Static and Dynamic Evaluation of Financing Efficiency in Enterprises’ Low-Carbon Supply Chain: PCA–DEA–Malmquist Model Method
Round 1
Reviewer 1 Report
Please find attachment.
Comments for author File: 
Comments.pdf
Author Response
Dear Editor and Reviewers,
Thank you very much for giving us an opportunity to revise and re-submit our manuscript. We are very encouraged by this decision. We are grateful for your constructive comments, which are extremely helpful for us to polish the manuscript. We have revised the manuscript based on your comments and suggestions. We have highlighted our major changes in blue colour in the revised version. Below are our point-by-point responses to your comments and suggestions.
We have made our best efforts to revise the paper. We hope our revisions can satisfy you.
Kind Regards,
The Authors
Responses to Reviewer 1’s Comments
This is indeed a good read.
I have observed some fundamental flaws. Therefore, it requires major changes.
Authors’ Responses:
Thank you very much for your kind words and giving us an opportunity to revise and re-submit our manuscript. We have revised the manuscript based on your comments and suggestions.
- L 97-98 you people wrote “Carbon tax, carbon tariff, carbon trading, and other factors are added to improve the whole mode of production and reduce resource consumption “.
- Is the dual-carbon target (i.e., carbon peaking and carbon neutralization) forcing financial bubble in carbon credits? Perhaps you can read https://doi.org/10.3390/jrfm15080367. Establish the link.
Authors’ Responses:
Thank you very much for pointing this out. It is an extremely helpful comment. First, we re-read the literature (Yang, et al., 2018, Zhou, et al., 2021) and revised the original sentence.
Second, we add the relationship between the dual-carbon target and the financial bubble and point out the important role of the low-carbon supply chain (Cariou et al., 2019; Ghosh et al., 2022).
Please see the blue text on Pages 2 and 3.
References:
Cariou P, Parola F, Notteboom T (2019): Towards low carbon global supply chains: A multi-trade analysis of CO2 emission reductions in container shipping. INT J PROD ECON 208: 17-28.
Ghosh B, Papathanasiou S, Dar V, Gravas, K (2022): Bubble in Carbon Credits during COVID-19: Financial Instability or Positive Impact (“Minsky” or “Social”)?. J. Risk Financ. Manag 15, 367.
Yang L, Chen Y, Ji J (2018): Cooperation modes of operations and financing in a low-carbon supply chain. SUSTAINABILITY-BASEL 10, 821
Zhou X, Li T, Ma X (2021): A bibliometric analysis of comparative research on the evolution of international and Chinese green supply chain research hotspots and frontiers. ENVIRON SCI POLLUT R 28, 6302-6323
- Why did you use ‘PCA-DEA-Malmquist’? What are the assumptions and limitations of this model? How robust is this model? In fact, PCA mayn’t be a good calculator.
Authors’ Responses:
Thank you very much for the extremely helpful comments. We make the following clarifications.
Due to the characteristic of transforming multiple indicators into several representative comprehensive indicators, the PCA model can simplify complex problems without losing too much useful information, thus greatly improving the efficiency of analysis. In addition, the PCA model can also assign weights to each index according to the variance contribution rate. Therefore, the influence of human subjective factors on the research results is avoided. Because of these two advantages, the PCA model is widely used in management (Petroni and Braglia 2000,Hatami-Marbini et al. 2020). Combined with previous practices of supply chain scholars, we used the PCA model to measure the financial behavior of a low-carbon supply chain. Finally, we calculated the financing efficiency of a low-carbon supply chain by using the DEA-Malmquist model through behavioral scores of low-carbon supply chain finance and other indicators of low-carbon supply chain finance.
To ensure the validity of PCA in the context of our study, two statistical tests, the Barlett's test and the Kaiser-Meyer-Olkin test are conducted. The first test examines whether or not the intercorrelation matrix comes from a population in which the variables are non-collinear (i.e. an identity matrix) and the second test is a test for sampling adequacy. In both cases the tests support the view that the data are likely to factor well.
In the revised draft, we have pointed out in detail the advantages of the PCA model and the reasons why we use the PCA model to measure low-carbon supply chain finance behavior.
These arguments can be found in the blue text on Page 4.
References:
Hatami-Marbini A, Hekmat S, Agrell PJ (2020): A strategy-based framework for supplier selection: A grey PCA-DEA approach. OPER RES-GER, 1-35.
Petroni A, Braglia M (2000): Vendor selection using principal component analysis. J SUPPLY CHAIN MANAG 36, 63-69.
- Globally Carbon emission is persistent, read https://doi.org/10.1007/978-3-030-92957-2_10, when a time series is persistent having long memory (long range dependence) it is absolutely imperative to use Functional Principal Component Analysis (FPCA) and not PCA. FPCA works on the estimate of the long-run covariance function. Therefore, it can model a fractal time series, unlike PCA. How can you justify your stand?
Authors’ Responses:
Thank you very much for pointing this out. It is extremely helpful. We make the following clarifications.
PCA model can also be applied to time series data. For example, Florackis and Ozkan (2009) used the PCA model and a large sample of listed non-financial UK firms over the period 1999-2005 to calculate managerial entrenchment. Florackis and Ozkan (2009) pointed out the advantages and applicability of the PCA model.
Thanks to the reviewer for proposing the Functional Principal Component Analysis (FPCA) model. The FPCA model has advantages that the traditional PCA model does not have. Therefore, we point out in the conclusion that the model adopted in this paper needs to be improved, which needs to be further explored in subsequent studies.
Please see the blue text on Pages 4 and 15.
References:
Florackis C, Ozkan A (2009): The impact of managerial entrenchment on agency costs: An empirical investigation using UK panel data. EUR FINANC MANAG 15: 497-528.
- You should provide credible links to access Ruisi database L 286!
Authors’ Responses:
Thank you very much for pointing this out. It is an extremely helpful comment.
We have added credible links to access Ruisi database in the revised draft.
Please see the blue text on Page 8.
- Suggesting a pluralistic investigation where FPCA is an integral part.
Authors’ Responses:
Thank you very much for your insightful comments. We fully respect your viewpoint.
We did a lot of research on the differences between PCA and FPCA. FPCA is indeed a relatively cutting-edge model and has been less studied in China. In our study, we adopted the more popular PCA model. Although there is no strong frontier, we can still ensure that the PCA model can process panel data through a large number of classical literature analyses.
For example, Serap & Mert (2013) gathered annual data on energy consumption, real GDP per capita, energy prices, and financial development indicators for the period 1990 -- 2011, and constructed two indexes representing banking and stock market variables as an indicator of financial development employing Principle Component Analysis (PCA).
The FPCA model has advantages that the traditional PCA model does not have. Therefore, we point out in the conclusion that the model adopted in this paper needs to be improved, which needs to be further explored in subsequent studies.
Please see the blue text on Page 15.
Florackis C, Ozkan A (2009): The impact of managerial entrenchment on agency costs: An empirical investigation using UK panel data. EUR FINANC MANAG 15,497-528.
Çoban S, Topcu M (2013): The nexus between financial development and energy consumption in the EU: A dynamic panel data analysis. ENERG ECON 39, 81-88.
Author Response File: Author Response.pdf
Reviewer 2 Report
The paper develops a PCA-DEA-malmquist model to evaluate the financing efficiency of enterprises' low-carbon supply chain. The paper is well organized, and it can be published after following issues are resolved:
(1)The research motivation and research gap should be focused in the first section.
(2)It will be better if the detail steps of the proposed PCA-DEA-malmquist model are presented.
(3)There are vast majority of references related to DEA and green supply chain mangement practice. It will be better if more related references are reviewed especially in recent five years, such as:
1)Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs).
2)Energy efficiency evaluation of oil producing economies in Africa: DEA, malmquist and multiple regression approaches.
3)Efficiency assessment of seaport terminal operators using DEA Malmquist and epsilon-based measure models.
...
(4)It will be better if the practical implications could be highlighted in discussion section.
Author Response
Dear Editor and Reviewers,
Thank you very much for giving us an opportunity to revise and re-submit our manuscript. We are very encouraged by this decision. We are grateful for your constructive comments, which are extremely helpful for us to polish the manuscript. We have revised the manuscript based on your comments and suggestions. We have highlighted our major changes in blue colour in the revised version. Below are our point-by-point responses to your comments and suggestions.
We have made our best efforts to revise the paper. We hope our revisions can satisfy you.
Kind Regards,
The Authors
Responses to Reviewer 2’s Comments
- The research motivation and research gap should be focused in the first section.
Authors’ Responses:
Thank you very much for your comments. They are extremely helpful.
According to your comments, we have revised the first part of the paper a lot and deleted some redundant content. We further clarified the research motivation of low carbon supply chain financing efficiency evaluation and compared it with existing literature (Han & Wang 2018, Wang et al. 2021, Xia et al. 2022, Yang et al. 2018), indicating the important contribution of our research.
References:
Han Q, Wang Y (2018): Decision and coordination in a low-carbon e-supply chain considering the manufacturer’s carbon emission reduction behavior. SUSTAINABILITY-BASEL 10, 1686
Wang Y, Yu Z, Jin M, Mao J (2021): Decisions and coordination of retailer-led low-carbon supply chain under altruistic preference. EUR J OPER RES 293, 910-925.
Xia T, Wang Y, Lv L, Shen L, Cheng T (2022): Financing decisions of low-carbon supply Chain under Chain-to-Chain competition. INT J PROD RES, 1-24
Yang L, Chen Y, Ji J (2018): Cooperation modes of operations and financing in a low-carbon supply chain. SUSTAINABILITY-BASEL 10, 821
Please see the blue text on Pages 1-3 in the revised version.
(2) It will be better if the detail steps of the proposed PCA-DEA-malmquist model are presented.
Authors’ Responses:
Thank you very much for your comment. It is extremely helpful.
We have further introduced the detail steps of the proposed PCA-DEA-malmquist model in 3.1 "Model selection" in the revised version.
Specifically, in the process of using the PCA-DEA-Malmquist index model, we first constructed an index system for evaluating the financing efficiency of enterprises' low-carbon supply chain, including the total assets of enterprises, asset-liability ratio, commercial credit, and other traditional indicators for measuring financing efficiency. We innovatively designed the financial behavior scale of the low-carbon supply chain for enterprises and integrated it into a measurement index system. Secondly, to overcome the difficulty in measuring qualitative indicators, we collected corporate social responsibility reports of 205 listed companies and used principal component analysis (PCA) to calculate the weights of enterprises' financial behavior scale on the low-carbon supply chain. Finally, we used the DEA-BBC model for static analysis of efficiency value, and the DEA-Malmquist index model for dynamic analysis of efficiency value. Due to space limitations, the detailed formulas of PCA and DEA models will not be listed in this article.
Please see the blue text on Pages 4-5 in the revised version.
(3) There are vast majority of references related to DEA and green supply chain management practice. It will be better if more related references are reviewed especially in recent five years, such as:
1)Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs).
2)Energy efficiency evaluation of oil producing economies in Africa: DEA, malmquist and multiple regression approaches.
3)Efficiency assessment of seaport terminal operators using DEA Malmquist and epsilon-based measure models.
...
Authors’ Responses:
Thank you very much for the extremely helpful comments.
Based on your comments, we have updated the literature and content to include some of the latest research in the last five years.
References:
Ghosh B, Papathanasiou S, Dar V, Gravas, K (2022): Bubble in Carbon Credits during COVID-19: Financial Instability or Positive Impact (“Minsky” or “Social”)?. J. Risk Financ. Manag 15, 367
Huang C, Chan FT, Chung SH (2022) Recent contributions to supply chain finance: towards a theoretical and practical research agenda. INT J PROD RES 60, 493-516
Tachega MA, Yao X, Liu Y, Ahmed D, Li H, Mintah C (2021): Energy efficiency evaluation of oil producing economies in Africa: DEA, malmquist and multiple regression approaches. Clean. Environ. Syst 2, 100025
Wang C, Nguyen N, Fu H, Hsu H, Dang T (2021): Efficiency assessment of seaport terminal operators using DEA Malmquist and epsilon-based measure models. Axioms 10, 48
Wang Y, Yu Z, Jin M, Mao J (2021): Decisions and coordination of retailer-led low-carbon supply chain under altruistic preference. EUR J OPER RES 293, 910-925
Zhou F, Wang X, Lim MK, He Y, Li L (2018): Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs). J CLEAN PROD 196, 489-504
…
(4) It will be better if the practical implications could be highlighted in discussion section.
Authors’ Responses:
Thank you very much for the extremely helpful comments.
We fully respect your viewpoint that the practical implications could be highlighted in discussion section. Therefore, we added a separate section of practical implications to the conclusion of the revised draft.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
I am satisfied with the changes.
