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Peer-Review Record

Comparative Study on Low-Carbon Strategy and Government Subsidy Model of Pharmaceutical Supply Chain

Sustainability 2023, 15(10), 8345; https://doi.org/10.3390/su15108345
by Yan Wen and Lu Liu *
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Sustainability 2023, 15(10), 8345; https://doi.org/10.3390/su15108345
Submission received: 16 April 2023 / Revised: 9 May 2023 / Accepted: 17 May 2023 / Published: 21 May 2023

Round 1

Reviewer 1 Report

This paper developed a differential game model of the secondary pharmaceutical supply chain consisting of pharmaceutical enterprises and medical institutions in the context of centralized drug procurement policy, considering the government subsidy and consumers' low-carbon preferences. It has some significance. However, I have the following concerns.

1.        In Literature Review, the literature related to the government subsidy in a supply chain should be reviewed. For example:

Barman A., De P.K.,  Chakraborty A.K., Lim C.P., Das R., Optimal pricing policy in a three-layer dual-channel supply chain under government subsidy in green manufacturing, Mathematics and Computers in Simulation, 2023, 204, 401-429

Xu C., Wang C., Huang R., Impacts of horizontal integration on social welfare under the interaction of carbon tax and green subsidies, International Journal of Production Economics, 2020, 222, 107506

It is suggested that author(s) introduce the papers related to the supply chain with different power structures into the literature review, and identify the differences between the previous papers and current paper. Thus, the authors have to differentiate further and rethink about their work's innovations.

2 In Numerical Analysis, where the initial values of the parameter comes? Explanations of the basis for setting the values of these parameters should be presented.

3)A discussion about the application in real context is essential to support the reader in evaluating the effectiveness of the model. 

5) There are not enough managerial insights in this paper. Merely all the Propositions the presents of mathematical results. But authors should provide managerial insights to the market, pharmaceutical enterprises and sometimes government according to the background of the paper.

6) In Appendix A, the Proofs of Propositions should provide the second-order optimality conditions.  

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper constructs a differential game model of the secondary pharmaceutical supply chain, in order to identify the effects of health insurance reimbursement and consumers' low-carbon preferences, with respect to under four government subsidy models.

The main discussion in the Introduction section (e.g., lines 34-70) are provided without any references from the literature or from reports.

The literature review section does not clearly identify the research gaps and how the manuscript intends to handle these. For instance, the methodologies of the earlier studies in the literature are generally not mentioned, making it difficult to identify if and how the manuscript has a methodological contribution.

The parameters and notation need to be more clearly defined in Section 3.

Table 1 denoting the notation and definitions needs to be moved to (or referenced to) in an earlier place. During the statements of the assumptions, the variables G(.) (Equation 1), R(.), S(.) (Equation 3) are not defined.

Derivation of the equations 1 – 8 and the underlying models need to be better explained.

 

Implications of the models and results in Section 4 need to be better elaborated, providing insights beyond  theoretical results.  

 Minor editing of English language required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The author proposed a game model to illustrated pharmaceutical supply chain on its low carbon strategy and compared several scenarios to find the possible insight for the industry. The paper is really interesting and insightful.

nevertheless, I think the authors could improve their current work. 

1. The number of references are still quite limited. There are many other studies (although not directly related with pharmaceutical industry) that cover the game model such as this one. Additional references might help to understand the current research position better.

2. There are several assumptions that being used for developing the model. One of them is the assumption of deterministic linear function for representing demand. Is there any other reference that might back up such choices? Why linear? The 4th assumption mentioned about customer surplus. I did not find the explanation about this both in text and appendix. How can the author calculate it? I think there should be more explanation about it.

3. I hope the discussion regarding the results can help the reader understand better about this topic as it is still quite limited whereas figures itself are not selfexplanatory.

 

I think moderate review can be done, especially in the discussion part.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

This paper has been improved after revision. 

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