Research on the Sustainable Development Path of Regional Economy Based on CO₂ Reduction Policy

Round 1

Reviewer 1 Report

In this manuscript, Qiu and co-workers utilized data envelopment analysis technique to measure the Green Total Factor Productivity. This report clearly helped China to find out a balance between the economic development and the sustainability of environment. It will be great if the mode can provide some predictions about the growth rate in next 10-20 years. It is also valuable to provide some information about the cost of achieving the target RE development.

Author Response

In this manuscript, Qiu and co-workers utilized data envelopment analysis technique to measure the Green Total Factor Productivity. This report clearly helped China to find out a balance between the economic development and the sustainability of environment. It will be great if the mode can provide some predictions about the growth rate in next 10-20 years. It is also valuable to provide some information about the cost of achieving the target RE development.

Reply: Thank you very much for your confirmation. We have made a forecast for the growth rate in the next 10-20 years according to your suggestions, and have provided some information to achieve sustainable development of the regional economy. See details in the revised paper as follows:

In addition, from the change trend of green total factor productivity growth rate in various years in Figure 4, it can be predicted that the growth rate of green total factor productivity will still be in a slow growth trend in the next 20 years, and the growth rate will significantly increase with the introduction of carbon emission reduction policies.

From the above results, it can be concluded that improving green total factor productivity in various regions requires the government to increase investment in education and research and development, and formulate corresponding policies to adjust the industrial structure and marketization level, which can effectively improve the sustainable development level of the regional economy and ensure long-term, effective and rapid development of the regional economy.

Author Response File: Author Response.pdf

Reviewer 2 Report

It is an interesting idea to study Sustainable Development Path of Regional Economy based on CO₂ Reduction Policy. The research content and results of the paper can provide some available information for the peers. A revision is needed and I recommend the author to improve the manuscript according to the following comments:

 

1. Introduction: the study analyzes the influencing factors of TFP, What are the influencing factors?

2. Some sentences are too long to understand, and should be reorganized. For example: “Sustainable RE development means that...and thus an intensive economic growth mode can be realized.”

3. What does an increase in TFP mean for carbon emissions?

4. SD RE: Sustainable Development of regional economy?

5. “EF_cement denotes CO produced per ton of cement produced 2”, I do not know the meaning.

6. References were needed for equation (1).

7. Section 3.2: What are the model variables in Figure 2 based on? Or, why did you choose these variables?

8. “From Table 1...while the region with lower carbon emission is the eastern region of China. ” I think some specific analysis of the information in Table 1 is necessary.

9. Which cities belong to the central, western, and eastern regions of China, respectively. (Table 1, Figure 3, Figure 4...)

Author Response

It is an interesting idea to study Sustainable Development Path of Regional Economy based on CO2 Reduction Policy. The research content and results of the paper can provide some available information for the peers. A revision is needed and I recommend the author to improve the manuscript according to the following comments:

1.Introduction: the study analyzes the influencing factors of GTFP, What are the influencing factors?

Reply: Thank you very much for your kind comments. The influencing factorsof green total factor productivity include technological innovation, management innovation, and the degree of openness to the outside world. This comment was added in Section 2.2 of the revised paper.

2.Some sentences are too long to understand, and should be reorganized. For example: “Sustainable RE development means that...and thus an intensive economic growth mode can be realized.”

Reply: Thank you very much for your kind comments. The long sentences have been reorganized in the revised paper. For example:

The sentence “Sustainable RE development means that...and thus an intensive economic growth mode can be realized” was changed to “Sustainable RE development refers to the pursuit of not only the quantity of economic development, but also the assurance of quality in its development process. This is to achieve cleaner productionandcivilizedconsumption, thereby improving the efficiencyofeconomicactivities. Ultimately, it is to realize anintensiveeconomicgrowthmode^[16-17].”

3. What does an increase in GTFP mean for carbon emissions?

Reply: Thank you very much for your kind comments. The mean of increasing GTFP on carbon emissions was added in Section 2.2 of the revised paper. As follows:

Therefore, an increase in GTFP indicates a decrease in carbon emissions and energy consumption, so the implementation of carbon emission reduction policies can improve green total factor productivity. That is, the higher the implementation of carbon emission reduction policies in the region, the corresponding increase in green total factor productivity in the region, and the corresponding reduction in carbon emissions in the region.

4. SD RE: Sustainable Development of regional economy?

Reply: Thank you very much for your kind comments. SD RErepresented“Sustainable Development of Regional Economy”.

5. “EFcement denotes CO produced per ton of cement produced 2”, I do not know the meaning.

Reply: Thank you very much for your kind comments. This sentence was changed to “EF_cementrepresents the CO₂ generated per ton of cement produced.”

6. References were needed for equation (1).

Reply: Thank you very much for your kind comments. The reference was added in the revised paper as follows:

[24]Li, W., Yang, G., Li, X. (2019). Modeling the evolutionary nexus between carbon dioxide emissions and economic growth. Journal of Cleaner Production, 215(APR.1), 1191-1202. doi: https://doi.org/ 10.1016/j.jclepro.2019.01.100

7. Section 3.2: What are the model variables in Figure 2 based on? Or, why did you choose these variables?

Reply: Thank you very much for your kind comments. The reasons for selecting the model variables in Figure 2 have been explained in the revised paper as follows:

In the present study, based on previous research experience and according to the current regional economic development situation, six variables were selected as explanatory variables, which have a significant influence on carbon emissions[26].

8. “From Table 1...while the region with lower carbon emission is the eastern region of China. ” I think some specific analysis of the information in Table 1 is necessary.

Reply: Thank you very much for your kind comments. The information in Table 1 has been analyzed in detail. Please see details in the revised paper as follows:

In Table 1, Shanxi, Henan, Anhui, Hubei, Jiangxi, and Hunan belong to the central region of China; Shaanxi, Sichuan, Yunnan, Guizhou, Guangxi, Gansu, Qinghai, Ningxia, Xinjiang, Inner Mongolia, Chongqing, and Tibet belong to the western region of China; Hebei, Beijing, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Hainan, Jilin, Heilongjiang, and Liaoning belong to the eastern region of China.According to Table 1, the top three provinces with total carbon emissions are Shandong, Shanxi, and Hebei, with total carbon emissions of 935.2715 million tons, 702.1321 million tons, and 695.1835 million tons, respectively. In addition, it can be seen that the top three provinces with carbon emission intensity are Hebei, Ningxia, and Jilin, with carbon emission intensities of 3.76t · 1000USD-1, 2.18t · 1000USD-1, and 2.16t · 1000USD-1, respectively.From Table 1 and the above results, it can be seen that there are significant differences in carbon emissions and intensity among regions in China, and regions with higher carbon emissions intensity are mostly located in the central and western regions of China, especially in the western region, where the provinces with higher carbon emissions intensity are the most, while regions with lower carbon emissions are mostly located in the eastern region of China.

9. Which cities belong to the central, western, and eastern regions of China, respectively. (Table 1, Figure 3, Figure 4...)

Reply: Thank you very much for your kind comments. We have now described the provinces included in the eastern and western regions of China. See the details in the revised paper.

In Table 1, Shanxi, Henan, Anhui, Hubei, Jiangxi, and Hunan belong to the central region of China; Shaanxi, Sichuan, Yunnan, Guizhou, Guangxi, Gansu, Qinghai, Ningxia, Xinjiang, Inner Mongolia, Chongqing, and Tibet belong to the western region of China; Hebei, Beijing, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Hainan, Jilin, Heilongjiang, and Liaoning belong to the eastern region of China.

 

In addition, We checked the whole text and corrected all the grammatical and spelling mistakes.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study incorporated CO2 emissions into economic model to calculate TFP efficiency value and its growth rate, examined the productivity of each region in China, and discussed the driving factors behind it. This is an valuable research which can give relevant policy suggestions that can help China's sustainable economic development. There are some specific comments to improve the manuscript.

 

1. Author said that to ensure the regional economic(RE) development and ensure that the environmental level does not decline, Carbon Reduction Policy(CRP) is crucial. What is the importance of carbon reduction policies?

2. What regression models have been used to analyze the factors that influence TFP and its growth rate? Please explain in the introduction.

3. Section 2.2, What are the carbon reduction policies?

4. Please supplement economic model (1) with sources, or references.

5. Does Table 1 include all the provinces of China? 2001-2020 or 2000-2020? Optimize Table 1 to divide the province into central, western and eastern regions of China.

6. Section 5.2, What is fixed-effects model?

Author Response

This study incorporated CO2 emissions into economic model to calculate TFP efficiency value and its growth rate, examined the productivity of each region in China, and discussed the driving factors behind it. This is an valuable research which can give relevant policy suggestions that can help China's sustainable economic development. There are some specific comments to improve the manuscript.

1. Author said that toensuretheregionaleconomic(RE)developmentandensurethattheenvironmentalleveldoesnotdecline,CarbonReductionPolicy(CRP)iscrucial. What is the importance of carbon reduction policies?

Reply: Thank you very much for your kind comments. The importance of carbon emission reduction is specifically described in Section 2.3 of the revised paper. See below:

AscanbeseeninFigure1,eachregionhasachievedthegoalofimprovingtheproductioncapacityoftheregionaleconomy,reducingtheenergyconsumptionlevelandloweringtheenvironmentalpollutionlevelbyimplementingthestructuraladjustmentaspect,increasingthetechnologicaldevelopmentaspectandcontrollingtheCO2incrementaspectofthecarbonemissionreductionpolicy.Thus,theTFPoftheregionwillbeimproved,andtheSDoftheregion'seconomywillbepromoted.

2. What regression models have been used to analyze the factors that influence GTFP and its growth rate? Please explain in the introduction.

Reply: Thank you very much for your kind comments. The type of regression model has been added in the introduction of the revised paper. Seebelow details:

The research analyzes the influencing factors of green total factor productivity and its growth rate through static and dynamic regression model analysis and econometric empirical models, hoping to provide some appropriate carbon emission reduction policy recommendations through the analysis results, Make contributions to the sustainable development of China's regional economy.

3. Section 2.2, What are the carbon reduction policies?

Reply:Thank you very much for your kind comments. Carbon emmision reduction policies include Carbon emission tax policy, Carbon trading policy, Renewable energy policy, and so on.

4. Please supplement economic model (1) with sources, or references.

Reply:Thank you very much for your kind comments. A reference was added to the economicmodel(1) in the revised paper.

[24]Li, W., Yang, G., Li, X. (2019). Modeling the evolutionary nexus between carbon dioxide emissions and economic growth. Journal of Cleaner Production, 215(APR.1), 1191-1202. doi: https://doi.org/ 10.1016/j.jclepro.2019.01.100

5. Does Table 1 include all the provinces of China? 2001-2020 or 2000-2020? Optimize Table 1 to divide the province into central, western and eastern regions of China.

Reply:Thank you very much for your kind comments. Table 1 includes most provinces in China, and the age should be from 2001 to 2020. According to yoursuggestion,Table 1 was optimized. Please see details in the revised paper.

6. Section 5.2, What is fixed-effects model?

Reply:Thank you very much for your kind comments. The fixed-effect model has been explained in Section 5.2. See the details in the revised paper as follows:

Fixed effect model, or fixed effect regression model, is a panel data analysis method. It refers to experimental designs in which the experimental results only want to compare the differences between specific categories or categories of each covariate and the interaction effects with specific categories or categories of other covariates, rather than infer from this to other categories or categories that are not included in the same covariate. Fixed effect regression is a class of variable methods that vary with individuals but not with time in spatial panel data. The fixed effect model has n different intercepts, one of which corresponds to an individual. These intercepts can be represented by a series of binary variables.

Author Response File: Author Response.pdf

Reviewer 4 Report

Thank you for the opportunity to review this interesting paper. I believe the topic is timely and relevant, and there is potential to add to the literature; however, some major issues should be cleared up for the next step.

 

1. Abstract
• Please be more specific about the research purpose and justify the theoretical gap.
• The abstract should be written in the order of research motivation, research gap, theoretical positioning (i.e., argument), methodology, and summary of results. The current manuscript focused on the findings too much.
2. Introduction
• It seems that there is a lack of theoretical explanation. It is because the gap identification is not explained clearly and is limited in the current form. Also, there is very little evidence to support the authors’ arguments on the gap justification. Could you please clarify the theoretical gaps that have not been discovered in the existing theories? What theory was employed in this study to fill the theoretical gap? Please try to tackle the existing theories and literature from which the two RQs suggested by the authors were derived, and present the evidence. How did you define RQ with what evidence from existing studies?
• Please address China's emphasis in the research context.
• Please clearly present the theoretical gap derived from RQ as "First, Second, Third".
3. Methodology
• Make your research context richer.
• Please document an appropriate extraction method for sample justification, generalization, and analytical technique for the integrated review.
• Please clarify the reason why authors take static and dynamic panel model. Generally, we use system GMM for estimating the regional comparison models.
• It is necessary to show the relationship between the elements used in the study as a single framework or figure. Figure 2 does not fit as a research model. It would be best if you elaborated on the research model to deliver what your RQ aims for.
• Please clarify why each variable can play as a key role in influencing RE.
• Please show VIF using correlations.
• Please display the data construct consisting of metrics combined with each variable.  
4. Conclusion
•  
• The theoretical contribution of this study is difficult to find. The theoretical contribution should be made clear of what has been extended in the existing literature. It is considered that the current theoretical implications are sufficient to make meaningful linkages of existing studies. Please review the following papers and provide updates for theoretical and managerial contributions.
• For consumer green innovation: Open for green innovation: From the perspective of green process and green consumer innovation, 11(12), 3234.
• For green process/product innovation: How do intellectual property rights and government support drive a firm’s green innovation? The mediating role of open innovation. Journal of Cleaner Production, 317, 128422.
• For green managerial innovation: Structural relationships a firm’s green strategies for environmental performance: The roles of green supply chain management and green marketing innovation, Journal of Cleaner Production, 356, 131877. 

Author Response

(x) Extensive editing of English language and style required

Reply: Thank you very much for your kind suggestion. We checked the whole text and corrected all the grammatical and spelling mistakes.

Thank you for the opportunity to review this interesting paper. I believe the topic is timely and relevant, and there is potential to add to the literature; however, some major issues should be cleared up for the next step. 

1. Abstract

(1) Please be more specific about the research purpose and justify the theoretical gap.

Reply: Thank you for your suggestion, and the summary has been changed according to your suggestion. The details are shown below.

With the rapid growth of China's economic growth, a large number of greenhouse gas emissions have led to a significant increase in environmental pressure. Currently, China has not well controlled the balance between greenhouse gas emissions and economic growth. In order to improve the sustainable development level of China's regional economy and effectively control domestic CO2 emissions, research is conducted to analyze the trend of regional economic change based on carbon emission policies, and then find suitable paths to achieve sustainable development of regional economy.

(2) The abstract should be written in the order of research motivation, research gap, theoretical positioning (i.e., argument), methodology, and summary of results. The current manuscript focused on the findings too much.

Reply: Thank you for your reminder. The overall structure of the summary has been sorted out and rewritten. The rewritten comments are shown as follows:

Abstract: With the rapid growth of China's economic growth, a large number of greenhouse gas emissions have led to a significant increase in environmental pressure. Currently, China has not yet achieved a good balance between greenhouse gas emissions and economic growth. To improve the sustainable development of China's regional economy and effectively control domestic CO2 emissions, research is conducted to analyze the trend of regional economic change based on carbon emission policies. And then this study finds suitable paths to achieve sustainable development of regional economy. Inthisstudy,CO2emissionsareincorporatedintoaneconomicmodeltocalculatetheGreenTotalFactorProductivity(GTFP)efficiencyvalueanditsgrowthrateineachregionofChina. This is to examinetheproductivityofeachregioninChina; And it also aims to discussthedrivingfactorsbehindit,soastogiverelevantpolicysuggestionsthatcanhelpChina'ssustainableeconomicdevelopment. The ultimate goal is to achievethesustainableREdevelopment.Themethodusedtomeasurethe GTFPefficiencyistheslacks-basedmeasure(SBM)basedondataenvelopmentanalysis(DEA)technique.Theregressionanalysisoftherelevantdriversisbasedontheregressionanalysisofthepaneldatamodel. The research results show that the level of urbanization and industrial structure are the main influencing factors for the increase of CO2 emissions. Consequently, macro regulation can appropriately reduce CO2 emissions. In addition, the implementation of carbon emission reduction policies such as industrial structure optimization, education investment, and market-oriented reform also promote the sustainable development of the regional economy. Therefore, appropriate carbon emission reduction policies can improve the level of sustainable development of regional economy. It also can ensure the stability of the regional environmental level.

2. Introduction

(1) It seems that there is a lack of theoretical explanation. It is because the gap identification is not explained clearly and is limited in the current form. Also, there is very little evidence to support the authors’ arguments on the gap justification. Could you please clarify the theoretical gaps that have not been discovered in the existing theories? What theory was employed in this study to fill the theoretical gap? Please try to tackle the existing theories and literature from which the two RQs suggested by the authors were derived, and present the evidence. How did you define RQ with what evidence from existing studies?

Reply: Thank you very much for your kind comments. We have added existing literature to fill in the theoretical gap according to your request. And define RQ by processing existing literature. The details were shown as follows:

Currently, many studies have provided many methods to improve the sustainable development level of regional economy. For example, Li et al. proposed a new two-stage stochastic interval parameter fuzzy programming strategy model based on the water environment system to improve the sustainable development level of regional economy and environment. The model can solve the complexity and uncertainty of water supply systems and apply the method to planning resource management and developing regional environmental sustainability. The resulting results can not only help decision-makers formulate resource allocation strategies, but also provide insight into the benefits between economic and environmental objectives ^[9]. In addition, the Smyslova team has established a system to improve the sustainability of socio-economic development in the region based on modern geographic information system technology in response to the low level of sustainability of socio-economic development in the region. The research results indicate that using geographic information systems in formulating measures to improve the sustainable socio-economic development of the region can help improve the quality of complex system state analysis. This system not only helps to address practical issues in allocating resources or analyzing the effectiveness of resource deployment, but also helps to implement strategic planning principles using digital technology and ensure the timeliness of decisions made in the field of investigation^[10]. However, there are few studies that combine regional economic sustainable development with carbon emission reduction policies, so this study will combine the two to fill the gap in this field.

(2) Please address China's emphasis in the research context.

Reply: Thank you very much for your kind comments. In the introduction, we have explained China's key tasks in the research context. The detailis shown below.

In this context, China's regional economic level will more or less change with the adjustment of carbon emission reduction policies, so it is of important practical significance to analyze the internal relationship between carbon emission reduction policies and sustainable development of regional economy.

(3) Please clearly present the theoretical gap derived from RQ as "First, Second, Third".

Reply: Thank you very much for your kind comments. The theoretical gaps that will be studied are detailed as below in the revised paper.

Through this study, we found the following two theoretical gaps with current research. The first point is that carbon emission reduction policies and regulations can indeed effectively improve the sustainable development level of regional economies. The second point is that different carbon emission reduction policies and regulations have different effects on the sustainable development level of regional economies.

3. Methodology

(1) Make your research context richer.

Reply: Thank you very much for your kind suggestion. The research background has been enriched according to your suggestion. The details in the revised paper are shown as follows.

The data used in the study are panel data from various provinces in China from 2001 to 2020. Among them, the fixed price GDP of each province in 2000 is the output indicator, the number of employees in the whole society of each province is the labor factor input indicator, and the total energy consumption of each province is the energy factor input indicator. The above variable data are derived from the "China Energy Statistical Yearbook" and various regional statistical yearbooks over the years.

(2) Please document an appropriate extraction method for sample justification, generalization, and analytical technique for the integrated review.

Reply: Thank you very much for your kind comments. We have explained the data source in the revised paper as follows.

The above variable data are derived from the "China Energy Statistical Yearbook" and various regional statistical yearbooks over the years.

(3) Please clarify the reason why authors take static and dynamic panel model. Generally, we use system GMM for estimating the regional comparison models.

Reply: Thank you very much for your kind comments. The reasons for using both static and dynamic panel models have been described in Section 3.1. As follows:

The data used in the study are panel data from various provinces in China from 2001 to 2020. Among them, the fixed price GDP of each province in 2000 is the output indicator, the number of employees in the whole society of each province is the labor factor input indicator, and the total energy consumption of each province is the energy factor input indicator. The above variable data are derived from the "China Energy Statistical Yearbook" and various regional statistical yearbooks over the years.

The estimation methods for both models have been adjusted, and bothof them are estimated using the system GMM method.

(4) It is necessary to show the relationship between the elements used in the study as a single framework or figure. Figure 2 does not fit as a research model. It would be best if you elaborated on the research model to deliver what your RQ aims for.

Reply: Thank you very much for your kind comments. Because the relationship between the explanatory variables in the study is not too close, and it is not possible to display the chess relationship as a single graph. Therefore, the explanatory variables selected for this study are shown together in the form of Figure 2. In addition, various explanatory variables of the research model have been elaborated in detail according to your requirements. See details:

Light and heavy industries, represented by manufacturing, will consume more energy and have a greater impact on the environment than agriculture and services. The ratio of GDP of the secondary industry is used here. Urbanization is the biggest era background in recent China. The advancement of urbanization has brought about a huge demand for energy and building materials, and the demand for energy and industrial products by urban residents is far greater than that of rural areas. Logically, it will lead to an increase in CO2 emissions, but it is also a huge driving force for China's economic growth. Therefore, urbanization is included in the explanatory variable and expressed as the proportion of urban residents to the total population. Energy intensity is the energy consumption required per unit of GDP output, reflecting the level of science and technology and the efficiency of energy utilization. It is an indicator of comprehensive factors. This indicator logically connects economic development and energy consumption, and is the focus of energy conservation and emission reduction.

(5) Please clarify why each variable can play as a key role in influencing RE.

Reply: Thank you very much for your kind comments. The role of explanatory variables in influencing the regional economy has been explained in the revised paper. See details:

Marketization variables comprehensively reflect the regulatory role of the market on the economy and the allocation of factors. They are also the main direction of market-oriented reform led by the government in China, and have a relatively obvious incentive effect. Therefore, they are considered as typical institutional variables. Research and development investment is used to examine the impact of China's independent research and development investment on green total factor productivity. More investment in research and development of new technologies will logically lead to production technologies that are more conducive to improving production efficiency. Therefore, there is reason to believe that R&D investment will affect actual production efficiency, so it is included in the explanatory variable. The natural logarithm of expenditure on introducing foreign funds is the expenditure variable for purchasing foreign technology. In fact, in addition to independently developing new production technologies, it is easier to achieve the effect of improving production by directly purchasing production technologies that are conducive to improving production efficiency from abroad. Therefore, there is reason to believe that the cost of foreign technology purchases will affect China's green total factor productivity, so this indicator is selected as the explanatory variable. FDI refers to the degree of foreign trade. When foreign investors invest in establishing factories in China, they inevitably communicate and exchange information with the location of the factory, which will promote the improvement of the production efficiency of domestic enterprises within the investment location. In addition, foreign investment has attracted a large number of local unemployed residents to obtain employment and provided them with higher wages. To some extent, it has also provided them with more efficient production technology and higher production efficiency. Therefore, it is necessary to include foreign investment in the explanatory variables. Edu is the number of years of education per capita, used to examine the impact of human capital on green total factor productivity. The length of education actually determines the level of education received. Although not everyone will become a skilled person after education, in fact, the level of public education will affect the probability of the emergence of top talent and the overall productivity of the entire society.

(6) Please show VIF using correlations.

Reply: Thank you very much for your kind comments. We have described the relevance of relevant explanatory variables in the revised paper. As follows:

In addition, the study also analyzed the correlation between various explanatory variables, and the results are shown in Table 4.

As shown in Table 4, Table 4 describes the correlation between the six explanatory variables. According to Table 4, the strongest correlation between MAR and FDI is 0.7369, which is higher than the correlation between other variables. This result indicates that the two explanatory variables are more closely related, and if one of them is adjusted, the other variable is more affected.

(7) Please display the data construct consisting of metrics combined with each variable.

Reply: Thank you very much for your kind comments. Due to the different actual conditions in different regions and cities, the specific parameters for each variable cannot be given, but the relevant parameter symbols have been given in Equation (11).

4. Conclusion

(1) The theoretical contribution of this study is difficult to find. The theoretical contribution should be made clear of what has been extended in the existing literature. It is considered that the current theoretical implications are sufficient to make meaningful linkages of existing studies. Please review the following papers and provide updates for theoretical and managerial contributions.

Reply: Thank you for your reminder. According to your request, the theoretical contribution of this research has been added to the existing theory. See the below details.

By comparing the progress of this study with related studies. Firstly, it can be found that from the perspective of green consumer innovation in the current relevant literature, new green consumption patterns have a promoting effect on the sustainable development of the regional economy. On this basis, this study also found that optimizing industrial structure can better promote green consumption, thereby improving the level of sustainable development of regional economy. Secondly, it is also found that the existing literature believes that reasonable open innovation behavior can promote the sustainable development of regional economy by improving the sustainable development level of enterprises. In this study, it was also found that independent innovation research can effectively improve the sustainable development level of regional economy. Finally, the research found that relevant research shows that green supply chain development and green marketing innovation of enterprises have a significant positive effect on achieving sustainable economic development of enterprises, and they can also promote sustainable development of regional economy. In this study, it is also found that industrial structure adjustment can effectively promote the sustainable development level of regional economy. In addition, the study also conducted a specific analysis of the areas involved in carbon emission reduction policies, and found that adjustments in education, independent research and development, industrial structure, and marketization levels can significantly increase the level of sustainable development of the regional economy. Therefore, the results of this study can provide data reference for regional sustainable development in China.

(2) For consumer green innovation: Open for green innovation: From the perspective of green process and green consumer innovation, 11(12), 3234.

Reply: Thank you for your reminder. We have added a comparison according to your request. See details:

Firstly, it can be found that from the perspective of green consumer innovation in the current relevant literature, new green consumption patterns have a promoting effect on the sustainable development of the regional economy. On this basis, this study also found that optimizing industrial structure can better promote green consumption, thereby improving the level of sustainable development of regional economy.

(3) For green process/product innovation: How do intellectual property rights and government support drive a firm’s green innovation? The mediating role of open innovation. Journal of Cleaner Production, 317, 128422.

Reply: Thank you for your reminder. We have added a comparison according to your request. See details:

Secondly, it is also found that the existing literature believes that reasonable open innovation behavior can promote the sustainable development of regional economy by improving the sustainable development level of enterprises. In this study, it was also found that independent innovation research can effectively improve the sustainable development level of regional economy.

(4) For green managerial innovation: Structural relationships a firm’s green strategies for environmental performance: The roles of green supply chain management and green marketing innovation, Journal of Cleaner Production, 356, 131877. 

Reply: Thank you for your reminder. We have added a comparison according to your request. See details:

Finally, the research found that relevant research shows that green supply chain development and green marketing innovation of enterprises have a significant positive effect on achieving sustainable economic development of enterprises, and they can also promote sustainable development of regional economy. In this study, it is also found that industrial structure adjustment can effectively promote the sustainable development level of regional economy.

Author Response File: Author Response.pdf

Round 2

Reviewer 4 Report

The authors have made a good effort to address most of my comments from the previous review, although some additional discussion of the literature is needed to strengthen the theoretical contributions of the paper. I encourage the authors to consider exploring the findings of this study from a broader range of theoretical perspectives to enhance the contribution of this research further. For example, please clearly distinguish 2-3 theoretical contributions and divide the practical contributions in the same way.

Author Response

The authors have made a good effort to address most of my comments from the previous review, although some additional discussion of the literature is needed to strengthen the theoretical contributions of the paper. I encourage the authors to consider exploring the findings of this study from a broader range of theoretical perspectives to enhance the contribution of this research further. For example, please clearly distinguish 2-3 theoretical contributions and divide the practical contributions in the same way.

Reply: Thank you for your suggestion. We have added 2-3 theoretical and practical contributions to the article according to your requirements. The content is as follows:

However, there are few studies that combine sustainable development of regional economy with carbon reduction policies. Therefore, this study combines the two to not only fill the gap in this research, but also provide practical strategies for achieving sustainable development of regional economy. With the development of empirical models, research on SBM models and DEA techniques is also increasing. In order to objectively calculate the efficiency of provincial green innovation, Li proposed an SBM model based on DEA technology and fuzzy evaluation, and used this model to calculate the green innovation efficiency of 30 provincial industrial enterprises. The results showed that this model improved the accuracy and authenticity of the evaluation of green innovation economic efficiency ^[11]. In order to better calculate the sustainable development of regional economy, DEA technology and SBM model have also been applied in the study to calculate the sustainable development of regional economy. This method not only provides a new testing method for the calculation of regional economic sustainable development, but also provides new ideas for exploring regional green sustainable development. In addition, the study also expresses the level of sustainable development of regional economy through green total factor productivity, which not only provides a new indicator for sustainable development of regional economy, but also improves the level of sustainable development of regional economy by promoting the growth of green total factor productivity, providing new methods for improving the level of sustainable development of regional economy.

 

Inaddiiton, the language and spelling errors were checked and correct.