Review Reports

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

Much improved manuscript. I have no further comments to make. 

Wishing you continued success in your work.

Author Response

We sincerely thank the reviewer for their positive evaluation of our revised manuscript. We truly appreciate your supportive comments and encouragement.

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Thank you for the opportunity to review this interesting article. In one place, it discusses different approaches to quality assurance in higher education and compares the effects based on case studies. Therefore, it will be very useful for researchers, as well as practitioners in higher education and evaluators. 

The abstract and introduction of the paper are informative and holistically introduce the topic to the reader. 

The literature review is not comprehensive, but it includes relevant and up-to-date sources. It presents different approaches for QA, with the advantages, as well as disadvantages of individual methods.

Methodologically it is built on the multiple case study comparison of five universities, studying their performance metrics. The research is presented, but in a very limited way, and the methods are mentioned without detail. A Delphi survey with five experts was used, Bayesian analysis and the model was implemented using Python, and Markov Chain Monte Carlo sampling, which are all established and suitable methods. Authors might present the analysis a little better.

Results are presented in an organised way, discussed and commented. Future research potential and limitations of the study are also presented.

Author Response

I sincerely thank the reviewer for the positive overall evaluation and for highlighting the need to present the methodological details more clearly. Following this suggestion, we have substantially expanded the Methodology section:

• • In Section 3.3 (Analytic Hierarchy Process) we now describe the Delphi procedure in detail, including the selection of five experts, the two iterative rounds, and the measurement of consensus using Kendall’s W.

  • In Section 3.4 (Bayesian modeling) we have added a comprehensive description of the model specification, prior distributions, and MCMC implementation (number of chains, iterations, burn-in, and convergence diagnostics). We also provide details on the use of Python (PyMC3) for estimation.
    These additions improve the transparency, reproducibility, and robustness of the methodology.

• Manuscript Change: Expanded methodology descriptions added at the end of Section 3.3 (Delphi process) and Section 3.4 (Bayesian modeling and MCMC), with the new text highlighted in bold in the revised manuscript.

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

The paper presents an ambitious attempt to integrate advanced mathematical models with traditional quality assurance frameworks in higher education, offering a novel approach to enhancing quality assurance systems. However, several critical issues were identified that significantly impact the paper's validity and overall impact.

One of the primary concerns is the inaccurate representation of QA standards in Figure 1. Figure 1 summarises standards (like the ESG) and procedures (like accrediation) and shows their proportion as five domains. This is a rather meaningless mixture of incomparable areas of quality assurance in higher education..

A fundamental error in defining ESG further compromises the paper's credibility. Initially, the European Standards and Guidelines (ESG) are correctly identified as relevant to higher education. However, in Section 2, the author defines ESG as Environmental, Social, and Governance standards.

The paper also asserts that higher education institutions (HEIs) are increasingly evaluated based on quantitative metrics, which may not hold true across all regions, such as the European Higher Education Area (EHEA). This overgeneralization needs to be addressed by providing a more nuanced discussion that reflects the variability of approaches in different regions.

Furthermore, the author fails to distinguish between the quality assurance of individual programs and the institutional quality of management systems. This distinction is vital for a comprehensive understanding of QA in higher education. It is essential to make this differentiation clear in the paper to provide a more accurate and relevant contribution to the field.

The inclusion of digital education technologies in the discussion feels odd and unnecessary. This section does not contribute meaningfully to the paper's core focus and should be removed to maintain a coherent and focused narrative.

The paper's engagement with recent literature is OK, but the confusion between different ESG standards detracts from this. Ensuring that all references are correctly understood and cited is essential for the paper's validity.

Overall, the paper has potential due to its unique integration of methods and engagement with recent literature. However, the significant errors in conceptual understanding and structure reduce its impact and credibility. Addressing these issues is essential to enhance the paper's contribution and overall quality.

Author Response

RC: One of the primary concerns is the inaccurate representation of QA standards in Figure 1. Figure 1 summarises standards (like the ESG) and procedures (like accreditation) and shows their proportion as five domains. This is a rather meaningless mixture of incomparable areas of quality assurance in higher education.
AR: We thank the reviewer for this important observation. Figure 1 has been completely redesigned to distinguish clearly between quality assurance frameworks (ESG, ISO 9001, EFQM), procedures (accreditation, peer review), and emerging tools (AI & Big Data). The revised structure avoids the earlier conceptual overlap.
Manuscript Change: Section 2, Figure 1 replaced; caption revised.

RC: A fundamental error in defining ESG further compromises the paper's credibility. Initially, the European Standards and Guidelines (ESG) are correctly identified as relevant to higher education. However, in Section 2, the author defines ESG as Environmental, Social, and Governance standards.
AR: We sincerely regret this confusion. In the revised manuscript, ESG is used consistently as the European Standards and Guidelines for Quality Assurance in the EHEA. Where references to Environmental, Social, and Governance appear, these are now explicitly labeled as “corporate ESG” to avoid ambiguity.
Manuscript Change: Section 2.1 revised; terminology corrected throughout.

RC: The paper asserts that higher education institutions are increasingly evaluated based on quantitative metrics, which may not hold true across all regions, such as the European Higher Education Area (EHEA).
AR: We appreciate this valuable remark. The manuscript now provides a more nuanced discussion, stating that while quantitative indicators are widely adopted globally, peer review, accreditation procedures, and qualitative assessments remain central within the EHEA.
Manuscript Change: Introduction and Section 2 revised.

RC: The author fails to distinguish between the quality assurance of individual programs and the institutional quality of management systems.
AR: We fully agree with this observation. The manuscript has been updated to explicitly distinguish program-level QA (curricula, learning outcomes, program accreditation) from institutional-level QA (governance, management systems, strategic QA frameworks).
Manuscript Change: New paragraph added at the end of Section 2; additional clarification in Section 7 (Discussion).

RC: The inclusion of digital education technologies in the discussion feels odd and unnecessary.
AR: We agree that this section required adjustment. We have condensed Section 4, reframing digital education technologies as a supporting factor in QA (e.g., student engagement metrics, online assessment integrity) rather than as a separate QA domain.
Manuscript Change: Section 4 opening paragraph rewritten.

RC: The paper's engagement with recent literature is OK, but the confusion between different ESG standards detracts from this.
AR: All terminology has been carefully revised to consistently distinguish ESG (European Standards and Guidelines) from corporate ESG. References were cross-checked to ensure conceptual accuracy.
Manuscript Change: Section 2.1 and references re

Reviewer 4 Report (New Reviewer)

Comments and Suggestions for Authors

The article is of great interest to higher education researchers and administrators.
The quality frameworks described are those typically used by higher education institutions to assess teaching quality.
The use of various statistical tools for projecting positions in international rankings is novel and well described. Thus, the complementary use of instruments, such as DEA, AHP, and Bayesian modelling to compare and present cases in quality frameworks, such as the EFQM Excellence Model or ISO 9001, is pertinent and relevant for higher education institutions.
The results have been clearly presented and applied in cases that reveal the validity of the proposals. The figures and tables are relevant and facilitate reading.
However, reducing the number of sections dedicated to describing the quality models and the methods to be used would be important. Although some readers may have limited knowledge of these models and instruments, the length of these sections may distract the reader from other fundamental aspects, such as the presented cases.

Author Response

RC: Reducing the number of sections dedicated to describing the quality models and the methods to be used would be important. Although some readers may have limited knowledge of these models and instruments, the length of these sections may distract the reader from other fundamental aspects, such as the presented cases.

AR: We thank the reviewer for this constructive suggestion. In response, we have streamlined Section 2 (quality assurance frameworks) by condensing the descriptions of EFQM and ISO 9001, focusing only on their most relevant aspects for higher education quality assurance. Similarly, in Section 3 (Methods), the introductory part was revised to provide a concise overview of DEA, AHP, and Bayesian modeling before the detailed subsections, and the DEA and MLM descriptions were shortened to avoid redundancy.

At the same time, we deliberately retained a more detailed discussion of AHP and Bayesian modeling, as these methods represent the paper’s main methodological contributions and are less frequently integrated into QA research. We believe that their fuller presentation adds to the clarity and originality of the study while ensuring that readers can fully appreciate their application in the case studies.

Manuscript Change: Section 2 (EFQM, ISO 9001) shortened; Section 3 introduction revised and DEA/MLM condensed. AHP and Bayesian modeling retained in detail due to their central relevance.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript provides a comprehensive overview of various quality assurance frameworks and addresses the challenges and benefits of implementing these frameworks in HE. The revisions that I would suggest are as follows:

1. In the introduction section, more context can be added about the challenges faced by HEIs in ensuring quality ( ie globalization) and the benefits they would gain by implementing strong QA systems.
2.  Some confusion is caused over the use of ESG. Specifically, line 30 the European Standards and Guidelines ( 2015) have the acronym ESG. The same acronym appears on line 85 but it refers to a different framework. When transitioning between frameworks consistency of language should be ensured.
3. When outlining the benefits of each framework , more depth analysis would improve the text. For example, how can the challenges of ISO 9001 be mitigated? Also, the section on AI and Big data seems to be a bit underdevelopped.  
4. Although several references are used in the text, the manuscript would benefit from a broader range of literature resources. For example, line 158 "Empirical studies ..." makes a reference to one article, line 173 "A comparative...." could benefit from expanding more on the details of the article. 
5. Similar to comment 4 above, the AHP methods and what they can provide ( line 216-217) does not sound very convincing. 
6. Line 232, "A case study..." but the case study is not mentioned (  no reference is included)
7. The aim of  the section on Digital Education and Sustainability in quality assurance is not quite clear . It does not seem to fit well in the article. How is it linked to the aims of the article? (line 55-63) 
8. In the conclusion section, the points that are made could be elaborated more and some effort should be made to provide a more balanced perspective. 

On the whole, additional literature as well as deeper discussions of each framework would improve the manuscript. 

Comments on the Quality of English Language

While generally well-written , there are a few sentences that can be rewritten for clarity. For example, the phrase "This personalized approach fosters more efficient knowledge acquisition..." (line 65) could be simplified to enhance readability. Also, you could avoid repetition of structures such as the "Despite....Nevertheless,..." which appear on lines 97& 99, lines 127&129. On the whole, the manuscript could benefit from language editing to improve small errors and the overall flow. 

Reviewer 2 Report

Comments and Suggestions for Authors

Figure 1 presents an overview of different frameworks used to evaluate QA; however, it's not clear how these percentages were calculated nor what the context is for such a graph. For example, are the authors intending to suggest that this pie chart reflects global QA frameworks or European frameworks? It would be helpful to contextual the research findings. Overall, the paper provides a comprehensive overview of quantitative frameworks for evaluating institutional effectiveness, but more time needs to be spend critiquing the relevance of these metrics. 

Reviewer 3 Report

Comments and Suggestions for Authors

While the clear structure and coherent line of argumentation are commendable, the text lacks specificity, both in its claims and in the supporting references.

However, some questions arise regarding

• Higher education and university structures are highly diverse, so I wonder to whom the percentages in the first figure refer
• the second figure actually is not convincing
•  see also my comments in the references, which I will copy into this section:

The references are not standardised, e.g. for ‘de Toledo, J. C. (2021). The impact of ISO 9001 certification on Brazilian firms’ performance: ‘ is incomplete. Authors and pages are missing. In other references, the year is at the end, in some it is after the author's name.

There is a noticeable mismatch between the statements made in the text and the references cited.

While the claims are articulated in abstract and generalized terms, the references provided do not adequately support this level of abstraction, thereby limiting the traceability and evaluability of the argument’s evidential basis. --> for example the sentence in 81-83 uses a study on Peer review of teaching (PRT) which is a systematic review of the PRT literature, non of the key components or mechanisms were mentioned. This also applies to citation [6]. The authors could have cited, Alenezi, M., & Alanazi, F. (2024). Integrating environmental, social, and governance values into higher education curriculum. International Journal of Evaluation and Research in Education, 13(5), 3493–3503

"A study by Smith & Taylor (2020)" (112/113) and "Martinez et al. (2021)" (121/122) can not be found. The studies mentioned aren't even part of the cited literature. I have checked. 
Although the statements pertain to higher education, the supporting literature primarily addresses healthcare [8] or corporate settings [9], resulting in a lack of contextual specificity. Another example can be found in lines 273–276, where "AI-powered plagiarism detection and multi-modal evaluation techniques to minimize cheating risks" is mentioned. However, the cited source discusses academic integrity during the COVID-19 pandemic and does not refer to AI at all. Moreover, AI only began to gain widespread attention as a discourse from 2022 onwards, not in 2020.; The same applies to line 350-354 and reference [30], which, in my view, constitutes a questionable citation that does not adequately support the associated claim, furthermore I would say this is an false claim.