scholarly journals IT2 Hybrid Decision-Making Approach to Performance Measurement of Internationalized Firms in the Baltic States

2019 ◽  
Vol 11 (1) ◽  
pp. 296 ◽  
Author(s):  
Hasan Dinçer ◽  
Serhat Yüksel ◽  
Renata Korsakienė ◽  
Agota Giedrė Raišienė ◽  
Yuriy Bilan
Keyword(s):  
Decision Making ◽  
Performance Measurement ◽  
Positive Influence ◽  
Decision Makers ◽  
Baltic States ◽  
Integrated Method ◽  
The Baltic ◽  
Interval Type ◽  
Decision Making Model

International activities of firms contribute to environmental socio-economic development and have a positive influence on prosperity of countries. The novelty of this study is to extend prevailing theory on the performance measurement of internationalized firms by suggesting a hybrid decision-making model based on interval type 2 fuzzy sets for the Baltic states. The integrated method is defined as the interval type-2 (IT2) decision making trial and evaluation laboratory qualitative flexible multiple criteria method (DEMATEL-QUALIFLEX). IT2 DEMATEL is used for weighting each criterion of internationalized firms and IT2 QUALIFLEX is applied for ranking the Baltic states, respectively. Within this context, six different criteria are defined for ranking the internationalized firms of the Baltic states. The ranking of all three countries enable us to conclude that Estonia demonstrates the best results of internationalized firms. Meanwhile, Latvia has the worst performance of internationalized firms. The findings are useful for decision makers responsible for supportive policies focused on the research and development (R&D) and internationalization of firms. The implications for managers lie in the awareness of necessary conditions for successful internationalization. The study extends prevailing knowledge on the performance measurement of internationalized firms and provides findings on multinational companies (MNCs) in the Baltic states’ context.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

Evaluation of Renewable Energy Alternatives using Hesitant Fuzzy TOPSIS and Interval Type-2 Fuzzy AHP

2015 ◽  
pp. 191-224 ◽  
Author(s):  
Başar Öztayşi ◽  
Cengiz Kahraman
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Fuzzy Sets ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Priority Weights ◽  
Interval Type

The selection among renewable energy alternatives is a fuzzy multicriteria problem with many conflicting criteria under uncertainty. In many decision-making problems, the Decision Makers (DM) define their preference in linguistic form since it is relatively difficult to provide exact numerical values during the evaluation of alternatives. Therefore, in many studies, fuzzy logic is successfully used to model this kind of uncertainty. In this chapter, the authors try to capture this uncertainty by using interval type-2 fuzzy sets and hesitant fuzzy sets. They propose a fuzzy multicriteria method for the evaluation of renewable energy alternatives, in which the priority weights of the criteria are determined by interval type-2 fuzzy AHP, and the alternatives are ranked using hesitant fuzzy TOPSIS. A case study is also given.

Evaluation of Renewable Energy Alternatives Using Hesitant Fuzzy TOPSIS and Interval Type-2 Fuzzy AHP

2017 ◽  
pp. 1378-1412 ◽  
Author(s):  
Başar Öztayşi ◽  
Cengiz Kahraman
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Fuzzy Sets ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Priority Weights ◽  
Interval Type

The selection among renewable energy alternatives is a fuzzy multicriteria problem with many conflicting criteria under uncertainty. In many decision-making problems, the Decision Makers (DM) define their preference in linguistic form since it is relatively difficult to provide exact numerical values during the evaluation of alternatives. Therefore, in many studies, fuzzy logic is successfully used to model this kind of uncertainty. In this chapter, the authors try to capture this uncertainty by using interval type-2 fuzzy sets and hesitant fuzzy sets. They propose a fuzzy multicriteria method for the evaluation of renewable energy alternatives, in which the priority weights of the criteria are determined by interval type-2 fuzzy AHP, and the alternatives are ranked using hesitant fuzzy TOPSIS. A case study is also given.

scholarly journals A Big-Bang Big-Crunch Optimized General Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making

2013 ◽  
Vol 3 (2) ◽  
pp. 117-132 ◽  
Author(s):  
Syibrah Naim ◽  
Hani Hagras
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Group Decision Making ◽  
General Type ◽  
Group Decision ◽  
Big Bang ◽  
Decision Makers ◽  
Big Crunch ◽  
Interval Type

Abstract Multi-Criteria Group Decision Making (MCGDM) aims to find a unique agreement from a number of decision makers/users by evaluating the uncertainty in judgments. In this paper, we present a General Type-2 Fuzzy Logic based approach for MCGDM (GFLMCGDM). The proposed system aims to handle the high levels of uncertainties which exist due to the varying Decision Makers’ (DMs) judgments and the vagueness of the appraisal. In order to find the optimal parameters of the general type-2 fuzzy sets, we employed the Big Bang-Big Crunch (BB-BC) optimization. The aggregation operation in the proposed method aggregates the various DMs opinions which allow handling the disagreements of DMs’ opinions into a unique approval. We present results from an application for the selection of reading lighting level in an intelligent environment. We carried out various experiments in the intelligent apartment (iSpace) located at the University of Essex. We found that the proposed GFL-MCGDM effectively handle the uncertainties between the various decision makers which resulted in producing outputs which better agreed with the users’ decision compared to type 1 and interval type 2 fuzzy based systems.

A New Method for Solving Multi-Criteria Multi-Attributes Decision Making Based on the Ranking of Type-2 Fuzzy Variables

2021 ◽  
Vol 10 (1) ◽  
pp. 20-42
Author(s):  
Dhiman Dutta ◽  
Mausumi Sen ◽  
Ashok Deshpande ◽  
Biplab Singha
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Ranking Method ◽  
Ranking Methods ◽  
Fuzzy Variables ◽  
Decision Making Problem ◽  
Criteria Weights ◽  
Interval Type ◽  
Very High

In this paper, the authors have proposed the concept of interval type-2 triangular fuzzy variables. Then, they studied the concepts of value and ambiguity of interval type-2 triangular fuzzy variables and interval type-2 trapezoidal fuzzy variables. They introduced the concept of value and ambiguity in order to define the ranking method for the interval type-2 fuzzy variables. A comparative result of the various other ranking methods is also given in the tabular form. A multi-criteria multi-attributes decision-making problem is provided to explain the ranking method in which the evaluation ratings of the alternatives on the attributes, and the criteria weights as provided by the decision makers are expressed as linguistic terms (e.g., very high, medium, fair, and good). The multi-criteria multi-attributes decision-making problem is then worked out by applying the proposed algorithm.

scholarly journals An Interactive Data-Driven (Dynamic) Multiple Attribute Decision Making Model via Interval Type-2 Fuzzy Functions

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 584
Author(s):  
Baykasoğlu ◽  
Gölcük
Keyword(s):  
Decision Making ◽  
Historical Data ◽  
Multiple Attribute Decision Making ◽  
Data Driven ◽  
Decision Matrix ◽  
Multiple Attribute ◽  
Ranking Of Alternatives ◽  
Interval Type ◽  
Decision Making Model

A new multiple attribute decision making (MADM) model was proposed in this paper in order to cope with the temporal performance of alternatives during different time periods. Although dynamic MADM problems are enjoying a more visible position in the literature, majority of the applications deal with combining past and present data by means of aggregation operators. There is a research gap in developing data-driven methodologies to capture the patterns and trends in the historical data. In parallel with the fact that style of decision making evolving from intuition-based to data-driven, the present study proposes a new interval type-2 fuzzy (IT2F) functions model in order to predict current performance of alternatives based on the historical decision matrices. As the availability of accurate historical data with desired quality cannot always be obtained and the data usually involves imprecision and uncertainty, predictions regarding the performance of alternatives are modeled as IT2F sets. These estimated outputs are transformed into interpretable forms by utilizing the vocabulary matching procedures. Then the interactive procedures are employed to allow decision makers to modify the predicted decision matrix based on their perceptions and subjective judgments. Finally, ranking of alternatives are performed based on past and current performance scores.

scholarly journals The Likelihood Ranking Methods for Interval Type-2 Fuzzy Sets Considering Risk Preferences

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Meng Zhao ◽  
Song-song Qin ◽  
Qi-wang Li ◽  
Fu-qiang Lu ◽  
Zhe Shen
Keyword(s):  
Decision Making ◽  
Risk Preferences ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Ranking Methods ◽  
Decision Matrix ◽  
Signed Distance ◽  
Multiple Attribute ◽  
Interval Type

This paper proposes a ranking method that considers the risk preferences of decision makers for multiple-attribute decision-making problems in a multiple-interval type-2 trapezoidal fuzzy set environment. First, decision makers are classified according to the risk preferences and a measurement method of risk preferences is proposed. Second, a risk preference decision matrix is obtained and a new calculation formula of likelihood is defined. Finally, we obtain the ranking results of alternatives by calculating the signed distance. Our example analysis shows that the proposed method is scientific and reasonable, and different risk preferences influence the results of decision making. Comparison with previous methods shows that the proposed algorithm is more feasible; it is applicable for decision making on both risk preferences and risk conservation.

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