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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: No

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: No

Reviewer #2: I Don't Know

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3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: This study investigated the influencing factors on bicycle ridership in Xianyang, China. I have some severe concerns on this paper.

Major comments:

(1) The paper needs to be restructured in a more logical way. For example, in chapter 1, the GWR appears suddenly and the reader cannot follow the context, making it difficult to understand the contributions of the paper. Research questions and hypotheses should be clearly explained. Also, please explain the intention of each analysis. You need to explain logically whether the main contribution of this study is in the application of GWTR, in the data, in the application to Xianyang, or in the research questions.

(2) GWR is known to suffer from multicollinearity (see e.g., Murakami et al., spatial statistics 19, 68-89), and attention should be paid not only to global multicollinearity as analyzed in the paper, but also to location-specific local multicollinearity (e.g., by examining correlations between regression coefficient estimates or using diagnostic statistics for local multicollinearity). When local multicollinearity is strong, the regression coefficient estimates are almost impossible to interpret because they face identification problems. Also you should explain why you chose this method among various other spatially varying coefficients models (SVCM) that can mitigate local multicollinearity problem, such as multiscale GWR and Bayesian SVCM.

(3) Figures are not properly explained in the text, and there is no explanation of the vertical and horizontal axes. In the first place, all the figures are almost impossible to understand due to resolution problems. If Figure 5 is taken from ArcGIS, it should be indicated as such.

(4) GWR is a method for cross-sectional data, while GWTR is a method for time series cross-sectional (TSCS) or panel data. Then, why you can compare? How?

(5) The GWTR may be formulated with assuming that a sample is influenced by previous samples, but it is unclear how that part was formulated, weights were given, and bandwidth was estimated (or calibrated), since neither the method nor the results are described.

Minor comments:

(6) I could not understand the intention of the Moran I analysis of the explanatory variables in Table 5. Also, it is odd that sd is all 0.

(7) This paper needs to be native checked.

(8) It is not effective to distribute data in PDF format. Please consider to use other formats such as csv.

Reviewer #2: This paper explored the temporal and spatial distribution characteristic of cycling, identified the relationship between cycling behavior and built environments based on 2022 Daily Trip Survey in Xianyang, China. Then GTWR and GWR models are established include socio-economic factors, road factors and built environmental factors. In particular, four new findings are presented, mainly by setting two original indicators as built environmental factors. This also means that the findings are useful for a timely topic in a low- and middle-income country. However, there are some uncertainties and concerns regarding the characteristics of the data used, the statistical significance of the analysis results, and the validity of the discussion and conclusions, which require appropriate additions and corrections. In addition, the figure showing the spatial distribution of the regression coefficients is not very clear, and we strongly request that it be replaced with a clearer figure.

▼Page 8-9, Equations (1) to (3).

The formula needs to be laid out properly. In addition, the hat "�" seems to be garbled, so I ask for confirmation.

▼Page 8-12, Methodology.

Since previous studies comparing the results of the combined use of GWR and GTWR have been accumulated, including a paper by the developers of GTWR (Fotheringham and Yao, 2015 (https://doi.org/10.1111/gean.12071)), a review of the methodology should be included to clarify the position of this study. Therefore, it is necessary to clarify the position of this study by including a review of the methodology.

▼Page 15, Table 1.

The item name on the left, "Variables," is not a "Level 1 factor." Since the item names are different, you need to unify them into one of the two.

▼Page 16-17, Table 2.

Dependent Variable Y needs to be clarified specifically because it is unclear whether bicycle trips are counted on an origin basis or a destination basis.

▼Page 16, Line 320.

There is a space between "of" and "traffic."

▼Page 19, Table 4.

In each value, I wish to consider significant figures.

▼Figure 2.

As can be seen from Figure 2, there is some variation in the area of the research unit. Therefore, is there a possibility that there is a problem with the aggregation unit when setting the variables? It is necessary to clarify the appropriateness of the setting of the explanatory variables in terms of unit area.

▼Page 22-26, 5.3 Spatial characteristic of variables based on GTWR.

In order to evaluate the validity of the results in terms of statistical significance, isn't it necessary to show the spatial distribution of the t-values of the regression coefficients? This point needs to be explained.

In addition, to judge whether the statistical analysis was performed appropriately and rigorously, it is necessary to clarify what statistical application was used and, if there were any conditions set for the analysis.

▼Page 22, Line 375.

I think it should be "This" and not "his", so I would like it to be corrected.

▼Page 26-29, 5.4 Temporal heterogeneity.

When considering temporal heterogeneity, it is first necessary to clearly state how the t that appears in Equations 3 and 4 is set in the analysis, including its units.

▼Figures 3a and 3b.

The legends for Figures 3a and 3b need to be in English and the units should be shown.

▼Figures 6 and 7.

The graph showing the spatial distribution of regression coefficients has low visibility and we would like it to be replaced with something clearer.

The numerical values for each category in Figures 6 and 7 are difficult to read and I would like this to be improved.

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what does this mean? ). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

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<p>Spatiotemporal Heterogeneity of Bicycle Ridership Based on GTWR Model

PONE-D-24-25989R1

Dear Dr. Zhang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Hironori Kato, Dr. Eng.

Academic Editor

PLOS ONE

Editor Comments:

Both reviewers recommended accepted. Congratulations for successful revisions!

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: I believe this paper has been substantially revised. No further comment from me.

I believe this paper has been substantially revised. No further comment from me.

Reviewer #2: I have confirmed that your response to the peer review has been sufficiently addressed. Therefore, I have no additional comments.

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what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: No

Reviewer #2: Yes:  Tetsuharu Oba

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