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Article
Publication date: 5 March 2018

Dilip Kumar Sen, Saurav Datta and S.S. Mahapatra

The purpose of this paper is to attempt supplier selection considering economic, environmental and social sustainability issues.

Abstract

Purpose

The purpose of this paper is to attempt supplier selection considering economic, environmental and social sustainability issues.

Design/methodology/approach

Subjective human judgment bears some kind of vagueness and ambiguity; fuzzy set theory has immense potential to overcome this. Owing to the advantage of intuitionistic fuzzy numbers set over classical fuzzy numbers set; three decision-making approaches have been applied here in intuitionistic fuzzy setting (namely, intuitionistic-TOPSIS, intuitionistic-MOORA and intuitionistic-GRA) to facilitate supplier selection in sustainable supply chain.

Findings

The stated objective of this research “to verify application potential of different decision support systems (in intuitionistic fuzzy setting) in the context of sustainable supplier selection” has been carried out successfully. A case empirical research has been conducted by applying three different decision-making approaches: intuitionistic fuzzy-TOPSIS, intuitionistic fuzzy-MOORA and intuitionistic fuzzy-GRA to an empirical data set of sustainable supplier selection problem. The ranking orders thus obtained through exploration of aforesaid three approaches have been explored and compared.

Originality/value

As compared to generalized fuzzy numbers, intuitionistic fuzzy numbers exhibit a membership degree, a non-membership degree and the extent of hesitation; a better way to capture inconsistency, incompleteness and imprecision of human judgment. Application potential of aforesaid three decision support approaches has been demonstrated in this reporting for a case sustainable supplier selection.

Details

Benchmarking: An International Journal, vol. 25 no. 2
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 1 February 2016

Shouzhen Zeng and Yao Xiao

The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic

Abstract

Purpose

The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic fuzzy ordered weighted averaging weighted averaging (OWAWA) distance TOPSIS (IFOWAWAD-TOPSIS) method for intuitionistic fuzzy multiple-criteria decision making (MCDM) problems.

Design/methodology/approach

Based on the OWAWA operator, the authors develop the intuitionistic fuzzy OWAWA distance measure, then the IFOWAWAD-TOPSIS method is obtained by using the IFOWAWAD and traditional TOPSIS.

Findings

The developed IFOWAWAD-TOPSIS method can overcome the drawback of traditional TOPSIS method that cannot consider both the subjective information of attributes and the attitudinal character of decision maker.

Research limitations/implications

Clearly, this paper is devoted to the OWA operator, MCDM and intuitionistic fuzzy theory.

Practical implications

The developed method is applicable in a wide range of situations such as decision-making, statistics, engineering and economics. A numerical example concerning investment selection is given to illustrate the practicability and usefulness of the proposed approach.

Originality/value

This paper fulfils an identified need to study how to make a decision considering both the subjective information of attribute and the attitudinal character of decision maker in intuitionistic fuzzy environment.

Details

Kybernetes, vol. 45 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 14 July 2020

Seyyed Habibollah Mirghafoori, Hossein Sayyadi Tooranloo and Sepideh Saghafi

In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic

Abstract

Purpose

In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy environment. Assessment of electronic service quality (ESQ) of libraries is significantly important according to their major roles. It should be noted that the ESQ has a significant impact on customer satisfaction, which improves organizational performance. Accordingly, low ESQ means waste of organizational resources and poor user satisfaction. So, there is a dire need to reflect reasons inducing failure modes in academic library ESQ. Thus, investigation of failure modes affecting academic library ESQ is highly important. One solution in this area is utilization of the intuitionistic fuzzy (IF) failure mode and effects analysis (FMEA) as one of the widely used methods for prediction and identification of failure modes.

Design/methodology/approach

The present study in terms of objective is applied and in terms of the type of method is descriptive-analytical. The research sample included four experts of Yazd academic Libraries (Iran). To collect data, three types of questionnaires were distributed among experts. The purpose of the first questionnaire was to identify and reach an agreement on e-library failure modes. Type II questionnaire was used to determine the importance of identified risk factors and Type III questionnaire was used to prioritize the factors.

Findings

Results indicate that the difficulty of using websites, lack of provided information feedback to users and lack of links on the website to users' are the main priorities for improving ESQ in the studied academic libraries.

Originality/value

In this approach, the Intuitionistic fuzzy Elimination Et Choix Traduisant la REalité and technique for order of preference by similarity to ideal solution method were used to rank failure modes in academic library ESQ within the FMEA framework.]

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Book part
Publication date: 5 October 2018

Long Chen and Wei Pan

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision…

Abstract

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

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Article
Publication date: 2 November 2015

Yujia Liu, Jian Wu and Changyong Liang

The purpose of this paper is to propose novel attitudinal prioritization and correlated aggregating methods for multiple attribute group decision making (MAGDM) with…

Abstract

Purpose

The purpose of this paper is to propose novel attitudinal prioritization and correlated aggregating methods for multiple attribute group decision making (MAGDM) with triangular intuitionistic fuzzy Choquet integral.

Design/methodology/approach

Based on the continuous ordered weighted average (COWA) operator, the triangular fuzzy COWA (TF-COWA) operator is defined, and then a novel attitudinal expected score function for triangular intuitionistic fuzzy numbers (TIFNs) is investigated. The novelty of this function is that it allows the prioritization of TIFNs by taking account of the expert’s attitudinal character. When the ranking order of TIFNs is determined, the triangular intuitionistic fuzzy correlated geometric (TIFCG) operator and the induced TIFCG (I-TIFCG) operator are developed.

Findings

Their use is twofold: first, the TIFCG operator is used to aggregate the correlative attribute value; and second, the I-TIFCG operator is designed to aggregate the preferences of experts with some degree of inter-dependent. Then, a TIFCG and I-TIFCG operators-based approach is presented for correlative MAGDM problems. Finally, the propose method is applied to select investment projects.

Originality/value

Based on the TIFCG and I-TIFCG operators, this paper proposes a novel correlated aggregating methods for MAGDM with triangular intuitionistic fuzzy Choquet integral. This method helps to solve the correlated attribute (criteria) relationship. Furthermore, by the attitudinal expected score functions of TIFNs, the propose method can reflect decision maker’s risk attitude in the final decision result.

Details

Kybernetes, vol. 44 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 6 July 2021

Mustafa Agdas and Cevriye Gencer

This study proposes a dynamic performance evaluation model to support the material availability of the public institution under performance- based logistics (PBL) and to…

Abstract

Purpose

This study proposes a dynamic performance evaluation model to support the material availability of the public institution under performance- based logistics (PBL) and to select the most appropriate service provider.

Design/methodology/approach

The model consists of four stages. In the first stage, a criteria set to evaluate alternatives is created. In the second stage, the DEA-MTFP index method is applied for performance evaluation of the alternatives by using crisp data. In the third stage, IFS theory is utilized for aggregating decision-maker judgments on alternatives, and in the last stage, the results of both methods are turned into single value, and it is selected as the most suitable alternative.

Findings

It is verified that the proposed approach can be implemented to the real-life dynamic multi-criteria decision-making (MCDM) problem that have crisp and fuzzy data under the PBL strategy.

Practical implications

This paper offers an integrated approach for performance analysis of service providers in a dynamic MCDM problem in which crisp and fuzzy data are used together. To illustrate applicability and validity of the proposed model, it is applied to a real-life problem.

Originality/value

This paper utilizes the DEA-MTFP index method and IFS theory in an integrated way.

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Article
Publication date: 3 July 2017

Santoso Wibowo and Srimannarayana Grandhi

The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group…

Abstract

Purpose

The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group decision-making problem and present a new multicriteria group decision-making approach for effectively evaluating the performance of KM practices to meet the interests of various stakeholders in small and medium enterprises (SMEs).

Design/methodology/approach

A new multicriteria group decision-making approach is developed for evaluating the performance of KM practices of individual SMEs. Intuitionistic fuzzy numbers are used for representing the subjective assessments of decision makers in evaluating the relative importance of the evaluation criteria and the performance of individual KM practices with respect to specific evaluation criteria. A fuzzy multicriteria group decision-making algorithm is developed for measuring and benchmarking the performance of alternative KM practices.

Findings

The proposed multicriteria group decision-making approach is capable of effectively evaluating the performance of KM practices through adequately considering the presence of multiple decision makers, the multi-dimensional nature of the evaluation problem, and appropriately modeling the subjectiveness and imprecision of the evaluation process. The presentation of an example shows that the proposed fuzzy multicriteria group decision-making algorithm is simple to use and efficient in computation.

Research limitations/implications

The outcome of the multicriteria group decision-making approach is highly dependent on the inputs provided by the decision maker.

Practical implications

The novelty from this research lies in the utilization of a multicriteria group decision-making approach for evaluating the performance of KM practices in an organization. The outcome from the performance evaluation process allows the enterprise to adopt appropriate KM practices for achieving competitive advantages.

Social implications

The proposed multicriteria group decision-making approach has a significant social implication as it can be used as a decision-making tool for providing various decision makers in SMEs with useful and strategic information concerning the performance of KM practices in a given situation.

Originality/value

The originality of this paper lies in the development of the multicriteria group decision-making approach for effectively measuring and benchmarking the performance of KM practices of individual SMEs.

Details

Benchmarking: An International Journal, vol. 24 no. 5
Type: Research Article
ISSN: 1463-5771

Keywords

Content available
Article
Publication date: 26 July 2018

Peide Liu and Hui Gao

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the…

Abstract

Purpose

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

Design/methodology/approach

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

Findings

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

Originality/value

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

Details

Marine Economics and Management, vol. 1 no. 1
Type: Research Article
ISSN: 2516-158X

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Article
Publication date: 6 February 2019

Mohamadreza Mahmoudi, Hannan Amoozad Mahdiraji, Ahmad Jafarnejad and Hossein Safari

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main…

Abstract

Purpose

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).

Design/methodology/approach

To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.

Findings

To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

Originality/value

In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.

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Article
Publication date: 3 March 2016

Eric Afful-Dadzie and Anthony Afful-Dadzie

The paper proposes an intuitionistic fuzzy TOPSIS multi-criteria decision making (MCDM) method for the selection of start-up businesses in a government venture capital…

Abstract

Purpose

The paper proposes an intuitionistic fuzzy TOPSIS multi-criteria decision making (MCDM) method for the selection of start-up businesses in a government venture capital (GVC) scheme. Most GVC funded start-ups fail or underperform compared to those funded by private venture capitals due to a number of reasons including lack of transparency and unfairness in the selection process. By its design, the proposed method is able to increase transparency and reduce the influence of bias in GVC start-up selection processes. The proposed method also models uncertainty in the selection criteria using fuzzy set theory that mirrors the natural human decision making process.

Design/methodology/approach

The proposed method first presents a set of criteria relevant to the selection of early stage but high potential start-ups in a Government Venture Capital (GVC) financing scheme. These criteria are then analyzed using the TOPSIS method in an intuitionistic fuzzy environment. The intuitionistic Fuzzy Weighted Averaging (IFWA) Operator is used to aggregate ratings of decision makers. A numerical example of how the proposed method could be used in GVC start-up candidates’ selection in a highly competitive government venture capital scheme is provided.

Findings

The methodology adopted increases fairness and transparency in the selection of start-up businesses for fund support in a government-run venture capital scheme. The criteria set proposed is ideal for selecting start-up businesses in a government controlled venture capital scheme. The decision making framework demonstrates how uncertainty in the selection criteria are efficiently modelled with the TOPSIS method.

Practical implications

As government venture capital schemes increase around the world, and concerns about failure and underperformance of GVC funded start-ups increase, the proposed method could help bring formalism and ensure the selection of start-ups with high success potential.

Originality/value

The framework designs relevant sets of criteria for a selection problem, demonstrates the use of extended TOPSIS method in intuitionistic fuzzy sets and apply the proposed method in an area that has not been considered before. Additionally, it demonstrates how intuitionistic fuzzy TOPSIS could be carried out in a real decision making application setting.

Details

Management Decision, vol. 54 no. 3
Type: Research Article
ISSN: 0025-1747

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