Transmission Mechanism of Post-COVID-19 Emergency Supply Chain Based on Complex Network: An Improved SIR Model
Round 1
Reviewer 1 Report
The article is devoted to developing an improved SIR model based on a complex network to study the law of propagation of the risk of the emergency supply chain. The study's relevance is justified by the fact that, since the COVID-19 epidemic has swept the whole world, the emergency supply chain is facing severe uncertainty risks. To maintain the stability of the emergency supply, measures are being prepared to prevent risks and emergencies. Therefore, in this study, the authors first calculate the initial risk value using a fuzzy integrated assessment approach and then build an improved SIR model based on a complex network to investigate the law of distribution of emergency supply chain risk. As a result of modeling, the authors draw several conclusions. A large number of nodes becomes the initial source of risk, and the risk spreads faster. The higher the initial level of infection, the faster the spread of risk. The rate of recovery of network nodes is inversely related to the degree of spread of risk. Appropriately increasing the network node exclusion rate contributes to improving the stability of the emergency supply chain network. Considering the law of distribution of emergency supply chain risks, this article proposes appropriate risk prevention measures. It proposes establishing an early warning system for the risks of nodal enterprises in combination with a targeted immunization strategy.
Despite the satisfactory quality of the article, some shortcomings need to be corrected.
- Expanding the abstract with numerical results obtained within the study is recommended.
- It is recommended to define the aim of the research.
- The concrete improvement of the SIR model made by the authors should be described in detail in the Methods section.
- It is unclear which data is used for the experimental investigation.
- In line 291, it is a mistake. It should be “S is converted into I”
- Usually, researchers use state “E” for the exposed state in modification of SIR models. Authors propose it for “eliminated”. Maybe it would be better to use another name of the state, e.g. D – deleted.
- In model (1), proposed by the authors, the equation for state E is missed.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper has a nice topic but there is a lack of representation. The main problem of this study is that the authors use methods and approaches, but there is no significance of those methods as they are not discussed how this model uses those methods to find results.
1. Define clearly the "Improved SIR model" in the Introduction section under the subsection "1.1. Improved SIR model" and why is it called improved.
2. This paper selects a fuzzy comprehensive assessment approach. Provide either a flowchart, pseudocode, or algorithm, or write an understandable representation of the method related to this SIR model.
3. The study uses a risk propagation network. Provide the algorithm for the risk propagation simulation. The use of the algorithm is not important but how a tool is being used for research, is the contribution. Just putting a name and pictures does not justify the contribution.
4. As it is an "Improved SIR model", provide improvement and changes in the algorithm than a traditional SIR model clearly.
5. There is no evidence of data. Provide questionnaires, location/places of enterprises & universities. What kind of supply chain did the authors consider?
6. How does the financial risk of the study "Assessing the financial rеsоurсе curse hypothesis in Iran: Thе nоvеl dynаmiс АRDL approach" can be analyzed by this improved SIR model?
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
The paper deals with the stability maintaining of the emergency supply chain (ESC). The authors first calculate the initial risk value using the fuzzy comprehensive evaluation approach and then build an improved SIR model based on a complex network. Throught simulation of improved SIR model based on a complex network simulation were identified four main causes of faster spread of risk. In the conclusion, authors proposes relevant risk prevention measures and suggests that a risk early warning system of node enterprises should be established in combination with the target immunization strategy.
I appreciate that the process of creating a SIR complex model and the results of simulations are thoroughly described and justified in chapter 5. I can state that the methodology used led to relevant results. The research results can lead to the improvement of risk management of the ESC.
Recommendations for the article improving:
1. Change the letter e to a capital E in line 54.
2. Why the model is called „The Complicated Network-Based SIR Model“. Can it be called complex model...., as in the text? Line 152
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
The research on the topic of the Post-COVID-19 Emergency Supply Chain is important and great to discover. But as for details I would like to ask authors to correct before printing, then:
1.Please add a clear definition of Emergency Supply Chain
2. Authors should develop a "true" discussion section, in which they broadly comment on the results obtained. I would like to know how the results were similar to or different from other studies. This is not clear.
3. The implications for research, theory, practice and society are not clear though I can see that these aspects can be elaborated further.
4. What makes this study unique and how are the findings advancing the field? Or what are they contributing to practice?
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Thanks for the authors for their analysis and considering of reviewer's comments and recommendations. I will support that publication.
Author Response
It's a great honor to get your recognition of this work and thank you for improving the quality of the paper.
Reviewer 2 Report
The revision is good. Few amendments are required.
1. Provide an author's contribution table in the Literature review section.
2. Add the Answer to the Point 6 of the previous questions in the discussions section.
3. Provide insights for "A bi-objective robust possibilistic cooperative gradual maximal covering model for relief supply chain with uncertainty" and add in the discussions section.
Author Response
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Author Response File: Author Response.pdf
