Research on Autonomous Vehicle Technology Innovation Ecosystem in China Based on System Dynamics

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. A large part of the Introduction is a failed tentative to compare “two different technology routes […] derived in the field of autonomous driving: single-vehicle intelligent autonomous driving and vehicle-road-cloud integrated autonomous driving” (p.1, lines 39–40). Since there is no neat face-to-face comparison and no clearly stated purpose then: why to compare them? It is recommended to address this issue.
2. The introductory part (p.3) contains formulations like “this article studies …” (lines 93–94) and “this article aims to improve …” (lines 105–108); both are long phrases which, unfortunately, failed to formulate the research objectives. It is strongly recommended to clearly and unambiguously state the study objective/s.
3. The formulation “… continuous maturation of autonomous driving …” (p.1, line 35) is arguable, since “maturation” is just a stage of the life cycle. Revision is suggested.
4. The literature review related to innovation ecosystems (2.1) looks outdated (with one exception, references are more than a decade old) and fails to identify the literature gap and set the background for the research in discussion. It is highly recommended to update the references; also, to extend and improve the above section of the paper as suggested.
5. The methodology section: The author/s propose a “system dynamics model” (p.5, line 231–232) which assumes that “technological innovation ecosystem of autonomous vehicles is a continuous and progressive process” (p.6, lines 239– 240). This dynamic and progressive process looks in contradiction with other basic assumptions (p.6): “time delay is not considered in this article” (2); and “there is no change in the general direction of the national policy guidelines” (3). Therefore, coherent and documented discussion on this matter is highly recommended.
6. It is recommended to highlight the original elements of the study – as compared to the state-of-the-art international literature.
7. Limitations and further research mainly should be identified and reported.
8. It is recommended that final part of the proposed paper to include (besides general statements) more concrete and specific recommendations addressed to the main stakeholders of the ecosystem described.
9. It would be advisable to develop and insert a discussion about the social and managerial implications of the research presented.
10. There are phrases that looks unfinished (e.g., “Domestic car companies represented by Ideal, Azure, Changan, Geely, and smart driving suppliers such as Huawei, Sensetime, and Haomo.” (p.2, lines 55–56). It is strongly recommended to revise the proposed paper entirely from this standpoint.
11. The author/s mention “the research of Xu and Hu” (p.12, line 470) but neither citations nor references are provided. This issue should be addressed.
12. The author/s claim “15 years of prediction” (p.13, line 515). Nevertheless, the formulation must be revised since the “prediction” is associated with 7 (seven) years (2023–2030) only. The 15 years might be total years of study.
13. In addition: as it is rather risky to make predictions in that case when the prediction horizon (7 years: 2023–2030) is comparable to the period of available data (8 years: 2015–2023), a documented discussion on this topic is strongly recommended.
14. The graphs (figures 1-to-5) are useful and nice. Nonetheless, it is suggested to turn writing more legible.
15. The same applies to diagrams (figures 6-to-15).
16. For the sake of ease of reading and communicating author/s’ ideas, it is suggested to split excessively long paragraphs (by respective ideas).
17. It is suggested to avoid and reformulate tautologic definitions (e.g., “Autonomous vehicle technology innovation ecosystem is an innovation ecosystem … “ (p.5, line 220).
18. For avoiding potential confusions, it is suggested to analyse the possibility of using a more suitable word than “route” in the context of this paper.
19. Spacing, punctuation and orthography should be double-checked across the paper.

Comments on the Quality of English Language

(per comments addressed to author/s)

Author Response

Dear reviewer，please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The competition in the autonomous vehicle industry is provoked through key innovative technologies. Therefore, for the emerging autonomous vehicle industry, breakthroughs in technology and innovation are key elements of development. They depend on the most advanced technological achievements. Quite a few automobile companies are actively involved in the research and development of autonomous vehicle technologies, which promotes the development of the autonomous vehicle industry. Therefore, the article and the modeling and research findings presented in it are very relevant and significant in today's research.

Very interesting article. I have a few suggestions:
1. When describing Fig. 1, 2, 3  it is not clear how it relates to the presented model (Fig. 4), because it are named as subsystems, and in the model itself they are not visible, they merge. I would suggest highlighting or highlighting that place in the model with different colors (Fig. 4).
2. You claim that the members of the research group traveled to different cities - Beijing, Chongqing etc., conducting on-site research and interviewing numerous autonomous vehicle companies and consumers in the market. You just did not provide information about the specifics of those interviews? Where are their results? How did this affect your model?
3. Very interesting research, but I missed comparing the results of your research with the results of other researchers.

Author Response

Dear reviewer，please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This paper focuses on the research of China's autonomous driving technology innovation ecosystem, which has important practical significance and theoretical value. From the perspective of the innovation ecosystem, the paper uses the system dynamics method to build a model and conduct simulation analysis, exploring the impact of different elements on autonomous driving technology innovation. The research ideas are clear, the method selection is reasonable, and the conclusions are forward-looking and guiding to a certain extent.

However, there are still some relatively major flaws in the paper:

1. Although the paper conducts historical tests in model validation, the settings of some parameters still have certain ambiguity. Is it possible to add an appendix to explain the data sources of each parameter, whether it is enterprise-level micro-data, international comparison data, or personal hypothesized data, so as to enhance the accuracy and persuasiveness of the model.

2. In the first sentence of the methodology section, it is stated that "Autonomous vehicle technology innovation ecosystem is an innovation ecosystem composed of five technological innovation main bodies, including government, universities and research institutes, intermediary organizations, and market consumers" Here, enterprises are not mentioned. However, in the subsequent elaboration, enterprises are emphasized while market consumers are downplayed.

3. In the innovation resource supply subsystem, it seems that all the power sources are government support. Isn't market demand a driving force for increasing the supply of innovation resources? Even in Figure 4, I don't see that market demand can promote the supply of innovation resources. Does market demand only affect the diffusion rate? This is a relatively big problem because it seems to deny the economic theory that the market drives technological innovation.

4. How is the "Financial scale" in the model characterized? It seems to be a variable that is not affected by changes in other factors. Does government support have no impact on it? Generally speaking, the technology fields supported by the government are more likely to obtain financing and loans.

5. In the technology innovation diffusion subsystem, the author uses many variables that are not explained. I can understand that these variables may come from the technology innovation diffusion theory, but the specific connotations of these variables in this study need to be explained.

6. Figure 1 and Figure 3 seem to have a lot of repetitive content. Figure 3 only seems to have one more element of industry-university-research cooperation, but the text description of the paper includes various incentives and guarantees. Can these incentives and guarantees correspond to the relationships presented in Figure 3?

7. Some equations in the model are confusing. For example, where do the several weight factors in the calculation formula for autonomous driving R&D investment come from? Where does the initial value of 378 for the technological innovation level come from?

8. The paper conducts a sensitivity analysis for the research results, which is good. But can the authors draw some more specific policy recommendations through the sensitivity analysis? Currently, the policy recommendations in the paper seem to be relatively weak.

9. The paper indicates in both the abstract and the introduction that it aims to solve the problem of autonomous driving technology route decision-making. However, the research method does not distinguish between the two technology routes. The research results also cannot support the research conclusions. The key point mentioned in the paper is that the government's investment in infrastructure can improve the level of technological innovation. But is it possible that investing this part of the funds in other aspects can also improve the level of technological innovation, such as education, R&D, and corporate tax reduction? The inconsistency among the purpose, method, result, and conclusion may be the biggest flaw of the paper.

Author Response

Dear reviewer，please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

1. In Section 3.1, the paper proposes to analyze the technological development of autonomous vehicles through a system dynamics model. However, there is limited explanation of how the two technology routes, single-vehicle intelligence and vehicle-road-cloud integration, are quantitatively compared within this model. The paper would benefit from a clearer description of the metrics and parameters used to evaluate and compare the impacts of these two approaches on technological innovation. Specifically, how are the advantages of vehicle-road-cloud integration, such as the role of 5G and infrastructure, being weighed against the more self-contained approach of single-vehicle intelligence?
2. To enhance the depth and richness of the article, it is recommended to include references to the following papers that further elaborate on the advantages and characteristics of autonomous vehicles.  Qin, Y., Luo, Q., & Xiao, T. (2024). Capacity modeling for mixed traffic with connected automated vehicles on minor roads at priority intersections. Transportation Planning and Technology, 1-25.

3. The model makes several assumptions about the stability of external factors, such as national policy guidelines and infrastructure developments. These assumptions may oversimplify the real-world dynamics of autonomous vehicle development.
4. The paper focuses heavily on the two technological routes (single-vehicle intelligence vs. vehicle-road-cloud integration), but there is a lack of detailed discussion regarding the synergies between these technologies, especially in hybrid models.
5. While the paper discusses the technological and economic elements of autonomous vehicle innovation, it offers little exploration of consumer behavior and societal impacts, which are crucial for the successful adoption of autonomous driving technology.
6. The paper mentions that data for the system dynamics model is sourced from official publications, such as the China Statistical Yearbook and the China Automotive Industry Yearbook. However, the methodology for data collection and processing is not sufficiently detailed. For example, how were the variables and parameters derived from these sources? Were any assumptions made regarding data completeness or accuracy? More transparency regarding data selection, processing, and any potential limitations or biases would strengthen the paper's credibility and allow for better replication of the results.

Author Response

Dear reviewer，please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

1. (formerly #2). The author/s’ long answer (instead to clearly state the research objective/s) reads that “It [the study] constructs an innovation ecosystem …” – which is confusing if not plainly wrong: “It” cannot construct an innovation ecosystem which is already in place (“It” may barely construct a model of …). Rephrasing (in shorter and clear statements) and reformulation are highly recommended.
2. (formerly #4). The list of references has been improved; however the literature gap is not emphasized. It is suggested to be.
3. (formerly #5). The contradiction between the core concept of the proposed model (“system dynamics” which implies continuous changes) and study hypotheses (not considering the significant time delay – hypothesis 1; and “no change in the general direction” – hypothesis 2) is still on. Complexity of the system (hypothesis 3) is not a reason to bypass this obvious contradiction (both in theory and practice). It is recommended to address this issue and solve the problem.
4. (formerly #7). Some research limitations and further study are presented. However, one of the limitations (contradiction dynamic/change versus static/non-change) is not discussed. It should be.
5. (formerly #8). The author/s have formulated recommendations addressed to policy makers in more details; however, recommendations to other main stakeholders (companies producing autonomous vehicles, R&D units, etc.) are not visible. It is suggested to be.
6. (formerly #10 & #16). There still are long phrases, sometimes extended as a paragraph (e.g., p.9) as well as phrases that look unfinished (e.g., first paragraph under 3.2.4, lines 392–397, et al.). For the sake of clarity, it is recommended to carefully revise the paper from this standpoint.

Comments on the Quality of English Language

See suggestions to authors (comment vi).

Author Response

Reviewer 3 Report

Comments and Suggestions for Authors

I accept the vast majority of the authors' revisions. However, I still have some concerns regarding several equations in Appendix A:

1. In Equation (8), the direct addition of three parameters seems a bit arbitrary. There should be differences in the influence weights of different parameters.
2. How was Equation (12) derived? In fact, there are real data available for the number of R&D patents. Has the simulation result been compared with the real data?
3. Why is market demand negatively correlated with the level of technological innovation in Equation (14)? This seems to contradict the causal diagram.
4. Why is the adoption rate negatively correlated with market demand in Equation (19)? This relationship is not reflected in the causal diagram either.

Author Response

Reviewer 4 Report

Comments and Suggestions for Authors

I have no further comments.

Author Response

Dear reviewer, thank you so much for your reviewing! We deeply appreciate your recognition of our research work.

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

I. It is recommended that revised Abstract to explicitly mention the period under scrutiny (2015–2030).

II. Relative to the research hypotheses (p.6):

• It is suggested to declare that hypotheses (1) and (3) are simplifying hypotheses.
• It is recommended to significantly reformulate the hypothesis (2) [“The development situation of the autonomous vehicle industry is basically stable during the operation of the model, and there is no change in the general direction of the national policy guidelines.” (lines 244–246)], making clear that “stability” refers strictly to the “national policy guidelines” only (and not to the vehicle industry itself).

III. The main “research object” (line 235, et al.) that refers to (2015-2030) period should explicitly be written as “research interval / time horizon", etc., and understood as such (in time terms).

IV. It was suggested (and still is) that research limitations (last part of Conclusions) to be highlighted as a distinct sub/section.

V. It was suggested (and still is) that paper Conclusion to be written in short, punchy statements (and not in general terms) declaring to what extent the research objective/s were reached.

VI. In the same line of thought, several concluding remarks (pp.21–22) are long phrases not documented, with uncertain time horizon or simply wrong. It is recommended to revise this part (reformulate, document, or give up / remove) in terms of:

• time dimension / time horizon – e.g., “the revenue from technological innovation will show a better [?] growth trend in the future [what “future”?], and the level of industrial development and the competitiveness of enterprises will reach a higher level in the future [which future?]” (lines 851–853); “by then [when?], China's ability in artificial intelligence algorithms and decision-making chips in the field of autonomous driving will also be further [what “further” means?] improved” (lines 854–855);
• certainty and precision (there is excess of “should”): e.g., “Autonomous driving enterprises should actively participate in the construction of new infrastructure” (line 877); “Universities and research institutes should continue to expand the construction of technological innovation and exchange platforms” (lines 883–884); “Government and enterprises should establish a consumer demand feedback mechanism” (line 891); “consumers should actively participate in technology testing” (line 894); “Financial institutions should explore diversified financing models to support the R&D” (line 898); of course they should but how (specifically)?

VII. It is recommended to redesign the figures (6–to–15) to make their texts legible.

Comments on the Quality of English Language

See comments to author/s.

Author Response

Comments 1: It is recommended that revised Abstract to explicitly mention the period under scrutiny (2015–2030).
Response 1: Thank you for your constructive comments. Based on your feedback, we have clearly added the period under scrutiny (2015–2030) in the abstract. The changes are as follows:

Abstract
Based on the perspective of innovation ecosystem, the system dynamics research method is used to construct a technological innovation ecosystem model of autonomous vehicle in China. Using Vensim PLE software for simulation to obtain the development trend of technological innovation from 2015 to 2030, and to explore the impact of various elements inside the system on the overall system. The research finds that the dynamic mechanism of China's autonomous vehicle technology innovation ecosystem mainly includes the innovation resource supply subsystem, the technology innovation diffusion subsystem, and the incentive and guarantee subsystem. Each subsystem interacts to jointly promote continuous innovation and iterative upgrading of technology. Education investment, infrastructure construction, innovation platform construction and other factors all have a positive impact on the technological innovation level of autonomous vehicle, and the effect of multiple parameter changes is far more significant than that of single factor changes. The number of research and development patents, level of technological innovation, actual adopters of technological innovation, and benefits of technological innovation are all showing a good growth trend in the future. Accordingly, it is concluded that there should be optimization of scientific research investment strategies, acceleration of infrastructure layout, and expansion of application scenarios. These insights provide theoretical basis and practical guidance for promoting the high-quality development of autonomous vehicle technology in China.
(Please refer to page 1 of the revised paper)

Comments 2: Relative to the research hypotheses (p.6):
It is suggested to declare that hypotheses (1) and (3) are simplifying hypotheses.
It is recommended to significantly reformulate the hypothesis (2) [“The development situation of the autonomous vehicle industry is basically stable during the operation of the model, and there is no change in the general direction of the national policy guidelines.” (lines 244–246)], making clear that “stability” refers strictly to the “national policy guidelines” only (and not to the vehicle industry itself).
Response 2: Thank you very much for your insightful suggestion on the hypotheses. As suggested, we have reformulated hypothesis (2) to clarify that "stability" strictly. The changes are as follows:

3.1. Boundaries and Assumptions of the System Model
…
Referring to the studies of Zhao et al. [23] and Xi [24], according to the research needs, the following basic assumptions are made for the model:
(1) In order to simplify the system dynamics model, the time delay problem is not considered in this article.
(2) During the operation of the model, the national policy guidelines remain stable with no significant changes in the general direction of these guidelines.
(3) The autonomous vehicle industry chain is relatively complex. In order to simplify the model, this article only considers the roles of five parties: enterprises, government, universities and research institutes, intermediary organizations, and market consumers, while the roles of other secondary subjects are ignored.
(Please refer to page 6 of the revised paper)

Comments 3: The main “research object” (line 235, et al.) that refers to (2015-2030) period should explicitly be written as “research interval / time horizon", etc., and understood as such (in time terms).
Response 3: We sincerely appreciate your careful review and the valuable comment. As suggested, we have revised the text to clarify that 2015–2030 denotes the time horizon of our study.

3.1. Boundaries and Assumptions of the System Model
Determining the system boundary and assumptions is the basis for establishing the system dynamics model. The release of “Made in China 2025” in 2015 marked the starting point of the development of autonomous vehicle in China. Since then, the “Strategy for the Innovative Development of Intelligent Vehicles” and the “Technology Roadmap for Energy-saving and New Energy Vehicles” have specified 2025 and 2030 as the two key nodes of technological innovation.
Accordingly, this article focuses on China’s autonomous vehicle industry, with the time horizon set from 2015 to 2030, to explore the dynamics of technological innovation within this period. During the past decade, the government has continuously is-sued relevant policies to support and encourage the development of autonomous vehicles, creating a favorable policy environment for them. In the selection of innovation subjects, this paper mainly considers subjects that have significant influence on the system. Referring to the studies of Zhao et al. [23] and Xi [24], according to the research needs, the following basic assumptions are made for the model.
(Please refer to page 5, line 237-239 of the revised paper)

Comments 4: It was suggested (and still is) that research limitations (last part of Conclusions) to be highlighted as a distinct sub/section.
Response 4: Thank you very much for your valuable comments in our manuscript. We fully agree with your suggestion of making the research limitations as a distinct section.

5.3 Limitations and Future Research
Although this research has made some achievements in exploring the evolution of technological innovation of autonomous vehicle, it also has the following limitations. Current model simplifies reality by excluding time - delay factors, which are present in technology development, policy implementation, and market response. Incorporating time - delays in future work will enhance the realism of the model. The study assumes stable national policies during the research period, yet policies in this field change constantly due to technological progress, social needs, and international trends. Future research should explore how dynamic policy adjustments, like subsidy or regulation changes, affect the system. The model only accounts for five main stakeholders, while the industry's complex supply chain includes many secondary stakeholders. Future models should incorporate these to better represent industry relationships. Data col-lection is limited to the domestic market, overlooking international factors influencing autonomous vehicle technology innovation, like different regional tech requirements, consumer preferences, and regulations. Expanding data sources to include international data will lead to a more comprehensive analysis.
(Please refer to page 23 of the revised paper)

Comments 5: It was suggested (and still is) that paper Conclusion to be written in short, punchy statements (and not in general terms) declaring to what extent the research objective/s were reached.
Response 5: Thank you for your professional comments on our manuscript. Based on your suggestion, we have revised the statement in the conclusion section to clearly demonstrate the research objectives. The changes are as follows:

5.1 Conclusions
Based on the system dynamics method, this article constructs a model of China's autonomous vehicle technology innovation ecosystem, obtains a development trend map for 2015-2030 through dynamic simulation of the model, and explores the effect of different elements in the autonomous technology innovation ecosystem on the industry's future technological innovation results output.
The main results of this study can be summarized as follows:
1. This article identified the components and interactions within the autonomous vehicle technology innovation ecosystem. The model confirmed that the synergistic effects of multiple innovation main bodies, environment and subsystems are crucial for driving the iterative innovation and upgrading of autonomous driving technology.
2. The simulation results of model clearly show the continuous growth trend of relevant innovation indicators during the period of 2024-2030. This is consistent with the 2030 milestones in the Intelligent Networked Vehicle Technology Roadmap 2.0, indicating that China's autonomous vehicle industry is on track for large-scale commercial operation and industry transformation.
3. It is demonstrated the significant positive impacts of infrastructure construction, innovation platform construction, educational investment and other elements on technological innovation levels. The analysis highlighted that considering multiple parameter changes provides a more accurate prediction of technological and market trends, offering a robust basis for policy formulation and enterprise decision-making.
(Please refer to page 21-22 of the revised paper)

Comments 6: In the same line of thought, several concluding remarks (pp.21–22) are long phrases not documented, with uncertain time horizon or simply wrong. It is recommended to revise this part (reformulate, document, or give up / remove) in terms of:
time dimension / time horizon – e.g., “the revenue from technological innovation will show a better [?] growth trend in the future [what “future”?], and the level of industrial development and the competitiveness of enterprises will reach a higher level in the future [which future?]” (lines 851–853); “by then [when?], China's ability in artificial intelligence algorithms and decision-making chips in the field of autonomous driving will also be further [what “further” means?] improved” (lines 854–855);
certainty and precision (there is excess of “should”): e.g., “Autonomous driving enterprises should actively participate in the construction of new infrastructure” (line 877); “Universities and research institutes should continue to expand the construction of technological innovation and exchange platforms” (lines 883–884); “Government and enterprises should establish a consumer demand feedback mechanism” (line 891); “consumers should actively participate in technology testing” (line 894); “Financial institutions should explore diversified financing models to support the R&D” (line 898); of course they should but how (specifically)?
Response 6: We sincerely appreciate your valuable feedback regarding the clarity of the time dimension / time horizon and the issue of certainty in our manuscript. As suggested by the reviewer, we have revised the relevant statements with more precise time references based on simulation results and specific implementation paths. The changes are as follows:

5.1 Conclusions
2. The simulation results of model clearly show the continuous growth trend of relevant innovation indicators during the period of 2024-2030. This is consistent with the 2030 milestones in the Intelligent Networked Vehicle Technology Roadmap 2.0, indicating that China's autonomous vehicle industry is on track for large-scale commercial operation and industry transformation.
5.2 Policy Suggestions
Based on the research results, in order to better enhance the technological innovation capability of autonomous vehicle, this study puts forward suggestions from the perspectives of the main stakeholders of technological innovation.
In the context of increasingly fierce competition in global autonomous driving technology, government can establish a research group on autonomous driving technology to closely monitor the policy trends of foreign governments in the field of autonomous driving, in order to grasp cutting-edge trends and development models. In terms of financial support, government can allocate special funds from the fiscal budget to provide direct funding support for innovative and promising autonomous driving technology research and development projects. At the same time, government can introduce preferential policies for talent introduction to attract outstanding talents from home and abroad to participate in the innovation and development of autonomous driving technology.
Autonomous driving companies actively participate in the construction of new infrastructure based on their technological advantages, promoting the technology from the validation stage to large-scale marketization. On the one hand, by cooperation with the government to accelerate the coverage of 5G networks across the region to ensure real-time data collection and transmission for autonomous vehicles. On the other hand, by integrating IoT and big data resources, it has improved the intelligence level of transportation infrastructure and constructed a municipal intelligent transportation sensing platform.
Universities and research institutes can attract domestic and foreign peers to participate and expand the influence of technology innovation exchange platforms by holding annual international forums on autonomous driving technology and regularly organizing online academic exchange seminars. In deepening industry university re-search cooperation, cooperation agreements are signed with universities and enterprises to establish demonstration bases for the application of research and development achievements within enterprises. The research achievements of universities and re-search institutes are tested and optimized in actual production and operation scenarios to promote the transformation of scientific research achievements. As the end-users of technology implementation, consumer demand perception and feedback are crucial for technological iteration. Government and enterprises can establish a consumer demand feedback mechanism by conducting regular market re-search, establishing user experience testing platforms, setting up consumer feedback hotlines and email addresses, etc., to timely obtain consumers' needs and suggestions for autonomous driving technology. At the same time, consumers also need to actively participate in technology testing and demonstration applications, provide real scenario data for technology optimization, promote technology to be closer to market demand, and form a virtuous cycle of innovative market innovation.
Financial institutions can explore diversified financing models by establishing special venture capital funds, conducting intellectual property pledge financing, issuing special bonds, and other means to support the research and commercialization of autonomous driving technology. They can provide financial support to startups through equity financing and bond issuance. In addition, a dedicated venture capital fund can be established to focus on supporting technology projects with innovation and market potential.
(Please refer to page 22-23 of the revised paper)

Comments 7: It is recommended to redesign the figures (6–to–15) to make their texts legible.
Response 7: Thank you very much for pointing out the issue. We have redesigned figures (6-15 to make them clearer. The specific modifications have been presented in the manuscript.

4. Response to Comments on the Quality of English Language
Point 1: The English could be improved to more clearly express the research.
Response 1: Thank you very much for your insightful suggestions. As suggested by the reviewer, we have reprocessed the languages in the manuscript to express the research more clearly.

5. Additional clarifications
We sincerely thank you for all the constructive and helpful comments on our paper.
Before closing, we thank you and the review team for helping us improve the quality of our paper. Thank you very much.