What Can Machine Learning Teach Us about Australian Climate Risk Disclosures?
Round 1
Reviewer 1 Report
Interesting study concerning an increasing need to have information about risk related with climate changes.
A comparison with similar studies obtained in other economic regions could be useful to understand some of the conclusions presented.
The accuracy tests performed for the output of the 4 mah«chine learning models could be described with more detail to provide a better understanding of the nature of the evaluation parameters.
Author Response
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Reviewer 2 Report
This paper deals with “What can machine learning teach us about climate risks?”. The manuscript needs to be revised according the following comments.
1- The Abstract is not sufficiently clear, it doesn't include the private information about the work.
2- Please avoid using abbreviations in the Abstract if possible.
3- I would like to see more discussion of the literature so that I can clearly identify the article relates to competing ideas. More in-depth analysis of the author's contribution of this paper in the introduction section.
4- The manuscript needs to better organize and write.
5- The results of figures should be explained. No physical explanation is provided. Only the results are presented.
6- The results should be extended to support the proposed approach effectively.
7- The author is encouraged to provide a greater depth of discussion about each figure and Table, improve the figure quality and modify the conclusion as well.
Author Response
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Reviewer 3 Report
The paper presents interesting research on identifying the priorities and strategies of Australian companies managing climate risk. Overall, the paper is well written with a flow that is very easy to follow. All the methods and discussions are supported by published literature. I think the paper is suitable for the journal's readership, and the novelty is appropriately justified.
I have a concern with the title of the paper. I think the title of the paper, What can machine learning teach us about climate risks?, may be misleading. The title is vague and doesn't reveal enough about what the paper is about. For instance, machine learning is employed in a wide range of climate research applications, from risk prediction and modelling to strategy evaluation and planning, but in this work, it is used to analyze CRDs from major Australian firms. I advise the authors to be more descriptive and match the title to the content of the article.
Some minor comments:
· Lines 372-390 can be moved to methodology.
· Figures 4 and 5 are blurred. Please replace these figures with high-resolution images.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
The article makes good use of support vector machine and k-means clustering to detect and classify Australian companies by climate risk type and climate risk response. In my opinion, the contribution is innovative, well-structured and suitable for the prestigious journal Sustainability.
Author Response
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Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
According to me, the current status of the paper can be accepted for publication.
