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Article
Publication date: 9 July 2018

Serhat Aydin

The purpose of this paper is to present the augmented reality (AR) eyeglass selection problem based on Neutrosophic MULTIMOORA method which is a very new multi-objective method.

Abstract

Purpose

The purpose of this paper is to present the augmented reality (AR) eyeglass selection problem based on Neutrosophic MULTIMOORA method which is a very new multi-objective method.

Design/methodology/approach

The author evaluates five AR goggles according to six different criteria. Criteria have different weights and determined by analytic hierarchy process. The author used neutrosophic MULTIMOORA method in order to evaluate AR eyeglasses.

Findings

Five different AR eyeglasses were evaluated and the best one was selected according to six different criteria (benefit and non-benefit). According to Neutrosophic MULTIMOORA method, Sony AR eyeglass is selected as the best one. Neutrosophic MULTIMOORA method uses simple computational equations and it handles multi-objective decision making problems effectively.

Originality/value

Evaluating AR goggles by using the Neutrosophic MULTIMOORA method for the first time is the originality of this paper.

Details

Journal of Enterprise Information Management, vol. 31 no. 4
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 17 April 2020

Huimin Li, Lelin Lv, Feng Li, Lunyan Wang and Qing Xia

The application of the traditional failure mode and effects analysis (FMEA) technique has been widely questioned in evaluation information, risk factor weights and…

Abstract

Purpose

The application of the traditional failure mode and effects analysis (FMEA) technique has been widely questioned in evaluation information, risk factor weights and robustness of results. This paper develops a novel FMEA framework with extended MULTIMOORA method under interval-valued Pythagorean fuzzy environment to solve these problems.

Design/methodology/approach

This paper introduces innovatively interval-value Pythagorean fuzzy weighted averaging (IVPFWA) operator, Tchebycheff metric distance and interval-value Pythagorean fuzzy weighted geometric (IVPFWG) operator into the MULTIMOORA submethods to obtain the risk ranking order for emergencies. Finally, an illustrative case is provided to demonstrate the practicality and feasibility of the novel fuzzy FMEA framework.

Findings

The feasibility and validity of the proposed method are verified by comparing with the existing methods. The calculation results indicate that the proposed method is more consistent with the actual situation of project and has more reference value.

Practical implications

The research results can provide supporting information for risk management decisions and offer decision-making basis for formulation of the follow-up emergency control and disposal scheme, which has certain guiding significance for the practical popularization and application of risk management strategies in the infrastructure projects.

Originality/value

A novel approach using FMEA with extended MULTIMOORA method is developed under IVPF environment, which considers weights of risk factors and experts. The method proposed has significantly improved the integrity of information in expert evaluation and the robustness of results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 13 no. 1
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 27 May 2021

Evans Opoku-Mensah, Yuming Yin, Love Offeibea Asiedu-Ayeh, Dennis Asante, Priscilla Tuffour and Sandra Asantewaa Ampofo

Existing studies have found that most merger and acquisition (M&A) activities do not create the intended synergy. These studies have mainly investigated how firms'…

Abstract

Purpose

Existing studies have found that most merger and acquisition (M&A) activities do not create the intended synergy. These studies have mainly investigated how firms' internal factors contribute to M&A successes or failures. The current study differs from the earlier ones by exploring how governments' activities can contribute to the creation of acquisition synergy.

Design/methodology/approach

A novel technique based on multi-objective optimization by ratio analysis and complex proportional assessment method under an interval-valued intuitionistic fuzzy (IVIF) environment is proposed to prioritize these government roles needed during the M&A process focusing on the Chinese M&A market.

Findings

Enactments of regulations and loan guarantees are the most important strategies to help Chinese acquirers overcome acquisition failures. While tax relief ranks third, government training support ranks fourth. Finally, the result shows that government institutional support is the least to help acquirers overcome acquisition failures.

Practical implications

The government has a role to play in the acquisition success. Although this study has prioritized governments' role in relative importance order, the authors recommend that governments capable of providing all these strategies should do so without any specific order. However, if otherwise, governments should not neglect the strategies with less weight completely but rather consider reducing capital allocations to such strategies. Moreover, this study shows how firms with stronger business ties with government officials may enjoy success during acquisition activities. The authors recommend that firms intending to make acquisitions develop stronger ties with governments in order to benefits from governments.

Originality/value

This is the first study to develop a theoretical framework showing how government can contribute to M&A success. The study achieves this by extending Keynesian's arguments and identifies five (5) ways in which governments can ensure acquisition success. Second, within fuzzy multi-criteria decision-making (F-MCDM) research, this study is the first to show the applicability of integrated multi-objective optimization by ratio analysis (MULTIMOORA) and complex proportional assessment (COPRAS) techniques in an IVIF environment. The novel methodology proposed in this study offers an insightful research method to future studies focusing on group decision problems.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

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Article
Publication date: 17 March 2021

Samaneh Zolfaghari and Seyed Meysam Mousavi

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the…

Abstract

Purpose

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the safety of patients, so they should be managed thoroughly. It is an intricate multi-attributes decision-making problem with uncertainty. Uncertain information in the form of fuzzy sets theory has been applied widely to describe the different aspects of system uncertainty. This study aims to present a new methodology to manage the healthcare system failures due to the multi-attributes decision-making process.

Design/methodology/approach

This study introduces a new risk evaluation methodology by failure mode and effect analysis (FMEA) and MULTIMOORA method. Group decision-making process in this methodology is presented under uncertain information in the form of interval-valued hesitant fuzzy linguistic sets (IVHFLSs). IVHFLSs encompass both qualitative and quantitative interpretation of experts to reflect their preferences, as well the ability and flexibility of derivation of linguistic information by several linguistic terms increase. To avoid the different ranking order of MULTIMOORA approaches, a new interval multi-approaches multi-attribute methodology, namely, technique of precise order preference (TPOP), is extended to provide precise ranking order.

Findings

The application and precision of proposed integrated IVHFL-MULTIMOORA methodology with TPOP is examined in a case study of healthcare systems. The results indicate the superiority of proposed methodology to prioritize and assess the failures as well as handling system uncertainty.

Originality/value

This study addresses the challenges of an organization to prioritize potential failures by implementing FMEA method. Moreover, this paper contributes to making the manager's ability in decision-making. The value of this study can be discussed in two aspects. First and foremost, this study provides a new FMEA-based methodology to rank failures precisely. The results prove that the proposed methodology is more robust to changes of different ranking order methods, applied by FMEA. On the other hand, using the capability of IVHFLSs allows collecting accurate information in an ambiguous and uncertain environment.

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Article
Publication date: 23 June 2020

Nezir Aydin and Sukran Seker

Low cost carriers (LCCs) have become one of the most significantly growing parts of the airline servicing market. This new player has redesigned the whole airline…

Abstract

Purpose

Low cost carriers (LCCs) have become one of the most significantly growing parts of the airline servicing market. This new player has redesigned the whole airline industry, which was previously led by the national/international full-service airline companies. Considering such advancements, the hub locations of LCCs became an important issue than ever before. Within this concept, a guiding framework is developed for an LCC company, which is in search of a new hub airport location within Turkey to satisfy the demand and attract new passengers.

Design/methodology/approach

An interval-valued intuitionistic fuzzy (IVIF) sets based weighted aggregated sum product assessment (WASPAS) and multi-objective optimization by ratio analysis (MULTIMOORA) methods are developed for decision-making processes.

Findings

Five airport locations are evaluated using the developed method. Results showed that in determining hub locations for LCCs, potential number of passengers of the city, airport quality and the number of hotels within the city are obtained as the three most important criteria among 12 evaluation criteria. The best location for the LCC company is determined as Antalya Airport.

Research limitations/implications

To apply the proposed method to a different set of alternatives, data gathered on comparing location of alternatives from experts should be updated.

Originality/value

Proposed hybrid framework is presented as the first time in the literature as a decision-making tool. In order to validate framework's applicability, efficiency and effectiveness, a comparison and a sensitivity analysis are conducted at the end of the study.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

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Book part
Publication date: 6 April 2021

Yeter Demir Uslu, Emre Yılmaz and Pakize Yiğit

In this study, it is aimed to correctly weigh the criteria for the selection of qualified manager in a healthcare facility and to make the right selection among candidates…

Abstract

In this study, it is aimed to correctly weigh the criteria for the selection of qualified manager in a healthcare facility and to make the right selection among candidates with an objective method. In this study, in which the health manager selection was carried out with fuzzy Analytical Hierarchy Process (AHP) and MULTIMOORA methods, 8 candidates were evaluated according to 12 personnel selection criteria. Comparative matrices of qualified health manager selection criteria were presented to the expert opinion and analyzed with the fuzzy AHP method. According to the analysis result, among the 12 criteria; The “Crisis Management Skill” criterion is in the first place with 12.5% weight; The “Social Responsibility Awareness” criterion was found to be in the last place with 3.2% weight. The MULTIMOORA method was applied by analyzing the interview scores and criterion weightings of the candidates evaluated by the jury. According to the results of MULTIMOORA, Candidate 1 first place and Candidate 6 ranked last.

Details

Strategic Outlook in Business and Finance Innovation: Multidimensional Policies for Emerging Economies
Type: Book
ISBN: 978-1-80043-445-5

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Article
Publication date: 23 August 2013

Saurav Datta, Nitin Sahu and Siba Mahapatra

The purpose of this paper is to report an efficient decision‐support system for industrial robot selection. It seeks to analyze potential robot selection attributes with a…

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Abstract

Purpose

The purpose of this paper is to report an efficient decision‐support system for industrial robot selection. It seeks to analyze potential robot selection attributes with a relatively new MCDM approach which employs grey set theory coupled with MULTIMOORA method.

Design/methodology/approach

Use of interval‐valued grey numbers (IVGN) adapted from grey theory has been explored to tackle subjective evaluation information collected from an expert group; finally MULTIMOORA (multi‐objective optimization by ratio analysis) method has been applied in order to aggregate individual criterion/attribute scores into an equivalent evaluation index towards evaluating feasible ranking order of candidate alternative robots.

Findings

An empirical study has also been shown here for better understanding of the said selection‐module; effectively applicable to any other decision‐making scenarios.

Originality/value

This method is computationally very simple, easily comprehensible, and robust which can simultaneously consider numerous subjective attributes. Grey MULTIMOORA ranking is expected to provide a good guidance to the managers of an organization to select the feasible robot. It will also provide a good insight to the robot manufacturer so that it can improve its product or introduce a new product to satisfy customer needs.

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Article
Publication date: 6 June 2020

Reza Fattahi, Reza Tavakkoli-Moghaddam, Mohammad Khalilzadeh, Nasser Shahsavari-Pour and Roya Soltani

Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is…

Abstract

Purpose

Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.

Design/methodology/approach

In this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.

Findings

To show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.

Originality/value

To the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

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Article
Publication date: 29 January 2019

Nimet Yapıcı Pehlivan and Zeynep Gürsoy

This study aims to determine the ranking of the 81 provinces at the NUTS-3 level in Turkey with respect to the personal satisfaction and public services satisfaction by…

Abstract

Purpose

This study aims to determine the ranking of the 81 provinces at the NUTS-3 level in Turkey with respect to the personal satisfaction and public services satisfaction by applying Fuzzy Multi-Criteria Decision-Making methods to the Life Satisfaction Survey Results.

Design/methodology/approach

Fuzzy TOPSIS, Fuzzy MULTIMOORA and Fuzzy ARAS are implemented to assess life satisfaction of the individuals who lived in provinces, based on Life Satisfaction Survey 2013 for Turkey’s national comparison. In the solution process, 14 indicators for personal satisfaction and 38 indicators for public services satisfaction were considered.

Findings

The results showed that personal health satisfaction, earnings from work satisfaction and monthly income satisfaction are the most important criteria in terms of personal satisfaction. Also, healthcare services satisfaction, judicial services satisfaction and education services satisfaction have the highest importance in terms of public services satisfaction. The final ranking of the 81 provinces is obtained by considered methods. According to the ranking results, there is no significant difference between the east and the west part of Turkey in terms of personal satisfaction, whereas there is a distinct difference between them in terms of satisfaction with public services.

Originality/value

This study is the first research for evaluating the ranking of the provinces at the NUTS-3 level in Turkey according to the Life Satisfaction Survey 2013 results considering 14 indicators for personal satisfaction and 38 indicators for public services satisfaction by using FMCDM approaches that have not been applied before.

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Article
Publication date: 11 January 2016

Jindong Qin and Xinwang Liu

The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision…

Abstract

Purpose

The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision making (MAGDM) and applied the proposed MAGDM model for supplier selection under 2-tuple linguistic environment.

Design/methodology/approach

The supplier selection problem can be regarded as a typical MAGDM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MAGDM problems with 2-tuple linguistic information based on traditional MM operator. The MM operator is a well-known mean type aggregation operator, which has some particular advantages for aggregating multi-dimension arguments. The prominent characteristic of the MM operator is that it can capture the whole interrelationship among the multi-input arguments. Motivated by this idea, in this paper, the authors develop the 2-tuple linguistic Muirhead mean (2TLMM) operator and the 2-tuple linguistic dual Muirhead mean (2TLDMM) operator for aggregating the 2-tuple linguistic information, respectively. Some desirable properties and special cases are discussed in detail. Based on which, two approaches to deal with MAGDM problems under 2-tuple linguistic information environment are developed. Finally, a numerical example concerns the supplier selection problem is provided to illustrate the effectiveness and feasibility of the proposed methods.

Findings

The results show that the proposed can solve the MAGDM problems within the context of 2-tuple linguistic information, in which the attributes are existing interaction phenomenon. Some 2-tuple aggregation operators based on MM have been developed. A case study of supplier selection is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.

Practical implications

The proposed methods can solve the 2-tuple linguistic MAGDM problem, in which the interactions exist among the attributes. Therefore, it can be used to supplier selection problems and other similar management decision problems.

Originality/value

The paper develop some 2-tuple aggregation operators based on MM, and further present two methods based on the proposed operators for solving MAGDM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

Details

Kybernetes, vol. 45 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

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