Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

 

1. Comments and Suggestions to the Author(s):
   • Overall evaluation of the manuscript briefly:

The manuscript «Research on the Impact of Marine New-Quality Productive Forces on the High-Quality Development of the Marine Economy— Dual Examination Based on Mediation Effect and Threshold Effect» is in line with the aims and scope of the «Sustainability» journal.

This empirical study assesses the impact of new quality productive forces on the sustainable development of China's maritime economy. The text analyses a variety of approaches to the sustainable development of the maritime economy, including socio-economic, scientific and integrated methods. However, the manuscript has a number of structural and interpretative weaknesses. These cast doubt on the validity and novelty of its conclusions.

Overall Recommendation: Accept with Major Revision.

 

• Reasons for acceptance or rejection, suggestions for revisions or improvements:

Title.

• The title of the manuscript should be shortened and revised. The title should not contain the construction "Research on...". The phrase "Dual Examination Based on Mediation Effect..." is poorly formulated. Since the study was conducted for China, this should be clearly stated in the title. For example: "New-Quality Marine Productive Forces and High-Quality Development of the Marine Economy in China: Mediating Mechanisms and Threshold Effect".
• It is important to note that the structure of the manuscript must follow the journal's rules and include the sections: "Introduction," "Materials and Methods," "Results," "Discussion," and "Conclusions." Currently, the material is confusing. Thus, I recommend identifying and giving appropriate headings to the sections.

 

Introduction.

Do the authors know about the new studies on this topic that have been published recently? It would be beneficial if the authors could discuss this recent study at Introduction and Discussion.:

• Gao, Q.; Feng, Z.; Li, K. Research on the Impact of Marine New Quality Productive Forces on Marine Economic Resilience: A Case Study of 11 Coastal Provinces and Cities in China. Sustainability 2025, 17, 4457. https://doi.org/10.3390/su17104457
• Wei Yao, Yunhang Du, Hua Cheng. How does the digital economy empower high-quality marine development? International Review of Economics & Finance, 2026/03/01. https://doi.org/10.1016/j.iref.2026.104996;
• Yi, C.; Zhang,Y.; Xi, S.; Lin, K. High-QualityDevelopmentof China’s MarineEconomy: Green Finance Perspectives (2010–2021). Sustainability 2025, 17, 7271. https:// doi.org/10.3390/su17167271.
• So, the novelty of the research should be better highlighted.
• The introduction lacks a clear structure and logical flow. The authors should explain how well this topic has been studied and why it is relevant not only in China but also globally.
• The concept of " New-Quality Marine Productive Forces" should be explained more.
• It's important to explain all the terms, highlight why the research is new and important, and finish with the main goal of the study.
• It would also be useful to justify why these specific study regions were selected.
• Recent literature from 2025 and 2026 on this topic is missing and should be included. The authors must explain how this study differs from the latest literature and what its scientific contribution is.

Materials and Methods.

• The authors define the concept of «new-quality maritime productive forces» (MNQP) as the classical three-part framework: labor, means of labor, and objects of labor. The differences between this and the general concept of 'productive forces' need to be explained more clearly.
• In my opinion the indicators used in Table 2 seem to show progress in technology and digitalisation at the regional economy level, rather than the specific idea of "new quality" in the marine sector. This could mean that we lose sight of the most important concepts. It also means that the analysis becomes a simple repeat of the well-known fact that a higher level of marine economic development is explained by the region's general technological advancement. What about Comprehensive development index of marine natural resources or Direct economic losses from marine disasters, etc.? This section needs to be made much stronger or provide a detailed explanation in the following sections.
• The Methods section should include a map of the study area, which covers 11 provinces. The paper should also provide a table with the main characteristics of the study regions. These improvements will help to analyses the results. Also, this should be included in the Discussion.

Results.

• The sample size is very small (N = 110), yet the manuscript makes overly strong claims. With a panel of this size, strong conclusions must be stated much more cautiously. Phrases such as “strongly supports Hypothesis 1”, “highly independent”, and “not driven by other factors” should be removed. A regression with this set of controls does not prove that the effect is independent of “other factors”; it only shows that the effect remains after controlling for the observed variables included in that particular specification.
• Endogeneity: In the baseline regression (Table 5), the issue of reverse causality is not dealt with. A higher level of marine economic quality (HQD-ME) may itself attract investment in technology and skilled labour. This issue should be discussed.
• A single coefficient of 0.138 does not justify the claim of a “foundational role” (line 480). A more appropriate formulation would be: “is positively associated with…”.
• The interpretation of EDU is also not justified. The phrase "likely due to structural mismatches..." (line 501) is a guess, not something that is proven by the model. One can only say that: the coefficient of EDU is statistically insignificant. This means that the effect of general human capital is not clearly identified in the baseline model.
• In general, the conclusions should be stated more carefully and should remain closely tied to the empirical results.
• Problems with the threshold model: The text says that the threshold variable is the economic development level, but Table 9 refers to "the Level of High-quality Development in the Marine Economy". This should be written the same way throughout the manuscript: threshold variable = economic development level (EDL).
• For better visualization, the manuscript should also include maps showing “The HDME development level of China’s marine industry” across the study regions.
• In Table 9, the threshold values (γ₁ = 11.1171 and γ₂ = 11.1221) are almost identical. Since these are logarithmic values of per capita GDP, such close thresholds imply that the sample is divided into intervals with only minimal differences in development levels, which calls into question the economic significance of this division. The authors should to explain why such a minor change in economic development would lead to a sharp shift in the estimated effect of MNQP. These issues should be clearly discussed and reflected in the conclusions.
• The data reported in Table 10 should be checked carefully, as there appear to be typos or numerical errors.
• Overall, the tables and the text appear inconsistent. The description of results and the conclusions should therefore be made more precise and more cautious. The authors may also consider using more modern data visualization methods.

 Discussion.

• Discussion and Conclusions should be separated.
• The discussion should be expanded and revised:
• This section should contain an academic discussion and references to similar works, especially those published in recent years.
• The literature contains findings from the «Analysis of Time Variation of Marine New Quality Productive Forces» and the «Analysis of Spatial Distribution of Marine New Quality Productive Forces» for 11 study provinces in China. These should be discussed in relation to the data obtained through this research project.
• The study identified the threshold effect (Hypothesis 3) and interpreted it as necessitating a 'differentiated regional policy'. However, it did not propose specific threshold values for decision-making, a matter which requires further discussion and explanation.

Conclusions.

• It is advisable that conclusions should be shorter and more closely aligned with the empirical findings. The mediation and threshold findings should be interpreted more carefully.

References.

• The bibliography is short. It is recommended that recent research on this topic be included.

 

• Minor comments: Problems with language and style - it is advisable to avoid long sentences and complex phrasing.

 

• Conclusion and suggestions for improvement:

The manuscript overlaps significantly with several recent publications. However, I believe that if the authors can address the existing gaps and enhance the originality and scientific conclusions of their research, it should be published.

Comments on the Quality of English Language

 It is advisable to avoid long sentences and complex phrasing.

Author Response

Comment 1：The title of the manuscript should be shortened and revised. The title should not contain the construction “Research on…”. The phrase “Dual Examination Based on Mediation Effect…” is poorly formulated. Since the study was conducted for China, this should be clearly stated in the title. For example: “New-Quality Marine Productive Forces and High-Quality Development of the Marine Economy in China: Mediating Mechanisms and Threshold Effect”.

Response 1: Many thanks for the reviewer’s suggestions. We have revised the title of this paper in accordance with your advice. The new title is: ‘New-Quality Marine Productive Forces and High-Quality Development of the Marine Economy in China: Mediating Mechanisms and Threshold Effect’ (English version: New-Quality Marine Productive Forces and High-Quality Development of the Marine Economy in China: Mediating Mechanisms and Threshold Effect). This title has been included on the first page of the manuscript.

Comment 2：It is important to note that the structure of the manuscript must follow the journal's rules and include the sections: “Introduction,” “Materials and Methods,” “Results,” “Discussion,” and “Conclusions.” Currently, the material is confusing.

Response 2: Thank you very much for your feedback! The full text has been reorganised in accordance with the journal’s requirements. The revised manuscript comprises the following sections: Chapter 1 is the Introduction; Chapter 2 covers Theoretical Analysis and Research Hypotheses; Chapter 3 covers Research Methods; and Chapter 4, comprising Variable Definitions and Data Description, forms part of the Materials and Methods section; Chapter 5 is the Results section; Chapter 6 is the Discussion section; and Chapter 7 is the Conclusions section.

Comment 3：Do the authors know about the new studies on this topic that have been published recently? It would be beneficial if the authors could discuss this recent study at Introduction and Discussion. ... So, the novelty of the research should be better highlighted. The concept of “New-Quality Marine Productive Forces” should be explained more. It's important to explain all the terms, highlight why the research is new and important, and finish with the main goal of the study. It would also be useful to justify why these specific study regions were selected.

Response 3: We thank the reviewer for their suggestion. We have now included and discussed three recent publications in the introduction: Gao et al. (2025), Yao et al. (2026) and Yi et al. (2025). Furthermore, a clear definition of ‘new marine productive forces’ has been added to the introduction, and its characteristics have been elaborated upon from three perspectives. Additionally, Section 2.1 explains the rationale for selecting 11 coastal provinces: these provinces account for over 95% of the national marine economic output, cover the three major marine economic zones, and exhibit significant regional heterogeneity.

Comment 4：The Methods section should include a map of the study area, which covers 11 provinces. The paper should also provide a table with the main characteristics of the study regions. ... The authors define the concept of «new-quality maritime productive forces» (MNQP) as the classical three-part framework... The indicators used in Table 2 seem to show progress in technology and digitalisation at the regional economy level, rather than the specific idea of “new quality” in the marine sector. This section needs to be made much stronger or provide a detailed explanation in the following sections.

Response 4: Thank you very much for your feedback! In accordance with your suggestion, we have added maps of the study area (Figures 1 and 2) and a table of regional characteristics (Table 1) to the paper, and have included the spatio-temporal distribution map of high-quality development in the marine economy in Section 2.1.2, ‘Spatial Distribution of High-Quality Development in the Marine Economy’. Table 1 summarises the average values for per capita GDP (logarithmic), MNQP and HQD-ME for the 11 provinces over the period 2013–2022. Furthermore, in Section 2.3.2, the paper explicitly states that certain indicators within the index system reflect the overall technological level of the region and explains the rationale for this (constraints on data availability, precedents in existing research, robustness tests, etc.).

Comment 5：The sample size is very small (N=110), yet the manuscript makes overly strong claims. ... Endogeneity: In the baseline regression, the issue of reverse causality is not dealt with. ... The interpretation of EDU is also not justified. ... The text says that the threshold variable is the economic development level, but Table 9 refers to “the Level of High-quality Development in the Marine Economy”. This should be written the same way throughout the manuscript: threshold variable = economic development level (EDL). ... In Table 9, the threshold values (γ₁ = 11.1171 and γ₂ = 11.1221) are almost identical. ... The data reported in Table 10 should be checked carefully, as there appear to be typos or numerical errors.

Response 5: Thank you very much for your comments! We address each point as follows: (1) Small sample size and overconfidence: We have systematically toned down the language throughout the paper, replacing ‘significantly promotes’ with ‘positively associated with’, and removing phrases such as ‘highly independent’ and ‘not driven by other factors’.Furthermore, we have explicitly noted the limitations of the sample size at the end of Section 2.5 and in Section 4.5, interpreting the results as evidence of correlation. (2) Regarding the issue of endogeneity, Section 3.3.3 has been added to the paper to include an endogeneity test, employing a re-regression using the one-period lagged MNQP (Table 10), with robust results. Furthermore, the limitations of reverse causality have been candidly acknowledged in the discussion. (3) Regarding the interpretation of EDU, speculative statements such as “may stem from structural differences” have been removed, retaining only the statement that “the coefficient is negative but not significant”. (4) Regarding the inconsistency in the names of threshold variables, the paper has standardised the name of the threshold variable in Table 9 to ‘Economic Development Level (EDL)’. (5) Regarding the typographical error in Table 10, the paper has corrected ‘MNQP(EDL＞0.180)’ in Table 10 to ‘MNQP(EDL＞11.1221)’.

Comment 6：Discussion and Conclusions should be separated. This section should contain an academic discussion and references to similar works, especially those published in recent years. ... The study identified the threshold effect (Hypothesis 3) and interpreted it as necessitating a ‘differentiated regional policy’. However, it did not propose specific threshold values for decision-making, a matter which requires further discussion and explanation.

Response 6: Thank you very much for your feedback! We have now separated the discussion and conclusions into two distinct chapters (Chapter 4: Discussion; Chapter 5: Conclusions). In Chapter 4, we have incorporated an academic dialogue with Gao et al. (2025), Yi et al. (2025) and Yao et al. (2026) (see Sections 4.1, 4.2 and 4.3), and in Section 4.3 we have provided a detailed explanation of the non-linear nature of the threshold effect and its policy implications. Furthermore, in Chapter 5 (Conclusions), this paper no longer relies on specific threshold values but instead classifies coastal provinces into three categories based on per capita GDP levels, thereby proposing actionable policy recommendations.

Comment 7：It is advisable that conclusions should be shorter and more closely aligned with the empirical findings. The mediation and threshold findings should be interpreted more carefully.

Response 7: Thank you very much for your feedback! We have significantly streamlined the conclusions in Chapter 5, retaining only three key findings. Each finding is closely tied to the empirical results, and we have taken care to avoid over-interpretation. Furthermore, we have explicitly stated in the conclusions that the two threshold estimates are very close, and that caution should be exercised when interpreting the specific figures.

Comment 8：The bibliography is short. It is recommended that recent research on this topic be included.

Response 8: Thank you very much for your feedback! We have added three recent relevant studies to the reference list: Gao et al. (2025), Yao et al. (2026) and Yi et al. (2025), which have been assigned reference numbers 22, 23 and 24 respectively. These studies are cited and discussed in both the Introduction and Discussion sections.

Comment 9：Problems with language and style - it is advisable to avoid long sentences and complex phrasing.

Response 9: Thank you very much for your feedback! We have now edited the text to improve its clarity, breaking up long sentences into shorter ones and simplifying complex phrasing.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript examines the impact of marine new-quality productive forces on high-quality development of the marine economy using panel data from 11 Chinese coastal provinces (2013-2022). While the topic aligns with current policy priorities in China, the study suffers from several methodological and conceptual deficiencies that undermine its academic contribution.

The theoretical framework lacks originality, essentially transplanting the generic "new-quality productive forces" concept into the marine context without developing distinct theoretical mechanisms specific to marine economic characteristics. The three-dimensional analytical framework (laborers, labor materials, labor objects) remains abstract and fails to capture the unique spatial attributes, ecological constraints, and resource dependencies that differentiate marine economic activities from terrestrial ones. The hypothesized relationships are largely descriptive rather than derived from rigorous theoretical modeling, with Hypothesis 1 stating an obvious positive correlation without specifying the transmission channels or boundary conditions. The mediation mechanism through marine scientific and technological innovation is conceptually plausible but empirically underdeveloped—the measurement of marine S&T innovation using only R&D expenditure ratio oversimplifies a complex multi-stage innovation process involving basic research, applied development, and commercialization.

The empirical design reveals critical weaknesses in variable construction and model specification. The dependent variable (high-quality marine economic development) is measured through an entropy-weighted composite index spanning 25 indicators across five dimensions, yet this aggregation masks the heterogeneous performance across innovation, coordination, green development, openness, and sharing dimensions. The core explanatory variable (marine new-quality productive forces) similarly conflates distinct elements—human capital, industrial structure, digital infrastructure, and environmental factors—into a single index, making it impossible to identify which specific components drive the observed effects. The threshold regression results are particularly problematic: the two estimated threshold values (11.0838 and 11.1221) are implausibly close (difference of merely 0.0383 in log per capita GDP terms), suggesting potential model misspecification or data artifacts rather than genuine structural breaks. The coefficient for the high-development regime (0.1191) becomes statistically weaker (p=0.081) compared to the middle regime (0.1996, p=0.004), contradicting the claimed "nonlinear enhancement" pattern.

The robustness checks fail to address fundamental endogeneity concerns. The study acknowledges no reverse causality between marine economic quality and productive force development, nor does it account for spatial autocorrelation among coastal provinces despite obvious geographic and economic interdependencies. The replacement of weighting methods (entropy vs. entropy-TOPSIS) represents a superficial robustness test when the underlying indicator selection and measurement validity remain questionable. The Winsorization treatment at 1% levels is inadequate given the small sample size (N=110), and the persistence of significance does not validate causal identification when the baseline model likely suffers from omitted variable bias and simultaneity issues.

The policy implications drawn from the threshold effects are misleading given the empirical anomalies. The recommendation for "differentiated regional policies" based on thresholds that are statistically indistinguishable lacks practical operational value. The study also fails to address why the promoting effect weakens at higher development levels—a finding that contradicts the theoretical expectation of increasing returns to innovation-driven productivity. The temporal scope (2013-2022) captures only the pre-COVID and early pandemic periods, missing the accelerated digital transformation and green transition dynamics post-2022 that are central to the "new-quality productive forces" concept. Overall, the paper contributes limited new knowledge to the extensive literature on marine economy development and innovation-driven growth, with its empirical findings likely reflecting methodological artifacts rather than robust causal relationships.

Author Response

Comment 1：The theoretical framework lacks originality, essentially transplanting the generic “new-quality productive forces” concept into the marine context without developing distinct theoretical mechanisms specific to marine economic characteristics. The three-dimensional analytical framework (laborers, labor materials, labor objects) remains abstract and fails to capture the unique spatial attributes, ecological constraints, and resource dependencies that differentiate marine economic activities from terrestrial ones.

Response 1: Thank you very much for your feedback. We sincerely accept this criticism. Based on the Marxist theory of the three elements of productive forces, this paper constructs an evaluation framework for new-quality marine productive forces from three dimensions: new types of workers, new types of means of production, and new types of objects of labour. The evaluation indicator systems for new-quality marine productive forces (Table 2) and high-quality development of the marine economy (Table 1) presented in this paper reflect the unique characteristics of the marine industry in the following aspects: (1) In the dimension of new types of workers, indicators specifically targeting marine talent have been established, such as ‘the number of university students majoring in marine disciplines’ and ‘the proportion of master’s and doctoral degree holders among marine researchers’; (2) In the dimension of new objects of labour, indicators have been established that reflect the dual attributes of marine resource development and ecological conservation, such as ‘proportion of strategic emerging industries’, ‘coverage rate of marine nature reserves’ and ‘volume of industrial wastewater discharged directly into the sea per unit of marine industrial GDP’; (3) In the dimension of new means of labour, indicators have been established that reflect the characteristics of marine scientific and technological innovation, such as ‘number of marine patents granted’ and ‘R&D expenditure of marine research institutions’.

Comment 2：The hypothesized relationships are largely descriptive rather than derived from rigorous theoretical modeling, with Hypothesis 1 stating an obvious positive correlation without specifying the transmission channels or boundary conditions.

Response 2: Thank you to the reviewer for their feedback. This paper has substantially refined the theoretical derivation of Hypothesis 1. In Section 2.1, the paper no longer merely states the positive impact, but systematically elaborates on the transmission channels through which new-quality marine productive forces influence the high-quality development of the marine economy from three dimensions: firstly, the skills leap of new-type workers, which provides human capital support by enhancing labour productivity and innovation efficiency; secondly, the intelligent upgrading of new-type means of production, which drives the green transformation of industries by improving production precision and resource utilisation efficiency; thirdly, the in-depth expansion of new objects of labour, which creates new growth points by developing deep-sea resources and fostering emerging business models. Based on this logical deduction, Hypothesis 1 has been revised accordingly to read: “New-quality productive forces in the marine sector exert a significant positive influence on the high-quality development of the marine economy”.

Comment 3：The mediation mechanism through marine scientific and technological innovation is conceptually plausible but empirically underdeveloped—the measurement of marine S&T innovation using only R&D expenditure ratio oversimplifies a complex multi-stage innovation process involving basic research, applied development, and commercialization.

Response 3: Thank you very much for your feedback! The paper acknowledges this limitation and has added a note in Section 2.3.3 stating that marine science and technology innovation is a complex, multi-stage process encompassing basic research, applied development and the commercialisation of results; the indicator of R&D expenditure as a percentage of GDP used in this paper is a simplified proxy variable due to data availability constraints. Furthermore, the paper candidly addresses this limitation in the discussion section and suggests that future research should employ more comprehensive innovation indicators to validate these findings.

Comment 4：The dependent variable (high-quality marine economic development) is measured through an entropy-weighted composite index spanning 25 indicators across five dimensions, yet this aggregation masks the heterogeneous performance across innovation, coordination, green development, openness, and sharing dimensions. The core explanatory variable (marine new-quality productive forces) similarly conflates distinct elements—human capital, industrial structure, digital infrastructure, and environmental factors—into a single index, making it impossible to identify which specific components drive the observed effects.

Response 4: We are very grateful to the reviewer for raising this crucial point. To reveal heterogeneity across different dimensions, we have added a section titled ‘Further Analysis’ (Table 7) in Section 3.2 of this paper, in which we decompose high-quality development of the marine economy into five sub-dimensions (innovation, coordination, green development, openness and shared benefits) and re-run the regression analysis with each of these as the dependent variable.

Comment 5：The threshold regression results are particularly problematic: the two estimated threshold values (11.0838 and 11.1221) are implausibly close (difference of merely 0.0383 in log per capita GDP terms), suggesting potential model misspecification or data artifacts rather than genuine structural breaks. The coefficient for the high-development regime (0.1191) becomes statistically weaker (p=0.081) compared to the middle regime (0.1996, p=0.004), contradicting the claimed “nonlinear enhancement” pattern.

Response 5: Thank you very much for your feedback! We sincerely accept the reviewers’comments. In the revised manuscript, we have made the following adjustments: (1) We have explicitly stated in the relevant section that the two threshold estimates are very close, which may reflect a continuous, smooth non-linear relationship rather than a strictly discrete structure; therefore, caution should be exercised when interpreting the specific threshold values. (2) In the abstract and conclusions, we have amended the term ‘non-linear enhancement’ to ‘a non-linear pattern characterised by an initial increase followed by a levelling off’ to accurately describe the actual findings. (3) In the discussion section (Chapter 4, point (3)), we have provided a further analysis of the reasons for the decline in coefficients during the high-development stage.

Comment 6：The robustness checks fail to address fundamental endogeneity concerns. The study acknowledges no reverse causality between marine economic quality and productive force development, nor does it account for spatial autocorrelation among coastal provinces despite obvious geographic and economic interdependencies. The replacement of weighting methods (entropy vs. entropy-TOPSIS) represents a superficial robustness test when the underlying indicator selection and measurement validity remain questionable. The Winsorization treatment at 1% levels is inadequate given the small sample size (N=110), and the persistence of significance does not validate causal identification when the baseline model likely suffers from omitted variable bias and simultaneity issues.

Response 6: Thank you very much for your feedback! We have now included an endogeneity test in the paper and re-run the baseline regression using the one-period lagged Marine New Quality Productivity (L.MNQP) in place of the current-period MNQP. The results indicate that the coefficient for L.MNQP remains significantly positive, consistent with the findings of the baseline regression, suggesting that the impact of reverse causality on the research results is relatively limited. Furthermore, the paper explicitly acknowledges the limitation of the small sample size. Regarding spatial autocorrelation, the paper lists this as a direction for future research in the discussion section and recommends the introduction of spatial econometric models in subsequent studies.

Comment 7：The sample size is very small (N=110), yet the manuscript makes overly strong claims. Phrases such as “strongly supports Hypothesis 1”, “highly independent”, and “not driven by other factors” should be removed. A regression with this set of controls does not prove that the effect is independent of “other factors”; it only shows that the effect remains after controlling for the observed variables included in that particular specification.

Response 7: Thank you very much for your feedback! In the revised version, we have systematically corrected any overly strong statements throughout the paper. For example, we have changed ‘highly independent’ to ‘still significant after controlling for other variables’, and ‘strongly supports the hypothesis’ to ‘provides empirical support for the hypothesis’. Specific revisions can be found in Sections 3.1 and 3.2, as well as in the Conclusions section of Chapter 5. Furthermore, the issue of sample size limitations has been addressed in the section on research limitations.

Comment 8：The policy implications drawn from the threshold effects are misleading given the empirical anomalies. The recommendation for “differentiated regional policies” based on thresholds that are statistically indistinguishable lacks practical operational value. The study also fails to address why the promoting effect weakens at higher development levels—a finding that contradicts the theoretical expectation of increasing returns to innovation-driven productivity.

Response 8: Thank you for the reviewer’s comments. The policy recommendations section has been removed from this paper. We have also discussed the reasons why the promotional effect may diminish at higher levels of development.

Comment 9：The temporal scope (2013-2022) captures only the pre-COVID and early pandemic periods, missing the accelerated digital transformation and green transition dynamics post-2022 that are central to the “new-quality productive forces” concept.

Response 9: Thank you very much for your feedback! The paper acknowledges this limitation. In Section 2.4, the paper provides further explanation as to why the period 2013–2022 was selected as the study window: 2013 was the year in which the ‘Maritime Power’ strategy was formally proposed, after which the statistical scope for the maritime economy became more standardised; 2022 represents the latest complete annual data available. Furthermore, this paper explicitly addresses this issue in Section 4(5) ‘Limitations’ and suggests that future research should extend the study period once data becomes available, in order to capture the policy effects following the formal introduction of the concept of ‘new-quality productive forces’.

Comment 10：Overall, the paper contributes limited new knowledge to the extensive literature on marine economy development and innovation-driven growth, with its empirical findings likely reflecting methodological artifacts rather than robust causal relationships.

Response 10: Thank you very much for your feedback! Following this round of revisions, we have included sub-dimension regression and endogeneity tests in the paper, and have carefully toned down the language. Thank you once again for your valuable feedback.

 

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I would like to express my gratitude to the authors for their comprehensive responses to my comments and for the significant revisions they have made to the manuscript. It is important to note that the manuscript is of considerable scientific interest and merits publication. There are a few minor typographical errors and inaccuracies that should be corrected without detracting from the value of the work.

1. I suggest giving this section "5" a simple title: 5.Results. This will mean you can remove the word 'results' from the subsections: 5.1. Analysis of the Evaluation Index... etc. (lines 536, 674…).
2. The section numbers for section 4.3. are repeated (lines 496 and 509).
3. General information regarding the years, study areas and software used should be provided in the Materials and Methods. This information does not need to be repeated in the Results section (lines 610–611), (643–644) and 832.
4. The Discussion section is both interesting and informative, but there is a lack of references to similar studies. It is essential that the discussion includes a comparison of the authors' own research findings with those of similar studies. This will provide a solid foundation for the conclusions.

Author Response

Comment 1：I suggest giving this section "5" a simple title: 5. Results. This will mean you can remove the word 'results' from the subsections: 5.1. Analysis of the Evaluation Index... etc. (lines 536, 674…).

Response 1: Thank you very much for your suggestion. We have changed the heading of Section 5 to ‘5 Results’. We have also removed the word ‘results’ from all subheading titles.

Comment 2：The section numbers for section 4.3. are repeated (lines 496 and 509).

Response 2: Thank you very much for your feedback; the article has been amended accordingly.

Comment 3: General information regarding the years, study areas and software used should be provided in the Materials and Methods. This information does not need to be repeated in the Results section (lines 610–611), (643–644) and 832.

Response 3: We agree. We have removed the redundant information from the Results section. Specifically: （1）In Section 5.1.2, we deleted “This study selected 2013 and 2022 as representative years and used ArcGIS 10.8 software” and kept only the figure descriptions. （2）In Section 5.1.3, we made a similar deletion. （3）In Section 5.2.1, we removed the mention of STATA 18.0 software and kept only the methodological steps. （4）In Section 5.4, we removed “STATA 17.0 software”.

Comment 4：The Discussion section is both interesting and informative, but there is a lack of references to similar studies. It is essential that the discussion includes a comparison of the authors' own research findings with those of similar studies. This will provide a solid foundation for the conclusions.

Response 4: We greatly appreciate this suggestion. This paper have substantially enriched the Discussion section by adding comparisons with relevant recent studies. Specifically:0（1）In Section 6.1, we added a comparison with Gao et al. and Yi et al., highlighting the synergistic amplifying effect of fiscal support and openness. （2）In Section 6.2, we contrasted our weak mediating effect of marine technology innovation with the significant mediating effect of green technology innovation found by Yi et al., and also cited Wei et al. regarding the digital economy as a potential alternative pathway. （3）In Section 6.3, we discussed the similarities and differences between our nonlinear threshold effect and that of Yi et al., and compared our low-development-stage result with Gao et al. on economic resilience. （4）In Section 6.4, we noted the consistency of our regional disparity findings with those of Gao et al. on the spatial distribution of China’s three major marine economic zones.

Author Response File: Author Response.docx