Measurement of Regional Green Economy Sustainable Development Ability Based on Entropy Weight-Topsis-Coupling Coordination Degree—A Case Study in Shandong Province, China
Round 1
Reviewer 1 Report
This is good paper on a hot topic and will be read and discussed by a wider readership in development issuses. The methodology is novel and effective .but there are some questions, it is recommended that the authors make some changes in the manuscript.
1. The paper is good in terms of English language but there are still many places where improvements are needed as the paper is clearly written by non-native English writers. A proofreader is needed. Avoid the excessive use of repetition of the same words.
2. The introduction is too long and the proposal is divided into two parts.
3. For chart 1, how are the relationships between the indicators developed? The justification needs to be provided.
4. the number of decimal points reserved in charts is consistent.
5. When you introduce figures, tables you should indicate what and the unit of measurement for each variables (Figure 1 ,2and 3for example lack the description on the axes and it is difficult to verify while the trend expressed are clear)
Author Response
Dear Editors and Reviewers:
Thank you for your letter and for the reviewers’ comments concerning our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made correction which we hope meet with approval.
Revision file is presented under the “Track Changes” version. The main corrections in the paper and the responds to the reviewer’s comments are marked in red and italic as following:
1.The paper is good in terms of English language but there are still many places where improvements are needed as the paper is clearly written by non-native English writers. A proofreader is needed. Avoid the excessive use of repetition of the same words.
Modification explanation: In terms of English language, our paper has an improvement and revise under the suggestions of English proofreader.
2. The introduction is too long and the proposal is divided into two parts.
Modification explanation: We have felt very regret that we have not been able to refine it in accordance with your valuable advice. Because if we divide the introduction into two parts, it will make each of them too brief.
3. For chart 1, how are the relationships between the indicators developed? The justification needs to be provided.
Modification explanation: We have refined the description for the development of relationship between indicators.” The model mainly emphasizes the causal relationship between human economic activities and environmental changes: human production and life drive economic development, but also bring pressure to the local ecological environment, changing the original state and nature of resources and environment; Changes in the environment will also affect human life and urban development. In order to maintain the sustainable development of society, humans will take measures to respond to these changes.” (line 113-118 under revised manuscript).
4. The number of decimal points reserved in charts is consistent.
Modification explanation: I carefully considered your suggestion. The fact is that there is really no need to keep the last 5 digits of the decimal or more, so we keep the numbers in all the tables 4 digits after the decimal point. You can see the changes in the revised version of the article(in Table 3、Table 4、Table 5、Table 6).
5. When you introduce figures, tables you should indicate what and the unit of measurement for each variables (Figure 1 ,2and 3for example lack the description on the axes and it is difficult to verify while the trend expressed are clear)
Modification explanation: Thank you for your valuable suggestions and we have added Axis title of Figures. You can see the changes in the revised version of the article.
We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper.
We appreciate for Editors/Reviewers’ warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Min Wang
Sichuan University
2018-12-26
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The Authors show an interesting application of the TOPSIS and coupling coordination degree for an intertemporal and structural analysis of the green economy in Shandong Province (China).
The Authors apply a relatively new method of weighing, having its roots in the information theory (Shannon's entropy). Therefore the paper is of high originality. However, in my opinion the paper in some aspects can be improved.
The Authors reference mainly to Chinese authors, while there is a range of international literature on green economy measurement, as well as the TOPSIS method and its extensions (especially application of the Shannon's entropy for determining weights). The choice of an entropy method for weighing is methodologically interesting, however I think some explanation in this respect is necessary. Why this method of determining weights was applied and what are its advantages in comparison to other methods? It is worth explaining especially in the context of the scientific debate on weighing (see e.g. Decancq, K. and Lugo, A. (2013). Weights in multidimensional indices of wellbeing: An overview. Econometric Reviews, 2013 - Taylor & Francis).
In my opinion choice of some variables for the green economy index (table 1) is not sufficiently explained, especially when compared to e.g. OECD's Green Growth Indicators:
- “Per capita urban road area” taken as a stimulant
- Lack of any variable concerning amount of waste generated in the indication layer "Environmental pressures"
- variables concerning the state of the environment (S1) - there are no variables concerning e.g. air quality, water quality, biodiversity, while 3 variables concern green areas
Authors state that choice of variables is based on “previous research”, but don’t provide any references (lines 122-124).
My doubts concerning the choice of variables are a major reason why I recommend the text should be subject to a major revision (if the Authors decide to include another variables, the results may be different).
The presentation of results is clear, however taking into account the needs of international readers, the conlusions (lines 294-312) should be more of universal character and refer for example to the situation in other regions of China. In my opinion, the results need to be discussed with literature also from a methodological point of view.
Author Response
Dear Reviewers:
Thank you for your letter and the comments concerning our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made correction which we hope meet with approval.
The main corrections in the paper and the responds to the reviewers’ comments are marked in red and italic as following:
1.- The Authors reference mainly to Chinese authors, while there is a range of international literature on green economy measurement, as well as the TOPSIS method and its extensions (especially application of the Shannon's entropy for determining weights). The choice of an entropy method for weighing is methodologically interesting, however I think some explanation in this respect is necessary. Why this method of determining weights was applied and what are its advantages in comparison to other methods? It is worth explaining especially in the context of the scientific debate on weighing (see e.g. Decancq, K. and Lugo, A. (2013). Weights in multidimensional indices of wellbeing: An overview. Econometric Reviews, 2013 - Taylor & Francis).
Modification explanation: Thank you for your valuable suggestions and we have an improvement for the literature and added relevant content. First, we have cited researches of foreign authors (References under revised manuscript). Then we have perfected the explanation of entropy method. Index weight reflects the different importance of indicators in the evaluation process, and it is a comprehensive measure of subjective and objective responses to the relative importance of indicators in decision-making (or evaluation) issues. Decancq, K. and Lugo, A. [33] summarized eight methods for setting indicator weights and highlight their strengths and weaknesses. The entropy method employs the inherent information in the evaluation indicators to discriminate the utility value of the indicators, which avoids any subjective factors, and therefore has higher credibility than subjective weighting methods such as Delphi and AHP [34-35]. (line 193-199 under revised manuscript)
2.- In my opinion choice of some variables for the green economy index (table 1) is not sufficiently explained, especially when compared to e.g. OECD's Green Growth Indicators:
- “Per capita urban road area” taken as a stimulant
- Lack of any variable concerning amount of waste generated in the indication layer "Environmental pressures"
- variables concerning the state of the environment (S1) - there are no variables concerning e.g. air quality, water quality, biodiversity, while 3 variables concern green areas
Authors state that choice of variables is based on “previous research”, but don’t provide any references (lines 122-124).
Modification explanation: These comments are particularly meaningful and have important guiding significance for our further research. We regret that we did not elaborate on the basis for selecting the indicators. Therefore, we give a detailed description of each option in the indicator system. “Natural resources, population, science and technology, culture and education determine the level of regional economic development from the aspects of regional resource richness, production and consumption capacity, productivity development level and human resource quality. The development of green economy is an inevitable choice for the sustainable development of economy, society and ecological environment [26,27]. Green economy development is needed to alleviate the conflict among economic development and energy consumption, resource utilization and the environmental protection [28,29].
Shi, B. and Yang, H [30] selected 85 indicators to evaluate the urban green economy from the perspectives of economy, society and resources. Shi, L and Xiang, X [31] from the driving force-pressure-state-impact-response selected 19 indicators including regional GDP, unit GDP energy, carbon emissions per unit of GDP, public perception of low-carbon cities, and forest coverage to evaluate urban low-carbon economy. Shen Juqin and Sun Yue.[32] combined with the DPSIR model to select 28 indicators for evaluation of fixed asset investment, energy consumption, green coverage, per capita disposable income, and sewage treatment rate from the factors affecting regional green GDP development .
This paper selects 26 indicators that affect regional green economy development from five aspects: economy, society, environment, energy and technology. Because the impact is difficult to measure, to avoid uncertainty in the “I-impact” factor index in the DPSIR model criterion layer construction, a criterion layer based on the DPSR, namely the drivers-pressures-state-response, is established. Therefore, the 26 indicators are divided into economic driving force D1, social driving force D2, energy pressure P1, environmental pressure P2, environmental state S1, and science and technology response R1,total of 6 blocks, to measure regional green economy development.
The choice of economic driving indicators selected fixed asset investment, foreign trade volume GDP growth rate, per capita GDP, per capita disposable income of urban residents, and household consumption level from the perspectives of internal and external, national individual and income expenditure as the basis for measuring the standard economic driving force.
The choice of social driving force indicators selected the family size, per capita water use, per capita urban road area, and 10,000-person bus ownership of the household registration population from the population problem and infrastructure security level that have significant impact on social development.
Energy pressure indicators were selected by analyzing the relationship between economic development and energy consumption. The energy consumption and power consumption of the two major factors that constrain economic development are selected for measurement.
Environmental pressure chose the industrial production that is the most vulnerable to the environment during the economic development process. Therefore, industrial wastewater discharge, industrial smoke (powder) dust emissions, industrial solid waste comprehensive utilization, SO2 emissions per unit of GDP, and chemical oxygen demand emissions are selected as the basis for measurement.
The choice of environmental status indicators is mainly based on the perspective of green life. The pollution-free treatment rate of living garbage, the per capita park green area, the forest coverage rate, and the green area coverage of the built-up area were selected as the basis for measurement.
As an important part of promoting green development of science and technology, science and technology response indicators should be selected from the process of investment in science and technology innovation, output and application. Therefore, R&D expenditures accounted for the proportion of GDP, the proportion of R&D personnel with high education (master's degree or above), the number of patents granted by 10,000 people, the proportion of secondary industry to GDP, and the proportion of tertiary industry to GDP as the basis for measuring scientific and technological response. The specific indicator system is shown in Table 1.” (line 124-179 under revised manuscript).
Firstly, we taken “Per capita urban road area” as a stimulant, because we have divided the driving force into two parts: the economic driving force and the social driving force. The per capita road area was selected as an important infrastructure guarantee for economic development.
Secondly, we have given the clear explanation for the basis of environmental pressure indicator selection. The reason why lacking of any variable concerning amount of waste generated in the indication layer "Environmental pressures" is that the selection of environmental pressure indicators mainly considers the industrial production . The industrial production is most prone to pollution in the process of economic development as the research object. At the same time, we have taken the comprehensive utilization rate of industrial solid waste as an important indicator.
Thirdly, we have felt very regret that we have not taken air quality, water quality, biodiversity into account. Because the choice of environmental status indicators is mainly from the perspective of green life. At the same time considered the reliability of some indicators. We will continue to study this part in subsequent research.
Finally, in terms of references about choice of variables, we have added corresponding literature in the paper.
“26.Forsyth, T.; Levidow, L. An ontological politics of comparative environmental analysis: The green economy and local diversity. Glob. Environ. Politics 2015, 15, 140–151.
27. Newton, P.; Newman, P. Critical connections: The role of the built environment sector in delivering green cities and a green economy. Sustainability 2015, 7, 9417–9443.
28. Schmitz, H.; Lema, R. The global green economy: Competition or cooperation between Europe and China? Triple Chall. Eur. Econ. Dev. Clim. Chang. Gov. 2015, 5, 118–141.
29. Hu, A. Introduction: Entering the Green Industrial Revolution. In China: Innovative Green Development; Springer: Berlin, Germany, 2014.
30. Shi, B.; Yang, H.; Wang, J.; Zhao, J. City Green Economy Evaluation: Empirical Evidence from 15 Sub-Provincial Cities in China. Sustainability 2016, 8, 551.
31. Shi, L.; Xiang, X.; Zhu, W.; Gao, L. Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen. Sustainability 2018, 10, 3751.
32. Shen Juqin, Sun Yue. Research on Regional Green GDP Evaluation Index System Based on DPSIR Model[J]. Journal of Hohai University (Philosophy and Social Sciences), 2016(06): 61-66+100-101.” (References under revised manuscript).
3.- The presentation of results is clear, however taking into account the needs of international readers, the conclusions (lines 294-312) should be more of universal character and refer for example to the situation in other regions of China. In my opinion, the results need to be discussed with literature also from a methodological point of view.
Modification explanation: We were very regret for unclear expressions for this part, and we have made appropriate changes to conclusions:
This paper constructed a sustainable regional green economy development index system from five aspects; economic, social, technological, resource and environment; using DPSIR and entropy-TOPSIS-coupling coordination to horizontally and vertically quantitatively analyze the sustainable green economy development. And the model was verified by the actual situation of green economy development in Shandong Province from 2010 to 2016, which confirmed the feasibility of the method. The analysis in this study came to the following conclusions:
(1) The DPSIR was used to transform the internal development of each subsystem into a driver, a pressure, a state, or a response. Compared to traditional economic evaluations that tend to only reveal the surface conditions, the DPSIR was shown to more fully reveal the impact of the various factors on economic development and comprehensively analyze the interrelated relationships; therefore, based on the DPSIR theory, this paper established a green economic development evaluation index system, which provides a good theoretical framework for the global green economy development evaluation.
(2) The entropy weight-TOPSIS model established in this paper has important application value for the longitudinal analysis of green economy development. The analysis of the comprehensive green economy development scores each year was shown to determine the distance between the current development status and the ideal status in each year, thus allowing for a clarification of the green economy development trends; therefore, this method was also shown to have a good reference value for the multi-dimensional comprehensive analyses of regional green economic development systems.
(3) Coupling Coordination Theory was used to analyze the coordinated development of the various subsystems and identify the constraints on sustainable green economy development from economic, social, technological, resource, and environmental perspectives; therefore, as this method provides a valuable reference for the development of the green economy, targeted future development planning recommendations could be proposed based on the actual regional situation. (line 411-436 under revised manuscript).
We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper.
We appreciate for your warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Min Wang
Sichuan University
2018-12-26
Author Response File: Author Response.pdf
Reviewer 3 Report
The authors aim to construct a measurement system based on DPSIR model.
1. The contribution to the field of knowledge is good.
2. The reviewed references are adequate.
3. The abstract is not informative to describe their contribution.
4. The conclusion and suggestion are too long and not focused w.r.t. their obtained contributions.
5. Typing errors are founds in Figure 1, Line 114.
6. The authors need to revise their numbering system of figures, Figure 1 and Figure 2 are repeated numbered.
7. The authors need to revise the appearance of tables to avoid the improper word-break.
Author Response
Dear Reviewers:
Thank you for your letter and the comments concerning our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our research. We have studied comments carefully and have made correction which we hope meet with approval.
The main corrections in the paper and the responds to the reviewers’ comments are marked in red and italic as following:
1.-The abstract is not informative to describe their contribution.
Modification explanation: We were very regret for unclear expressions for this part, and we have made appropriate changes to abstract:
Abstract: Traditional development models are being slowly replaced by green economic development models. This paper views regional green economic development as a large complex system and develops a conceptual DPSIR (Drivers, Pressures, State, Impact, Response model of intervention) to construct a regional green economy development measurement index system, after which an entropy weight-TOPSIS-coupling coordination degree evaluation model is developed to quantitatively horizontally and vertically analyze regional green economy sustainable development trends and the coupled coordination status of each subsystem. The evaluation model is then employed to analyze the sustainable development of the green economy in Shandong Province from 2010 to 2016. The analysis results were found to be in line with the actual green economy development situation in Shandong Province, indicating that the measurement model had strong practicability for regional green economy development. Meanwhile, this model can demonstrate clearly how those indicators impact on the regional green economy sustainable development and fill the absence of existing studies on regional green economy sustainable development. (line 11-24 under revised manuscript).
2.-The conclusion and suggestion are too long and not focused w.r.t. their obtained contributions.
Modification explanation: Thank you for your valuable suggestions and we have add relevant content for this issue：
This paper constructed a sustainable regional green economy development index system from five aspects; economic, social, technological, resource and environment; using DPSIR and entropy-TOPSIS-coupling coordination to horizontally and vertically quantitatively analyze the sustainable green economy development. And the model was verified by the actual situation of green economy development in Shandong Province from 2010 to 2016, which confirmed the feasibility of the method. The analysis in this study came to the following conclusions:
(1) The DPSIR was used to transform the internal development of each subsystem into a driver, a pressure, a state, or a response. Compared to traditional economic evaluations that tend to only reveal the surface conditions, the DPSIR was shown to more fully reveal the impact of the various factors on economic development and comprehensively analyze the interrelated relationships; therefore, based on the DPSIR theory, this paper established a green economic development evaluation index system, which provides a good theoretical framework for the global green economy development evaluation.
(2) The entropy weight-TOPSIS model established in this paper has important application value for the longitudinal analysis of green economy development. The analysis of the comprehensive green economy development scores each year was shown to determine the distance between the current development status and the ideal status in each year, thus allowing for a clarification of the green economy development trends; therefore, this method was also shown to have a good reference value for the multi-dimensional comprehensive analyses of regional green economic development systems.
(3) Coupling Coordination Theory was used to analyze the coordinated development of the various subsystems and identify the constraints on sustainable green economy development from economic, social, technological, resource, and environmental perspectives; therefore, as this method provides a valuable reference for the development of the green economy, targeted future development planning recommendations could be proposed based on the actual regional situation. (line 411-436 under revised manuscript).
3.-Typing errors are founds in Figure 1, Line 114.
Modification explanation: Thank you for your valuable suggestions and we have modified the word “Driveers” into “Drivers” in Figure 1. (line 122 under revised manuscript).
4. -The authors need to revise their numbering system of figures, Figure 1 and Figure 2 are repeated numbered.
Modification explanation: We were sorry for the repetition of figure numbers, and we have reordered all graphs of the article.
5.-The authors need to revise the appearance of tables to avoid the improper word-break.
Modification explanation: Thank you for your valuable suggestions and we have improved the appearance of tables.
We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper.
We appreciate for your warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Min Wang
Sichuan University
2018-12-26
Round 2
Reviewer 2 Report
The Authors have complemented references concerning choice of the entropy weighting, as well as described their choice of variables more extensively (they explained why they hadn't made any changes in their set of variables). I find the changes satisfactory.
