Green Economic Efficiency and Coordinated Development in the Bohai Rim Region: Addressing Regional Disparities for Sustainable Innovation and Economic Transformation
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper mainly evaluates the green economic efficiency and total factor productivity (TFP) of five provinces in the Bohai Rim Region, and considers the regional gap between sustainable innovation and economic transformation. it still has some problems. We have identified several key issues that need to be addressed:
1.The introduction also contains a lot of background information, which leads to the core research question not being prominent enough. It is suggested to further clarify why the Bohai Rim Region is chosen as the research object and its significance.
2.This study evaluated the green economy performance, total factor productivity, and regional differences of five provinces, but lacked innovation.
3.The text mostly describes data and lacks analysis of the results.
Author Response
Comments 1: The introduction also contains a lot of background information, which leads to the core research question not being prominent enough. It is suggested to further clarify why the Bohai Rim Region is chosen as the research object and its significance.
Response 1: We are very grateful to the reviewers for carefully reviewing our manuscript and providing revision suggestions for issues that have not been highlighted. In the section of Introduction, we put forward the background of our study: severe dependence on natural resources has led to resource depletion and environmental degradation, which is not conducive to sustainable economic development. Thus, the Chinese government has implemented a series of strategies aimed at coordinating economic growth and ecological balance. At the same time, we explain the principles and importance of evaluating the efficiency exchanges and resource flows. Furthermore, we also put forward the economic and political characteristics of China: local governments have their own independent environmental and sustainable development policies, and there is homogeneity and heterogeneity between regions which increases the complexity of regional economic and environmental research. Based on this, we propose why we choose the Bohai Rim region as the research object and the significance of studying this region: As an important region for the development of traditional economy in northern China, the Bohai Rim is a special region with two municipalities and three provinces. It is a cluster of traditional industrial industries and plays an important role in Chinese economic development[18]. The region meets the definition of the bay area geographically and economically, but there are challenges in administrative planning and the circulation of economic factors. In terms of governance capacity, although the municipalities are not as large as the provincial regions in the term of area, the economic output and fiscal capacity of the five regions are comparable. At the same time, municipalities often enjoy greater economic and political rights. Under the task of economic transformation and promoting green economic development, the Chinese government has introduced the concept of the “Bohai Rim Economic Circle” in its strategic planning framework, aiming to take advantage of the region’s geographical advantages, optimize resource allocation and promote the flow of production factors to address the inherent complexity of the region[18, 19]. Based on the unique characteristics and strategic importance of the Bohai Rim Region, this study aims to address the following research problem: 1) How does the operation of the green economy vary across different types of regions within the Bohai Rim? 2) What are the patterns and efficiencies of factor input from the perspective of green transformation, and to what extent has the region transitioned from a labor-based economy to a high-tech economy? 3) How can the analysis of green economic performance provide actionable insights for promoting green, sustainable, and high-quality economic development? Through the revision, we strengthen the explanation of the purpose and significance of the study. And the importance of the Bohai Rim region in studying Chinese economic green transformation and regional development is further explained.
Comments 2: This study evaluated the green economy performance, total factor productivity, and regional differences of five provinces, but lacked innovation.
Response 2: We sincerely thank the reviewers for their detailed review of our manuscript. For our innovativeness, we provide explanations in sequence.
Firstly, we evaluate the green economic performance of the Bohai Rim Region from the perspective of promoting environmental technologies and fostering innovation. This is of significant practical importance from the standpoint of the development priorities of the People Republic of China and aligns with both international and domestic approaches to environmental sustainability assessment.
Secondly, our study is methodologically rigorous in terms of mathematical analysis. Using these tools, we focus on analyzing regional economic development and sustainability at the provincial level from a macroeconomic perspective. The novelty of our research lies in its approach: unlike other studies, we analyze green economic efficiency and total factor productivity from the perspective of green economic transformation and regional innovation. In our proposed research framework, we categorize the three provinces and two municipalities separately, taking into account the impact of regional innovation environments and technological transformation on green total factor productivity. We also analyze the respective effects of technological innovation and technological efficiency on the allocation of production factors. These aspects represent the innovative contributions of our study.
Likewise, we also understand the reviewers' concerns regarding the lack of clarity about the novelty of our manuscript. Therefore, we add an explanation of the novelty of this study in the introduction section: The innovations and contributions of our research are as follows: Firstly, we evaluate the green economic performance of the Bohai Rim Region from the perspective of promoting environmental technologies and fostering innovation. This is of significant practical importance from the standpoint of the development priorities of the People Republic of China and aligns with both international. Secondly, we analyze green economic efficiency and total factor productivity from the perspective of green economic transformation and regional innovation. In our proposed research framework, we categorize the three provinces and two municipalities separately and explore regional differences, taking into account the impact of regional innovation environments and technological transformation on green total factor productivity. We also analyze the respective effects of technological innovation and technological efficiency on the allocation of production factors.
Comments 3: The text mostly describes data and lacks analysis of the results.
Response 3: We appreciate the reviewers' comments on our conclusion section. Given that our research framework employs various mathematical models to evaluate the green economic performance of the Bohai Rim Region, the generation and description of data derived from these models are indispensable in this study. Moreover, data analysis is a crucial step in drawing our conclusions. At the same time, in response to the reviewers' suggestions, we make improvements to the conclusion section. Based on the data analysis, we further analyze the results by integrating relevant literature and report, such as: "This stability is linked to the strategic adjustments in their industrial structures and the promotion of diversified industrial development in both cities. Around 2014, Beijing launched its '321' strategy, aiming to gradually increase the share of tertiary industries, while Tianjin began responding to the national 'Belt and Road' initiative, focusing on the development of manufacturing and port logistics[52, 53]." and "As key industrial provinces in northern China, these three regions have driven innovative and high-quality advancements in their traditional industries—these being the cornerstone of their economies—from 2011 to 2022. Despite the influence of natural resource endowments and historical development, they have successfully pursued innovation-driven and high-quality development initiatives. This strategic focus has played a crucial role in ensuring the quality of their green economy development[54-56]. Under the strategic layout and gradual advancement, the green economic efficiency of each region around the Bohai Bay has generally improved." Combining the analysis of data and literature, we respond to the question we originally raise in the introduction: "How does the operation of the green economy vary across different types of regions within the Bohai Rim?". After analyzing the differences in green economy in the five regions, based on the research framework, we explore the level of factor allocation within the region and the technical efficiency and technological progress that affect factor allocation. Furthermore, combining the analysis of green economic efficiency and factor allocation, we explore the changes in regional differences. This arrangement makes our structure more reasonable and enhances the academic value of our research.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe issue addressed by the authors is current and interesting for the reader. It can serve as a source of inspiration for both theorists and practitioners. It may also be a starting point for further scientific exploration.
The text is clear. The authors logically present their scientific argument.
The title indicates the subject matter discussed in the text.
The abstract is well-written, comprehensive, and sufficiently concise.
The keywords are appropriate.
The introduction requires refinement. The authors write, "The objective of this study is to examine the macroregion of the Bohai Rim Region..." (lines 76-77). The objective of the study cannot be to "examine". However, in the abstract, the authors state, "This study evaluates the efficiency of green economic performance and total factor productivity (TFP) across five provinces in the region, incorporating regional innovation capabilities and green innovation outputs into the green economy input-output system..." (lines 11-13). The authors must correctly define the objective of the conducted analysis. This section should also be supplemented with a description of the text structure.
The authors conducted a literature review (56 sources). It is relevant to the subject matter, but only 48% of the cited literature was published between 2020 and 2024. The authors need to increase the number of cited sources by at least 10 recent ones, not older than 5 years. No self-citations were found.
The section "Literature Review and Background" consists of two subsections. In my opinion, Section 2.1 "Green Economic Efficiency and Green Total Factor Productivity" should be expanded with content from the latest literature. The content of Section 2.2 "Research background" should be moved to the Introduction, where the authors place the topic in context.
The authors must absolutely formulate research questions and/or hypotheses.
In the "Results and Discussions" section, the authors should refer to the research questions and/or hypotheses they have set, clearly indicating the answers to the research questions and/or how the hypotheses were verified. Additionally, in this section, the authors should refer to the findings of other researchers.
The "Conclusions" section contains the conclusions from the conducted analyses. The authors should supplement this section by indicating the limitations of their study and suggesting potential directions for further research.
Author Response
Comments 1: The introduction requires refinement. The authors write, "The objective of this study is to examine the macroregion of the Bohai Rim Region..." (lines 76-77). The objective of the study cannot be to "examine". However, in the abstract, the authors state, "This study evaluates the efficiency of green economic performance and total factor productivity (TFP) across five provinces in the region, incorporating regional innovation capabilities and green innovation outputs into the green economy input-output system..." (lines 11-13). The authors must correctly define the objective of the conducted analysis. This section should also be supplemented with a description of the text structure.
Response 1: We sincerely appreciate the reviewers pointing out the shortcomings in the definitions and textual structure of our introduction section. In fact, as described in the abstract, we evaluated the green economic performance and factor allocation levels in the Bohai Rim Region, and based on this, assessed regional disparities. We further revise the shortcomings in the introduction. The revised parts are as follows:
As an important region for the development of traditional economy in northern China, the Bohai Rim is a special region with two municipalities and three provinces. It is a cluster of traditional industrial industries and plays an important role in Chinese economic development[18]. The region meets the definition of the bay area geographically and economically, but there are challenges in administrative planning and the circulation of economic factors. In terms of governance capacity, although the municipalities are not as large as the provincial regions in the term of area, the economic output and fiscal capacity of the five regions are comparable. At the same time, municipalities often enjoy greater economic and political rights. Under the task of economic transformation and promoting green economic development, the Chinese government has introduced the concept of the “Bohai Rim Economic Circle” in its strategic planning framework, aiming to take advantage of the region’s geographical advantages, optimize resource allocation and promote the flow of production factors to address the inherent complexity of the region[18, 19]. Based on the unique characteristics and strategic importance of the Bohai Rim Region, this study aims to address the following research problem: 1) How does the operation of the green economy vary across different types of regions within the Bohai Rim? 2) What are the patterns and efficiencies of factor input from the perspective of green transformation, and to what extent has the region transitioned from a labor-based economy to a high-tech economy? 3) How can the analysis of green economic performance provide actionable insights for promoting green, sustainable, and high-quality economic development?
Based to this, the Super-SBM and global Malmquist-Luenberger indicator model in this study is applied to analyse the shifts in the green economic efficiency (GEE) and the green total factor productivity (GTFP) over a 12-year period, while also investigating the decomposition factors of technological efficiency and technological progress. Using the computed GEE results, the study explores regional disparities between the two municipalities directly under the central government and the three provinces, employing the Theil index methodology, and further analyses the changes in regional differentials within the Bohai Rim Region. The innovations and contributions of our research are as follows: Firstly, we evaluate the green economic performance of the Bohai Rim Region from the perspective of promoting environmental technologies and fostering innovation. This is of significant practical importance from the standpoint of the development priorities of the People Republic of China and aligns with both international. Secondly, we analyze green economic efficiency and total factor productivity from the perspective of green economic transformation and regional innovation. In our proposed re-search framework, we categorize the three provinces and two municipalities separately and explore regional differences, taking into account the impact of regional innovation environments and technological transformation on green total factor productivity. We also analyze the respective effects of technological innovation and technological efficiency on the allocation of production factors.
Such modifications improve the rationality of our text structure and elaborate on our research purpose, research significance and innovation.
Comments 2: The authors conducted a literature review (56 sources). It is relevant to the subject matter, but only 48% of the cited literature was published between 2020 and 2024. The authors need to increase the number of cited sources by at least 10 recent ones, not older than 5 years. No self-citations were found.
Response 2: We thank the reviewers for checking our references and pointing out areas that still need improvement. We revise our manuscript based on the reviewers' comments. Along with this process, we supplement recent research to ensure the accuracy and timeliness of the paper and enhance the academic value of the article.
Comments 3: The section "Literature Review and Background" consists of two subsections. In my opinion, Section 2.1 "Green Economic Efficiency and Green Total Factor Productivity" should be expanded with content from the latest literature. The content of Section 2.2 "Research background" should be moved to the Introduction, where the authors place the topic in context.
Response 3: We thank the reviewers again for their comments on the shortcomings of our “Literature Review and Background” section. In particular, we make improvements based on the comments on the references in the previous revision. In Section 2.1, we add the latest literature content for “Green Economic Efficiency and Green Total Factor Productivity”. As for the research background, in the previous revision, we incorporate the research theme, content, and innovations into the Introduction section. Since the Introduction already provides an overview of the research background, emphasizing the Chinese government's aspiration for green transformation to achieve sustainable economic development. Therefore, in this section, in order to introduce our research framework below, and ensure the length and structure of the article are reasonable, we make some modifications here and briefly describe the scope of our research area. The modified parts are as follows:
2.2. Research Area Scope
The Bohai Rim Region, a vast economic area spanning the entire Bohai Sea coast and part of the Yellow Sea coast, is shown in Figure 1. Benefiting from the advantageous natural geography of a bay area, it is surrounded by land on three sides and bordered by the sea on one side[42]. From the perspective of administrative division and regional strategic planning, the Bohai Rim Region encompasses the core of Chinese governance and key municipalities, along with the Xiong'an New Area, a national special economic zone currently undergoing vigorous development and construction initiatives by the Chinese government. Additionally, Beijing and Tianjin serve as pioneering platforms for carbon emissions trading. Liaoning acts as a leader in revitalizing the traditional heavy industrial base in the northeast and restructuring its industrial framework, while Shandong serves as a key hub for economic growth in the northern region.
For an extended period, an economy-centered strategy has predominated, leading to the marginalization of environmental protection and the significant depletion of natural resources. In response to the urgent need for sustainable economic development, the region has adopted and implemented the green economy model under government leadership. By concurrently addressing environmental restoration and ecological management, the region is gradually reducing its dependence on natural resources through a structural economic transformation. To ensure long-term sustainability, this transformation involves increasing the proportion of the tertiary sector in the economy, fostering innovation in green technologies and sustainable production within primary and secondary industries, and progressively shifting from traditional industries to high-tech sectors. The development of a coordinated and sustainable green economy is crucial for the rational allocation of regional production factors and the efficient circulation of resources[43, 44]. Regional advantages can be further harnessed through the rational allocation of production factors and the efficient circulation of resources.
Comments 4: In the "Results and Discussions" section, the authors should refer to the research questions and/or hypotheses they have set, clearly indicating the answers to the research questions and/or how the hypotheses were verified. Additionally, in this section, the authors should refer to the findings of other researchers.
Response 4: We thank the reviewer again for pointing out the shortcomings in our results analysis. In conjunction with the questions we raised in the introduction, we further refine our conclusions.
In the introduction, we raise three questions, as follows: 1) How does the operation of the green economy vary across different types of regions within the Bohai Rim? 2) What are the patterns and efficiencies of factor input from the perspective of green transformation, and to what extent has the region transitioned from a labor-based economy to a high-tech economy? 3) How can the analysis of green economic performance provide actionable insights for promoting green, sustainable, and high-quality economic development?
Our corresponding structures are:
1) How does the operation of the green economy vary across different types of regions within the Bohai Rim?
“The Super-SBM model calculates the green economy efficiency (GEE) for the five provinces within the Bohai Rim Region from 2011 to 2022...(4.1. Calculation Results of GEE).”
2) What are the patterns and efficiencies of factor input from the perspective of green transformation, and to what extent has the region transitioned from a labor-based economy to a high-tech economy?
"To further investigate the dynamics of green technology innovation in the five provinces of the Bohai Rim Region over different periods from 2011 to 2022...(4.2. Factor Analysis of GTFP)."
3) How can the analysis of green economic performance provide actionable insights for promoting green, sustainable, and high-quality economic development?
"Through dividing the five provinces of the Bohai Rim Region into two groups—municipalities directly under the central government (Beijing and Tianjin) and provinces (Hebei, Liaoning, and Shandong)...(4.3. Theil Indicator Analysis)."
This arrangement makes our article more rigorous in structure. Through a series of studies, we answered the questions we raised.
At the same time, we also combine relevant reports and studies to further analyze our results,such as “This stability is linked to the strategic adjustments in their industrial structures and the promotion of diversified industrial development in both cities. Around 2014, Beijing launched its '321' strategy, aiming to gradually increase the share of tertiary industries, while Tianjin began responding to the national 'Belt and Road' initiative, focusing on the development of manufacturing and port logistics[52, 53].” and “As key industrial provinces in northern China, these three regions have driven innovative and high-quality advancements in their traditional industries—these being the cornerstone of their economies—from 2011 to 2022. Despite the influence of natural resource endowments and historical development, they have successfully pursued innovation-driven and high-quality development initiatives. This strategic focus has played a crucial role in ensuring the quality of their green economy development[54-56]. Under the strategic layout and gradual advancement, the green economic efficiency of each region around the Bohai Bay has generally improved.”. Combining literature and reports, we analyze the green economy of five regions, and further analyze the changes in factor allocation and its influencing factors as well as regional differences.
Comments 5: The "Conclusions" section contains the conclusions from the conducted analyses. The authors should supplement this section by indicating the limitations of their study and suggesting potential directions for further research.
Response 5: We are very grateful to the reviewer for pointing out that there are still some deficiencies in the conclusion section of the article. In this section, we summarize the conclusions and contributions of the corresponding analyses of three models(the Super-SBM model, the Global Malmquist-Luenberger model and Theil indicator analysis). We also acknowledge that our research has broad prospects and some issues deserve further exploration.
Firstly, through the analysis of green economic efficiency and combined with relevant literature and reports, we conclude that the green economic performance in the Beijing-Tianjin region first decreases, then increases and gradually stabilizes. At the same time, we conclude that under the basic role of traditional industries in the three regions, the green economy performance in Hebei, Liaoning and Shandong remain improved. Therefore, in the future, further time and space measurement and analysis can be carried out for the five regions based on the industrial structure and strategic blueprint of each region.
Secondly, through the calculation results of GML, we conclude that the production factor allocation efficiency in Beijing and Tianjin is higher than in Hebei and Liaoning. Whereas, the improvement of the level of technological progress in Beijing has promoted the improvement of the level of production factors. The reason for the decline in the decline in the level of production factors in other regions is the decline in the technical efficiency. Due to the differences in industrial structures and regional characteristics in various regions, it is worth exploring how to further promote the advancement of green technology and improve technological efficiency, as well as exploring the impact of improving green technology progress and technological efficiency on the green economy.
Thirdly, through the analysis of the Theil index, we further point out that the inter-provincial green economic gap has widened and the gap between administrative regions needs targeted policies to make up for it. Therefore, in the future, in addition to further measuring the impact of regional industrial structure complementarity and regional resource flow on regional integration, it should also be possible to use computing methods such as big data and machine learning to evaluate advanced cases in other regions and conduct comparative research in combination with the development of the Bohai Rim region.
Based on the above three points, we add the outlook for future research in the section of conclusion:
Based on the results of this study, there are some issues worth exploring in depth in the future regarding the differences and dynamics at the micro level within the region. Firstly, future studies could conduct more granular time-space analyses of the five regions, considering their distinct industrial structures and strategic blueprints. This would provide deeper insights into the role of tailored policies of sustaining green economic growth and industrial upgrades. Secondly, given the disparities in production factor allocation efficiency and technological efficiency, future research could focus on strategies to promote green technology advancement and enhance technological efficiency. Further, it needs to explore the influence of industrial structure complementarity and resource flow on regional integration. Future research could leverage computational tools such as big data and machine learning to evaluate successful cases in other regions and conduct comparative studies with the Bohai Rim region, offering feasible insights for targeted policy design. In summary, this study provides reference and suggestions for the sustainable development of the green economy and the coordinated development of regional integration in the Bohai Bay area.
Therefore, after drawing the conclusion, we further put forward the prospect which makes the structure of the article more rigorous, thus improving the academic value.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors' article is dedicated to a comprehensive study of "green" economic efficiency (Green Economic Efficiency, GEE), employing modern economic and mathematical models and methods for its assessment. A numerical evaluation of the GEE indicator is utilized to analyze its impact on the sustainable development of the Bohai Bay region in China. The article's topic is highly relevant, as issues related to environmental sustainability align with current international and national trends in regional development. Particular attention is given to the dynamics of changes in the indicators used for a comprehensive assessment of GEE. This focus is crucial from the perspective of the People’s Republic of China’s development priorities, particularly in the context of promoting environmentally friendly technologies and fostering innovation.
The article employs several methodological approaches, including the Super-SBM model, which enables a precise estimation of the GEE indicator by accounting for both desirable and undesirable outputs. The global Malmquist-Luenberger indicator (GML) is applied to analyze the dynamics of changes in total factor productivity (TFP) between consecutive periods, particularly in the context of technological progress. Additionally, the Theil indicator is used to assess regional and interregional disparities.
In our opinion, the application of the Super-SBM model is a methodologically sound choice and deserves special commendation. Its ability to incorporate both economic and environmental dimensions into the analysis of regional development is particularly noteworthy.
The novelty of the article lies in the integration of these methods for analyzing five key regions of the Bohai Bay (Beijing, Tianjin, Hebei, Liaoning, Shandong), which allows for an in-depth examination of the critical aspects of economic development and environmental sustainability in these regions.
The article demonstrates methodological rigor in its use of advanced analytical tools. The study's results have practical implications and can serve as a foundation for developing regional strategies for sustainable development in the PRC.
- Review 1. The authors analyze the dynamics of "green" total factor productivity (GTFP) for the period 2011–2022. However, the results may be influenced by external factors (e.g., economic crises or changes in regional policies), which are not accounted for in the proposed model.
- Review 2. The article uses data with varying units of measurement (e.g., energy consumption, GDP, carbon dioxide emissions), which were evidently normalized. However, the text does not provide an explicit description of the data normalization methodology. The absence of a clear explanation raises concerns about the validity of the results derived from the Super-SBM model.
Author Response
Comments 1: The authors analyze the dynamics of "green" total factor productivity (GTFP) for the period 2011–2022. However, the results may be influenced by external factors (e.g., economic crises or changes in regional policies), which are not accounted for in the proposed model.
Response 1: We sincerely thank the reviewer’s suggestion to consider the external influences in our models of the manuscript. In fact, we also consider the impact of these factors (such as economic crises or changes in regional economic policies) on the green economic efficiency and the green total factor productivity.
Firstly, in the choice of indicators, we select the indicator “Resources of regional innovation input”, which takes into account the establishment of enterprises, the investment of foreign investors, the investment attraction, the innovative technology and the brand transformation. These indicators are affected by the regional innovation environment, regional market vitality and financial markets. Therefore, we include “Resources of regional innovation input” in the input indicators and distinguished them from traditional input indicators (such as labor, capital and energy). At the same time, we also select “Economic output” and “Science and technology output” as output indicators, which are affected by economic crises and changes in regional economic policies. Therefore, in order to further illustrate that our research is based on the existing model and its calculation results are obtained after considering external influences, we make the following explanation:
“Meanwhile, this study select the China Regional Innovation and Entrepreneurship Indicator (IRIEC) to reflect the innovation capabilities across different regions [38]. This indicator assesses a region’s innovation capabilities across five dimensions: the number of new enterprises, attracting foreign investment, attracting venture capital, the number of patent authorizations and the number of trademark registrations. It is characterized by its objectivity, real-time nature, and multidimensional approach. In addition, innovation capacity is also affected by external factors, such as economic crises and regional policy changes. Therefore, we include it as an additional input indicator.”.
This paragraph is after Table 1, and we also explain: From the perspective of output, we select “Economic output” and “Science and technology output” as output indicators. Therefore, our input-output system fully considers the impact of external factors.
Secondly, combined with the relevant literature and reports, we have explained the reasons for the changes in the curves of Figure 3 to 5 in the section of results. In the manuscript, it is reflected “This stability is linked to the strategic adjustments in their industrial structures and the promotion of diversified industrial development in both cities. Around 2014, Beijing launched its ‘321’ strategy, aiming to gradually increase the share of tertiary industries, while Tianjin began responding to the national ‘Belt and Road’ initiative, focusing on the development of manufacturing and port logistics[51, 52].”, “As key industrial provinces in northern China, these three regions have driven innovative and high-quality advancements in their traditional industries—these being the cornerstone of their economies—from 2011 to 2022. Despite the influence of natural resource en-dowments and historical development, they have successfully pursued innova-tion-driven and high-quality development initiatives. This strategic focus has played a crucial role in ensuring the quality of their green economy development[53-55].”.
Therefore, in the process of analyzing the efficiency of green economy, we consider the impact of policy changes and the strategic planning on the curve fluctuation. Based on this, we explore the differences among different regions from the perspective of technical efficiency and technological progress within the region, as well as the degree of different area under jurisdiction. We also add at the beginning of this section: The Super-SBM model calculates the Green Economy Efficiency (GEE) for the five provinces within the Bohai Rim Region from 2011 to 2022, as shown in Table 3. The table indicates that, from 2011 to 2022, the average GEE across the five provincial-level regions consistently exceeded or equalled 1, with Beijing having the highest GEE value of 1.037. In contrast, Liaoning recorded the lowest GEE value of 1.000, showing a slight 3.7% difference between the two regions. This suggests that, as a key region of northern Chinese economy, the operational efficiency of the green economy is relatively high and stable. In connection with relevant reports and studies, we further analyze the green economic efficiency and the varying reasons in the five provinces of Bohai Rim region.
However, we also acknowledge that our research is still in progress and some issues deserve further exploration. We can further explore the impact of regional innovation environment, market vitality and policy changes on the green economy through tools of econometrics. Therefore, beyond the scope and research perspective of this manuscript, we can further explore these factors and related effects.
Comments 2: The article uses data with varying units of measurement (e.g., energy consumption, GDP, carbon dioxide emissions), which were evidently normalized. However, the text does not provide an explicit description of the data normalization methodology. The absence of a clear explanation raises concerns about the validity of the results derived from the Super-SBM model.
Response 2: The standardization of data is essential for the computation in both the Super-SBM model and Global Malmquist-Luenberger model. The reason is that these measurement indicators of input and output in the manuscript are different. Here, we thank the reviewer for reminding us to explicitly describe the data standardization method. We transform data of different dimensions into a unified scale, which can eliminate the impact of dimensions and ensure that each feature has equal importance in mathematical modeling and data analysis. In this manuscript, the method we have used is discrete standardization, which is also known as Min-Max Normalization. It applies a linear transformation to the raw data, mapping the results to the range of 0 to 1. We add the description of this method in the manuscript, following Table 2. After modifying the original text, the description of this part is: “At the same time, the Super-SBM model is employed to calculate the Green economic efficiency (GEE) for each province, while the global Malmquist-Luenberger (GML) indicator model is used to assess the global technological progress Indicator (GTC) and global technical efficiency indicator (GTE) of GTFP and its components. Furthermore, the Theil index is applied to analyze the level disparities among different regions. Due to the dimensions and magnitudes of all indicators are different, we adopt a discrete standardization method for the purpose of eliminating the impact of dimensions of the data. By linearly mapping the data to the interval in the range from 0 to 1, the indicators of the samples are comparable. The steps are as follows:”. Such modifications clearly explain the methods of data normalization and its roles, further illustrate the effectiveness of the Super-SBM and other models.
