-->PONE-D-25-58646-->-->A Sensitivity Study on the Measurement of Urban Polycentricity in Chinese Cities: Center Definition, Indicator Selection, and Their Interaction Effects-->-->PLOS One

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: I Don't Know

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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-->5. Review Comments to the Author

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Reviewer #1: This is a robust study, addressing a topic that has been extensively explored and discussed through different theoretical and methodological approaches throughout decades. The article makes this clear and defines its methodological choices. However, it seems that a more in-depth discussion on the conceptualization of morphological and functional centrality would be appropriate, as to present the wide range of possibilities in literature. For instance, those connected to geotecnologies and spatial dynamic analysis - that seem to be better suitable for the dynamic reading required.

Although this study explores different methods and demonstrates some significant differences in its findings, its conclusion that there is a clear need for more dynamic ways of understanding urban centrality is well-founded. It offers interesting contributions to the field by comparatively examining specific methods and its performance/output.

The absence of certain data is justified due to their nature and the requirement for protection.

Reviewer #2: Advantages

1) Academic Originality and Filling the Research Gap

This paper makes a clear contribution by shifting focus from simply identifying polycentricity to critically examining how it is measured. The authors show that existing research is fragmented and lacks common standards, making cross-study comparison unreliable. This paper directly addresses that problem. The authors tackle this by using a Linear Mixed-effects Model (LMM) to quantify these interactions, moving the field from chasing a single definitive answer toward understanding where and why results diverge. Interestingly, this paper uses mobile signaling data to combine both static (morphological) and dynamic flow (functional) perspectives into one coherent framework, rather than analyzing only one dimension as most prior studies did.

2) Validity and Rigor of Characterizing Centers

The morphology-function distinction is a well-established framework. The authors apply it carefully and consistently throughout. Morphological Dimension is measured through the evenness of center sizes, using static data such as working population distribution, whereas Functional Dimension is measured through the relative importance of commuting flows, using dynamic mobile signal data to capture how people move between centers. The authors test their findings across 4 different center identification methods and 5 different indicators. This multi-method approach is designed to reveal how much results shift depending on the tools used. Additionally, the LMM isolates the effect of methodological choices from actual urban variation—a statistically sound approach for a multi-city comparative study.

Improvements

The authors have made great efforts to quantitative analysis. In part 5 and 6, interpretation and implications of the findings should be developed through these followings:

1. Strengthening the Functional Characterization

The reliance on commuting flows as the primary measure of functional polycentricity is a notable limitation. While commuting data is valuable, urban function extends well beyond employment-home linkages—social, recreational, and service-oriented movements are equally central to how cities actually operate. As it stands, the functional dimension captures only one slice of urban life. The authors should explicitly acknowledge this boundary, and where the data permits, incorporate non-work-related flows or at minimum discuss how the polycentric structure might shift during weekends or leisure periods. This would give a clearer picture of each city's functional rhythm.

2. Deepening the Socio-Economic Context of Case Studies

The 3 case cities—Hangzhou, Wuhan, and Nanning—are treated largely as interchangeable test subjects. Each city carries distinct geographical and policy histories that directly shape why certain measurement methods perform well or poorly within them. Hangzhou's West Lake constraint, Wuhan's river-split "Three Towns" structure, and Nanning's economic geography are not background details—they are explanatory factors. The authors should include a brief spatial narrative for each city, connecting local conditions to specific methodological outcomes. For instance, explaining why the threshold method overestimates centers in one city but underestimates them in another would bridge the gap between statistical results and planning reality.

3. Providing a Practical Guide for Practitioners

The paper demonstrates that different methods produce different results, but it stops short of telling readers what to do with that finding. A practitioner finishing this paper may be left more uncertain than before, unsure which method to trust for their specific context. The authors should translate their findings into a practical decision-making framework—such as a synthesis table—that guides method selection based on city type, urbanization stage, or measurement goal. This would shift the paper's contribution from diagnosing a problem to actively solving it, making it a genuinely useful reference for future researchers and planners.

4. Visualizing the Interaction Effects

The LMM results are statistically sound but risk being inaccessible to a broader planning audience when presented primarily through text and tables. Since the interaction between indicator selection and center definition methods is the core of the paper's originality, it deserves a visual treatment that makes that interaction immediately legible. A heatmap or conceptual matrix—showing which indicators are robust across all center definitions and which are highly sensitive to definitional choices—would make the key findings far more communicable and impactful.

5. Expanding the Policy Implications

The paper's implications for urban planning policy remain insufficiently developed. The stakes of methodological misclassification are not merely academic: if a city planner relies on a flawed method and incorrectly determines that a city is monocentric, the downstream consequences—misallocated infrastructure, poorly targeted investment zones, ineffective transport planning—can be significant. This is especially consequential in the Chinese context, where polycentric development is actively pursued as a top-down planning strategy. The authors should add a focused discussion on policy sensitivity, making explicit how methodological bias translates into planning risk.

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Reviewer #1: Yes: Vânia Raquel Teles Loureiro

Reviewer #2: No

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A sensitivity study on the measurement of urban polycentricity in Chinese cities: center definition, indicator selection, and their interaction effects

PONE-D-25-58646R1

Dear Dr. Zhu,

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