An interval type 2 hesitant fuzzy MCDM approach and a fuzzy c means clustering for retailer clustering

Öner, Sultan Ceren; Öztayşi, Başar

doi:10.1007/s00500-018-3191-0

Cited by 30 publications

(11 citation statements)

References 44 publications

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“…User experience (C5): The user experience of dealing with smart e‐tourism data management applications enhances the information technology usability through human–computer interaction to meet users' requirements 95 …”

Section: Methodsmentioning

confidence: 99%

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Krishnan

Mohammed

Alnoor

et al. 2021

Int J of Intelligent Sys

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The benchmarking of smart e‐tourism data management applications falls under the problem of multicriteria decision‐making (MCDM). This claim is supported by three issues: 12 smart key concepts need to be considered in the evaluation, criteria importance, and data variation among these criteria. Thus, an MCDM solution is essential to overcome problem complexity. To end this, this study presents a decision‐making framework on the basis of the extension of interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency (IT2TR‐FWZIC) integrated with the Vlsekriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) method for evaluating and benchmarking the smart e‐tourism data management applications. Our methodology comprises two consecutive phases. In the first phase, a decision matrix is constructed using the intersection between the 12 key concepts and smart e‐tourism data management applications of each category and subcategory in smart e‐tourism. In the second phase, the integration of the IT2TR‐FWZIC formulation and VIKOR is presented to compute the weights for the 12 key concepts and benchmark the smart e‐tourism data management applications for each category. The results are as follows: (1) A clear difference is found among the criteria weights (12 smart key concepts). Specifically, the real‐time criterion achieves the highest importance weight (0.098), whereas augmented reality obtains the lowest weight (0.068). The context‐awareness and recommender systems have the same weight value (0.087), and the other eight criteria are distributed in between. (2) The smart e‐tourism data management applications are evaluated and benchmarked effectively per category and subcategories. (3) Benchmarked applications in each category are subjected to a systematic ranking in the evaluation process. The sensitivity analysis has shown high correlation outcomes to the systematic ranking results over the 31 scenarios of criteria weight changing. Moreover, a comparative analysis of the proposed work with other existing studies is also discussed.

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Section: Methodsmentioning

confidence: 99%

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Krishnan

Mohammed

Alnoor

et al. 2021

Int J of Intelligent Sys

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“…One disadvantage of traditional MCDM models is that they cannot convey the uncertain nature of the human decision-making process. In recent years, many researchers have integrated fuzzy set theory into their MCDM models in an attempt to overcome this disadvantage [19,20].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization Model for Selecting Temporary Hospital Locations During COVID-19 Pandemic

Wang¹,

Chou²,

Hsu³

et al. 2022

Computers, Materials &Amp; Continua

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The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed, and unnecessary costs may come into play. In this study, a decision support framework using a fuzzy analytic hierarchy process (FAHP) and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital, and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19. A case study is performed for Ho Chi Minh City using the proposed decision-making framework. The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic. The results of the study can be used to assist decisionmakers, such as government authorities and infectious disease experts, in dealing with the current pandemic as well as other diseases in the future. With the entire world facing the global pandemic of COVID-19, many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic. As the number of cases increases exponentially, it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria. As such, the proposed approach can also be applied to

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“…In recent years, the FCM algorithm method has been integrated with several multiple criteria decision-making methods, among which DEA (Azadeh, Anvari, Ziaei, & Sadeghi, 2010), TOPSIS (Bai, Dhavale et al, 2014), VIKOR (Akman, 2015), DEMATEL (Keskin, 2015), PROMETHEE (Bai, Zhang, Qian, Liu, & Wu, 2018) and an interval type 2 hesitant MCDM (Oner & Oztaysi, 2018) can be cited.…”

Section: Fuzzy C-means Algorithmmentioning

confidence: 99%

A new evaluation model for corporate financial performance using integrated CCSD and FCM-ARAS approach

Dahooie

Zavadskas

Vanaki

et al. 2019

Economic Research-Ekonomska Istraživanja

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The financial performance is an indicator of financial stability, health and condition of any organisation. It could be utilised as a proper measure of the firm's credibility and its ability to pay off debts. Financial institutions use this measure to determine the lending policy and applicants' credits. This study proposes a model based on the CCSD weighing method and hybrid FCM-ARAS approach for clustering and evaluating the financial performance to enable banks to identify target groups and design appropriate and relevant policies. Based on previous studies and the views of senior financial managers of a public bank in Iran, eight economic criteria were evaluated. The presented method was used to assess the financial performance of 58 manufacturing companies applying for loans from a federal bank in Iran. However, the CCSD method was used to calculate criteria weights, and a hybrid FCM-ARAS approach was developed and applied to financial evaluation and clustering the companies. The use of the CCSD method can eliminate errors caused by subjective models and human judgments, and increase the accuracy of the assessment. In this study, the debt ratio and equity to total assets and ROA were identified as the main criteria to assess financial performance.

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An interval type 2 hesitant fuzzy MCDM approach and a fuzzy c means clustering for retailer clustering

Cited by 30 publications

References 44 publications

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Optimization Model for Selecting Temporary Hospital Locations During COVID-19 Pandemic

A new evaluation model for corporate financial performance using integrated CCSD and FCM-ARAS approach

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