Round 1

Reviewer 1 Report

The paper seems interesting, if we analyse the topic.

But it requires a lot of changes.

First of all it's necessary to define better the aim.

The literature review must be improved. I suggest some papers below.

The research question must be deleted, in fact you develop research hypotheses (RHs). Moreover, the RHs must be linked with literature review in section 2, not presented in section 3.

I suggest to reduce RHs, they are too much.

I don't understand why you present case studies if you've a quantitative analysis. They are too poor and not in line with the paper. 

My suggestion is to concentrate on quantitative results. Moreover I ask you to redefine the conclusions and managerial implications

 

REFRENCES SUGGESTED

ESG and corporate financial performance: the mediating role of green innovation: UK common law versus Germany civil law

Chouaibi, S., Chouaibi, J., Rossi, M. EuroMed Journal of Business, 2021  

To invest or to harvest?: Corporate venture capital ambidexterity for exploiting/exploring innovation in technological business

 Economic value added and shareholders’ wealth creation: the portrait of a developing Asian country
Madan Lal Bhasin, Junaid M. Shaikh Related 
https://doi.org/10.1504/IJMFA.2013.053208  

The impact of corporate characteristics on the financial decisions of companies: evidence on funding decisions by Italian SMEs

Rossi, M., Lombardi, R., Siggia, D., Oliva, N. Journal of Innovation and Entrepreneurship, 2015, 5(1), 2  

The role of venture capital funds in financing innovation in Italy. Constraints and challenges for innovative small firms

Rossi, M. International Journal of Globalisation and Small Business, 2015, 7(2), pp. 162–180   Fostering tacit knowledge sharing and innovative work behaviour: an integrated theoretical view
Vikas Gupta; Asha Thomas
DOI: 10.1504/IJMFA.2019.104134    

Financing innovation: Venture capital investments in biotechnology firms

Mission statements and company financial performance revisited

https://doi.org/10.1504/IJMFA.2012.047855

Author Response

Dear Reviewer,

Many thanks for your valuable comments that enable us to submit a better paper.

Here are the revisions we performed in line with your comments:

 

Comment No. 1

 

Moderate English changes required

 

Revisions made by the authors

 

The proofreading was implemented to the entire text of the paper.

 

Comment No. 2

 

First of all it's necessary to define better the aim

 

Revisions made by the authors

 

The aim is now defined better in lines 60-66.  

 

Comment No. 3

 

The literature review must be improved. I suggest some papers below.

 

Revisions made by the authors

 

All suggested references have been included into the section “7 Limitations and further research gaps”:

• ESG and corporate financial performance: the mediating role of green innovation: UK common law versus Germany civil law. Chouaibi, S., Chouaibi, J., Rossi, M. EuroMed Journal of Business, 2021,   Text and reference added in lines 752-754
• Economic value added and shareholders’ wealth creation: the portrait of a developing Asian country. Madan Lal Bhasin, Junaid M. Shaikh Related 
  https://doi.org/10.1504/IJMFA.2013.053208 Text and reference added in lines 755-760.
• The impact of corporate characteristics on the financial decisions of companies: evidence on funding decisions by Italian SMEs. Rossi, M., Lombardi, R., Siggia, D., Oliva, N. Journal of Innovation and Entrepreneurship, 2015, 5(1), 2.  Text and reference added in lines 761-765.
• The role of venture capital funds in financing innovation in Italy. Constraints and challenges for innovative small firms. Rossi, M. International Journal of Globalisation and Small Business, 2015, 7(2), pp. 162–180.   Text and reference added in lines 766-773.
• Fostering tacit knowledge sharing and innovative work behaviour: an integrated theoretical view Vikas Gupta; Asha Thomas DOI: 10.1504/IJMFA.2019.104134    Text and reference added in lines 773-779
• Financing innovation: Venture capital investments in biotechnology firms. Mission statements and company financial performance revisited https://doi.org/10.1504/IJMFA.2012.047855. Text and reference added in lines 779-781.

 

Comment No. 4

 

The research question must be deleted, in fact you develop research hypotheses (RHs). Moreover, the RHs must be linked with literature review in section 2, not presented in section 3.

 

Revisions made by the authors

 

The RQs have been deleted in Section 3. The corresponding text in section 7 has been adjusted.

Hypotheses have been moved to Introduction, please see the lines 76-86.

 

Comment No. 5

 

I don't understand why you present case studies if you've a quantitative analysis. They are too poor and not in line with the paper.

 

 

Revisions made by the authors

 

We would kindly request for case studies to remain in the paper. Explanation of the reasons is provided in lines 242-254:

 

“Case studies dealing with implementing innovation activities on a national level were chosen to analyze South Korea's national innovation system (NIS) development process to extract the relevant contributing factors. Furthermore, a case study focusing on innovation activities in small and medium-sized enterprises (SMEs) was selected to analyze if and how national firms benefit from the South Korean innovation system. The general factors contributing to innovation in a functioning system should not differ much from a national to an organizational level, so it was essential to analyze both perspectives to detect parallels or particularities. In order to gain a better understanding of innovation in South Korea, the selected case studies were summarized, and questions to be answered through the analysis were identified. The problems the case deals with were described in the next step, and the case-specific processes and measures taken were explained. The part "results" lists the effects the implemented processes had on the case-specific problems, and out of the analysis up to this point, the factors contributing to innovation could be extracted in this part.”

 

 

Comment No. 6

 

My suggestion is to concentrate on quantitative results. Moreover I ask you to redefine the conclusions and managerial implications

 

Revisions made by the authors

 

                In sections 6-8, the focus is on quantitative factors.

The managerial implications have been added in lines 832-843.

 

 

We hope that the revisions made would meet your expectations.

 

Best regards,

The Authors

Author Response File: Author Response.pdf

Reviewer 2 Report

There are two fundamental issues that the authors did not address:

1. Time series where used but the influence of time was not analyzed (e.g. series stationarity).
2. From the start a multiple linear regression was used but for the model (improperly identified as a research method), but the authors did not offer any convincing argument for it.

Therefore, I considerer that the article has serious flaws and should be revised. 

Author Response

Dear Reviewer,

Many thanks for your valuable comments that enable us to submit a better paper.

Here are the revisions we performed in line with your comments:

 

Comment No. 1

 

English language and style are fine/minor spell check required.

 

Revisions made by the authors

 

The proofreading and spell check was implemented to the entire text.

 

Comment No. 2

 

Time series where used but the influence of time was not analyzed (e.g. series stationarity).

 

Comments by the authors

 

We did not analyze stationarity because stationarity is essential when making predictions about the future, as far as we are aware. Since we did not do the regression analysis for prediction purposes but rather analyzed the composition of innovation with past data.

Time series data was used to gather enough data points for the regression analysis to work. We also stated in our paper that the research does not deliver reliable predictions but is an indication of the importance of the analyzed quantitative innovation factors.  

 

Comment No. 3

 

From the start a multiple linear regression was used but for the model (improperly identified as a research method), but the authors did not offer any convincing argument for it.

 

Revisions made by the authors

 

An additional explanation why a multiple linear regression has been chosen is added in lines 397-402.

 

 

We hope that the revisions made would meet your expectations.

 

Best regards,

The Authors

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

No further comments.

Author Response

Dear Reviewer,

Many thanks for your valuable comments that enable us to submit a better paper.

Here are the revisions we performed in line with your comments:

Comment No. 1

This is an interesting study of innovation and growth in South Korea, however it doesn't fit into the theme of sustainability clearly enough. So please make the link of the paper to sustainability clearer so if fits the journal.

Revisions made by the authors

A new paragraph at the beginning of Introduction (lines 31 – 45) has been added, explaining the link between economic growth, innovation and sustainability.

Comment No. 2

There are also some issues with the modelling that the authors need to consider; there appears to be insufficient data for the estimation, the authors should consider using a panel data approach.

Comments by the authors  

Since the GDP can be correlating with, and be explained through numerous different variables, the regression had to be performed with enough datapoints over a sufficient number of years in order to achieve a solid reliability of the results. In this paper, the data used for the multiple regression was retrieved from the World Bank. Data from 1995 until 2018 was analyzed.

In this paper, a linear multiple regression model was used, of which the model specification states, that Yi, the dependent variable, has to be modeled as the function of the independent variables with corresponding coefficients, together with the constant term (ß0) and an error term (e). Before running the code for the model, an exploratory data-analysis was conducted in order to get to know the features of the data and to check if it is suitable for the model. For the regression, the chosen model fit a linear equation to the data observed. When using linear, multiple regression, the value of the dependent variable y, is associated with every value of the independent variable x. Through the ordinary least-squares model, the place of the line that is virtually fitted in between the datapoints, was being detected mathematically.

The ordinary least squares model calculated the best fit for the line by the minimization of the sum of the squares of the vertical difference from each of the data points to the line. Thus, the line in the regression model was virtually drawn where the datapoints were the closest to the line and the variance was minimized. After running the linear, multiple least squares regression with the selected independent and dependent variables, a summary of the model could be printed, the results could be viewed, and the data could be analyzed. The multiple regression was run in the program R, which is a free software for statistical computing.

In order to avoid an autocorrelation bias, which often occurs in time series data, the Durban Watson Test was run for the regression model. This test is supposed to avoid a misinterpretation due to positive autocorrelation of the residuals, which could lead to an overestimation of the statistical significance of the results

Time series data was used to gather enough data points for the regression analysis to work. We also stated in our paper that the research does not deliver reliable predictions but is an indication of the importance of the analyzed quantitative innovation factors.

Comment No. 3

Also the model needs to include the relevant control variables and account for the non-stationarity of the data.

Comments by the authors

We did not analyze stationarity because stationarity is essential when making predictions about the future, as far as we are aware. Since we did not do the regression analysis for prediction purposes but rather analyzed the composition of innovation with past data.

 

We hope that the revisions made would meet your expectations.

Best regards,

The Authors

Author Response File: Author Response.docx