County Town Comprehensive Service Functions in China: Measurement, Spatio-Temporal Divergence Evolution, and Heterogeneity of Influencing Factors
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsDear authors.
The topic of the manuscript is interesting.
The conducted research indicates the problem of uneven regional development in China.
The discussion and conclusions lack in references to the theory of regional development. The Authors do not attempt to compare the results of their research to other research or to the theory. The manuscript only represents research results, and this is insufficient.
Best regards
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper analyzes the spatial and temporal patterns and differentiation mechanisms of comprehensive service functions of county towns in China, which can provide a basis for the macro-control of county towns, and provide typical regional research results for the study of urban systems and urban-rural coordination in developing countries. However, the author could improve the quality from the following aspects:
1. The quality of English writing must be improved to be more academic.
2. Discussion is the contribution of your research, not conclusion.
3. Figure and table should be more clear, for example, there are no labels on Figure 3 to distinguish year 2012 and 2022.
4. Some titles are too long, 4.2 in line 353-355
Comments on the Quality of English LanguageThe English writing must be improved, for example, "From the viewpoint of the experience of town construction in developed countries, whether it is the development model of European countries, which is based on small towns, or the model of the United States, Japan, and Korea, which is based on large cities and promotes the development of small towns in a balanced way, it has been fully proven that giving importance to the construction of service functions in small towns is an inevitable choice for promoting the urban-rural integration and the healthy and sustainable development of urbanization (Abdolmatin et al., 2016; Paul et al., 2007; Powe, 2004)." in line 42-49, I cannot understand what you want to express.
"Furthermore, it conducts an empirical study of factors affecting the improvement of comprehensive service functions of county towns. " in line 489-490, it should be modified to be we.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsOverall Comment
Overall, the article provides a comprehensive analysis of the service function of small towns, particularly county towns, in China. However, several points could be criticized or improved:
1. Clarity and Structure: The article could benefit from a clearer structure. It jumps straight into discussing the analysis methods and results without providing sufficient context or introducing the problem statement and objectives.
2. Data and Methodology: While the use of Point of Interest (POI) data and advanced modeling techniques like Getis-Ord Gi*, Random Forest, and Multiscale Geographically Weighted Regression (MGWR) is commendable, the article lacks detail on the limitations and biases associated with these methods. It would be helpful to discuss potential sources of bias in the data and how they might impact the results.
3. Interpretation of Results: The article provides a detailed description of the results, including trends in the Comprehensive Service Function Index (CSFI) and key influencing factors. However, it could be strengthened by providing a more in-depth analysis and interpretation of the findings. For example, the article could discuss why certain regions experienced significant increases in service levels while others remained stagnant.
4. Generalization and External Validity: While the findings are based on data from county towns in China, the article could discuss the generalizability of the results to other developing countries or regions. It would be beneficial to explore how factors such as government capacity and economic development might influence the service function of small towns in different contexts.
5. Policy Implications: The article briefly mentions the need for differentiated strategies based on regional differences but could expand on the policy implications of the findings. For instance, it could discuss specific policy recommendations for policymakers and urban planners to enhance the service function of county towns in China.
6. Language and Presentation: The article could benefit from improved language and presentation to enhance readability and accessibility for a broader audience. This includes using clear and concise language, avoiding jargon where possible, and providing sufficient context for readers unfamiliar with the topic.
Overall, while the article provides valuable insights into the service function of small towns in China, addressing these criticisms could strengthen its contribution to the literature on urban-rural development and regional planning.
Specific comments
1. The citation "Sustainability 2021, 13, x FOR PEER REVIEW" indicates that the manuscript has been submitted to the journal "Sustainability" in 2021 and is currently under peer review. Please provide the reason or delete the “sign”?
2. Abstract: The abstract should be concise and follow a standard format including objectives, methods, results, and conclusions.
3. Introduction: The introduction is too brief and lacks specificity regarding the hypotheses and main questions of the study. It is essential to clearly outline the research questions and relate them to existing literature. Additionally, the significance of the study should be emphasized in the introduction section.
4. Data sources and research methodology
All references cited in the article appear to be inaccurate and do not adhere to the standard format. It is imperative to ensure that references are properly formatted according to the designated style guide. Furthermore, the reference to Tong et al. (2012) requires clarification and verification. Additionally, it's important to note that Taiwan is not under the political jurisdiction of China. Therefore, any references or statements that imply Taiwan is part of China should be revised to accurately reflect the geopolitical reality. We did not obtain the original data from the Gaode Open Platform website. The weighting analysis of each service function in Table 3 should include a clear description of how it was calculated. In this study, Multiscale Geographically Weighted Regression (MGWR) was employed to analyze the spatio-temporal heterogeneity of the 257 key influences. It is recommended to compare MGWR with other models such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM) to determine which best fits the assumptions regarding spatio-temporal characteristics.
5. Result
The figures, particularly Figures 4, 7, and 8-12, lack clarity regarding the use of light to deep blue dots. Therefore, improvements are needed to clarify the visual representations. Furthermore, while regression coefficients were depicted in Figures 10-12, the findings from Multiscale Geographically Weighted Regression (MGWR) are not adequately presented. To address this gap, it is suggested to include a new table in the Results section summarizing the findings from MGWR.
6. Discussion and Conclusion
The study's significance and the examination of hypotheses require elaboration. Furthermore, the authors should assess whether the study design information meets the STROBE statement. Some details seem vague and could impede replication efforts. To ensure transparency and replicability by STROBE guidelines, clarifications, and additional details are necessary. Regarding the Conclusion section, it should be concise and highlight the findings and further research directions. Consequently, some content may need to be moved to the Discussion section to achieve this objective.
Comments on the Quality of English Language
Overall Comment
Overall, the article provides a comprehensive analysis of the service function of small towns, particularly county towns, in China. However, several points could be criticized or improved:
1. Clarity and Structure: The article could benefit from a clearer structure. It jumps straight into discussing the analysis methods and results without providing sufficient context or introducing the problem statement and objectives.
2. Data and Methodology: While the use of Point of Interest (POI) data and advanced modeling techniques like Getis-Ord Gi*, Random Forest, and Multiscale Geographically Weighted Regression (MGWR) is commendable, the article lacks detail on the limitations and biases associated with these methods. It would be helpful to discuss potential sources of bias in the data and how they might impact the results.
3. Interpretation of Results: The article provides a detailed description of the results, including trends in the Comprehensive Service Function Index (CSFI) and key influencing factors. However, it could be strengthened by providing a more in-depth analysis and interpretation of the findings. For example, the article could discuss why certain regions experienced significant increases in service levels while others remained stagnant.
4. Generalization and External Validity: While the findings are based on data from county towns in China, the article could discuss the generalizability of the results to other developing countries or regions. It would be beneficial to explore how factors such as government capacity and economic development might influence the service function of small towns in different contexts.
5. Policy Implications: The article briefly mentions the need for differentiated strategies based on regional differences but could expand on the policy implications of the findings. For instance, it could discuss specific policy recommendations for policymakers and urban planners to enhance the service function of county towns in China.
6. Language and Presentation: The article could benefit from improved language and presentation to enhance readability and accessibility for a broader audience. This includes using clear and concise language, avoiding jargon where possible, and providing sufficient context for readers unfamiliar with the topic.
Overall, while the article provides valuable insights into the service function of small towns in China, addressing these criticisms could strengthen its contribution to the literature on urban-rural development and regional planning.
Specific comments
1. The citation "Sustainability 2021, 13, x FOR PEER REVIEW" indicates that the manuscript has been submitted to the journal "Sustainability" in 2021 and is currently under peer review. Please provide the reason or delete the “sign”?
2. Abstract: The abstract should be concise and follow a standard format including objectives, methods, results, and conclusions.
3. Introduction: The introduction is too brief and lacks specificity regarding the hypotheses and main questions of the study. It is essential to clearly outline the research questions and relate them to existing literature. Additionally, the significance of the study should be emphasized in the introduction section.
4. Data sources and research methodology
All references cited in the article appear to be inaccurate and do not adhere to the standard format. It is imperative to ensure that references are properly formatted according to the designated style guide. Furthermore, the reference to Tong et al. (2012) requires clarification and verification. Additionally, it's important to note that Taiwan is not under the political jurisdiction of China. Therefore, any references or statements that imply Taiwan as part of China should be revised to accurately reflect the geopolitical reality. We did not obtain the original data from the Gaode Open Platform website. The weighting analysis of each service function in Table 3 should include a clear description of how it was calculated. In this study, Multiscale Geographically Weighted Regression (MGWR) was employed to analyze the spatio-temporal heterogeneity of the 257 key influences. It is recommended to compare MGWR with other models such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM) to determine which best fits the assumptions regarding spatio-temporal characteristics.
5. Result
The figures, particularly Figures 4, 7, and 8-12, lack clarity regarding the use of light to deep blue dots. Therefore, improvements are needed to clarify the visual representations. Furthermore, while regression coefficients were depicted in Figures 10-12, the findings from Multiscale Geographically Weighted Regression (MGWR) are not adequately presented. To address this gap, it is suggested to include a new table in the Results section summarizing the findings from MGWR.
6. Discussion and Conclusion
The study's significance and the examination of hypotheses require elaboration. Furthermore, the authors should assess whether the study design information meets the STROBE statement. Some details seem vague and could impede replication efforts. To ensure transparency and replicability in accordance with STROBE guidelines, clarifications and additional details are necessary. Regarding the Conclusion section, it should be concise and highlight the findings and further research directions. Consequently, some content may need to be moved to the Discussion section to achieve this objective.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe author has revised the original paper according to the suggestions.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for Authors
1. Generally speaking, the revised manuscript has improved but it does not completely respond to our queries and is not enough to be completely illustrated. In particular, the article does not provide the theoretical frame to explicitly show what is the hypothesis. Therefore, I do recommend that a related-theoretical basis should be added, and mentioned the hypothesis in the introduction section.
2. I initially provided comments regarding the data and methodology, but upon reviewing the revised article, I found that my concerns were not fully addressed. The specific revisions mentioned on pages 21, lines 591-598 were not found to be responsive to my initial feedback.
3. I am unable to locate the precise sections where my comments (Comments 3-7 and 10-12) have been addressed in the revised manuscript. It would be helpful if the revised locations corresponding to my comments were explicitly mentioned to ensure that the manuscript has adequately addressed my concerns.
4. Figure 5 illustrates the spatial distribution of comprehensive service functions' hot and cold zones in China county towns from 2012 to 2021. However, the content should clarify how hot spots and cool spots are defined. It would be beneficial to provide the percentages of hot and cool spots to facilitate understanding. Additionally, showing the change in percentages of hot and cool spots from 2012 to 2021 would enhance the visualization and analysis of the real data.
5. Table 4 illustrates the factors influencing the evolution of spatio-temporal differentiation of comprehensive service functions in county towns in China. County general public budget revenue is highly correlated with other factors. Do you examine the correlation in these factors prior to data analysis in random forest modeling? Consequently, it may produce severe bias in Table 5 and Figure 6.
6. Figures 8-12 lack clarity in illustrating the spatial distribution of regression coefficients for county general public budget revenues. I suggest enhancing the figures by presenting the distribution of regression coefficients across different regions and comparing the data between 2012 and 2021. This comparative analysis would provide valuable insights into the changes over time and facilitate a better understanding of the spatial patterns associated with county general public budget revenues. I find it challenging to understand the meanings of the coefficients depicted in Figures 8-12. I am uncertain about the rationale behind classifying them into five groups. It seems that all coefficients should undergo testing, allowing for direct comparisons, rather than being grouped arbitrarily. Clarity on how coefficients are categorized and the rationale behind this classification would enhance the interpretation of the figures and the validity of the results.
7. I have recommended comparing MGWR with other models such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM) to determine which best fits the assumptions regarding spatio-temporal characteristics. These models can not only used to explain the spatial and temporal effects, but the spatial spillovers can be examined.
8. Additionally, I am concerned about the completeness and accuracy of the town data in China. If there are issues such as insufficient or missing data for each town, it's important to address how these problems are handled in the analysis. Clarifying the methods used to deal with incomplete or missing data would enhance the transparency and reliability of the study's findings.
9. In the Discussion section, the findings are not explicitly explained and compared to previous studies. It would be beneficial to provide a detailed analysis of the findings and compare them with existing literature to contextualize the results effectively. Additionally, discussing how the findings can be applied to inform policy implications and suggesting directions for further research would enhance the relevance and impact of the study. Finally, it is important to include a section on the limitations and strengths of the study in the last paragraph to provide a balanced assessment of the research findings.
Finally, I encourage the authors to respond clearly to my comments and revise the content accordingly. Specifically, I suggest moving redundant content from the introduction section to the Discussion section for better organization and clarity of presentation. Clear responses to comments and appropriate revisions will enhance the overall quality and coherence of the manuscript.
Comments on the Quality of English Language1. Generally speaking, the revised manuscript has improved but it does not completely respond to our queries and is not enough to be completely illustrated. In particular, the article does not provide the theoretical frame to explicitly show what is the hypothesis. Therefore, I do recommend that a related-theoretical basis should be added and mentioned the hypothesis in the introduction section.
2. I initially provided comments regarding the data and methodology, but upon reviewing the revised article, I found that my concerns were not fully addressed. The specific revisions mentioned on page 21, lines 591-598 were not found to be responsive to my initial feedback.
3. I am unable to locate the precise sections where my comments (Comments 3-7 and 10-12) have been addressed in the revised manuscript. It would be helpful if the revised locations corresponding to my comments were explicitly mentioned to ensure that the manuscript has adequately addressed my concerns.
4. Figure 5 illustrates the spatial distribution of comprehensive service functions' hot and cold zones in China county towns from 2012 to 2021. However, the content should clarify how hot spots and cool spots are defined. It would be beneficial to provide the percentages of hot and cool spots to facilitate understanding. Additionally, showing the change in percentages of hot and cool spots from 2012 to 2021 would enhance the visualization and analysis of the real data.
5. Table 4 illustrates the factors influencing the evolution of spatio-temporal differentiation of comprehensive service functions in county towns in China. County general public budget revenue is highly correlated with other factors. Do you examine the correlation in these factors prior to data analysis in random forest modeling? Consequently, it may produce severe bias in Table 5 and Figure 6.
6. Figures 8-12 lack clarity in illustrating the spatial distribution of regression coefficients for county general public budget revenues. I suggest enhancing the figures by presenting the distribution of regression coefficients across different regions and comparing the data between 2012 and 2021. This comparative analysis would provide valuable insights into the changes over time and facilitate a better understanding of the spatial patterns associated with county general public budget revenues. I find it challenging to understand the meanings of the coefficients depicted in Figures 8-12. I am uncertain about the rationale behind classifying them into five groups. It seems that all coefficients should undergo testing, allowing for direct comparisons, rather than being grouped arbitrarily. Clarity on how coefficients are categorized and the rationale behind this classification would enhance the interpretation of the figures and the validity of the results.
7. I have recommended comparing MGWR with other models such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM) to determine which best fits the assumptions regarding spatio-temporal characteristics. These models can not only used to explain the spatial and temporal effects, but the spatial spillovers can be examined.
8. Additionally, I am concerned about the completeness and accuracy of the town data in China. If there are issues such as insufficient or missing data for each town, it's important to address how these problems are handled in the analysis. Clarifying the methods used to deal with incomplete or missing data would enhance the transparency and reliability of the study's findings.
9. In the Discussion section, the findings are not explicitly explained and compared to previous studies. It would be beneficial to provide a detailed analysis of the findings and compare them with existing literature to contextualize the results effectively. Additionally, discussing how the findings can be applied to inform policy implications and suggesting directions for further research would enhance the relevance and impact of the study. Finally, it is important to include a section on the limitations and strengths of the study in the last paragraph to provide a balanced assessment of the research findings.
Finally, I encourage the authors to provide clear responses to my comments and revise the content accordingly. Specifically, I suggest moving redundant content from the introduction section to the Discussion section for better organization and clarity of presentation. Clear responses to comments and appropriate revisions will enhance the overall quality and coherence of the manuscript.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 3
Reviewer 3 Report
Comments and Suggestions for AuthorsDespite revisions made to the article in response to our comments, some of our concerns have not been fully addressed. It is imperative to carefully describe each comment and ensure that all aspects are adequately addressed.
1. The authors have not fully addressed my comments regarding the description of the weighting analysis for each service function in Table 3. This description must include a clear explanation of how the analysis was calculated. In this study, Multiscale Geographically Weighted Regression (MGWR) was utilized to examine the spatio-temporal heterogeneity of the 257 key influences. I strongly advocate for a comparative analysis of MGWR with other models, such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM), to determine which model best aligns with the assumptions regarding spatiotemporal characteristics.
2. I did not achieve a clear understanding of the findings presented in Figures 4, 7, and 8-12, which utilize light to deep blue dots. There is a need for improvement in clarifying the visual representations. To enhance clarity, I suggest reorganizing the new table to explicitly mention the regression coefficients depicted in Figures 10-12 resulting from Multiscale Geographically Weighted Regression (MGWR). This clarification will help readers better interpret the visual data and understand the implications of the regression coefficients in the context of the study.
3. The findings of the study rely on data gathered from county towns in China. I am concerned that the article may not have fully collected data from all towns and counties, which could pose methodological challenges. Additionally, the quality of information sourced from governmental data may affect the generalizability of the results. I recommend addressing these issues in the Discussion section to provide transparency about the data collection process and acknowledge potential limitations in the study's generalizability. Discussing these concerns will enhance the readers' understanding of the study's scope and the implications of the data sources used.
Overall, the article needs to be revised carefully based on our comments. Although the depth of research is still somewhat improved, it is limited by the difficulty of data acquisition and collection, which the author also mentions in the shortcomings and prospects.
Comments on the Quality of English Language
Despite revisions made to the article in response to our comments, some of our concerns have not been fully addressed. It is imperative to carefully describe each comment and ensure that all aspects are adequately addressed.
1. The authors have not fully addressed my comments regarding the description of the weighting analysis for each service function in Table 3. This description must include a clear explanation of how the analysis was calculated. In this study, Multiscale Geographically Weighted Regression (MGWR) was utilized to examine the spatio-temporal heterogeneity of the 257 key influences. I strongly advocate for a comparative analysis of MGWR with other models, such as the Spatial Error Model (SEM), Spatial Lag Model (SLM), and Spatial Durbin Model (SDM), to determine which model best aligns with the assumptions regarding spatiotemporal characteristics.
2. I did not achieve a clear understanding of the findings presented in Figures 4, 7, and 8-12, which utilize light to deep blue dots. There is a need for improvement in clarifying the visual representations. To enhance clarity, I suggest reorganizing the new table to explicitly mention the regression coefficients depicted in Figures 10-12 resulting from Multiscale Geographically Weighted Regression (MGWR). This clarification will help readers better interpret the visual data and understand the implications of the regression coefficients in the context of the study.
3. The findings of the study rely on data gathered from county towns in China. I am concerned that the article may not have fully collected data from all towns and counties, which could pose methodological challenges. Additionally, the quality of information sourced from governmental data may affect the generalizability of the results. I recommend addressing these issues in the Discussion section to provide transparency about the data collection process and acknowledge potential limitations in the study's generalizability. Discussing these concerns will enhance the readers' understanding of the study's scope and the implications of the data sources used.
Overall, the article needs to be revised carefully based on our comments. Although the depth of research is still somewhat improved, it is limited by the difficulty of data acquisition and collection, which the author also mentions in the shortcomings and prospects.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
