Analysis of OFDI Industry Linkage Network Based on Grey Incidence: Taking the Jiangsu Manufacturing Industry as an Example
Round 1
Reviewer 1 Report
This paper examines the interconnectedness of various sub-sectors within manufacturing in the OFDI process. This is a well-written paper with a clear structure that flows properly. there are some aspects that may increase the quality of this paper.
- The introduction section is too short. Hence, the authors may expand this section to provide a solid background of their research.
- Research limitations are not stated. Such limitations would help other researchers in their future research directions.
- The research recommendations are introduced in a very limited manner. The authors are suggested to thoroughly expand this section to indicate how this research can be particularly useful from a practical standpoint.
Overall, this is a very good research paper.
Author Response
Point 1: The introduction section is too short. Hence, the authors may expand this section to provide a solid background of their research.
Response 1: To solve this problem, we have revised the article and have added to it in the introduction's already. The additions are as follows：
Current academic research on the factors influencing manufacturing OFDI has mainly focused on the host country’s environment and image. However, we believe that in addition to the factors already studied by scholars, there is likely to be herd following behaviour in enterprises' investment decisions, which is reflected in the industry spillover phenomenon. At the same time, as Jiangsu Province is the largest economic province in China, its economic behaviour will affect other provinces. Therefore, we choose Jiangsu Province's manufacturing OFDI as the research object and study the correlation of each sub-sector within the manufacturing industry in the OFDI process from the perspective of a social network, which helps to understand the closeness of industry linkage in OFDI from an overall perspective, as well as the influence of each industry itself and the relationship between each other.
Point 2:Research limitations are not stated. Such limitations would help other researchers in their future research directions.
Response 2: We have divided Part V into 3 parts, Conclusion, Limitations and Recommendations. The study’s limitations are as follows：
5.2 Limitations
This paper establishes a network based on grey correlation theory for the OFDI industry in the Jiangsu manufacturing industry. However, the industry correlation obtained by the grey incidence method is undirected, which leads to the links in the social network being undirected. This is a limitation of this paper. This paper only analyses the characteristics of a single network and does not explain why the network shows such characteristics. Therefore, subsequent research in this paper could start with these two points and optimise the choice of industry association methods to create directional links and use appropriate methods to analyse the reasons for these network characteristics.
Point 3:The research recommendations are introduced in a very limited manner. The authors are suggested to thoroughly expand this section to indicate how this research can be particularly useful from a practical standpoint.
Response 3: We have added recommendations as follows：
Based on the characteristics of the network, which is the fast dissemination of information among industries in the OFDI process in Jiangsu Province, the government should consider the guidance of the dissemination of positive investment information to prevent blind investment when guiding the OFDI policy. The information about the investment crisis should prevent the contagion of the crisis because investment enterprises are afraid of the emergence of a similar crisis and are deterred from moving forward.
In addition, the chemical raw materials and chemical products manufacturing industry, general equipment manufacturing industry, special equipment manufacturing industry, and transportation equipment manufacturing industry, as key industries in Jiangsu's OFDI industry-related network, have a greater impact on other industries. Still, the fact that they are at the lower end of the global value chain affects other industries' technological development [51]. Therefore, the authors believe that when the government formulates policies to support enterprises' technological innovation and development towards intelligence, it can tilt towards key industries and improve the technological level of other industries through the inter-industry spillover effect to improve the quality of OFDI in the entire manufacturing industry.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The authors present in a well-argued way that from the perspective of each node (respectively industry), the correlation coefficient between equipment manufacturing and other industries is significantly higher, ie the influence of equipment production on other industries is significantly higher.
The article is well structured, and the literature studied is relevant to the subject and contributes to improving the image highlighted by the authors.
But I would add the discussion section (which is currently missing), through which the authors correlate the results obtained by them with similar ones in the literature, perhaps with comparisons with other areas.
- on lines 74, 85, 238. 279 - the point before the square bracket must be deleted
Author Response
Point 1: But I would add the discussion section (which is currently missing), through which the authors correlate the results obtained by them with similar ones in the literature, perhaps with comparisons with other areas.
Response 1: We have divided Part V into 3 parts, Conclusion, Limitations and Recommendations. The study's limitations are as follows：5.2 Limitations
This paper establishes a network based on grey correlation theory for the OFDI industry in the Jiangsu manufacturing industry. However, the industry correlation obtained by the grey incidence method is undirected, which leads to the links in the social network being undirected. This is a limitation of this paper. This paper only analyses the characteristics of a single network and does not explain why the network shows such characteristics. Therefore, subsequent research in this paper could start with these two points and optimise the choice of industry association methods to create directional links and use appropriate methods to analyse the reasons for these network characteristics.
Point 2: On lines 74, 85, 238. 279 - the point before the square bracket must be deleted
Response 2:The point before the square bracket has been deleted.
Author Response File: Author Response.pdf
Reviewer 3 Report
The research has been well designed and conducted. Also, the reference has been complete and well cited. However, to some extent, the article was not expressed in a way that the “Grey Incidence Analysis” means for. The authors might want to take the following comments for the revision consideration.
The merit of applying the theory has been its rationality in adapting to the real world “black” in information quantity and/or quality, which enables the provision of practical solutions for the business decision. According to Prof. Deng, the analysis system would better be applied in the situation when part of information is “grey.” However, in this article, while the authors did include the incidence “points” matrix in the evaluation, the background information, from complete to black, was not clearly shown, or be more precisely, the “grey numbers” were not defined clearly enough to rationalize the “Grey Incidence” application.
In regard to the conclusion, indeed, “Grey Analysis” does not attempt to find the best solution, rather, is aimed to provide decision maker with techniques to make a better solution for real world problems. In turns, the conclusion looks more like to tell readers a “conclusionary” result of “Probability” vis-à-vis “Grey” analysis.
Author Response
Point 1: The research has been well designed and conducted. Also, the reference has been complete and well cited. However, to some extent, the article was not expressed in a way that the “Grey Incidence Analysis” means for. The authors might want to take the following comments for the revision consideration.
The merit of applying the theory has been its rationality in adapting to the real world “black” in information quantity and/or quality, which enables the provision of practical solutions for the business decision. According to Prof. Deng, the analysis system would better be applied in the situation when part of information is “grey.” However, in this article, while the authors did include the incidence “points” matrix in the evaluation, the background information, from complete to black, was not clearly shown, or be more precisely, the “grey numbers” were not defined clearly enough to rationalize the “Grey Incidence” application.
In regard to the conclusion, indeed, “Grey Analysis” does not attempt to find the best solution, rather, is aimed to provide decision maker with techniques to make a better solution for real world problems. In turns, the conclusion looks more like to tell readers a “conclusionary” result of “Probability” vis-à-vis “Grey” analysis.
Response 1: In response to your comments, we have made the following changes in section 3.2 of the article, which reads as follows:
However, provincial-wide OFDI for each industry segment is not a continuous and stable economic behaviour. This results in frequent fluctuations in OFDI data for each manufacturing industry segment in Jiangsu Province. The authors then used Granger's test to determine the association between industries. Still, through verification, we found that the OFDI data of some industries in this paper passed the smoothness test and were able to make causal judgments. Still, we had to exclude the non-smooth industries when building the association network. This made it impossible to analyse whether there was a spillover relationship between the OFDI industries in Jiangsu Province, but only obtained some of the industries before the correlations.
The use of grey incidence analysis can make up for the shortcomings of the Granger test. It does not have harsh requirements on the sample size, nor does it require the smoothness of the data, which blurs the data requirements. If the data requirements under Granger are black or white, then the data requirements under the grey incidence method are grey.
Grey correlation analysis is one of the basic theories of grey system theory, based on the degree of similarity between the geometry of different time series curves to judge whether the development trend between the series is consistent with judging the closeness of the connection between the two, reflected in the graphical representation of the closer the geometry of the folds. The higher the degree of synchronous change, the greater the correlation between the corresponding series and vice versa [30, 31].
Author Response File: Author Response.pdf
Reviewer 4 Report
The paper fulfills the stated purpose presented in the introductory chapter. The literature review, as well as the methodology employed, along with the data used in the paper, are all fit and correspond to the research paper objectives. The paper is highly interesting and recommended for publishing!
Author Response
Thank you very much for your approval.
Round 2
Reviewer 3 Report
The revision looks good to the reviewer.
