Incremental Green Investment Rule Induction Using Intelligent Rough Sets from an Energy Perspective
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe article explores the intersection of green energy investment and rough set (RS) approaches, aiming to address challenges in decision-making processes within this domain.
The title effectively communicates the main focus of the article, but it could be slightly refined for clarity.
The abstract does a good job of introducing the topic and the problem being addressed. However, it could be made more concise by removing redundant phrases and unnecessary details. For example, the phrase "Energy-related green investment involves intricate economic behavior and management techniques" could be simplified to convey the same meaning in fewer words.
First of all, your summary introduces the concept of rough set (RS) methodology and its application in decision-making for green energy investments. Regardless, it could benefit from a brief explanation of what rough set methodology is and how it works, especially for readers who may not be familiar with this approach.
While the abstract mentions that the proposed intelligent rough set approach can handle problems with multiple outcome features and incremental rule generation, it could present more specific details about how exactly this is achieved. Providing a short overview of the methodology or algorithm used would help readers understand the novelty and significance of the proposed approach.
The abstract briefly touches upon the importance of identifying significant rules and ensuring the stability and robustness of decision-making in green energy investments. Instead, it could emphasize more explicitly the potential impact and significance of the proposed intelligent rough set approach in addressing these challenges. I also suggest ensuring that the abstract is free from grammatical errors and uses clear, concise language. Avoid overly technical jargon or ambiguous terms that may obscure the main points. Check for example: “But it’s not easy to reach th balance of economic and ecological objectives”.
The introduction presents an in-depth review of the context, problem statement, and objectives of your research. It outlines the importance of green energy investments in addressing environmental challenges and achieving sustainable development goals. Nevertheless, it would be helpful to clearly articulate the specific research problem or gap in the existing literature that your study addresses. Provide a concise statement that defines the problem and highlights why it is significant.
While you mention various terms related to green energy investments, such as environmentally friendly investments and socially responsible investing, consider providing brief definitions or explanations for readers who may not be familiar with these concepts.
As you quickly introduce the rough set theory (RST) and how it applies to managing qualitative data, you could want to give readers who might not be familiar with this approach a little more background information or an explanation. Describe how RST works and its advantages in processing imprecise and ambiguous data more explicitly.
Clearly state the main contribution or novelty of your research in the introduction. Specify how your proposed approach (IMORE - Incremental Multiple Outcomes Rule Extraction) advances existing methodologies or addresses limitations in previous studies. This will help readers understand the significance of your research from the outset.
The literature review chapter propose an extensive examination of existing research on green energy investments, big data technology, and the application of rough set methodology. Be that as it may, several areas could be enhanced to improve the review's effectiveness.
The chapter would benefit from explicitly stating the objectives of the literature review. Identifying specific research questions and how the review contributes to the understanding of the research topic would add clarity and relevance.
Reorganizing the literature review to group related studies or themes together would enhance the coherence and logical flow of ideas. A more cohesive narrative structure would aid readers in navigating the review more effectively. In addition, instead of solely summarizing individual studies, the review could synthesize findings to identify common themes, trends, or gaps in the literature. This would provide deeper insights into the research landscape and contribute to a more comprehensive analysis.
Another key point, offering critical analysis of the strengths and limitations of the existing research, including the methodologies used and the validity of findings, would demonstrate a rigorous evaluation of scholarly work. This would enrich the review and contribute to the scholarly discourse.
Some sentences are lengthy and may impede readability. Striving for clearer and more concise writing would improve comprehension and engagement with the review.
The third chapter, Solution Approach could benefit from a clearer structure to help readers follow the flow of information. Consider breaking down the content into subsections or bullet points for each step of the algorithm. Additionally, ensure that all notations used in the algorithm are clearly defined and explained. Readers should have a clear understanding of the symbols and variables used throughout the algorithm.
Equally important, providing an illustrative example of the IMORE algorithm in action would enhance understanding. You may think about including a hypothetical scenario and walking through each step of the algorithm with sample data.
Another key point, you could justify your methodology choices. Provide rationale for design choices made in the algorithm. Why was the IMORE approach chosen over alternative methods? What specific advantages does it offer in the context of green energy investments?
On the other hand, discuss potential challenges or limitations that may arise during the implementation of the IMORE algorithm. How might these challenges be addressed or mitigated? With this in mind, discuss the scalability of the IMORE algorithm, particularly in handling large datasets or complex decision-making scenarios. How does the algorithm perform as data volume increases?
Conclude the chapter by discussing potential future directions or extensions of the IMORE algorithm. Are there any areas for further research or refinement?
In this section the Table 3 seems to be missing.
The fourth chapter - A case of green investment in energy summarizes the key findings and implications of the case study on green energy investment decision-making. However, here are some suggestions to further enhance it:
· - Explicitly state the contribution of the case study and the proposed approach to the existing literature or practice in green energy investment. Highlight how the study fills a gap or advances understanding in the field.
· - Emphasize the practical implications of the findings for stakeholders involved in green energy investment, such as investors, companies, policymakers, and environmental organizations. How can they use the insights derived from the study to inform their decision-making processes or strategic planning?
· - Acknowledge any limitations or constraints of the study. This could include factors such as the scope of the data set, assumptions made in the analysis, or potential biases in the data collection process. Being transparent about limitations adds credibility to the study and suggests avenues for future research.
· - Offer suggestions for future research directions or extensions of the current study. This could involve exploring different variables or factors that influence green energy investment decisions, testing the proposed approach in different contexts, or evaluating its performance over longer time frames.
· - Consider framing the conclusion in a more engaging manner to captivate the reader's interest and leave a lasting impression. This could involve using compelling language, posing thought-provoking questions, or drawing connections to broader societal or environmental issues.
In the end, the study's major conclusions and contributions are succinctly outlined in the conclusion chapter. Regardless, here are some suggestions for improvement:
- The conclusion could be made more concise by eliminating redundant phrases and unnecessary repetition. Focus on presenting the main points clearly and succinctly.
- It would be beneficial to explicitly state the significance or potential impact of the proposed methodology and findings in addressing the identified shortcomings in previous studies.
- While the conclusion briefly mentions future study directions, it could be expanded to provide more specific suggestions or recommendations for further research. This could include identifying potential areas for improvement or extension of the proposed methodology, as well as discussing the broader implications for the field of green energy investment.
The English language is used correctly, but it would be worth a careful reading and a correction of the way of expression in some sentences. Some of the transitions between sentences and paragraphs could be smoother to improve the flow of the introduction.
Examples:
Green energy investments are specifically those made to reduce industrial emissions and lessen environmental contamination. [29]. Green energy investment is an economic behavior and complex management process, as it is not easy to reach both ecological goals and economic benefits. Green energy investment is a novel resource allocation strategy that allocates limited resources toward the advancement of renewable resources and green technology. [30], however, only when the green technology is profitable would firms make their investment [31].
Green investments research is on its way to make an interest in big data [22].
The algorithm contains pre-processing time. And the time complexity of Case II is the worst case in the whole IMORE algorithm (Table 3).
Author Response
The title effectively communicates the main focus of the article, but it could be slightly refined for clarity.
Response: The title has been slightly refined for clarity as suggested by the reviewer.
The abstract does a good job of introducing the topic and the problem being addressed. However, it could be made more concise by removing redundant phrases and unnecessary details. For example, the phrase "Energy-related green investment involves intricate economic behavior and management techniques" could be simplified to convey the same meaning in fewer words.
Response: The abstract has been made more concise as suggested by the reviewer in lines 15-29.
First of all, your summary introduces the concept of rough set (RS) methodology and its application in decision-making for green energy investments. Regardless, it could benefit from a brief explanation of what rough set methodology is and how it works, especially for readers who may not be familiar with this approach.
Response: The rough set methodology has been described briefly in lines 20-23 as suggested by the reviewer.
While the abstract mentions that the proposed intelligent rough set approach can handle problems with multiple outcome features and incremental rule generation, it could present more specific details about how exactly this is achieved. Providing a short overview of the methodology or algorithm used would help readers understand the novelty and significance of the proposed approach.
Response: The description of RS methodology and the novel of the proposed approach have been added in lines 23-29 as suggested by the reviewer.
The abstract briefly touches upon the importance of identifying significant rules and ensuring the stability and robustness of decision-making in green energy investments. Instead, it could emphasize more explicitly the potential impact and significance of the proposed intelligent rough set approach in addressing these challenges. I also suggest ensuring that the abstract is free from grammatical errors and uses clear, concise language. Avoid overly technical jargon or ambiguous terms that may obscure the main points. Check for example: “But it’s not easy to reach th balance of economic and ecological objectives”.
Response: “More explicitly on the potential impact and significance of the proposed intelligent rough set approach” has been emphasized as suggested by the reviewer (lines 23-29). A native English faculty member has proofread the manuscript to make sure of free from grammatical errors.
The introduction presents an in-depth review of the context, problem statement, and objectives of your research. It outlines the importance of green energy investments in addressing environmental challenges and achieving sustainable development goals. Nevertheless, it would be helpful to clearly articulate the specific research problem or gap in the existing literature that your study addresses. Provide a concise statement that defines the problem and highlights why it is significant.
Response: The research problem or gap is presented on page 2 (lines 90-94) as suggested by the reviewer.
While you mention various terms related to green energy investments, such as environmentally friendly investments and socially responsible investing, consider providing brief definitions or explanations for readers who may not be familiar with these concepts.
Response: the description is added in lines 41-50 as suggested by the reviewer.
As you quickly introduce the rough set theory (RST) and how it applies to managing qualitative data, you could want to give readers who might not be familiar with this approach a little more background information or an explanation. Describe how RST works and its advantages in processing imprecise and ambiguous data more explicitly.
Response: How RST working is described in lines 58-68 briefly. More detailed are provided in Section 2.1 (lines 178-198) and its advantages are presented in lines 193-198.
Clearly state the main contribution or novelty of your research in the introduction. Specify how your proposed approach (IMORE - Incremental Multiple Outcomes Rule Extraction) advances existing methodologies or addresses limitations in previous studies. This will help readers understand the significance of your research from the outset.
Response: the main contribution and novelty of the research based limitations in previous studies are presented on page 3 (lines 100-106) as suggested by the reviewer.
The literature review chapter propose an extensive examination of existing research on green energy investments, big data technology, and the application of rough set methodology. Be that as it may, several areas could be enhanced to improve the review's effectiveness. The chapter would benefit from explicitly stating the objectives of the literature review. Identifying specific research questions and how the review contributes to the understanding of the research topic would add clarity and relevance.
Response: The objectives and contribution of the literature review are explicitly stated on page 3 (lines 108-112) as suggested by the reviewer.
Reorganizing the literature review to group related studies or themes together would enhance the coherence and logical flow of ideas. A more cohesive narrative structure would aid readers in navigating the review more effectively. In addition, instead of solely summarizing individual studies, the review could synthesize findings to identify common themes, trends, or gaps in the literature. This would provide deeper insights into the research landscape and contribute to a more comprehensive analysis.
Response: The literature review section is re-organized to three subsections in a more cohesive narrative structure way. And a summary to identify common themes, trends, or gaps in the literature is added in Section 2.3 (page 5) as suggested by the reviewer.
Another key point, offering critical analysis of the strengths and limitations of the existing research, including the methodologies used and the validity of findings, would demonstrate a rigorous evaluation of scholarly work. This would enrich the review and contribute to the scholarly discourse.
Response: The critical analysis of the strengths and limitations of the existing research, specifically rough set based rule induction, are presented in Sections 2.2 and the findings are summarized in 2.3.
Some sentences are lengthy and may impede readability. Striving for clearer and more concise writing would improve comprehension and engagement with the review.
Response: A native English faculty member has proofread the manuscript to make sentences more readable.
The third chapter, Solution Approach could benefit from a clearer structure to help readers follow the flow of information. Consider breaking down the content into subsections or bullet points for each step of the algorithm. Additionally, ensure that all notations used in the algorithm are clearly defined and explained. Readers should have a clear understanding of the symbols and variables used throughout the algorithm.
Response: The solution approach is divided to three subsections (3.1-3.3) in a clearer structure as suggested by the reviewer. The notations used in the algorithm are clearly defined and explained on pages 6-10.
Equally important, providing an illustrative example of the IMORE algorithm in action would enhance understanding. You may think about including a hypothetical scenario and walking through each step of the algorithm with sample data.
Response: Illustrative examples are presented in Section 3.2 as suggested by the reviewer.
Another key point, you could justify your methodology choices. Provide rationale for design choices made in the algorithm. Why was the IMORE approach chosen over alternative methods? What specific advantages does it offer in the context of green energy investments? On the other hand, discuss potential challenges or limitations that may arise during the implementation of the IMORE algorithm. How might these challenges be addressed or mitigated?
Response: The IMORE approach chosen over alternative methods is explained on (p5, (lines 246-248) as suggested by the reviewer. The limitation is described pages 16-17 (lines 527-535).
With this in mind, discuss the scalability of the IMORE algorithm, particularly in handling large datasets or complex decision-making scenarios. How does the algorithm perform as data volume increases?
Response: Table 19 (page 16) shows that IMORE is more efficient than MORE. The time complexity of IMORE is linear. Consequently, the scalability of the IMORE algorithm is not a problem as data volume increases (lines 515-523).
Conclude the chapter by discussing potential future directions or extensions of the IMORE algorithm. Are there any areas for further research or refinement?
Response: The discussion is added pages 16-17 (lines 527-535) as suggested by the reviewer.
In this section the Table 3 seems to be missing.
Response: New tables are added and the tables are renumbered. Thanks for the correction.
The fourth chapter - A case of green investment in energy summarizes the key findings and implications of the case study on green energy investment decision-making. However, here are some suggestions to further enhance it:
Explicitly state the contribution of the case study and the proposed approach to the existing literature or practice in green energy investment. Highlight how the study fills a gap or advances understanding in the field.
Response: The contribution of the case study and the gap are presented on page 17 (lines 538-543) as suggested by the reviewer.
Emphasize the practical implications of the findings for stakeholders involved in green energy investment, such as investors, companies, policymakers, and environmental organizations. How can they use the insights derived from the study to inform their decision-making processes or strategic planning?
Response: the practical implications and insights from the study are presented on page 17 (Lines 544-553) as suggested by the reviewer.
Acknowledge any limitations or constraints of the study. This could include factors such as the scope of the data set, assumptions made in the analysis, or potential biases in the data collection process. Being transparent about limitations adds credibility to the study and suggests avenues for future research.
Response: the limitation of the study is presented on pages 16&17 (lines 527-535), and page 22 (lines 675-681) as suggested by the reviewer.
Offer suggestions for future research directions or extensions of the current study. This could involve exploring different variables or factors that influence green energy investment decisions, testing the proposed approach in different contexts, or evaluating its performance over longer time frames.
Response: the future research directions or extensions of the study is presented on page 22 (lines 675-681) and the conclusion section (lines 710-722) as suggested by the reviewer.
Consider framing the conclusion in a more engaging manner to captivate the reader's interest and leave a lasting impression. This could involve using compelling language, posing thought-provoking questions, or drawing connections to broader societal or environmental issues.
Response: the conclusion is gramed on page 22 (lines 680-685) as suggested by the reviewer.
In the end, the study's major conclusions and contributions are succinctly outlined in the conclusion chapter. Regardless, here are some suggestions for improvement:
The conclusion could be made more concise by eliminating redundant phrases and unnecessary repetition. Focus on presenting the main points clearly and succinctly.
Response: The conclusion is re-written. The main points are focused to present clearly and succinctly as suggested by the reviewer (Section 5).
It would be beneficial to explicitly state the significance or potential impact of the proposed methodology and findings in addressing the identified shortcomings in previous studies.
Response: The impact, contribution and findings are summarized on page 22 (lines 696-710) as suggested by the reviewer.
While the conclusion briefly mentions future study directions, it could be expanded to provide more specific suggestions or recommendations for further research. This could include identifying potential areas for improvement or extension of the proposed methodology, as well as discussing the broader implications for the field of green energy investment.
Response: The future study is enriched as suggested by the reviewer (lines 712-724).
Comments on the Quality of English Language
The English language is used correctly, but it would be worth a careful reading and a correction of the way of expression in some sentences. Some of the transitions between sentences and paragraphs could be smoother to improve the flow of the introduction.
Response: A native English faculty member has proofread the manuscript.
Examples:
Green energy investments are specifically those made to reduce industrial emissions and lessen environmental contamination. [29]. Green energy investment is an economic behavior and complex management process, as it is not easy to reach both ecological goals and economic benefits. Green energy investment is a novel resource allocation strategy that allocates limited resources toward the advancement of renewable resources and green technology. [30], however, only when the green technology is profitable would firms make their investment [31].
Response: A native English faculty member has proofread these sentences in lines 120-129.
Green investments research is on its way to make an interest in big data [22].
Response: A native English faculty member has proofread the sentence in line 76.
The algorithm contains pre-processing time. And the time complexity of Case II is the worst case in the whole IMORE algorithm (Table 3).
Response: The time complexity of Case II is the worse in IMORE. The case does not save any computation and since the features of the new data set are identical to the features of the original data set and outcomes are not identical. That is, unfortunately the data are required to re-implemented.
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper presents a research study that utilizes the IMORE-based methodology within the framework of rough set (RS) techniques. The research initially examines the existing literature on green energy investment and RS methodologies, highlighting the limitations of earlier studies. This paper presents a novel approach for extracting incremental RS set rules in order to address dynamic database difficulties in the context of green energy investment. This approach effectively manages altered data. IMORE is utilized to assess a case. This paper presents a comprehensive analysis of the reduction outcomes of IMORE and MORE. The study also includes a robustness check to validate the findings.
From my perspective, the chosen research topic is both relevant and captivating, making it suitable for considering to be published in Sustainability, however, requires revisions to improve the caliber of the manuscript. I would like to provide the following suggestions for enhancing the overall quality of the paper.
· In the Introduction section, it is imperative to situate your article within the existing academic literature. Elucidate the additional contributions of your work to the existing body of knowledge.
· Research questions should be formulated in the Introduction section to establish the rationale for conducting the investigation. The Conclusion section should offer responses to the research questions.
· Enhance your literature review by providing an overview of the characteristics of generic multiple-criteria decision making (MCDM). The RS should be positioned in the paper as one of the various approaches that can be used to solve MCDM problems.
· The description of the IMORE algorithm should be reorganized and placed in the Appendix. The current format of the paper hinders the smooth flow of readability.
· Include a summary of the limitations, implications, and potential areas for future research in the Conclusion section.
Comments on the Quality of English LanguageThe paper is written in proper English, however, proofreeding is necessary to make stylistic corrections and typo errors.
Author Response
In the Introduction section, it is imperative to situate your article within the existing academic literature. Elucidate the additional contributions of your work to the existing body of knowledge.
Response: The introduction is improved as suggested by the reviewer. The research gap on page 2 (lines 90-95) and the novel on page 2 (lines 100-106) are highlighted in the introduction section.
Research questions should be formulated in the Introduction section to establish the rationale for conducting the investigation. The Conclusion section should offer responses to the research questions.
Response: The research problems are presented on page 2 (lines 90-95). The contribution of the study in the conclusion also responds to the problems (lines 696-710) as suggested by the reviewer.
Enhance your literature review by providing an overview of the characteristics of generic multiple-criteria decision making (MCDM). The RS should be positioned in the paper as one of the various approaches that can be used to solve MCDM problems.
Response: The literature related to multiple-criteria decision making (MCDM) is added as suggested by the reviewer (page 3, lines 130-138).
The description of the IMORE algorithm should be reorganized and placed in the Appendix. The current format of the paper hinders the smooth flow of readability.
Response: Since the other reviewer suggest to add illustrative example to make the algorithm more readable, the example for each case is added and subtitle are highlighted for the four cases and their pseudo cades. Hope that could make read flow smooth (Section 3).
Include a summary of the limitations, implications, and potential areas for future research in the Conclusion section.
Response: The limitations, implications, and future research are enriched as suggested by the reviewer (lines 712-724).
The paper is written in proper English, however, proofreading is necessary to make stylistic corrections and typo errors.
Response: A native English faculty member has proofread the manuscript.
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe manuscript has been improved after the first round of review thus contributing to an improved version.