AHP in Design for Six Sigma Project Selection

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The application of classical AHP for deriving the criteria weights is sound from a methodological viewpoint.

However, the manuscript would have benefited from an explanation of the calculation of the consistency ratio and the consistency of the expert opinions.

Without these figures, the accuracy of the results can be called into question, especially considering the high concentration of the weights (66%) on the two criteria.

The introduction of the 1-10 scoring scale is beneficial for the scalability and usability of the approach in an industrial context.

However, the transition from the AHP-based weight calculation to the direct scoring approach can lead to subjectivity.

The manuscript would have benefited from an explanation of the standardization process of the scoring approach. For instance, are any reference benchmarks defined for the scoring?

Your paper can’t overcome uncertainty information in decision making process, so compare your model with other uncertainty frameworks such as fuzzy set and neutrosophic set such as:

Digital twin and fuzzy framework for supply chain sustainability risk assessment and management in supplier selection.

An Extension of Root Assessment Method (RAM) Under Spherical Fuzzy Framework for Optimal Selection of Electricity Production Technologies Toward Sustainability: A Case Study

A Hybrid Approach of Neutrosophic with Multimoora in Application of Personnel Selection

The empirical validation, as achieved through a case study of twelve DFSS project concepts, adds to the applied contribution of the paper.

Nevertheless, it should be noted that the number of data points in the analysis is limited, and it would be interesting to explore to what extent sensitivity analysis has been carried out to determine the impact of changes in the weights of the criteria on the project ranking, in particular considering the strong weight of the Product Quality and Cost/Functionality criteria in the final weight structure.

The determination of classification thresholds, e.g., > 7.2 for high implementation potential and < 5.2 for discontinuation, is a valuable contribution to the applied paper, although the determination of these thresholds should be more robust.

Were these thresholds statistically determined, historically established, or managerially derived?

From a strategic point of view, the paper makes an extremely compelling case for the potential of structured selection to alleviate engineering hour and prototype cost wastage.

The paper could be improved, however, by including data on actual cost savings and efficiency gains that have been achieved because of implementation.

Such an inclusion would go a long way in improving the paper’s managerial implications.

In conclusion, the proposed AHP-normalized scoring system is pragmatic, transparent, and highly appropriate for an industrial DFSS environment. To increase the paper’s overall rigor, more methodological validation, classification criteria, and economic impact data should be included.

Author Response

Dear Sir/Madame,

 

We sincerely thank you for the constructive and insightful comments, which helped us significantly improve the methodological rigor, transparency, and managerial relevance of the manuscript. Below, each comment is addressed point-by-point, indicating the corresponding revisions made in the manuscript.

 

Comment 1

The manuscript would have benefited from an explanation of the calculation of the consistency ratio and the consistency of the expert opinions.

 

Response:

A detailed explanation of the Consistency Index (C.I.) and Consistency Ratio (C.R.) calculation has been added to Section 2.5 (Analytic Hierarchy Process Essentials). The calculated C.R. value (0.097) is explicitly reported and confirms acceptable consistency of expert judgments.

 

Comment 2

The transition from the AHP-based weight calculation to the direct scoring approach can lead to subjectivity.

 

Response:

This limitation is explicitly discussed in Section 4.2 (Limitations). The Results section clarifies how dominance of high-weight criteria mitigates subjectivity effects.

 

Comment 3

The manuscript would have benefited from an explanation of the standardization process of the scoring approach.

 

Response:

Section 2.6 now explains the standardized 1–10 scoring scale, benchmark references, and differentiation between linear and subjective criteria. Appendix A.1 provides criterion-specific scale descriptions.

 

Comment 4

The number of data points is limited and sensitivity analysis should be explored.

 

Response:

This limitation is acknowledged in Sections 3.2 and 4.2. Sensitivity analysis is identified as a key direction for future research.

 

Comment 5

The determination of classification thresholds should be more robust.

 

Response:

Thresholds are clarified as empirically derived managerial rules and their limitations are discussed in Section 4.2.

 

Comment 6

The paper could be improved by including data on actual cost savings and efficiency gains.

 

Response:

Managerial implications are strengthened by linking high project scores with reduced engineering hours and prototype cost avoidance, discussed in the Introduction, Results, and Discussion sections.

 

Summary

All comments have been fully addressed through expanded methodological explanations, explicit discussion of limitations, and strengthened managerial relevance. Thank you again for proper indication that helped to make our article better.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The paper deals with the analysis of sustainability and optimization of logistics and production processes in the context of contemporary requirements for efficiency and environmental responsibility, with the application of quantitative methods and empirical data. The topic is current and relevant to the field of sustainable management and logistics, but the manuscript requires significant improvements in terms of clarity of scientific contribution, methodological precision, depth of discussion and systematic interpretation of results.
The introduction presents the problem thematically correctly and points to the wider context of sustainability, efficiency and the need to improve the system, but it is not structured precisely enough in terms of research logic. Although the importance of the problem is indicated, the objectives of the research are not clearly and explicitly highlighted in a separate paragraph, nor are they operationalized through concrete research questions or hypotheses. The motivation is present at the descriptive level, but a clear formulation of the research gap in relation to the existing literature is missing. The scientific contribution of the work is not precisely articulated, that is, it is not clearly indicated whether the contribution is primarily methodological, empirical or conceptual. In the introduction, it should be clearly defined: what is known so far, what has not been sufficiently researched and in what way this paper improves it. Without that, the work leaves the impression of applying a familiar approach to a new context, but without a sufficiently emphasized element of originality.
The literature review includes relevant sources and is thematically related to sustainability, logistics and optimization models, however, it is predominantly narrative in nature. The authors cite a large number of papers, but do not systematically group them according to methodological approach, type of model, geographical context or type of problem. A comparative analysis of previous research, as well as a critical review of their limitations, is missing. The review of the literature should serve as a basis for the construction of the methodology, but the connection between the analyzed works and the specific elements of the model in this work is not clearly established. Also, it is not clear to what extent the literature review directly supports the research objectives. Although the references are relevant to the topic, it is necessary to synthesize the findings more deeply and clearly show how they influenced the research design.
The methodology is formally presented, but requires more precise and detailed elaboration. If a mathematical or optimization model is used, it is necessary to clearly define all sets, parameters, variables and assumptions, with consistent notation throughout the text. The lack of a precise explanation of individual parameters, as well as the absence of a discussion on the validity of the model's assumptions, was observed. If empirical data were used, it is necessary to explain in more detail their source, period of collection, method of processing and possible limitations. It is not entirely clear whether model validation or sensitivity analysis was carried out, which is especially important for optimization and simulation approaches. The methodological part should be expanded with an explanation of the choice of method in relation to alternative approaches from the literature, as well as a clear explanation of why this method is adequate for the set goal.

The results are quantitatively presented and provide insight into the performance of the model or system, but their interpretation remains partially superficial. In some parts, the text describes numerical values ​​without a deeper analytical interpretation of their meaning. What is missing is a clearer comparison of scenarios or variants, if they were analyzed, as well as an explanation of the cause-and-effect relationships between the input parameters and the obtained results. Also, it would be useful to include a sensitivity analysis to demonstrate the robustness of the model to changes in key parameters. The results should be more closely related to the objectives defined in the introduction, in order to clearly show that the research questions are adequately addressed.
The tables are informative, but in some cases overloaded with numerical data without additional analysis. It is necessary to check whether all the tables are necessary in the main text or whether part of the detailed data could be transferred to the appendix. Also, the titles of the tables should be more precise and self-sufficient, so that the reader can understand their content without going back to the text. Figures, if they include graphs or schematic representations, should be more clearly labeled, with legible legends and explanations of all labels. It is necessary to check whether all figures are adequately referenced and interpreted in the text, because each visual component must have a clear analytical function, not just an illustrative one.
The discussion is not sufficiently separated and deepened as a separate entity. Ideally, the discussion should relate the obtained results to previous research from the literature review and explain whether the findings are consistent with or deviate from earlier studies. In the paper, this segment is present implicitly, but not systematically elaborated. There is a lack of critical consideration of model limitations and realistic application conditions, as well as reflection on potential practical challenges of implementation of recommendations.
The implications of the research are partially indicated, but not clearly structured into theoretical and practical implications. It would be useful to specify how the results can contribute to the improvement of managerial decisions, public policies or further development of the model. The limitations of the research are not explicitly highlighted in a separate section, which represents a methodological shortcoming. Limitations related to data availability, simplified model assumptions, possible deterministic nature of the approach or limited generalizability of the results should be clearly stated. Guidelines for future research are present in general terms, but they should be specified, for example through the proposal of extending the model, including stochastic elements, multi-criteria optimization or application in other contexts.
References are thematically relevant and include a combination of theoretical and empirical works, but it is necessary to check their consistency in terms of citation style and completeness of bibliographic data. Also, it is advisable to include a larger number of recent works from the last few years in order to further strengthen the topicality of the research. In some parts, references are used more illustratively than analytically, so their integration into the argumentation should be deepened.
Overall, the paper has a solid thematic basis and potential for scientific contribution, but requires a clearer definition of goals and contributions, a deeper synthesis of the literature, a more precise methodological elaboration, a stronger discussion of the results, and an explicit statement of limitations and implications. Only after these refinements can the manuscript reach the level of methodological and conceptual maturity expected in international scientific journals.

Author Response

Dear Sir/Madame,

 

We sincerely thank you for the detailed and comprehensive review, which provided valuable guidance for strengthening the scientific logic, methodological rigor, and clarity of contribution of the manuscript. The comments were carefully considered and resulted in substantial revisions across the introduction, literature review, methodology, results, discussion, and limitations sections. Detailed responses are provided below.

 

General Comment

The manuscript requires significant improvements in terms of clarity of scientific contribution, methodological precision, depth of discussion and systematic interpretation of results.

 

Response:

We fully agree with this assessment. The manuscript has been substantially revised at structural and content levels. The introduction was rewritten to clearly define the research gap, objectives, and scientific contribution. The literature review was reorganized into methodologically coherent subsections, the methodology section was expanded and clarified, and the discussion and limitations were strengthened to ensure systematic interpretation of results and transparency of assumptions.

 

Comment on Introduction Structure

The introduction is thematically correct but not structured precisely enough in terms of research logic.

 

Response:

The introduction has been restructured to follow a clear research logic, progressing from problem context to research gap identification, explicit research question formulation, and statement of contribution. A dedicated paragraph now explicitly states the research objective and scope.

 

Comment on Research Objectives and Questions

The objectives of the research are not clearly and explicitly highlighted, nor operationalized through concrete research questions or hypotheses.

 

Response:

A separate paragraph has been added to the introduction explicitly stating the research objective and formulating a clear research question focused on scalable and transparent DFSS project selection. The scope and limitations of the research question are also clearly acknowledged.

 

Comment on Research Gap and Contribution

The research gap and scientific contribution are not clearly articulated.

 

Response:

The research gap is now explicitly defined in relation to limitations of full-scale AHP and purely subjective scoring models in industrial DFSS environments. The contribution is clearly stated as primarily methodological, proposing a hybrid AHP–normalized scoring framework validated through an industrial case study.

 

Comment on Literature Review Structure

The literature review is narrative and lacks systematic grouping and critical analysis.

 

Response:

The literature review has been reorganized into clearly defined subsections: Six Sigma and DFSS fundamentals, project selection in Six Sigma, project selection methods, decision analysis techniques, and AHP essentials. A comparative and critical discussion of methodological limitations in existing studies has been added, explicitly linking prior research to the proposed framework.

 

Comment on Methodological Precision

The methodology requires more precise elaboration, explanation of assumptions, data sources, and justification of method choice.

 

Response:

The methodology section has been expanded to explicitly define assumptions underlying the weighted sum aggregation, expert judgment reliability, scoring scale standardization, and criteria independence. The source, period, and processing of empirical data are now clearly described. Justification of the hybrid approach relative to alternative MCDA and fuzzy frameworks is provided.

 

Comment on Results Interpretation

Results are presented quantitatively but lack deeper analytical interpretation and explanation of cause-and-effect relationships.

 

Response:

The Results section has been expanded with analytical interpretation explaining how criteria weight structure drives project rankings. Explicit cause-and-effect relationships between dominant criteria (Product Quality and Cost/Functionality) and final rankings are discussed.

 

Comment on Sensitivity and Robustness

A sensitivity analysis is missing and model robustness should be discussed.

 

Response:

While a formal sensitivity analysis was not conducted, this limitation is now explicitly acknowledged in the Limitations section. The manuscript explains why ranking stability remains acceptable for high-potential projects and identifies sensitivity analysis as a priority for future research.

 

Comment on Tables and Figures

Tables and figures should be better structured, self-explanatory, and partially moved to the appendix.

 

Response:

Table titles were revised to be self-sufficient and descriptive. Detailed criteria description tables were moved to the appendix to improve readability of the main text. Figures were clarified with improved labeling and explicit references in the text.

 

Comment on Discussion and Implications

The discussion is insufficiently separated and lacks explicit implications and limitations.

 

Response:

A clearer discussion section has been developed, explicitly relating results to prior literature and practical DFSS applications. Managerial implications are structured and limitations are presented in a dedicated subsection, followed by clearly defined directions for future research.

 

Summary

All your comments were addressed through substantial restructuring and content enhancement of the manuscript, significantly improving clarity, methodological rigor, analytical depth, and transparency of contributions and limitations.

Thank you for very constructive comments that helped me grow academic perspective on the topic. Your comments have influenced this work, as well as my other academic publications that are currently being prepared.

Kind regards.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors,

I want to express my gratitude for your efforts in conducting this study using the Analytic Hierarchy Process and Six Sigma. However, the case study needs to clarify its validity and reliability, specifically regarding data triangulation, to provide clarity in the methodological procedure. This will allow for a better description of the detailed narrative and a deeper understanding of the phenomenon studied through a review of the evidence.

I suggest reviewing Robert Yin (2017) Case Study Research and Applications: Design and Methods.

Kind regards,

Author Response

Dear Sir/Madame,

We sincerely thank you for the constructive and focused comment regarding validity and reliability of the case study, particularly with respect to data triangulation and methodological transparency. This comment was carefully considered and led to targeted improvements in the methodology and limitations sections of the manuscript.

 

Comment

The case study needs to clarify its validity and reliability, specifically regarding data triangulation, to provide clarity in the methodological procedure.

 

Response:

We agree with the reviewer that explicit clarification of validity and reliability strengthens the methodological credibility of the case study. In response, the Materials and Methods section has been revised to clearly explain how data triangulation was achieved in the empirical analysis.

 

Specifically, triangulation is now described through the use of multiple evidence sources within the same organizational context, including: (i) expert judgments from product development supervisors used for criteria weighting and project scoring, (ii) documented project outcomes (successful completion versus discontinuation), and (iii) retrospective evaluation of completed and ongoing projects to validate scoring consistency over time. This approach aligns with established case study research principles.

 

Furthermore, the limitations of this triangulation approach are explicitly acknowledged. The manuscript now clarifies that while triangulation improves internal validity within the studied organization, external validity and generalizability remain limited due to the single-case, single-site nature of the study.

 

To address reliability, the manuscript emphasizes the use of standardized evaluation tools, fixed scoring scales, and consistent assessment procedures applied across all evaluated projects. These measures are intended to ensure repeatability of the evaluation process within the same organizational setting.

 

References to established case study methodology literature are included to support the adopted approach, and directions for future research explicitly propose multi-site studies and extended datasets to further strengthen validity and reliability.

 

Location in manuscript:

Materials and Methods section; Limitations subsection.

 

Summary

Your comment has been fully addressed by explicitly clarifying data triangulation, validity, and reliability considerations, while transparently acknowledging the methodological boundaries of the presented case study.

 

Thank you for your review and comments.

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

I suggest the authors refer to the work of Ronald A. Howard and Ali Abbas for a deeper understanding of utility theory and preference modeling.  Their work is correct.  Most of the literature is not.

Comments for author File: Comments.pdf

Author Response

Dear Sir/Madame,

 

We would like to begin by expressing our sincere gratitude for the
extensive time and effort you invested in reviewing our manuscript. We
truly appreciate the critical views presented in your report and thank
you for sharing your unique knowledge regarding the mathematical
foundations of decision science and utility theory.

We fully acknowledge your points concerning the "imperfect character" of
our proposal when viewed through the lens of rigorous mathematical
validity. We are conscious that methods like AHP and Six Sigma proceed
on specific assumptions that may be subject to debate from a theoretical
standpoint.

However, we would like to emphasize that the simplicity of the proposed
framework is a deliberate design choice. Our goal was to provide a tool
that is:
* Accessible and Understandable: Based on commonly acknowledged
practical tools that are easily applicable within an industrial
environment.
* Pragmatic: Tailored to the actual needs of Six Sigma professionals who
require a quick, transparent, and reliable method to assess the
potential of project concepts before committing significant engineering
resources.
* Scalable: By using a hybrid AHP-normalized scoring approach, we aimed
to mitigate "computational intensity" and "rank reversal" issues that
often arise in complex industrial settings.

Regarding your critique of the Six Sigma methodology, we would like to
clarify that our framework is explicitly aimed at applications in
enterprises that have already adopted Six Sigma as their principal
development strategy. Therefore, our paper does not attempt to address
or defend the fundamental validity of Six Sigma itself, but rather
focuses on improving a specific, critical step (project selection)
within that established organizational context. Despite the theoretical
flaws you noted, this methodology continues to be utilized successfully
in numerous industrial cases to drive efficiency and quality.

Thank you once again for your invaluable effort. We are confident that
your comments will guide us in making our proposal more methodologically
justified in our future research. Furthermore, we believe your insights
provide the necessary means to make the broader Six Sigma community more
aware of the possible flaws in the methodologies they commonly apply.

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Accept

Author Response

Dear Sir/Madame,

Thank you for review and your comments.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have corrected the paper in detail in accordance with the submitted reviews. Based on that, I suggest that the paper be accepted for publication.

Author Response

Dear Sir/Madame,

Thank you for review and your comments.

Reviewer 4 Report

Comments and Suggestions for Authors

If this paper is to be published, and in light of the reviewers' rebuttal to my earlier comments, I think they should be forthright in noting that their objective was to develop a method that is simple, prioritizing simplicity over correctness.  They might even go so far as to suggest that flipping a coin is an even simpler method that will probably work just as well.  I would add that a researcher once challenged me on the use of a coin, tested my hypothesis and found that, for his particular case, the coin did just as well as the incorrect decision method.

Comments for author File: Comments.pdf

Author Response

Dear Sir/Madame

 

Thank you for the opportunity to broaden our view on the decision-making topic in the area of Design for Six Sigma project selection.

To address your concerns without compromising the core contribution of the current research, we have introduced the following changes to the manuscript:

1. We have reiterated Methodological Limitations: In the "Research Limitations" section, we have disclosed the potential issues concerning linear independence and the validity of ordinal rankings. We have also proposed future improvements in Conclusion Section of the manuscript.
2. We have clarified the Research Scope: The model has been reframed as a descriptive decision-support tool rather than a normative mathematical proof.

On top of that, in future work on the decision-making topics, we will take into consideration valuable feedback we have received as review to this manuscript.

Thank you,

Authors