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

Round 1

Reviewer 1 Report

The authors performed an objective criticism of applying the fuzzy Step-Wise Weight Assessment Ratio Analysis method based on the Chang Triangular fuzzy number scale. 
The literature research shows that many studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values concerning the initial assessment of decision-makers. Therefore, the authors obtained a larger cross-section of studies, and seven representative studies (logistics, construction industry, financial performance management, supply chain) with different parameter structures and decision matrix sizes that have been singled out. The central hypothesis of this research implies that the application of this approach leads to wrong decisions because the weight values of criteria are incorrect. Afterward, a comparative analysis with the Improved fuzzy SWARA (IMF SWARA) method was created. Several negative conclusions have been reached using the fuzzy SWARA method and the Chang scale. As a general conclusion, the authors state that this approach is not adequate for application in multi-criteria decision-making problems because it produces inadequate management of processes and activities in various spheres. The list of my comments is as follows:
1. The introduction is very clear. The research gap and contribution is correctly identified.
2. Preliminaries show a good intro to the rest of the paper.
3. Methodology is clearly presented.
4. section number 4, very wide presented research and its results.
5. The discussion and the conclusion sections are properly. However, in conclusion, the authors should indicate future research directions.
6. The literature review can be a little more extensive. The authors can make one or two paragraphs about the intro to MCDA methods. And after that, show in this background SWARA methods. It will be rather interesting to show less popular methods like HFS COMET, SIMUS, SPOTIS, Intuistionic/fuzzy COMET.
7. References should be rather extended.

 

Author Response

Reviewer 1:

Thank you very much for the positive review.

The authors performed an objective criticism of applying the fuzzy Step-Wise Weight Assessment Ratio Analysis method based on the Chang Triangular fuzzy number scale. The literature research shows that many studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values concerning the initial assessment of decision-makers. Therefore, the authors obtained a larger cross-section of studies, and seven representative studies (logistics, construction industry, financial performance management, supply chain) with different parameter structures and decision matrix sizes that have been singled out. The central hypothesis of this research implies that the application of this approach leads to wrong decisions because the weight values of criteria are incorrect. Afterward, a comparative analysis with the Improved fuzzy SWARA (IMF SWARA) method was created. Several negative conclusions have been reached using the fuzzy SWARA method and the Chang scale. As a general conclusion, the authors state that this approach is not adequate for application in multi-criteria decision-making problems because it produces inadequate management of processes and activities in various spheres. The list of my comments is as follows:

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Comment 1: The introduction is very clear. The research gap and contribution is correctly identified.

Comment 2: Preliminaries show a good intro to the rest of the paper.

Comment 3: Methodology is clearly presented.

Comment 4: Section number 4, very wide presented research and its results.

Reply: Thank you for your positive comments.

Comment 5: The discussion and the conclusion sections are properly. However, in conclusion, the authors should indicate future research directions.

Reply: Thank you for your suggestions. The following have been added:

Future research is related to the promotion to use the IMF SWARA method or the Original SWARA method with some appropriate scales to avoid wrong decision-making. Also, some objective criticism should be performed for some similar problems in literature.

Comment 6: The literature review can be a little more extensive. The authors can make one or two paragraphs about the intro to MCDA methods. And after that, show in this background SWARA methods. It will be rather interesting to show less popular methods like HFS COMET, SIMUS, SPOTIS, Intuistionic/fuzzy COMET.

Reply: Thank you for your suggestion. Our opinion is that can be part of future research, so we have added it in the conclusion section.

Comment 7: References should be rather extended.

Reply: We have added the following references:

Altintas, K., Vayvay, O., Apak, S., & Cobanoglu, E. (2020). An extended GRA method integrated with fuzzy AHP to construct a multidimensional index for ranking overall energy sustainability performances. Sustainability, 12(4), 1602.

Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, 95(3), 649-655.

Samanlioglu, F., Burnaz, A. N., Diş, B., Tabaş, M. D., & Adıgüzel, M. (2020). An Integrated Fuzzy Best-Worst-TOPSIS Method for Evaluation of Hotel Website and Digital Solutions Provider Firms. Advances in Fuzzy Systems, 2020.

Deveci, M., Pamucar, D., Cali, U., Kantar, E., Kolle, K., & Tande, J. O. (2022). A hybrid q-rung orthopair fuzzy sets based CoCoSo model for floating offshore wind farm site selection in Norway. CSEE Journal of Power and Energy Systems.

Kizielewicz, B., Więckowski, J., Shekhovtsov, A., Wątróbski, J., Depczyński, R., & Sałabun, W. (2021). Study towards the time-based mcda ranking analysis–a supplier selection case study. Facta Universitatis, Series: Mechanical Engineering, 19(3), 381-399.

Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E., & Pamucar, D. (2022). Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, 108076.

Akyurt, İ. Z., Pamucar, D., Deveci, M., Kalan, O., & Kuvvetli, Y. (2021). A Flight Base Selection for Flight Academy Using a Rough MACBETH and RAFSI Based Decision-Making Analysis. IEEE Transactions on Engineering Management.

Stoilova, S., & Munier, N. (2021). Analysis of Policies of Railway Operators Using SWOT Criteria and the SIMUS Method: A Case for the Bulgarian Railway Network. Sustainability, 13(12), 6948.

Wątróbski, J., Sałabun, W., Karczmarczyk, A., & Wolski, W. (2017, September). Sustainable decision-making using the COMET method: An empirical study of the ammonium nitrate transport management. In 2017 Federated Conference on Computer Science and Information Systems (FedCSIS) (pp. 949-958). IEEE.

Faizi, S., Sałabun, W., Rashid, T., Zafar, S., & Wątróbski, J. (2020). Intuitionistic fuzzy sets in multi-criteria group decision making problems using the characteristic objects method. Symmetry, 12(9), 1382.

Reviewer 2 Report

The authors presented the results of an interesting study. The assessment of the correctness of both the MCDM themselves and the results of their use is essential in the context of a significant increase in the number of such methods recently. The choice of the most correct and appropriate MCDM for a particular study has become quite a difficult problem in its own right lately.
The authors quite convincingly and correctly prove the shortcomings of the Fuzzy SWARA method with the Chang scale.
However, we have a some minor clarifying proposals.
1. We propose to additionally use the original sources of formulas in section 2.1. In particular, we are referring to Chang's original paper from 1996, as well as more recent publications, such as https://doi.org/10.1155/2020/8852223
2. Moreover, we propose to expand the literature review with studies using different interpretations of fuzzy number operations, for example http://dx.doi.org/10.3390/su12041602.
3. We propose to additionally check the calculations criticized in Section 4.6. The fact is that authors often make unfortunate technical errors when copying the results of calculations from software tools into the text of the manuscript. Moreover, these errors are sometimes not related to the incorrectness of the calculations themselves.
4. Finally, we propose to label the axes on all graphs. This is especially true for the graph with two axes in Figure 4.

Author Response

Reviewer 2:

Thank you very much for the useful suggestions. We accepted all of the suggestions and we are sure that this will improve the quality and contribute to a better understanding of the paper.

The authors presented the results of an interesting study. The assessment of the correctness of both the MCDM themselves and the results of their use is essential in the context of a significant increase in the number of such methods recently. The choice of the most correct and appropriate MCDM for a particular study has become quite a difficult problem in its own right lately. The authors quite convincingly and correctly prove the shortcomings of the Fuzzy SWARA method with the Chang scale. However, we have a some minor clarifying proposals.

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Comment 1: We propose to additionally use the original sources of formulas in section 2.1. In particular, we are referring to Chang's original paper from 1996, as well as more recent publications, such as https://doi.org/10.1155/2020/8852223

Reply: We have added both references.

Comment 2: Moreover, we propose to expand the literature review with studies using different interpretations of fuzzy number operations, for example http://dx.doi.org/10.3390/su12041602.

Reply: This reference has been added.

Comment 3: We propose to additionally check the calculations criticized in Section 4.6. The fact is that authors often make unfortunate technical errors when copying the results of calculations from software tools into the text of the manuscript. Moreover, these errors are sometimes not related to the incorrectness of the calculations themselves.

Reply: We totally understand your concern, but we have checked it a few times. The authors seem not familiar with TFNs, so our 4.6. the subsection is correct.

Comment 4: Finally, we propose to label the axes on all graphs. This is especially true for the graph with two axes in Figure 4.

Reply: Axes in Figures 2, 3, 4, and 5 have been added.

Reviewer 3 Report

In this paper, it is performed an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (Triangular fuzzy number) scale. 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 with different parameter structures and decision matrix sizes have been singled out. It has been set the main hypothesis which implies that the application of this approach leads to wrong decisions because the weight values of criteria are incorrect. A comparative analysis with the Improved fuzzy SWARA (IMF SWARA) method has been created and it has been reached a number of negative conclusions on using the fuzzy SWARA method and the Chang scale.

The manuscript Objective criticism and negative conclusions on using the Fuzzy SWARA method in multi-criteria decision-making represent a very quality study with emphasis on the previously wrong made decisions. Science needs more such papers deal with criticism that gives exactly proofs.

The paper has large potential and will be useful for the wider scientific community because treats a very important field (MCDM) and indicates previously wrong-made decisions. Wrong decisions have a negative influence on all further activities in different areas, so this paper is a high contribution to literature that can improve the whole MCDM area.   

It is especially important that authors divide their criticism on the application of the Fuzzy SWARA method in combination with Chang TFN scale, not on Fuzzy SWARA in general, because the main problem is a combination of this method with previously mentioned scale.

The paper has well structure and it is written in a clear way.

Apart from these advantages, the paper can be improved by the next suggestions.

• Few recent relevant studies can be added to the introduction as follows:
• Line 95: should be Fuzzy SWARA instead Fuzzy SWAR
• Line 201 and 202. Why you have applied MathType to represent TFN values of criteria ER, ENVR, and SR, while in the rest of the paper you have shown these values in common brackets? Please correct.
• In conclusion you should note that the application of Fuzzy SWARA and other appropriate scales can give good results.
• Implication for managers should be better explained.

Author Response

Reviewer 3:

Thank you very much for the useful suggestions. We accepted all of the suggestions and we are sure that this will improve the quality and contribute to a better understanding of the paper.

In this paper, it is performed an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (Triangular fuzzy number) scale. 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 with different parameter structures and decision matrix sizes have been singled out. It has been set the main hypothesis which implies that the application of this approach leads to wrong decisions because the weight values of criteria are incorrect. A comparative analysis with the Improved fuzzy SWARA (IMF SWARA) method has been created and it has been reached a number of negative conclusions on using the fuzzy SWARA method and the Chang scale.

The manuscript Objective criticism and negative conclusions on using the Fuzzy SWARA method in multi-criteria decision-making represent a very quality study with emphasis on the previously wrong made decisions. Science needs more such papers deal with criticism that gives exactly proofs.

The paper has large potential and will be useful for the wider scientific community because treats a very important field (MCDM) and indicates previously wrong-made decisions. Wrong decisions have a negative influence on all further activities in different areas, so this paper is a high contribution to literature that can improve the whole MCDM area.   

It is especially important that authors divide their criticism on the application of the Fuzzy SWARA method in combination with Chang TFN scale, not on Fuzzy SWARA in general, because the main problem is a combination of this method with previously mentioned scale.

The paper has well structure and it is written in a clear way.

Apart from these advantages, the paper can be improved by the next suggestions.

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Comment 1: Few recent relevant studies can be added to the introduction.

Reply: Three new studies have been added to the introduction section.

Comment 2: Line 95: should be Fuzzy SWARA instead Fuzzy SWAR.

Reply: Thank you. Corrected.

Comment 3: Line 201 and 202. Why you have applied MathType to represent TFN values of criteria ER, ENVR, and SR, while in the rest of the paper you have shown these values in common brackets? Please correct.

Reply: Thank you. Corrected. Now is uniformly in the whole paper.

Comment 4: In conclusion you should note that the application of Fuzzy SWARA and other appropriate scales can give good results.

Reply: Very good observation. We have added the following in the conclusion: It is important to note that the application of Fuzzy SWARA and other appropriate scales can give good results.

Comment 5: Implication for managers should be better explained.

Reply: We have extended previously described managerial implications so now looks: Decision-making is a very important process for all areas of profession, science and other spheres of life and management, so the application of MCDM methods should contribute to the selection of the best solution from a given set of considered alternatives. If IMF SWARA is applied instead of the previously described inadequate approach, negative conclusions and shortcomings can be eliminated. It is especially important for managers who very often need quick and successful decision-making on which they base further management strategies. In that way, quality management should be significantly improved and managers can achieve better results in their fields.