Multi-Attribute Utility Analysis of Sustainable Supplier Selection Based on Optimized Genetic Algorithm

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper proposes a sustainable supplier selection model based on a combination of multi-attribute utility analysis (MAUT) and an optimized genetic algorithm (GA) with the aim of reducing carbon emissions and increasing the efficiency of order allocation in sustainable supply chains. This is achieved by integrating economic, environmental and social decision-making criteria. The abstract contains the main research objectives, lists key results such as the significant impact of the technological level on supplier selection and the stability of the optimized GA, and emphasizes the contribution through improving the decision-making process in sustainable supply chain management, but it should be supplemented by a clearer emphasis on concrete implications for theory and practice. The introductory part provides motivation by pointing out the complexity of supplier selection and the growing demands for sustainability, however, explicitly formulated research objectives, research questions and a clear statement of contributions are missing; a separate paragraph should be added in which it will be precisely defined what the paper wants to achieve, which specific gaps in the literature it fills and in what way the combination of MAUT, TOPSIS and optimized GA represents an original contribution compared to existing studies. The literature review currently represents primarily a descriptive listing of previous applications of MAUT and GA, without a critical review of their shortcomings, limitations in the context of sustainable supply chain management or a clear explanation of why this particular integration of methods is needed. This section needs to be reorganized so that research gaps are identified, existing approaches are compared and the need for the proposed model is argued. The methodological section does not describe the basic set or sample on which the model was tested - the Wind Industry Chain and SC database with 200 suppliers is mentioned, but without details on sample selection, data collection method, representativeness and sampling limitations. The methods are presented mathematically, but there is no explanation of how the weights of the criteria were determined, how the model was validated and whether experts from practice were involved. The results contain statistical indicators such as standardized path coefficients, significance levels, which confirm the validity of the model. However, a more detailed statistical analysis of the differences between the models is missing and confidence intervals for key parameters are not presented, which would further strengthen the evidence on the importance of the research. The discussion is combined with the conclusion. This should be changed and done in a way that answers the question of why these results were obtained and whether these results have been confirmed in previous research. The conclusion should be separate. The limits of the research are mentioned in passing in the last paragraph without a special subtitle, stating the lack of an integrated analysis of the low-carbon concept and insufficiently researched corporate social responsibility, but more precise limitations such as dependence on a specific data set, linearity assumptions in the MAUT model or geographical limitations of the case are missing. There is also no special subtitle with directions for future research, nor are the implications formulated - theoretical, practical and managerial, which is necessary to add in order for the paper to gain full academic significance. The tables and figures are informative, but have shortcomings - Table 1 provides only computer specifications and should be supplemented with algorithm parameters and corrected since the text is indented. Figures 7 and 8 contain insufficiently clear labels for axes and units of measurement, and the reference values ​​for RMSEA and fit indices are not compared with common limit values ​​in the literature. The references cover the period from 2021 to 2024 and are mostly relevant, but are cited inconsistently and are not consistent with the requirements of the MDPI Sustainability template. It is necessary to align the citation format according to the journal's instructions and check that all references are actually cited in the text. All of the above changes need to be implemented in order for the paper to meet the standards of scientific review and be ready for publication.

Author Response

Thank you very much for your comment. I have provided a detailed response and modifications in the following Word document. Thank you

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This paper proposes a hybrid decision-making model for sustainable supplier selection and order allocation. By integrating Multi-Attribute Utility Analysis, Fuzzy TOPSIS, and an optimized Genetic Algorithm (GA), the authors aim to balance economic targets with environmental impacts (carbon emissions). While the topic of sustainable supply chain management is highly relevant and the mathematical formulation appears sound, the manuscript lacks methodological novelty and rigorous algorithmic validation. Several major concerns must be addressed to elevate the paper to a publishable standard.

1. Key parameters of the GA optimization process must be provided (e.g., population size, number of generations, crossover/mutation rates, convergence criteria).
2. The description of data sources is vague. The authors should clarify the data collection period, sample selection criteria, and whether any data cleaning or preprocessing was performed.
3. The discussion section is overly general and lacks practical managerial insights.
4. Although the core theme of the paper is sustainability, the results and discussion do not deeply analyze how environmental factors actually influence decision-making. A sensitivity analysis is recommended to explore this aspect.

Author Response

Thank you very much for your comment. I have provided a detailed response and modifications in the following Word document. Thank you

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors 

Kindly consider the feedback below (details are in the annotated comments in the attached manuscript):

1. The topic is timely and relevant; however, the manuscript does not clearly demonstrate how the proposed model contributes to reducing carbon emissions and environmental pollution. The links between procurement cost reduction, supplier productivity, delivery delays, and environmental sustainability are not sufficiently established.

2. The interpretation of coefficients and significance levels requires a clearer explanation to support the validity of the results.

3. Figures 3 require substantial clarification, including how indicators were calculated, how factors were ranked, and the assumptions underlying their general applicability. Figures 7 and 8 lack legibility in their current form.

4. The actual application focuses predominantly on economic outcomes, with limited integration of social and environmental sustainability aspects. The motivation regarding a large number of suppliers is not well aligned with the actual application involving only five suppliers, and should be qualified.

5. Empirical validation lacks sufficient detail; stating that data from 200 companies were used is insufficient to establish credibility.

6. Formatting, citation consistency, and repeated references require attention throughout.

Hope the input will assist in improving your submission.

Kind regards

Reviewer

Comments for author File: Comments.pdf

Comments on the Quality of English Language

Good

Author Response

Thank you very much for your comment. I have provided a detailed response and modifications in the following Word document. Thank you

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have revised the paper in accordance with the submission to the reviewers. The paper should now be accepted.

Reviewer 2 Report

Comments and Suggestions for Authors

I have no comments.