An Integrated Fuzzy Best-Worst-TOPSIS Method for Evaluation of Hotel Website and Digital Solutions Provider Firms

Samanlıoğlu, Funda; Burnaz, Ayşe Nur; Diş, Berke; Tabaş, Mehmet Doğukan; Adıgüzel, Mehmet

doi:10.1155/2020/8852223

Cited by 11 publications

(6 citation statements)

References 40 publications

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“…Moreover, integrating MEREC with the other objective and subjective weighting methods like Entropy, IDOCRIW (Integrated Determination of Objective CRIteria Weights), WE-BIRA (Weight Balancing Indicator Ranks Accordance), ACW (Adaptive Criteria Weights), SWARA and considering other methods of expert evaluation can be the focus in future research [68][69][70][71][72]. Another area for future research could be to apply the proposed method to real-world problems, such as designing geographic information systems, economic indicators assessment, evaluations in tourism management, and pollution management [2,[73][74][75]. Future research can be enriched by the proposed method in a vaguely determined environment, e.g., fuzzy and neutrosophic environments [3,76,77].…”

Section: Discussionmentioning

confidence: 99%

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Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

et al. 2021

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The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.

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Section: Discussionmentioning

confidence: 99%

“…Solving linear and ono-linear programming models is a common way to deal with MODM problems. On the other hand, MADM is a branch of MCDM that deals with issues defined by discrete decision variables, a limited number of alternatives and attributes [2][3][4][5]. The focus of this study is on this branch of MCDM.…”

Section: Introductionmentioning

confidence: 99%

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

et al. 2021

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“…The basic operations with TFNs are presented here primarily because of Section 4.6 and two examples in which the following equations have not been complied with. The operational laws of TFN are Υ = (l 1 , m 1 , u 1 ) and Υ = (l 2 , m 2 , u 2 ) [18,19].…”

Section: Preliminaries-operations With Fuzzy Numbersmentioning

confidence: 99%

Objective Criticism and Negative Conclusions on Using the Fuzzy SWARA Method in Multi-Criteria Decision Making

Stević

Das

Tešić³

et al. 2022

Mathematics

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The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres.

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“…The results of their research show that the technology aspect is the most influential factor. Samanlioglu et al [14] proposed MCDM models, including fuzzy FBWM and Fuzzy TOPSIS, for evaluation of a hotel website and digital solutions provider firms.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Digital Marketing Technologies with Fuzzy Linguistic MCDM Methods

Trung

Thanh

2022

Axioms

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Technology is becoming the tool that changes how people live every day, and the marketing strategies of businesses are also gradually shifting to the industry 4.0 mindset of constant growth and development. Digital marketing has changed human habits of information accessibility, determined their interactions, and witnessed the birth of a variety of new marketing technologies. Marketers are creating digital marketing products and services that enhance the experience for consumers, products, and services that are also delivered through high digital marketing networks. As a result, data sources become more abundant and allow consumers to have more choices. All products, services, technologies, and data are increasingly meeting the needs of consumers, thereby confirming the effectiveness of digital marketing in today’s market. However, the evaluation and selection of digital marketing technology is very complex since it has many conflicting criteria and goals. The multi-criteria decision-making model (MCDM) is a powerful technique widely used for solving this type of problem. Thus, the author proposed a fuzzy linguistic MCDM method for evaluation of digital marketing technologies. After determining the evaluation criteria and alternatives, two MCDM methods, including Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation and selection of digital marketing technologies procedure. Finally, an application is present to demonstrate the potential use of the proposed methodology. The main contribution of this study is to propose a Spherical fuzzy MCDM model to support planners and decision makers in the digital marketing technology evaluation and selection processes. A case study is also performed to showcase the feasibility of the proposed approach.

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An Integrated Fuzzy Best-Worst-TOPSIS Method for Evaluation of Hotel Website and Digital Solutions Provider Firms

Cited by 11 publications

References 40 publications

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

Objective Criticism and Negative Conclusions on Using the Fuzzy SWARA Method in Multi-Criteria Decision Making

Evaluation of Digital Marketing Technologies with Fuzzy Linguistic MCDM Methods

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