Mapping of the Quintuple Helix Model Pillars and Digitalization in European Union Countries

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper addresses a current and relevant topic and is generally well structured and theoretically grounded, but there are some aspects that could be improved:

- It would be useful to emphasize more precisely how your study adds to previous empirical research on these models.
- The methodology is well chosen and clearly described, but a more detailed presentation of the cluster selection criteria and the average values ​​for each would be useful.
- The conclusions are correct and supported by the results, but could be formulated more specifically, indicating the practical implications for governance and the development of intellectual capital in low-performing countries.
- A short section of public policy recommendations, based on the results obtained, would also be useful.
- The tables are clear, but graphical representations (maps, diagrams) that would help visualize the differences between groups of countries are missing.

Comments on the Quality of English Language

The English used is correct, but the text would benefit from a minor linguistic revision to eliminate redundancies and improve fluency.

Author Response

Dear reviewer,

Thank you for your comments. We strongly appreciate your time and effort to improve our manuscript and we are thankful for all your comments.

Numbering of lines to identify inserted text and changes is implemented through: Monitoring changes - All revisions - Display all revisions in the text.

 

 

Comments and Suggestions for Authors

The paper addresses a current and relevant topic and is generally well structured and theoretically grounded, but there are some aspects that could be improved:

- It would be useful to emphasize more precisely how your study adds to previous empirical research on these models.

Added in section Introduction and Literature rewiev

- The methodology is well chosen and clearly described, but a more detailed presentation of the cluster selection criteria and the average values ​​for each would be useful.

Modified, added line 313 -399 and section methodology

- The conclusions are correct and supported by the results, but could be formulated more specifically, indicating the practical implications for governance and the development of intellectual capital in low-performing countries.

Added in section results, discussion and conclusion

- A short section of public policy recommendations, based on the results obtained, would also be useful.

Added in section conclusion

- The tables are clear, but graphical representations (maps, diagrams) that would help visualize the differences between groups of countries are missing.

Added in section results

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for the opportunity to review this paper. In its current form, however, it presents theoretical and methodological deficiencies that make it unsuitable for publication. Below are some of my main concerns.

The Introduction lacks a presentation of the paper’s contributions to the existing literature, its novelty and originality, as well as the usefulness of the obtained results.

Although the basic concepts are defined, there is no critical analysis of the corresponding literature to identify the main studies that have developed these concepts in different contexts. The mere listing of titles of several papers (lines 134–139), without any critical analysis, can hardly be considered such an effort. The theories underpinning the study are also not discussed (there is only a brief mentioning  of “theories of digitalization”). These omissions significantly reduce the scientific quality of the paper.

The research question appears twice, in two consecutive paragraphs (lines 147–150 and 158–160), and is repeated for a third time in the first paragraph of Section 2.

I recommend that the authors split the first section into two — Introduction and Literature Review — and ground the research question rigorously in the relevant theories and literature.

The structure of the paper is also missing from the Introduction.

The authors do not explain why the indicators of the Global Sustainable Competitiveness Index (GSCI) 2024 represent the Quintuple Helix model, nor do they mention any other studies that have used this approach. The content of the variables used is also not explained at all.

The analyzed period — which, as I understand, is only one year — is very short. How does this affect the results? This limitation should be discussed.

The Conclusions section merely summarizes the results obtained, without offering any policy or stakeholder recommendations.

The paper’s approach is simplistic and represents only the beginning of a research endeavor that I hope the authors will successfully pursue to enrich and advance the literature in this field.

Author Response

Dear reviewer,

Thank you for your comments. We strongly appreciate your time and effort to improve our manuscript and we are thankful for all your comments.

Numbering of lines to identify inserted text and changes is implemented through: Monitoring changes - All revisions - Display all revisions in the text.

 

Comments and Suggestions for Authors

Thank you for the opportunity to review this paper. In its current form, however, it presents theoretical and methodological deficiencies that make it unsuitable for publication. Below are some of my main concerns.

The Introduction lacks a presentation of the paper’s contributions to the existing literature, its novelty and originality, as well as the usefulness of the obtained results.

Although the basic concepts are defined, there is no critical analysis of the corresponding literature to identify the main studies that have developed these concepts in different contexts. The mere listing of titles of several papers (lines 134–139), without any critical analysis, can hardly be considered such an effort. The theories underpinning the study are also not discussed (there is only a brief mentioning  of “theories of digitalization”). These omissions significantly reduce the scientific quality of the paper.

Added in section Introduction and Literature rewiev

The research question appears twice, in two consecutive paragraphs (lines 147–150 and 158–160), and is repeated for a third time in the first paragraph of Section 2.

The first time it is stated generally and the second time it is specified in the relationship between digitalization vs. governance and intellectual capital.

I recommend that the authors split the first section into two — Introduction and Literature Review — and ground the research question rigorously in the relevant theories and literature.

Modified

The structure of the paper is also missing from the Introduction.

Added, line 75 -78

The authors do not explain why the indicators of the Global Sustainable Competitiveness Index (GSCI) 2024 represent the Quintuple Helix model, nor do they mention any other studies that have used this approach. The content of the variables used is also not explained at all.

Added table 1 and text 246-259

The analyzed period — which, as I understand, is only one year — is very short. How does this affect the results? This limitation should be discussed.

Our study focuses on mapping the structure of QH parameters and digitalization in EU countries. The limitations of the study related to the dynamics of development over time are mentioned in the discussion, lines 585 -588

The Conclusions section merely summarizes the results obtained, without offering any policy or stakeholder recommendations.

Added 625-634

The paper’s approach is simplistic and represents only the beginning of a research endeavor that I hope the authors will successfully pursue to enrich and advance the literature in this field.

Yes, we are aware of this fact, but our study focuses on mapping the structure of QH parameters and digitalization in EU countries, which presents its limits. But it is the primary research of the project, which will continue.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The paper examines how Quintuple Helix dimensions — proxied by GSCI 2024 pillars (Natural, Social, Intellectual, Economic, Governance) — relate to digitalization (DESI 2024) across the 27 EU countries. Using z-standardized scores, the authors run K-means to identify three clusters and then compute Pearson correlations among variables, concluding that countries with higher digitalization also show stronger governance and intellectual capital, while natural capital correlates mainly with economic capital. 

Major issues (and concrete fixes)

1) Conceptual alignment and originality: The Quintuple Helix (QH) framing is rich, but the empirical model ends up as a cross-sectional clustering + bivariate correlations exercise. Claims about “mutual influence” or QH impact” are causal in tone, yet the design is descriptive. The narrowing from the full QH to Governance and Intellectual Capital vis-à-vis DESI is asserted but not theoretically derived; why not also Social/Natural in the main model?

Revise: Recast the contribution as descriptive mapping of EU country profiles, not causal “impact; Provide a clear theory-of-change for why governance and intellectual capital should be the closest companions of DESI (e.g., institutional capacity → absorptive capacity); If keeping “influence” language, add a temporal or panel element (DESI & GSCI over multiple years) or use instrumented designs—otherwise shift wording to “association/structure.”

2) Variable provenance and comparability: The study mixes two composite indices (GSCI pillars and DESI). It is not fully clear whether scales and directions are fully harmonized beyond z-scores, and whether component overlap may mechanically inflate correlations (e.g., governance components overlapping with DESI enablers).

Revise: Add a table of indicators (at least at the pillar dimension level) showing construct coverage and potential overlaps; state expected signs; Report unit and direction checks before standardization (higher=better for all?), and run partial correlations controlling for GDP per capita, education spend, or population size to test whether relationships persist beyond development level.

3) K-means design, k-selection, and validation: K-means is sensitive to k choice and scale. The manuscript does not report how k=3 was chosen, nor initialization, convergence, or stability. ANOVA on cluster means is presented, but the paper itself notes the non-inferential nature of those F-tests after clustering. Also, n=27 is small for stable clusters in 6-D space.

Revise: Justify k via elbow, silhouette, and gap statistic; report average silhouette per cluster. Add robustness: (i) hierarchical clustering (Ward), (ii) GMM/mixture models, (iii) bootstrap stability (Jaccard) of cluster memberships, and consider PCA to reduce dimensionality (retain PCs explaining ≥80% variance) and then cluster in PC-space; show a biplot with country labels.

4) Internal consistency of cluster summaries: Table 2 shows identical DESI mean “89” for Clusters 1 and 2, despite very different compositions; this either reflects rounding, an input/labeling error, or insufficient precision to distinguish groups on the variable of interest. Units for the “Ø” row are also unclear.

Revise: Report means ± SD (or medians with IQR) to one decimal place, specify units/scale (original index vs. standardized), and add a country-level appendix so readers can verify the inputs.

5) Correlation analysis and confounding: Pearson correlations are informative but bivariate and vulnerable to confounding. Given the high co-movement of development indicators in the EU, Governance↔Intellectual (r=.771) and DESI↔Governance (r=.435) might reflect third variables. No multiple-testing control or influence diagnostics (e.g., Luxembourg/Ireland outliers) are reported. 

Revise: Add partial correlations (control GDPpc, education, region dummies); Apply Holm/Benjamini–Hochberg to correlation p-values; Provide influence checks (leave-one-out correlations) and a correlogram with confidence ellipses.

6) Natural capital” finding needs nuance: The paper concludes that Natural Capital has no tie to governance/digitalization but correlates with the economy (r=.476). This might be a composition artifact (GSCI Natural mixes biophysical assets; DESI captures digital adoption) or non-linear relationships.

Revise: Test non-linear associations (Spearman, LOWESS) and partial correlations; Discuss the plausible decoupling between ecological stock measures and digital readiness in mature economies; consider eco-innovation proxies as a bridge variable.

7)Methods and reporting checklist (add to the paper): Pre-processing: confirm positive orientation of all indices; show correlation matrix of raw pillars + DESI; report KMO if any dimensionality reduction is used; Clustering: justify k, report silhouette/gap, initialization, iterations, and stability; add map visualizing clusters. Inference keep ANOVA on cluster means as descriptive; avoid p-value language implying hypothesis testing after clustering. Robustness: PCA→K-means; hierarchical clustering; outlier sensitivity; partial correlations. Transparency: provide a data and code repository (script to download GSCI/DESI, cleaning, analysis); the current statement “data contained within the article” limits reproducibility.

Minor edits (quick wins)

Define acronyms on first use (GSCI, DESI) in the Abstract and Methods.

Standardize significance notation (p<.05, *p<.01) and remove mixed decimals (e.g., “Sig. = 0.000” → p<.001).

Ensure country names and cluster lists are alphabetized within clusters; add counts per cluster.

Add figure captions explaining what each color/edge means in Figure 2; include CI bands if showing correlations as edges.

Clarify software versions (SPSS 20) and random seeds for reproducibility.

Optional reframing (if the author revises).

Title (more precise): Quintuple Helix Pillars and the EU’s Digitalization Landscape: A Cluster and Correlation Mapping with GSCI & DESI (2024).

My final decision is "Major revision" good luck. 

Author Response

Dear reviewer,

Thank you for your comments. We strongly appreciate your time and effort to improve our manuscript and we are thankful for all your comments.

Numbering of lines to identify inserted text and changes is implemented through: Monitoring changes - All revisions - Display all revisions in the text.

 

Comments and Suggestions for Authors

The paper examines how Quintuple Helix dimensions — proxied by GSCI 2024 pillars (Natural, Social, Intellectual, Economic, Governance) — relate to digitalization (DESI 2024) across the 27 EU countries. Using z-standardized scores, the authors run K-means to identify three clusters and then compute Pearson correlations among variables, concluding that countries with higher digitalization also show stronger governance and intellectual capital, while natural capital correlates mainly with economic capital. 

Major issues (and concrete fixes)

1) Conceptual alignment and originality: The Quintuple Helix (QH) framing is rich, but the empirical model ends up as a cross-sectional clustering + bivariate correlations exercise. Claims about “mutual influence” or QH impact” are causal in tone, yet the design is descriptive. The narrowing from the full QH to Governance and Intellectual Capital vis-à-vis DESI is asserted but not theoretically derived; why not also Social/Natural in the main model?

Revise: Recast the contribution as descriptive mapping of EU country profiles, not causal “impact; Provide a clear theory-of-change for why governance and intellectual capital should be the closest companions of DESI (e.g., institutional capacity → absorptive capacity); If keeping “influence” language, add a temporal or panel element (DESI & GSCI over multiple years) or use instrumented designs—otherwise shift wording to “association/structure.”

Modified as structure

2) Variable provenance and comparability: The study mixes two composite indices (GSCI pillars and DESI). It is not fully clear whether scales and directions are fully harmonized beyond z-scores, and whether component overlap may mechanically inflate correlations (e.g., governance components overlapping with DESI enablers).

Revise: Add a table of indicators (at least at the pillar dimension level) showing construct coverage and potential overlaps; state expected signs; Report unit and direction checks before standardization (higher=better for all?), and run partial correlations controlling for GDP per capita, education spend, or population size to test whether relationships persist beyond development level.

Modified, added table 1 + text, line 246 - 259

3) K-means design, k-selection, and validation: K-means is sensitive to k choice and scale. The manuscript does not report how k=3 was chosen, nor initialization, convergence, or stability. ANOVA on cluster means is presented, but the paper itself notes the non-inferential nature of those F-tests after clustering. Also, n=27 is small for stable clusters in 6-D space.

Revise: Justify k via elbow, silhouette, and gap statistic; report average silhouette per cluster. Add robustness: (i) hierarchical clustering (Ward), (ii) GMM/mixture models, (iii) bootstrap stability (Jaccard) of cluster memberships, and consider PCA to reduce dimensionality (retain PCs explaining ≥80% variance) and then cluster in PC-space; show a biplot with country labels.

Modified, added line 313 -399

4) Internal consistency of cluster summaries: Table 2 shows identical DESI mean “89” for Clusters 1 and 2, despite very different compositions; this either reflects rounding, an input/labeling error, or insufficient precision to distinguish groups on the variable of interest. Units for the “Ø” row are also unclear.

Revise: Report means ± SD (or medians with IQR) to one decimal place, specify units/scale (original index vs. standardized), and add a country-level appendix so readers can verify the inputs.

Modified table 4

5) Correlation analysis and confounding: Pearson correlations are informative but bivariate and vulnerable to confounding. Given the high co-movement of development indicators in the EU, Governance↔Intellectual (r=.771) and DESI↔Governance (r=.435) might reflect third variables. No multiple-testing control or influence diagnostics (e.g., Luxembourg/Ireland outliers) are reported. 

Revise: Add partial correlations (control GDPpc, education, region dummies); Apply Holm/Benjamini–Hochberg to correlation p-values; Provide influence checks (leave-one-out correlations) and a correlogram with confidence ellipses.

Added analyse and sumarization in table 5, Based on the results of the Benjamini–Hochberg procedure, the results are insignificant, so we did not process the correlogram with reliability ellipses.

6) Natural capital” finding needs nuance: The paper concludes that Natural Capital has no tie to governance/digitalization but correlates with the economy (r=.476). This might be a composition artifact (GSCI Natural mixes biophysical assets; DESI captures digital adoption) or non-linear relationships.

Revise: Test non-linear associations (Spearman, LOWESS) and partial correlations; Discuss the plausible decoupling between ecological stock measures and digital readiness in mature economies; consider eco-innovation proxies as a bridge variable.

Added, line 567-587

7)Methods and reporting checklist (add to the paper): Pre-processing: confirm positive orientation of all indices; show correlation matrix of raw pillars + DESI; report KMO if any dimensionality reduction is used; Clustering: justify k, report silhouette/gap, initialization, iterations, and stability; add map visualizing clusters. Inference keep ANOVA on cluster means as descriptive; avoid p-value language implying hypothesis testing after clustering. Robustness: PCA→K-means; hierarchical clustering; outlier sensitivity; partial correlations. Transparency: provide a data and code repository (script to download GSCI/DESI, cleaning, analysis); the current statement “data contained within the article” limits reproducibility.

We have comprehensively addressed all points in the checklist by confirming the positive orientation of all indices, including the correlation matrix of raw data, detailing the clustering procedures (justification of k, stability, initialization), confirming the descriptive use of ANOVA, validating robustness through PCA and partial correlations.

 

Minor edits (quick wins)

Define acronyms on first use (GSCI, DESI) in the Abstract and Methods.

Standardize significance notation (p<.05, *p<.01) and remove mixed decimals (e.g., “Sig. = 0.000” → p<.001).

Ensure country names and cluster lists are alphabetized within clusters; add counts per cluster.

Modified

Add figure captions explaining what each color/edge means in Figure 2; include CI bands if showing correlations as edges.

Added, line 298-303

Clarify software versions (SPSS 20) and random seeds for reproducibility.

Added, line 211-215

Optional reframing (if the author revises).

Optional modified

Title (more precise): Quintuple Helix Pillars and the EU’s Digitalization Landscape: A Cluster and Correlation Mapping with GSCI & DESI (2024).

Modified according to your requirements, but also the requirements of other reviewers - title optimization

My final decision is "Major revision" good luck. 

Thank you for your comments, which have improved our article. We believe that we have incorporated them sufficiently and that we will have good luck publishing this manuscript.

 

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have improved the paper, especially regarding methodological aspects, following most of the previous recommendations. However, it is still necessary to elaborate on “The theories underpinning the study which are not discussed (there is only a brief mention of ‘theories of digitalization’)” and to cite other studies that use the variables from Table 1, even if in different combinations or contexts.

Author Response

Dear reviewer,

Thank you for your comments. We strongly appreciate your time and effort to improve our manuscript and we are thankful for all your comments.

Numbering of lines to identify inserted text and changes is implemented through: Monitoring changes - All revisions - Display all revisions in the text.

 

The authors have improved the paper, especially regarding methodological aspects, following most of the previous recommendations. However, it is still necessary to elaborate on “The theories underpinning the study which are not discussed (there is only a brief mention of ‘theories of digitalization’)” and to cite other studies that use the variables from Table 1, even if in different combinations or contexts.

 

Your suggested edits to the theories have been added to the abstract and literature. Literature review, line 238-248 and added cite other studies that use the variables from Table 1, even if in different combinations or contexts, line 274-289.

The English was improved by an English speaker.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have substantially revised the manuscript and responded constructively to the previous set of comments. The inclusion of detailed methodological explanations (e.g., data orientation, k-selection, correlation table, and robustness checks) has improved the transparency of the analysis. The new title is clearer and better aligned with the content.

However, while the paper is now technically sound, several aspects still limit its conceptual rigor, interpretive depth, and positioning within the Systems readership. The manuscript remains largely descriptive and data-driven, with modest theoretical or managerial insight.

I commend the authors for their effort and responsiveness—the paper is improved—but further refinement is still needed before it reaches a publishable standard.

1) Conceptual framing and contribution

• The introduction and theory sections still read as an extended narrative of the Helix literature rather than a critical synthesis leading to a research gap.
• The paper now positions itself as a mapping exercise, yet still uses causal or deterministic phrasing such as “impact” or “influence.” Please ensure conceptual alignment: the study examines associations, not causal effects.
• The linkage between Quintuple Helix dimensions and DESI remains intuitive but under-theorized. Why should governance and intellectual capital exhibit the strongest correlations? What mechanisms or theoretical pathways are implied (e.g., absorptive capacity, institutional readiness, innovation governance)?
• Consider shortening the historical overview and focusing instead on how digitalization co-evolves with systemic innovation capacity in the EU context.

2. Methodological transparency and validation

Improvements are clear (indicator table, justification of k, correlation matrix). Yet:

• The n=27 sample size remains a limitation. Discuss implications for cluster stability and generalizability.
• Report silhouette, elbow, and gap statistic values numerically (not just conceptually) to demonstrate robustness of the 3-cluster solution.
• Partial correlations were added, but the interpretation is superficial. Consider reporting them explicitly in a table or appendix, noting which associations persist after controlling for GDP.
• If PCA was used, please specify the variance explained per component and loadings for transparency.

3. Results interpretation and depth

• The cluster results are well presented, but the discussion could move beyond descriptive contrasts. What typologies of EU digitalization–innovation ecosystems emerge? Are these “Nordic governance–knowledge leaders,” “Southern adaptive innovators,” and “Eastern catching-up economies”? Framing them this way would add analytical depth.
• The correlations remain modest (r≈.38–.43 for DESI links), so interpretation should avoid over-generalization. The paper could use these as patterns of association, not as validation of the Quintuple Helix model itself.
• The “Natural capital → economic capital” finding deserves a deeper policy interpretation: does this reflect a green-growth trade-off or structural decoupling?

4. Presentation and style

• The paper is now readable, though still dense in theory citations. Shorten the early sections (lines 30–120) by 20–25% to improve flow.
• The figures are helpful; ensure Figure 2 labels and arrows clearly denote correlation direction and magnitude.
• Replace decimal significance (“Sig.=0.000”) with conventional reporting (p < .001).
• Consider a graphical abstract or summary diagram linking Helix pillars ↔ DESI outcomes for clarity.

5. Limitations and future directions

The limitations paragraph (lines 364–368) is brief. Expand by highlighting:

• Cross-sectional design and small sample constraints.
• Potential endogeneity between governance quality and digital readiness.
• Future research could employ panel DESI–GSCI data (2015–2024) or mixed-methods case studies to test co-evolutionary dynamics.

My recommendation, Minor Revision (after targeted conceptual and interpretive improvements). The revision represents clear progress, improved clarity, structure, and methodological reporting, but it still lacks interpretive depth and stronger theoretical articulation. With these final adjustments, the paper could make a meaningful contribution as a descriptive systems-mapping of digitalization and innovation ecosystems across EU countries through a Quintuple Helix lens.

 

Comments on the Quality of English Language

NO comment

Author Response

Dear reviewer,

Thank you for your comments. We strongly appreciate your time and effort to improve our manuscript, and we are thankful for all your comments.

Numbering of lines to identify inserted text and changes is implemented through: Monitoring changes - All revisions - Display all revisions in the text.

The English was improved by an English speaker.

Comments and Suggestions for Authors

The authors have substantially revised the manuscript and responded constructively to the previous set of comments. The inclusion of detailed methodological explanations (e.g., data orientation, k-selection, correlation table, and robustness checks) has improved the transparency of the analysis. The new title is clearer and better aligned with the content.

However, while the paper is now technically sound, several aspects still limit its conceptual rigor, interpretive depth, and positioning within the Systems readership. The manuscript remains largely descriptive and data-driven, with modest theoretical or managerial insight.

I commend the authors for their effort and responsiveness—the paper is improved—but further refinement is still needed before it reaches a publishable standard.

1) Conceptual framing and contribution

• The introduction and theory sections still read as an extended narrative of the Helix literature rather than a critical synthesis leading to a research gap.

Modified and added, line 212-222

• The paper now positions itself as a mapping exercise, yet still uses causal or deterministic phrasing such as “impact” or “influence.” Please ensure conceptual alignment: the study examines associations, not causal effects.

Modified

• The linkage between Quintuple Helix dimensions and DESI remains intuitive but under-theorized. Why should governance and intellectual capital exhibit the strongest correlations? What mechanisms or theoretical pathways are implied (e.g., absorptive capacity, institutional readiness, innovation governance)?

Modified, and added, line 238-251

• Consider shortening the historical overview and focusing instead on how digitalization co-evolves with systemic innovation capacity in the EU context.

Due to the requests of other reviewers to expand the literature review, we cannot shorten it. Innovation capacity in context EU added. Added, line 178-189

1. Methodological transparency and validation

Improvements are clear (indicator table, justification of k, correlation matrix). Yet:

• The n=27 sample size remains a limitation. Discuss implications for cluster stability and generalizability.

Added, line 640-664

• Report silhouette, elbow, and gap statistic values numerically (not just conceptually) to demonstrate robustness of the 3-cluster solution.

WCSS and silhouette method values ​​are listed in Table 1. WCSS and Silhouette coefficient in conjunction with Adjusted Rand Index, Ward's method and Ward's method provide a strong, comprehensive and robust interpretation of the cluster model for determining the optimal number of clusters for K-means. Therefore, we do not consider it necessary to further expand this section, which could already overwhelm the reader.

• Partial correlations were added, but the interpretation is superficial. Consider reporting them explicitly in a table or appendix, noting which associations persist after controlling for GDP.

Added, line 542-581

• If PCA was used, please specify the variance explained per component and loadings for transparency.

PCA Biplot method is described in the work.

1. Results interpretation and depth

• The cluster results are well presented, but the discussion could move beyond descriptive contrasts. What typologies of EU digitalization–innovation ecosystems emerge? Are these “Nordic governance–knowledge leaders,” “Southern adaptive innovators,” and “Eastern catching-up economies”? Framing them this way would add analytical depth.

Modified, added to results, line 492-509

• The correlations remain modest (r≈.38–.43 for DESI links), so interpretation should avoid over-generalization. The paper could use these as patterns of association, not as validation of the Quintuple Helix model itself.

Modified, we pattern of word - association.

• The “Natural capital → economic capital” finding deserves a deeper policy interpretation: does this reflect a green-growth trade-off or structural decoupling?

Added, line 725-739

1. Presentation and style

• The paper is now readable, though still dense in theory citations. Shorten the early sections (lines 30–120) by 20–25% to improve flow.
• The section was expanded at the request of another Reviewer. To improve fluency and respond to your comment, we have restructured and condensed the text (instead of shortening) to maintain high information value while increasing fluency.
• The figures are helpful; ensure Figure 2 labels and arrows clearly denote correlation direction and magnitude.

Modified

• Replace decimal significance (“Sig.=0.000”) with conventional reporting (p < .001).

Modified

• Consider a graphical abstract or summary diagram linking Helix pillars ↔ DESI outcomes for clarity.

We did not consider a graphic abstract. Summary diagram is Figure 5.

1. Limitations and future directions

The limitations paragraph (lines 364–368) is brief. Expand by highlighting:

• Cross-sectional design and small sample constraints

Added, line 640-664

• Potential endogeneity between governance quality and digital readiness.

Added, line 640-664

• Future research could employ panel DESI–GSCI data (2015–2024) or mixed-methods case studies to test co-evolutionary dynamics.

The full answers to the review are provided in the attached file.

Author Response File: Author Response.docx