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Peer-Review Record

Hedonic Pricing of Houses in Megacities Pre- and Post-COVID-19: A Case Study of Shanghai, China

Sustainability 2022, 14(17), 11021; https://doi.org/10.3390/su141711021
by Yujiao Chen 1 and Zhengbo Luo 2,*
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3:
Sustainability 2022, 14(17), 11021; https://doi.org/10.3390/su141711021
Submission received: 26 July 2022 / Revised: 29 August 2022 / Accepted: 1 September 2022 / Published: 3 September 2022
(This article belongs to the Section Sustainable Urban and Rural Development)

Round 1

Reviewer 1 Report

Dear authors,

This is a very interesting article on the spatial distribution of house prices in Shanghai and the changes after the pandemic. The methodology is appropriate and quite innovative. At some parts of the discussion however, I think that conclusions based on the overall analysis are presented and not only the ones corresponding to the specific section of the analysis (see for example my comment on lines 262-269). The conclusions are interesting, especially the ones concerning the demand for larger houses after the pandemic. My comments concern the discussion of the regression coefficients and some clarifications or improvements which I believe are necessary:

Lines 324-332: I cannot see any significance results for the regression coefficients in Figure 6. This figure is anyway very hard to read. Also, the comment in lines 326-327 is not clear to me. Finally, why would we expect that the comparison of the methods (GWR and MGWR) would be different because of the pandemic?

Lines 345-351: I believe the discussion concerns the figures in Table 5. In some cases, it is not certain whether a figure is “small”, for example the bandwidth for transaction days in 2018 is quite large. In addition, if small numbers represent spatial heterogeneity I would expect that the regression coefficients are not stable in space (354-355, 358-360).

Lines 369-440. The comments on the sign of the regression coefficients for living area are very interesting (369-379). It seems to me that living area is always important for price, but not necessarily for price per sq.m. Therefore, the changing sign is a mathematical adjustment of the model to consider the factors you mention? If you can provide further elaboration on that matter, it would be useful. Similarly, the negative impact of bedrooms (lines 412-419) needs further explanation; small apartments are generally more expensive in terms of price per sq.m. especially when they are scarce in neighborhoods where large apartments prevail. Finally, is there an explanation for the positive impact of distance from the bus station? (435-437)

Conclusions (Line 19). What is the street scale? (the numbering of lines starts again with 1 in the conclusions section)

Lines 153-154: Something is probably wrong with reference 39, it cannot be found

Line 154: square meter?

Lines 157-160 and Table 1: it is not clear how many floors is low, middle and upper.

Lines 183-184: Since points is the spatial unit, spatial weights cannot be based on adjacency, this is appropriate for polygons.

Figure 2: the label of the Y-axis is in not in English

Lines 262-269: It does not seem that the discussion in this paragraph concerns spatial correlation.

Lines 289-291: The results concern the year 2021

Line 294, 300 etc.: The Middle Ring Road and other place names do not appear on a map

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Please follow the attached file

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Reviewer 3 Report

Line 12, no need to bold and italics Lianjia Real Estate and Gaode Map

Lines 13-14, deeply explores the hedonic of housing prices and its main influencing 13 factors, mainly using the MGWR model, MGWR is not hedonic regression. And Line 15 classic GWR, the results of MGWR… Please state clear which method or methods that you used in this paper.

Cite recent China housing price research paper like https://www.tandfonline.com/doi/abs/10.1080/14445921.2021.1961182

Better pack the footnote to the main body of the paper and condense that content.

The most commonly applied methods of housing price evaluation part, please add some new methods in literatures like artificial neural network:

Walled buildings, sustainability, and housing prices: An artificial neural network approach https://www.mdpi.com/2071-1050/10/4/1298

D. C. Wheeler & Páez, 2010 citation is in wrong format?

Data part, Lianjia Real Estate is needed not bolded.

In 2020, Lianjia Real Estate's national market share of second-hand housing reached 26.22%, what are the second and third most market share? Why only one source is used? Why 2020?

No need to bold Gaode Map

The research scope includes the whole area of Shanghai's administrative region, cov- 145 ering 16 districts 3 , namely, Jing'an, Huangpu, Xuhui, Changning, Putuo, Hongkou, 146 Yangpu, Pudong, Fengxian, Minhang, Jinshan, Songjiang, Qingpu, Jiading, Baoshan, and 147 Chongming What is the rationale for this sample?

Can the results be generalised?

Condense footnote 3 and pack to the main body of the paper

Make sure the copyright is obtained or the map is drawn by the author

What is the main originality of the variables that you study for this paper? It seems the variables are rather old.

Research method, not methodology

The whole section of 2.3 needs citations,

Comparative Study on Spatial Digital Mapping Methods of Soil Nutrients Based on Different Geospatial Technologies, https://www.mdpi.com/2071-1050/13/6/3270/htm

May be relevant.

Line 230, Code for the design of residential buildings (GB 50096-2011) needs not be bolded. Why this code is needed here?

Housing types, what are these?

Words like Cold-hot spots may be wrong in English

Please copy edit the paper by a native speaker.

Why 2018 and 2021 are selected?

The living area factor significantly impacts housing prices, negative inside the Inner Ring Road and outside the Outer Ring Road. Why?

The house orientation also positively affects the unit price of the house. The better 400 the house orientation, the higher the unit price What does it mean by better orientation?

Numbering of the figures may be wrong in MDPI format Figure 6.G1 and 6.G2

 

Results need to be expanded about what are the results imply, rather than stating which one is positive and negative, state which results are unexpected.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for doing suggested revisions.

Comments for author File: Comments.pdf

Author Response

Thanks for your comments. We have made some minor reversions and hope the manuscript has been improved accordingly.

Reviewer 3 Report

Concerning is a wrong word

104-113, missing citations.

Some citations have initials and most do not, check the citation format of MDPI and reformat all these.

2.3 Research Methodology should be research method

Lines 182-187, 218-228, 245-260 missing citations

In the following content, we only leave the year 2018 and 2021 as a comparison, why?

Polish English

On the other hand, from the overall regression coeffi- 339 cient, almost all the coefficients of MGWR were significant – only significant results were 340 drawn on the map, so what are the significant results? The following paragraph may state immediately (after rearranging the structure)

 “In 2018, the MGWR regression coefficients of 11 variables, namely, constant term, 354 area, transaction days, floor, total floor, orientation, number of bedrooms, building age, 355 building type, distance to the nearest subway station, and distance to the nearest bus sta- 356 tion were overall significant. However, the regression coefficient of distance to the nearest 357 primary school is not significant. In 2021, the MGWR regression coefficients of 11 varia- 358 bles were also overall significant, except for the number of bedrooms.”

339-341 may be moved before 354

Table 6 what do you mean by metro? Distance to metro? S_e?

Better state the full name when these abbreviations first appear

 

 

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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