Site Selection for Elderly Care Facilities in the Context of Big Data: A Case Study of Xi’an, China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I would like to congratulate the authors for their hard work and dedication. I truly appreciated seeing the application of POI data to such a globally significant issue as population aging. It was a pleasure to read your work, and the approach provides valuable insights into addressing this pressing challenge.

I only have a few small suggestions:

- I would suggest adding a brief section in the introduction that highlights the research gaps in this area. This would provide a stronger rationale for the study and emphasize its contribution to the field.

-An important observation concerns Figure 4, where the text on the graphs could be improved for better visibility. In its current form, the size and clarity of the text may make it difficult to read the details, especially for readers viewing the figures in print or on smaller screens. I recommend adjusting the text size and contrast to ensure better readability and a more user-friendly visual experience, or move the text outside the graphs

- I recommend providing a bit more detailed explanation of the criteria used for filtering the POI data and the justification behind these choices. This would enhance the transparency and replicability of the methodology.

Author Response

Dear Reviewer:

Thank you for your letter and for the comments concerning our manuscript entitled “The Site Selection of Elderly Care Facilities under the Context of Big Data: A Case Study of Xi’an, China” (ID: sustainability-3438902). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked up using the “Highlight” function in the paper. The main corrections in the paper and the responds to the comments are as following:

 

Responses to the comments of Reviewer (C, Comments; R, Response):

 

C: 1. I would suggest adding a brief section in the introduction that highlights the research gaps in this area. This would provide a stronger rationale for the study and emphasize its contribution to the field.

R: Thanks very much to the reviewer for this suggestion. We added a section in the introduction outlining the research gap and highlighting the advantages of the methodology. See Line 95-113.

 

C: 2. An important observation concerns Figure 4, where the text on the graphs could be improved for better visibility. In its current form, the size and clarity of the text may make it difficult to read the details, especially for readers viewing the figures in print or on smaller screens. I recommend adjusting the text size and contrast to ensure better readability and a more user-friendly visual experience, or move the text outside the graphs.

R: Thanks very much to the reviewer for this suggestion. We have modified Figure 4, moving the text out of the image. See Figure 4.

 

C: 3. I recommend providing a bit more detailed explanation of the criteria used for filtering the POI data and the justification behind these choices. This would enhance the transparency and replicability of the methodology.

R: Thanks very much to the reviewer for this suggestion. We have added the principles and rationale for POI data selection in the POI data processing section. See Line 302-307, 313-318.

 

We would like to thank you again for the deliberation and help. We think these suggestions are very meaningful!

 

With best regards,

Yours sincerely,

Xianchao Zhao

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Despite its regional nature, this work addresses a current and very pertinent issue: optimising the location of elderly care facilities in Xi'an, China, using Big Data and the ID3 decision tree model. The research analyses Xi'an's ageing demographics and the distribution of existing facilities, using Points of Interest (POI) data and ArcGIS software to identify distribution patterns and predict optimal locations for new facilities.

The world's population is ageing rapidly, with China facing significant challenges due to the increase in the elderly population. The care system for the elderly in China is underdeveloped and with inadequately distributed facilities. In this regard, the authors draw on POI data collected via the Baidu Maps API and demographic data from the national census and use the ID3 algorithm to build a decision tree model that simulates and predicts optimal locations for elderly care facilities. This study concludes that elderly care facilities are mainly concentrated in the city centre of Xi'an, with lower density in outlying areas. The model predicted 3,172 suitable sites for new facilities, with an accuracy of 85.8 per cent when validating with existing facilities, and identified 1,263 priority sites for construction, mainly in the Lianhu, Xincheng and Beilin districts. The authors conclude that the use of POI data and machine learning algorithms improves accuracy and objectivity in the selection of sites for elderly care facilities and recommend expanding the range of facilities, improving public transport coverage, integrating medical care and financial incentives to attract investment.

 

The strengths of this work include the use of Big Data and Machine Learning Algorithms (the application of the ID3 algorithm to build a decision tree model is innovative and increases the accuracy of site selection; the use of Points of Interest (POI) data and tools such as the Baidu Maps API and ArcGIS software allows for a detailed and accurate analysis of the distribution of facilities); the choice of a Data-Based Approach (the collection and analysis of demographic and POI data provides a solid basis for decision-making; the validation of the model with an accuracy of 85.8% demonstrates the robustness and reliability of the method); the Social Relevance of this research (the study addresses a critical problem related to population ageing and the need to optimise elderly care facilities; the practical recommendations provide clear guidelines for improving elderly care services in Xi'an); an Integrated Urban Planning (the consideration of multiple factors, such as proximity to government and medical institutions, ensures that new facilities better meet the needs of the elderly population; the identification of priority sites for construction helps to direct urban planning efforts effectively).

Weaknesses of this work include dependence on existing data (the accuracy of the model depends on the quality and comprehensiveness of the available POI and demographic data; any gaps or inaccuracies in the data may affect the results; the study assumes that existing facilities are an approximately optimal solution, which may not always be the case in practice); subjective and cultural factors (the model may not adequately consider subjective and cultural factors that influence the choice of locations, such as personal preferences of the elderly and specific government policies; the unified categorisation of elderly care facilities may not reflect the different needs and types of services required); regional limitations (the study is specific to Xi'an and may not be directly applicable to other regions with different demographic and geographical characteristics; the approach may need significant adjustments to be applied in different urban contexts); the complexity of the model (the complexity of the model may make it difficult for urban planners and decision-makers who do not have a technical background in machine learning to implement it in practice).

 

The literature review is comprehensive, adequate and up-to-date. The methodology of the work is well described and appropriate. The presentation of the results is coherent, well-structured and supported by detailed analyses and clear visualisations. The study's conclusions provide a clear and comprehensive synthesis of the main findings, highlighting the effectiveness of the decision tree model, the importance of POI data and recommendations for future research and policy.

 

Just a minor note:

Figures 7 and 8 should be referred to in the text before they appear

 

Congratulations to the authors for their work!

Author Response

Dear Reviewer:

Thank you for your letter and for the comments concerning our manuscript entitled “The Site Selection of Elderly Care Facilities under the Context of Big Data: A Case Study of Xi’an, China” (ID: sustainability-3438902). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked up using the “Highlight” function in the paper. The main corrections in the paper and the responds to the comments are as following:

 

 

Responses to the comments of Reviewer (C, Comments; R, Response):

 

C: Figures 7 and 8 should be referred to in the text before they appear.

R: Thanks very much to the reviewer for this suggestion. The positions of Figures 7 and 8 in the text have been adjusted so that they appear after the paragraphs where they are first mentioned. See Figure 7 and 8.

 

 

We would like to thank you again for the deliberation and help. We think these suggestions are very meaningful!

 

With best regards,

Yours sincerely,

Xianchao Zhao

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The practical objectives of the research presented in the article are clear, as are the procedures adopted. However, there are two significant issues: 1. The scientific relevance of the article and the increase in knowledge it provides compared to the currently available literature is unclear; 2. The connection to the journal's theme, sustainability, is unclear.

Author Response

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “The Site Selection of Elderly Care Facilities under the Context of Big Data: A Case Study of Xi’an, China” (ID: sustainability-3438902). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked up using the “Highlight” function in the paper. The main corrections in the paper and the responds to the comments are as following:

 

Responses to the comments of Reviewer (C, Comments; R, Response):

 

C: 1. The scientific relevance of the article and the increase in knowledge it provides compared to the currently available literature is unclear.

R: Thanks very much to the reviewer for this suggestion. We added a section in the introduction outlining the existing research on machine learning in the selection of elderly care facilities locations. However, existing research focuses mainly on the accuracy of the models themselves, lacking an interpretation of the decision trees. Specifically, these studies have not analyzed which factors have a greater impact on the location selection of elderly care facilities. Additionally, there is often a lack of detailed comparative analysis of location selection at the street scale. See Line 95-113.

 

C: 2. The connection to the journal's theme, sustainability, is unclear.

R: Thanks very much to the reviewer for this suggestion. A section on the impact of the study on sustainable development has been added to the introduction. Additionally, a part highlighting the differences between this study and previous research has been included to emphasize its scientific contribution. The results and discussion sections of the manuscript now also emphasize the implications of the findings for sustainable development. The impact of this study on the quality of life of the elderly population in Xi’an and strengthen the connection with the journal's theme of sustainability has added in the manuscript. See Line 59-69, 477-488.

 

We would like to thank you again for their deliberation and help. We think these suggestions are very meaningful!

 

With best regards,

Yours sincerely,

Xianchao Zhao

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Dear authors

Hope you are well

Overall, the manuscript is well-written and provides valuable contributes into the optimization of elderly care facility locations using big data and machine learning. With some minor revisions, it would be very good to publish.  My suggestion are:

For the methodology section that you provide more details on the validation process of the decision tree model, and discuss potential limitations or biases in the data collection process, such as the accuracy of POI data from Baidu Map.

In the discussion section include a more detailed comparison of the predicted sites with the current distribution of elderly care facilities, and add the potential impact of the findings on the elderly population in Xi’an, including any social or economic benefits.

Finaly for the conclusion section a brief discussion on the limitations of the study and potential areas for future research will open this to more discussion in the future and highlight any unexpected findings or insights gained from the study (optional).

Best wishes

•  

Author Response

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “The Site Selection of Elderly Care Facilities under the Context of Big Data: A Case Study of Xi’an, China” (ID: sustainability-3438902). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked up using the “Highlight” function in the paper. The main corrections in the paper and the responds to the comments are as following:

 

Responses to the comments of Reviewer (C, Comments; R, Response):

 

C: 1. For the methodology section that you provide more details on the validation process of the decision tree model, and discuss potential limitations or biases in the data collection process, such as the accuracy of POI data from Baidu Map.

R: Thanks very much to the reviewer for this suggestion. In the methodology section, the criteria for grid division in Xi'an and the details validation process of the decision tree model have been added, along with a discussion of potential limitations of the POI data. See Line 256-259, 268-273, 302-307, 313-318.

 

C: 2. In the discussion section include a more detailed comparison of the predicted sites with the current distribution of elderly care facilities, and add the potential impact of the findings on the elderly population in Xi’an, including any social or economic benefits.

R: Thanks very much to the reviewer for this suggestion. The discussion section now includes a detailed comparison between existing elderly care facilities in Xi’an and the predicted locations, as well as an added section on the impact of the study’s findings on the elderly population in Xi’an, along with its potential social and economic benefits. See Line 422-433, 477-488.

 

C: 3. Finaly for the conclusion section a brief discussion on the limitations of the study and potential areas for future research will open this to more discussion in the future and highlight any unexpected findings or insights gained from the study (optional).

R: Thanks very much to the reviewer for this suggestion. In the conclusion, possible future research optimization directions and ideas have been included. See Line 547-552.

 

We would like to thank you again for their deliberation and help. We think these suggestions are very meaningful!

 

With best regards,

Yours sincerely,

Xianchao Zhao

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

I continue to have the same doubts expressed in the first round of review regarding the relevance of the article to the scientific debate and to the scope of the journal. However, since these are matters that concern the journal's editors more than the reviewers, if the editorial board considers the article suitable for publication, I have no further comments to make.