to benefit and cost criteria. As a result, the best alternative has been identified, which represents the highest similarity to the ideal solution expressed by the value of the relative closeness index.


Author(s):  
Deniz Okul ◽  
Cevriye Gencer ◽  
Emel Kizilkaya Aydogan

Stochastic multi-criteria acceptability analysis (SMAA-2) and the technique for order preference by similarity to ideal solution (TOPSIS) are methods for evaluating alternatives with multiple criteria. SMAA is a method that is used for solving multi-criteria decision-making problems with uncertain, inaccurate information, and does not require preference information from the decision makers. The TOPSIS method is based on the principle of determining a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution. This paper proposes a new method, SMAA-TOPSIS, by combining the SMAA and TOPSIS methods. The SMAA-TOPSIS method was executed for two problems: drug benefit-risk analysis and machine gun selection. This paper found that TOPSIS could be used with uncertain and arbitrarily distributed values for weights and criteria measurements by using a combination of SMAA and TOPSIS. Also, we obtained clearer and consistent SMAA outputs.


Corn is a staple food ingredient, one of the areas where people consume corn instead of rice is Southeast Sulawesi. Qualified corn is one of the superior seeds, while some types of superior corn are hybrid corn and composite corn. The TOPSIS method is one of the multi criteria decision-making methods with simple concepts and efficient competition and has the ability to measure relative performance and alternative decisions in mathematical form. To make it easier to find qualified corn, the Technique for Order preference method is used. Similarity to Ideal Solution. This is facilitating corn farmers to choose good and productive corn crop quality, applying the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) in determining quality, to help provide alternatives in m determine qualified corn plants. Based on the results of research conducted on 10 qualified corn alternatives that had been tested, a result is obtained: V1 = 0.577350 V2 = 0.474992 V3 = 0.510529 V4 = 0.463630 V5 = 0.609622 V6 = 0.435983 V7 = 0.533048 V8 = 0.373977 V9 = 0.530333 V10 = 0.448275 From the results it can be concluded that V5 = 0.609622 had fulfilled the requirements and can be said to be good qualified corn.


2019 ◽  
Vol 13 (01) ◽  
pp. 2050002
Author(s):  
Aliya Fahmi ◽  
Muhammad Aslam ◽  
Fuad Ali Ahmed Almahdi ◽  
Fazli Amin

In this paper, we define the new idea of triangular cubic hesitant fuzzy number (TCHFN). We discuss some basic operational laws of triangular cubic hesitant fuzzy number and hamming distance of TCHFNs. We introduce the new concept of triangular cubic hesitant TOPSIS method. Furthermore, we extend the classical cubic hesitant the technique for order of preference by similarity to ideal solution (TOPSIS) method to solve the Multi-Criteria decision-making (MCDM) method based on triangular cubic hesitant TOPSIS method. The new ranking method for TCHFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.


Author(s):  
Vu Duc Thanh ◽  
Luu Huu Van ◽  
Nguyen Thi Anh Tuyet ◽  
Hoang Minh Tuan

The COVID-19 pandemic has led to disruptions in consumers' lifestyles and purchases, as well as businesses' online business models. Online platforms are increasingly used for shopping purposes. To evaluate and choose an e-commerce platform requires using many criteria and decision makers. Therefore, the process of evaluating and selecting an e-commerce platform is viewed as a multi-criteria decision-making problem. The objective of this study is to develop a multi-criteria decision-making model to help consumers evaluating the e-commerce platforms. In the proposed model, the ratings of alternatives and the weights of the criteria are evaluated using the linguistic variable. Simulation examples are used to show the effectiveness of the model in practice.  Keywords: Fuzzy TOPSIS, E-Commerce Platform, Mcdm, Fuzzy Sets.


Author(s):  
Merve Cengiz Toklu

Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.


Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 259 ◽  
Author(s):  
Chun-Ho Chen

The type of criterion weight can be distinguished according to different decision methods. Subjective weights are given by decision makers based on their knowledge, experience, expertise, and other factors. Objective weights are obtained through multi-step calculations of the evaluation matrix constructed from the actual information about the evaluation criteria of the alternatives. A single consideration of these two types of weights often results in biased results. In addition, in order to build an effective supply chain source, buyers must find suitable quality products and/or service providers in the process of supplier selection. Based on the above reasons, it is difficult to accurately select the appropriate alternative. The main contribution of this paper is to combine entropy weight, analytic hierarchy process (AHP) weight, and the technique for order preference by similarity to an ideal solution (TOPSIS) method into a suitable multi-criteria decision making (MCDM) solution. The TOPSIS method is extended with entropy-AHP weights, and entropy-AHP weights are used instead of subjective weights. A novel decision-making model of TOPSIS integrated entropy-AHP weights is proposed to select the appropriate supplier. Finally, we take the selection of building material suppliers as an example and use sensitivity analysis to show that the combination of the TOPSIS method based on entropy-AHP weights can effectively select the appropriate supplier.


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