A Multi-granular Linguistic Decision Model for Evaluating the Quality of Network Services

Herrera, Francisco; Herrera‐Viedma, Enrique; Martínez, Luis; Mata, Francisco; Sánchez, Práxedes Muñoz

doi:10.1007/978-3-662-07950-8_5

Cited by 6 publications

(4 citation statements)

References 44 publications

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“…Hence, various MCDM methods have been extensively proposed to handle these problems in the economic, social, and management sciences [9][10][11][12][13][14][15][16][17][18]. Among them, AHP is one of the most popular MCDM methods, which has been identified as an essential method to solve MCDM problems, as well as one of the more practical ways of economic management and other fields [19][20][21][22].…”

Section: Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

Jia

Zhang

et al. 2020

Sustainability

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A high-quality credit index system is essential for technological small and medium-sized enterprises (TSMEs) to obtain financing from various institutions, such as banks, venture capital. Some attempts have made to construct the credit index system for TSMEs. However, the current credit index systems for TSMEs have placed too much emphasis on their financial ability with few prominent technological and talent indicators. Therefore, this study has proposed a dynamic credit index system for TSMEs in China using the Delphi and the Analytic Hierarchy Process (AHP) methods. This credit index system covers a wide range of indicators to measure the enterprises’ controller ability, operation and management ability, financial ability, and innovation capacity. This study made some contributions in the following aspects: (1) This study proposed a credit index system for TSMEs that highlights the main characteristics of technological innovation and talents of enterprises in China. (2) The credit index system is also highly adaptable as it can dynamically adjust the index weight according to the life cycles of TSMEs. (3) A case study of evaluating the credit of three TSMEs in China was selected to verify the feasibility and the effectiveness of this system. The results show that the credit index system constructed in this study provides a comprehensive and systematic model for evaluating the credit of TSMEs in China.

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Section: Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

Jia

Zhang

et al. 2020

Sustainability

Self Cite

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“…In the decision-making method, [5]- [7] have addressed the complexity issue in the decision-making method and it always a claim that one method is better and simple as compared to others. However, this claim lacks empirical justification.…”

Section: Introductionmentioning

confidence: 99%

Relative Complexity Index for Decision-Making Method

Hanif¹,

Mohamad²,

Dom³

2021

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The complexity of a method has been discussed in the decision-making area since complexity may impose some disadvantages such as loss of information and a high degree of uncertainty. However, there is no empirical justification to determine the complexity level of a method. This paper focuses on introducing a method of measuring the complexity of the decision-making method. In the computational area, there is an established method of measuring complexity named Big-O Notation. This paper adopts the method for determining the complexity level of the decision-making method. However, there is a lack of applying Big-O in the decision-making method. Applying Big-O in decision-making may not be able to differentiate the complexity level of two different decision-making methods. Hence, this paper introduces a Relative Complexity Index (RCI) to cater to this problem. The basic properties of the Relative Complexity Index are also discussed. After the introduction of the Relative Complexity Index, the method is implemented in Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method.

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“…It is natural that each evaluator has his/her own opinion and preference in the evaluation process due to different educational background, culture and experience [1]. There are several approaches to manage this situation such as multi-granular linguistic information and linear programming model [2], fusion method [3], preference ranking organization method (PROMETHEE) [4], multi-granular uncertain linguistic information [5] as to name a few. In this paper, we focus on multi-granular uncertain linguistic information as a tool to evaluate the alternatives based on different opinion with different measurement scales.…”

Section: Introductionmentioning

confidence: 99%

Consistent linguistic fuzzy preference relation with multi-granular uncertain linguistic information for solving decision making problems

Ridzuan

Mohamad

2016

AIP Conference Proceedings

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Multi-granular information in decision making is an approach used to cater heterogeneity in the evaluation process which normally presented using linguistic form. Sometimes the decision maker may use non homogeneous scales in the evaluation. This will increase the complexity in computation. This paper proposes a hybrid decision making model that combines the multi-granular uncertain linguistic information and consistent linguistic preference relations (CLFPR) to cater this problem. The proposed method able to evaluate the alternatives or criteria based on the different opinions with different scales using a minimum number of pairwise comparisons. The method uses several interval representations of linguistic judgment as its multi-granular representation to give decision makers flexibility in the evaluation. The evaluation will be aggregated into CLFPR values and before obtaining the final result. An illustrative example will be given to show the effectiveness of the proposed method.

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A Multi-granular Linguistic Decision Model for Evaluating the Quality of Network Services

Cited by 6 publications

References 44 publications

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

Relative Complexity Index for Decision-Making Method

Consistent linguistic fuzzy preference relation with multi-granular uncertain linguistic information for solving decision making problems

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