Sensitivity Analysis of Optimal Commodity Decision Making with Neural Networks: A Case for COVID-19
Round 1
Reviewer 1 Report
Dear author(s)
It was my pleasure to review your manuscript entitled “Sensitivity Analysis of Optimal Commodity Decision Making with Neural Networks: A case for COVID-19 ” and advise you to prosper your current research project. In my view, your topic has touched on a critical issue in a fascinating context. However, there are many spaces to be improved in terms of argumentation, theoretical background, research method, and findings. I hope my below comments would help you develop your work into groundbreaking research in your domain.
The positioning of the paper is not entirely clear. It is better to explain the gap in this article further.
The introduction should clearly illustrate (1) what we know (the key theoretical perspectives and empirical findings) and what we do not know (major, unaddressed puzzle, controversy, or paradox does the study address, or why it needs to be addressed and why this matters) and (2) what we will learn from the study, and how the study fundamentally changes, challenges, or advances scholars’ understanding. Much sharper problematization is required so that the introduction draws the reader into the paper. At the end of the introduction, we should have a clear idea of what the paper is about (i.e., its motivation, the gap in understanding that the paper is trying to address, and a summary of theoretical contributions).
Paragraph 3 explains what we need to find out.
Paragraph 4 explains briefly what this paper will do to find out, the method, etc.
Paragraph 5, with no references, explains the structure of this paper.
This is one of the most critical parts of the paper that found lacking detail.
The method should be adequately described to show how the research was conducted to improve clarity and transparency.
What were the reasons for using the method?
• How is validity and reliability done?
The conclusion shows the final results of your research (you need a conclusion for your research). Also, the conclusion should be revised to highlight the aims of the study, summarize the finding, and the significance and usefulness of the study.
It is better to add these two parts (Limitation and future directions) after the conclusion.
Best of luck with the further development of the paper.
Author Response
Please see the file of responses.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
I have the following concerns.
1. Robust estimates of your method are not given. It is necessary to clarify the stopping rule in order to maximize the expected reward.
2. Clarify what the efficiency of using ANN is. Show the gain compared to the model [20] by the runtime parameter. What sample size was used for training the network.
3. What about jump diffusion?
4. A similar article was published in the journal Inventions (mdpi), 2022, 7(3), 82. Pay attention to it.
5. There are no articles on this issue for 2022 in the references.
Author Response
Please see the file of responses.
Author Response File: Author Response.pdf
Reviewer 3 Report
This paper presents a method with ANN to study the impact of demand shocks on a producer’s decision to sell a commodity during economic turmoil, caused by events such as COVID-19. My major comments are listed below.
1. The link between COVID-19 and the research problem studied in this paper is relatively weak, or at least not well illustrated. In particular, the application part did not extensively describe the issues caused by COVID-19 in the research problem, and how the proposed method could resolve it. As the major focus of this paper, such a link needs to be better described.
2. Similarly, the real-life data are not extensively involved in the analyses and application. Also, this paper does not seem to compare the performance of the proposed models to that of popular existing models. The applicability and outperformance of their new model are therefore difficult to see for the readers.
3. The paper needs to be carefully proofread. Even at the beginning of introduction the sub-title “Discussion on GBM and mean reverting processes” is clearly redundant. In some places, “Figure” should be used instead of “plot”. Those are just two simple examples. Also, please be consistent with illustration style. The Figure 1 has inappropriate X-axis label with unnecessary blank space left on the right side.
Author Response
Please see the file of responses.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Dear authors
Hope you are doing well. According to the review of this article, the corrections have been made.
Good luck
Reviewer 2 Report
I am almost satisfied with the answers to my comments.
Reviewer 3 Report
I thank the authors for revising the paper. I support publication with no further concerns.
