Shared Cycling Demand Prediction during COVID-19 Combined with Urban Computing and Spatiotemporal Residual Network

Round 1

Reviewer 1 Report

Article is a good read. But there is scope of improvement in the conclusion section. Please elaborate the novelty of work. The similarities and difference of findings from the previous study need to be include. Further there are several social implication of this work, Please add. Have a relook at Figure 7 and try to simplify it. 

Author Response

Dear Reviewer,

 

    Thanks to the editors for arranging the review and the reviewers for their valuable comments.The author has carefully answered the questions as required by the reviewer, and has made careful revisions to the article. All revisions of the article are marked by the review function.As a result of your suggestions, the revised articles are better.Thanks again to the editors and reviewers for their help.Please see the attachment.

 

Kind regards,

 

Author

Author Response File: Author Response.pdf

Reviewer 2 Report

 

This paper designed a bike-sharing demand forecasting model considering the severity of COVID-19 lock down. To predict the bike-sharing demand, the authors used the bike-sharing, geographic information, climate, and epidemic data. I consider the work a good paper, I had only a few minor observations.

In Figure 3, the text in the vertical axis is illegible and the columns are tangled. Please correct it

In addition, the conclusions need to be developed further in order to highlight the unique contributions of the paper, theoretical and managerial implications.

The English language quality of this paper is globally appropriate and acceptable. However, some minor revisions and spell check seem to be necessary.

Author Response

Dear Reviewer,

 

    Thanks to the editors for arranging the review and the reviewers for their valuable comments.The author has carefully answered the questions as required by the reviewer, and has made careful revisions to the article. All revisions of the article are marked by the review function.As a result of your suggestions, the revised articles are better.Thanks again to the editors and reviewers for their help.Please see the attachment.

 

Kind regards,

 

Author

Author Response File: Author Response.pdf

Reviewer 3 Report

The article concerns an interesting topic which is "Shared cycling demand prediction during COVID-19 combined with urban computing and spatiotemporal residual network". The topic of the article is very timely due to the pandemic aspects.

Overall, in my opinion the article fits into the thematic scope of the journal and the special issue.

I have some comments on the article that need to be corrected in order for it to be published.

From the editorial point of view:

1. Pay attention to the English language and carefully study the entire article.

2. It should be checked whether the formatting of the work complies with the MDPI standards. In my opinion, references to literature, eg [1], should be written differently. Check the template.

From the substantive point of view:

The literature review is okay, as well as the methodology and the results obtained. When making corrections, you should focus on discussing the results and summing up.

3. There is no chapter in the paper that would be devoted to discussing the obtained results. It should be added.

4. In the discussion chapter, should discuss not only your results, but also refer to work carried out by other authors on the same topic. There are also many other barriers to the development of shared mobility than the factors you took into account in the model. A lot of them are connected to social and transport exclusions and are related to all of shared mobility services not only bike sharing. Please refer to 'Mobility Modeling and Prediction in Bike-Sharing Systems' and 'Social barriers and transportation social exclusion issues in creating sustainable car-sharing systems'. 

5. The summary needs to be completely changed. There is no reference to the purpose of the article - whether it was achieved. Sequentially, there is no indication of what can improve the application of the model? Please indicate specific recommendations and refer to e.g. policies for managing shared mobility systems, e.g. 'The concept of rules and recommendations for riding shared and private e-scooters in the road network in the light of global problems'. 

Good luck!

Author Response

Dear Reviewer,

 

    Thanks to the editors for arranging the review and the reviewers for their valuable comments.The author has carefully answered the questions as required by the reviewer, and has made careful revisions to the article. All revisions of the article are marked by the review function.As a result of your suggestions, the revised articles are better.Thanks again to the editors and reviewers for their help.Please see the attachment.

 

Kind regards,

 

Author

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The article has been significantly improved and is suitable for publication in its current form.  Thank you to the authors for the changes made.