Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I am presenting my comments on the article titled: An Empirical Study on the Impact of Public Data Openness on High-Quality Regional Economic Development: Data from China's 31 Provinces.

1. Introduction:

The authors did not identify a research gap and did not pose any research questions. I would personally ask research questions related to hypotheses H1:H3. Finding answers to research questions should be the goal of the article. Authors should also clearly state this goal in the introduction.

2. Hypothesis development:

Theoretical analysis framework diagram is drawn incorrectly. Mediation analysis requires three variables, and four variables appear in the diagram (figure1) . I would personally draw two diagrams: 1) PDO+ Envir+ REHQD (with H1 and H2) , and 2) PDO+ Alloca+ REHQD (with H1 and H3). Such two diagrams would well reflect the idea of ​​the mediation analysis that the authors planned to perform. The current diagram in Figure 1 is misleading to the reader.

3.Research Design:

3.1. The authors did not provide all the steps in the mediation analysis. The third step is missing: REHQDLit = α+β1 PDOit + β2 Mit φ1 Controlsit + μi + ε1it

3.2. Personally, I would add the model with the control variables to the appendix as a digression.

4. Results.

4.1. In my opinion, the authors only verified hypothesis 1. 4.2. The authors did not verify hypothesis 2 and hypothesis 3 because they did not complete the mediation analysis. In the table contained in rows 560-563 the authors showed (in two separate models) that PDO is a significant predictor of Envir and a significant predictor of Alloca. Demonstrating this is a condition for the existence of mediation but does not prove it. There is a lack of models such as 1) REHQDL~PDO+Envir and 2) REHQDL~PDO+Alloca. Only the analysis of these two models will complete the mediation analysis and allows for the verification of hypothesis 2 and hypothesis 3. Of course, the authors could also calculate these models with control variables to continue the ideas from the previous analyses. However, I personally would treat this as a digression and put the models with control variables in the appendix.

4.2. When interpreting the results of mediation analysis, authors should calculate: 1) ACME (Average Causal Mediation Effect, ACME = a*b), 2) ADE (Average Direct Effect, ADE=c’), 3) Total Effect (ACME+ADE), 4) Proportion Mediated (ACME/Total effect). Explanation: a, b and c' are the coefficients from the regression models involved in the mediation analysis. Authors should become familiar with the mediation analysis procedure and learn how to read the a, b and c' coefficients.

4.3. In my opinion, the table in rows 594-596 is unnecessary and confusing. Earlier, the authors explain that REHQDL is a dependent variable calculated from four indicators. Alternatively, this table could be included in the attachment as a digression.

5. Discussion:

The discussion should be adapted to the results related to the mediation analysis (we do not know these results yet, because the mediation is incomplete). The results should be commented on in the context of the literature analysis.

Author Response

1.The authors did not identify a research gap and did not pose any research questions. I would personally ask research questions related to hypotheses H1:H3. Finding answers to research questions should be the goal of the article. Authors should also clearly state this goal in the introduction.

Response:

We sincerely thank the reviewer for this valuable suggestion. Indeed, clarifying the research gap and formulating precise research questions are crucial for establishing a study's theoretical contribution. While existing literature has recognized public data openness (PDO) as a potential driver of economic development (Cai et al., 2024; Xiong et al., 2023), and reports highlight the varying levels of PDO implementation across China (Fudan University, 2024), critical gaps remain. First, most studies focus on macro-level outcomes like entrepreneurial vitality (Cai et al., 2024) or enterprise innovation (Chen & Jiang, 2024), leaving the underlying mechanisms—how PDO translates into broader, high-quality economic development (REHQDL)—largely unexplored (Wang et al., 2025; Fang et al., 2023). Second, the specific pathways through which PDO influences resource allocation efficiency (Alloca) and environmental regulation (Envir), two pivotal dimensions of high-quality development (Yu & Wu, 2023; Zhao, 2024), are not sufficiently theorized or tested.

To address these gaps, our study situates itself within the evolving discourse on data-driven development (Nikiforova, 2021; Zhang et al., 2021). We have substantially revised the Introduction to explicitly frame this research gap. Specifically, we now pose the following research questions (RQs), which are directly aligned with our hypotheses H1–H3:

RQ1: What is the direct effect of PDO on REHQDL?

RQ2: Does business environment optimization mediate the relationship between PDO and REHQDL?

RQ3: Does facctor allocation efficiency (Alloca) mediate the relationship between PDO and REHQDL?

Addressing these RQs constitutes the primary objective of this study. By doing so, we move beyond establishing a mere correlation and delve into the causal mechanisms, thereby providing a more nuanced understanding of how PDO contributes to sustainable and high-quality economic outcomes, as called for by recent research (Guo et al., 2024; Xu et al., 2025).

2. Theoretical analysis framework diagram is drawn incorrectly. Mediation analysis requires three variables, and four variables appear in the diagram (figure1). I would personally draw two diagrams: 1) PDO+ Envir+ REHQDL (with H1 and H2), and 2) PDO+ Alloca+ REHQDL (with H1 and H3). Such two diagrams would well reflect the idea of the mediation analysis that the authors planned to perform. The current diagram in Figure 1 is misleading to the reader.

Response:

We appreciate your insightful observation. Following your suggestion, we have redrawn the theoretical framework and now present it as two separate diagrams.This adjustment accurately reflects the mediation analysis design and avoids potential misunderstanding caused by the previous four-variable model.

3. The authors did not provide all the steps in the mediation analysis. The third step is missing: REHQDLit = α+β1 PDOit + β2 Mit + φ1 Controlsit + μi + ε1it

Response:

Thank you for pointing this out. We have now added the third-step regression model in the 4.1 Model Specification section.This ensures that the mediation analysis procedure is now complete and transparent.

4. Personally, I would add the model with the control variables to the appendix as a digression.

Response:

Thank you for your valuable suggestions. We fully concur with your perspective and have incorporated the model incorporating control variables as supplementary material in Appendix 1.

4.1 In my opinion, the authors only verified hypothesis 1. The authors did not verify hypothesis 2 and hypothesis 3 because they did not complete the mediation analysis. In the table contained in rows 560-563 the authors showed (in two separate models) that PDO is a significant predictor of Envir and a significant predictor of Alloca. Demonstrating this is a condition for the existence of mediation but does not prove it. There is a lack of models such as 1) REHQDL~PDO+Envir and 2) REHQDL~PDO+Alloca. Only the analysis of these two models will complete the mediation analysis and allows for the verification of hypothesis 2 and hypothesis 3. Of course, the authors could also calculate these models with control variables to continue the ideas from the previous analyses. However, I personally would treat this as a digression and put the models with control variables in the appendix.

Response:

We sincerely appreciate your detailed and constructive feedback. In response, we have now conducted the complete mediation analysis. The results of these models have been added to the 5.3 Mechanism Analysis section, enabling full verification of hypotheses H2 and H3. Models including control variables have been moved to the Appendix, as per your recommendation. Models including control variables have been moved to the Appendix, as per your recommendation.

4.2 When interpreting the results of mediation analysis, authors should calculate: 1) ACME (Average Causal Mediation Effect, ACME = a*b), 2) ADE (Average Direct Effect, ADE=c’), 3) Total Effect (ACME+ADE), 4) Proportion Mediated (ACME/Total effect). Explanation: a, b and c' are the coefficients from the regression models involved in the mediation analysis. Authors should become familiar with the mediation analysis procedure and learn how to read the a, b and c' coefficients.

Response:

Thank you for this valuable and precise suggestion. We have now calculated and reported the ACME, ADE, Total Effect, and Proportion Mediated. The results and their interpretation have been added to the 5.3 Mechanism Analysis section, strengthening the methodological rigor of our mediation analysis.

4.3 In my opinion, the table in rows 594-596 is unnecessary and confusing. Earlier, the authors explain that REHQDL is a dependent variable calculated from four indicators. Alternatively, this table could be included in the attachment as a digression.

Response:

We are most grateful for your constructive suggestions. The four-dimensional differentiated regression analysis of regional economic high-quality development through public data openness provides supplementary empirical evidence that is both multidimensional and concrete for the core research hypothesis of this paper. This further enhances the persuasiveness of the research conclusions and their practical implications. Following thorough discussion among the three authors, we hope to retain this table.

5. The discussion should be adapted to the results related to the mediation analysis (we do not know these results yet, because the mediation is incomplete). The results should be commented on in the context of the literature analysis.

Response:

Thank you for this valuable advice. We have thoroughly revised the Discussion section to align it with the updated mediation analysis results. The revised discussion integrates the new empirical findings and interprets them in light of the literature, providing a more coherent theoretical and practical contribution.

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript employs the CRITIC weighting method, mediation analysis, and other empirical techniques to examine how public data openness affects high-quality regional economic development; while introducing the “resource–asset–capital” evolutionary pathway and using factor allocation efficiency as a mediating variable shows a degree of innovation, there are notable issues in research design, logical coherence, and methodological detail. The main comments are as follows:

Major:

1. The measurement of variables is insufficiently transparent; the specific computational steps of the CRITIC method and the logic used to determine the weights are not clearly described, undermining methodological reproducibility and the credibility of the findings.

2. The mediating variable “factor allocation efficiency” is measured as the reciprocal of market distortion; the theoretical grounding is inadequate, and the economic meaning and plausibility of this inverse relationship are not clearly explained.

3. The selection of control variables (e.g., tax level, government size) lacks articulation of the underlying theoretical mechanisms; the linkage with the core variables—expected directions and channels of influence—remains insufficiently specified.

4. In the robustness checks, the “truncation” procedure does not report the truncation proportion or the rationale for its choice, limiting the verifiability of the robustness claims.

5. The mechanism analysis only establishes the presence of a mediation effect without decomposing the relative magnitudes or contribution shares of direct versus indirect effects, which weakens the explanatory power of the proposed pathways.

Minor:

1. Academic English usage is nonstandard in places; for example, the opening background employs “Facing the background…,” which is not idiomatic in scholarly writing.

2. Redundancy and weak logical linkage occur in the theoretical framework; the construction “combined… to investigate” yields a loose argumentative chain.

3. Inconsistencies exist between table numbering and in-text citations; for instance, the text states “…with results showed in Table 3,” while the corresponding table is titled “Table 1. Robustness test results,” indicating a mismatch.

4. Punctuation and typesetting are irregular: mixing Chinese and English punctuation, failure to capitalize the first letter after a colon, and missing spaces after punctuation; a unified language and formatting check across the manuscript is advisable.

5. Tense usage in the abstract is inappropriate in places—for example, using the past tense “showed” instead of the conventional present “show.”

6. It is not recommended to list method-centric terms such as “Benchmark regression” as keywords; keywords should foreground the core substantive content of the study.

     

Author Response

1.The measurement of variables is insufficiently transparent; the specific computational steps of the CRITIC method and the logic used to determine the weights are not clearly described, undermining methodological reproducibility and the credibility of the findings.

Response:

  Thank you for pointing out this important issue. We have added a detailed description of the CRITIC weighting method, including the formulae, computational steps, and the rationale for determining indicator weights. These details are now presented in the 4.3. CRITIC Method for Determining Indicator Weights, which improves methodological transparency and reproducibility.

2.The mediating variable “factor allocation efficiency” is measured as the reciprocal of market distortion; the theoretical grounding is inadequate, and the economic meaning and plausibility of this inverse relationship are not clearly explained.

Response:

Thank you for your suggestion. In Section 4.2, ‘Variable Selection,’ we have applied the neoclassical growth theory and factor misallocation model (Huang et al.,2022;Xu et al.,2025), demonstrating that market distortions within factor misallocation lead to declines in total factor productivity, thereby impeding high-quality economic development. Consequently, a lower degree of market distortion inherently signifies more efficient resource allocation. This explicit inverse relationship provides direct theoretical justification for employing the reciprocal of market distortion as an effective and meaningful proxy indicator for factor allocation efficiency.

3.The selection of control variables (e.g., tax level, government size) lacks articulation of the underlying theoretical mechanisms; the linkage with the core variables—expected directions and channels of influence—remains insufficiently specified.

Response:

Thank you for your valuable suggestion. We have revised the 4.2. Variable Selection section to include detailed explanations for each control variable, clarifying their theoretical linkage with the core explanatory and dependent variables. This addition specifies the expected influence direction and the underlying economic mechanisms.

4.In the robustness checks, the “truncation” procedure does not report the truncation proportion or the rationale for its choice, limiting the verifiability of the robustness claims.

Response:

Thank you for your reminder. We have now specified that we winsorized all continuous variables at the 1st and 99th percentiles to mitigate the impact of extreme values, which is a conventional approach in the econometrics literature. This detail has been added to the robustness check section.

5.The mechanism analysis only establishes the presence of a mediation effect without decomposing the relative magnitudes or contribution shares of direct versus indirect effects, which weakens the explanatory power of the proposed pathways.

Response:

Thank you for this valuable and precise suggestion. We have now calculated and reported the ACME, ADE, Total Effect, and Proportion Mediated. The results and their interpretation have been added to the 5.3 Mechanism Analysis section, strengthening the methodological rigor of our mediation analysis.

Minor Issues

1.Academic English usage is nonstandard in places; for example, the opening background employs “Facing the background…,” which is not idiomatic in scholarly writing.

Response:

We have carefully reviewed and revised the entire manuscript for academic English style and idiomatic expression. Phrases such as “Facing the background…” have been replaced with more standard scholarly wording

2.Redundancy and weak logical linkage occur in the theoretical framework; the construction “combined… to investigate” yields a loose argumentative chain.

Response:

Thank you for this suggestion. We have streamlined the theoretical framework section by removing redundant expressions and rephrasing sentences to enhance logical flow and argumentative coherence.

3.Inconsistencies exist between table numbering and in-text citations; for instance, the text states “…with results showed in Table 3,” while the corresponding table is titled “Table 1. Robustness test results,” indicating a mismatch.

Response:

We appreciate your careful review. We have corrected all inconsistencies between the in-text references and table numbering to ensure accuracy throughout the manuscript.

4.Punctuation and typesetting are irregular: mixing Chinese and English punctuation, failure to capitalize the first letter after a colon, and missing spaces after punctuation; a unified language and formatting check across the manuscript is advisable.

Response:

We have standardized all punctuation, capitalization, and spacing throughout the manuscript, ensuring consistent use of English punctuation and proper formatting.

5.Tense usage in the abstract is inappropriate in places—for example, using the past tense “showed” instead of the conventional present “show.”

Response:

Thank you for this observation. We have revised the abstract to consistently use the present tense, as is standard in academic writing, replacing past forms such as “showed” with “show.”

6.It is not recommended to list method-centric terms such as “Benchmark regression” as keywords; keywords should foreground the core substantive content of the study.

Response:

Thank you for your suggestion. We have modified the keyword list and removed methodological terms .

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors did a very good job of improving the article. They completed the analysis of mediation in an exemplary manner and interpreted it well. They also refined the introduction of the article by providing research questions that now perfectly correspond to the analyses conducted. The discussion of the obtained results has also been significantly improved.

I really like this work now. Congratulations to the authors!

Reviewer 2 Report

Comments and Suggestions for Authors

All my suggestions have been fully addressed and are recommended for acceptance.