Electric Car Market Analysis Using Open Data: Sales, Volatility Assessment, and Forecasting
Round 1
Reviewer 1 Report
Title: Electric car market analysis using open data: sales, sustainability assessment and forecasting
Journal: Sustainability
Paper ID: sustainability-2025516
This manuscript uses open data to analyze the patterns and changes in the electric vehicle market over a decade, makes assessments and predictions, and offers recommendations for researchers, automakers, regulators and others. The topic is interesting. However, some inappropriate problem statements and assumptions needed to address. My concerns are listed as follows.
1. My first major concern focuses on the introduction.
(a) Line 8, Page 2. This is the first time that “independent analysis” is mentioned in this article, and you need to explain what it means. What does “independent” mean? Does it mean that the institutions are doing analysis independently, or that you are doing independent analysis based on institutional data? This seems a bit confusing.
(b) Line 18, Page 2. The term "one or another model" is too vague. You should indicate which methods or prediction models other scholars have used, and the accuracy of their predictions.
(c) Line 10, Page 1. (Electric vehicles enable zero-emission mobility and are becoming more and more popular). The actual emissions of electric vehicles are transferred upstream to power generation, especially in areas dominated by coal-fired power. It will take a long time for the clean energy to replace thermal power generation. So it should be mentioned that EVs can reduce carbon emission only during vehicle operation.
(d) Line 16, Page 2. What are the relevant conclusions and findings of previous studies on the prospect of EV sales? In my opinion, the section of Introduction lacks some summaries of previous relevant research results to support the persuasiveness of the paper.
2. My second major concern focuses on the methods.
(a) Line 9, Page 3. What is the quantitative analysis method used in the article? A definition of the key variable Vnorm can be presented to help the readers quickly understand the core techniques of the paper.
3. My second major concern focuses on the results and discussions.
(a) Line 34-38, Page 3. You raised two good questions. However, they are not answered in the following. In my opinion, if you think these two questions are difficult to solve, please give your analysis and reasons, or at least your predictions, rather than just asking questions.
(b) Figure 1, Page 4. Your interpretation of the picture is reasonable. Steady but slow linear growth from 2012 to 2018, was followed by much faster growth in 2020 and 2021. But in the picture, the green straight line representing Europe does not reflect this change; instead, it remains straight after 2018.
(c) Line 22, Page 4. Which “decisive action”? Not specified in the paper.
(d) Line 36-41, Page 4. These rows contain a large amount of proportional data, a set of graphs representing proportions (e.g. pie charts) can be considered to add.
(e) Line 38, Page 6. What is the exact definition of anxiety year? Is a year that does not grow at the projected rate an anxiety year? Is there a better way than just excluding anxiety years data, such as some smoothing measures?
(f) Lines 27, Page 3. What does 6.6 million sales compare to? The word ‘exceed’ would be confusing though after reading the paper we could know it compare to zero year.
(g) Lines 32-38, Page 3. Does Tesla's high production necessarily mean high market share? It is better to point out the relationship between EV production and market share.
(h) Line 1, Page 4. The data sources for all the charts in this article need to be pointed out one by one, which helps readers trace the source of data.
(i) Line 19, Page 6. Further analysis can be made of changes in EV sales in South Korea, Canada and Japan. In particular, which factors drive the unusual shift in electric car sales in Japan? This helps to explore the topic (sustainability of EV market) of paper.
(j) Line 32-35 Page 8. It is interesting that the variance of the Vnorm is a good indicator of the sustainability of the different countries’ EV market! However, a detailed formula of variance should be listed to help readers understand method rapidly.
(k) Line 17-19 Page 10. Does the unsatisfactory prediction result of the model in this paper mean that the market sales of EV market sales are unpredictable?
3. My third concern focuses on the conclusions.
(a) Line 50, Page 13. The "Normalized monthly sales" method is indeed a good one. However, if this paper wants to recommend this method, it should at least demonstrate its superiority over other methods. For example, how accurate are other scholars' methods? Is this paper's method more accurate than theirs? Or is it more stable?
4. The paper also suffers from some presentation issues. Below I list some examples and the list could be longer.
(a) Line 7, Page 1. Goal setting.
(b) Line 13, Page 1. Causes.
(c) Line 14, Page 1. “Automobile” here should be “automobiles”.
(d) Line 14, Page 1. Tense error, engine has become.
(e) Line 17, Page 1. Part of speech error: “refusing” should be “refusal”.
(f) Line 24, Page 1. Non-academic expression, the two phrases should be combined: “It takes a lot of time”.
(g) Line 2, Page 2. Missing “of”: Two (of) the most popular.
(h) Line 5, Page 2. Missing “a”: has (a) free interactive.
(i) Line 24, Page 2. Delete “of”: behind of industrial.
(j) Line 30, Page 2. “In the most articles”, delete “the”.
(k) Line 30, Page 2. Delete the “,” after articles.
(l) Line 30, Page 2. “As the result” should be “As a result” here.
(m) Line 31, Page 2. There should be a “which” before “arrived”.
(n) Line 36, Page 2. Lack a space between “2021” and “and”.
(o) Line 36, Page 2. Lack “the” between “of” and “first”.
(p) Line 51, Page 2. “As the result” should be “As a result” here.
(q) Line 6, Page 3. “In term of” should be “in terms of” here.
(r) Line 2, Page 4. Lack “of” between “three” and “the”.
(s) Line 26-27, Page 4. There should be a “the” before European, an “a” between “solid” and delete “has” and “in”.
(t) Line 30, Page 4. Tense error: became.
(u) Line 9, Page 5. Netherlands.
(v) Line 9, Page 6. Slip of pen: adapt.
(w) Line 17, Page 6. Lexical error: increased.
(x) Line 33, Page 6. Slip of pen: assess.
(y) Line 44, Page 6. Error: correspond.
(z) Line 4, Page 7. Error: These.
(a1) Line 11, Page 9. Line 14, Page 9. There should be a “to” after “amount”.
(b1) Line 6, Page 10. Delete “at”.
(c1) Line 15, Page 10. Error: decreases.
(d1) Line 18, Page 10. “How valuable can mid- and long-term predictions be?”
(e1) Line 23, Page 11. Lack “all” between “almost” and “forecasts”
(f1) Line 3, Page 13. Analysts.
(g1) Line 12, Page 13. “In” should be “of” here.
(h1) Line 14, Page 14. Lack “and” or “or” before “Japan”.
Author Response
Dear reviewer,
Thank you for your valuable recommendations. It was a pleasure to read such useful comments, so we are grateful for your efforts. Please find below our corrections and responses.
- My first major concern focuses on the introduction.
(a) Line 8, Page 2. This is the first time that “independent analysis” is mentioned in this article, and you need to explain what it means. What does “independent” mean? Does it mean that the institutions are doing analysis independently, or that you are doing independent analysis based on institutional data? This seems a bit confusing.
Response 1a: You are right, the wording was confusing and we have corrected it
was: “Another promising source of independent analysis is scientific publications, …”
now: “Another source of EV market analysis is scientific publications, …”
(b) Line 18, Page 2. The term "one or another model" is too vague. You should indicate which methods or prediction models other scholars have used, and the accuracy of their predictions.
Response 1b: You are right, the wording was confusing. In our work we don’t want to consider various theoretical models for EV market forecasting, so it would be more accurate to use more general formulation
was:
“In such theoretical papers, researchers study how one or another model can be used for market growth forecasting and how this forecast will change with variation of model’s parameters”
now:
“In such theoretical papers, researchers study how a model can be used for EV market growth forecasting and how this forecast will change with variation of the model’s parameters”
(c) Line 10, Page 1. (Electric vehicles enable zero-emission mobility and are becoming more and more popular). The actual emissions of electric vehicles are transferred upstream to power generation, especially in areas dominated by coal-fired power. It will take a long time for the clean energy to replace thermal power generation. So it should be mentioned that EVs can reduce carbon emission only during vehicle operation.
Response 1c: We cannot fully agree because “enable” mean “make possible” but not “provide” or “ensure”. But if such wording confused you it can easily confuse someone else, so we decided to make wording monosemantic.
was: “Electric vehicles (EV) enable zero-emission mobility …”
now: “Electric vehicles (EV) make a zero-emission mobility possible …”
(d) Line 16, Page 2. What are the relevant conclusions and findings of previous studies on the prospect of EV sales? In my opinion, the section of Introduction lacks some summaries of previous relevant research results to support the persuasiveness of the paper.
Response 1d: We've improved the introduction by removing some redundant sentences and rewording the last (summary) paragraph. We understand that a summary of previous research papers will be interesting, but since we propose a novel approach using 12-months period analysis, we can only conclude about its novelty.
- My second major concern focuses on the methods.
(a) Line 9, Page 3. What is the quantitative analysis method used in the article? A definition of the key variable Vnorm can be presented to help the readers quickly understand the core techniques of the paper.
Response 2a: Well, since we introduce a new method, we thought that it should be described in the main part of the manuscript. But if you think this will help to understand the results, why not. We have added a corresponding paragraph to the Methods.
- My second major concern focuses on the results and discussions.
(a) Line 34-38, Page 3. You raised two good questions. However, they are not answered in the following. In my opinion, if you think these two questions are difficult to solve, please give your analysis and reasons, or at least your predictions, rather than just asking questions.
Response 3a: Well, we think that culture of academic publication activity is changing. Modern authors are much more focused on metrics are productivity than several decades ago. Maybe because of that asking questions today is less popular than giving answers. It looks like today authors afraid to ask questions if they cannot give an answer. Is that right? We are not sure.
Analysis of Tesla’s role is very interesting, but we are afraid that this discussion will bring us away from the modern standards of an academic publication. We will try to start a work on a small study of the current situation at the US market of electric cars. But for this paper we would prefer to leave these two questions unanswered. Let us consider this as a specific author style.
(b) Figure 1, Page 4. Your interpretation of the picture is reasonable. Steady but slow linear growth from 2012 to 2018, was followed by much faster growth in 2020 and 2021. But in the picture, the green straight line representing Europe does not reflect this change; instead, it remains straight after 2018.
Response 3b: We added the following description to the Figure 1 caption:
“The linear and exponential approximations were made for EV sales volumes through 2018 and extended till 2021 to see the deviations of factual data from these simplified descriptions earlier made in [16].”
This description was in the initial version but later was lost during inner revisions.
(c) Line 22, Page 4. Which “decisive action”? Not specified in the paper.
Response 3c: Sounds reasonable. We have corrected the formulation and additionally have mentioned the Inflation Reduction Act of 2022
was:
“The results of 2021 and the decisive actions of legacy US automakers give hope for a change in growth rates in 2022 and beyond.”
now:
“The results of 2021, preliminary results of 2022, the Inflation Reduction Act of 2022 [29], and the massive announcements of legacy US automakers to create joint ventures with major lithium batteries manufactures give hope for a change in growth rates in 2022 and beyond.”
(d) Line 36-41, Page 4. These rows contain a large amount of proportional data, a set of graphs representing proportions (e.g. pie charts) can be considered to add.
Response 3d: The pie charts will be illustrative but not necessary. Also please mention that all graphics represent time dependencies and one pie charts will stand out more than it is supposed by the logic of the article.
(e) Line 38, Page 6. What is the exact definition of anxiety year? Is a year that does not grow at the projected rate an anxiety year? Is there a better way than just excluding anxiety years data, such as some smoothing measures?
Response 3e: We have corrected a little bit the wording of this sentence but not much. Further in text we discuss these anxieties in terms of deviations and even propose a possible quantitative method for its determination using conventional standard deviation. We think Fig. 4 is rather illustrative.
was:
“Anxious years was removed from averaging due to its deviation from the usual behavior.”
now:
“Anxious years (2019 for China, 2020 for the United States and Europe) were removed from averaging due to its deviation from the usual behavior (Fig. 3).”
(f) Lines 27, Page 3. What does 6.6 million sales compare to? The word ‘exceed’ would be confusing though after reading the paper we could know it compare to zero year.
Response 3f: We changed the word to avoid confusing:
was:
“Global EV sales exceeded 6.6 million”
now:
“Global EV sales reached 6.6 million per year in 2021”
(g) Lines 32-38, Page 3. Does Tesla's high production necessarily mean high market share? It is better to point out the relationship between EV production and market share.
Response 3g: We added the market share of Tesla in 2019
was:
“In the same year, Tesla alone produced 367 thousand electric cars, …”
now:
“In the same year, Tesla alone produced 367 thousand electric cars (about 17% of the global EV production), …”
(h) Line 1, Page 4. The data sources for all the charts in this article need to be pointed out one by one, which helps readers trace the source of data.
Response 3h: We added the sentence “The data are taken from open sources described in the first paragraph of the Methodology.” to captions for all figures. The list is rather large but the same for all the figures, so this relatively short sentence let us to avoid overloaded captions.
(i) Line 19, Page 6. Further analysis can be made of changes in EV sales in South Korea, Canada and Japan. In particular, which factors drive the unusual shift in electric car sales in Japan? This helps to explore the topic (sustainability of EV market) of paper.
Response 3i: You give us difficult tasks. How to discuss the very specific peculiarity of EV sales in Japan in few sentences? Well, maybe the following sentences will be enough:
“We suppose the decisive role of Toyota Motor Company with its commitment to traditional hybrids and doubts about the future of all-electric models, and the correlation between the global sales of Toyota Prius Prime and the EV sales in Japan (Fig. S3) somehow justify this point of view. Howbeit, the peculiarity of electric vehicle sales in Japan deserves detailed study, and this work can be an important contribution to the understanding of the sustainability of the global EV market.”
(j) Line 32-35 Page 8. It is interesting that the variance of the Vnorm is a good indicator of the sustainability of the different countries’ EV market! However, a detailed formula of variance should be listed to help readers understand method rapidly.
Response 3j: We added the formula for Standard deviation.
(k) Line 17-19 Page 10. Does the unsatisfactory prediction result of the model in this paper mean that the market sales of EV market sales are unpredictable?
Response 3k: We have deleted this sentence.
- My third concern focuses on the conclusions.
(a) Line 50, Page 13. The "Normalized monthly sales" method is indeed a good one. However, if this paper wants to recommend this method, it should at least demonstrate its superiority over other methods. For example, how accurate are other scholars' methods? Is this paper's method more accurate than theirs? Or is it more stable?
Response 3a: We don’t know other research articles using statistical analysis of monthly EV sales, so we cannot compare our method with alternative ones. We can add the sentence like “To our knowledge this is the first academic paper proposing to use statistical analysis of monthly EV sales data.” but we cannot guarantee the validity of the supposition.
- The paper also suffers from some presentation issues. Below I list some examples and the list could be longer.
Response 4: We're sorry you took the time to check our errors.
(a) Line 7, Page 1. Goal setting. (corrected)
(b) Line 13, Page 1. Causes. (corrected)
(c) Line 14, Page 1. “Automobile” here should be “automobiles”. (corrected)
(d) Line 14, Page 1. Tense error, engine has become. (corrected, now “… automobiles with internal combustion engine have become one …”)
(e) Line 17, Page 1. Part of speech error: “refusing” should be “refusal”. (corrected)
(f) Line 24, Page 1. Non-academic expression, the two phrases should be combined: “It takes a lot of time”. (corrected)
(g) Line 2, Page 2. Missing “of”: Two (of) the most popular. (corrected)
(h) Line 5, Page 2. Missing “a”: has (a) free interactive. (corrected)
(i) Line 24, Page 2. Delete “of”: behind of industrial. (corrected)
(j) Line 30, Page 2. “In the most articles”, delete “the”. (corrected)
(k) Line 30, Page 2. Delete the “,” after articles. (corrected)
(l) Line 30, Page 2. “As the result” should be “As a result” here. (corrected)
(m) Line 31, Page 2. There should be a “which” before “arrived”. (corrected)
(n) Line 36, Page 2. Lack a space between “2021” and “and”. (corrected)
(o) Line 36, Page 2. Lack “the” between “of” and “first”. (the sentence was removed to shorten introduction)
(p) Line 51, Page 2. “As the result” should be “As a result” here. (corrected)
(q) Line 6, Page 3. “In term of” should be “in terms of” here. (corrected)
(r) Line 2, Page 4. Lack “of” between “three” and “the”. (corrected)
(s) Line 26-27, Page 4. There should be a “the” before European, an “a” between “solid” and delete “has” and “in”. (corrected)
(t) Line 30, Page 4. Tense error: became. (corrected)
(u) Line 9, Page 5. Netherlands. (corrected)
(v) Line 9, Page 6. Slip of pen: adapt. (corrected)
(w) Line 17, Page 6. Lexical error: increased. (corrected)
(x) Line 33, Page 6. Slip of pen: assess. (corrected)
(y) Line 44, Page 6. Error: correspond. (corrected)
(z) Line 4, Page 7. Error: These. (corrected)
(a1) Line 11, Page 9. Line 14, Page 9. There should be a “to” after “amount”. (corrected)
(b1) Line 6, Page 10. Delete “at”. (corrected)
(c1) Line 15, Page 10. Error: decreases. (corrected)
(d1) Line 18, Page 10. “How valuable can mid- and long-term predictions be?” deleted, see Response 3k
(e1) Line 23, Page 11. Lack “all” between “almost” and “forecasts” (corrected)
(f1) Line 3, Page 13. Analysts. (corrected)
(g1) Line 12, Page 13. “In” should be “of” here. (corrected)
(h1) Line 14, Page 14. Lack “and” or “or” before “Japan”. (corrected)
Author Response File: 
Author Response.docx
Reviewer 2 Report
In this research study, the authors tried to Electric Car market analysis using open data. Some of the following points must be considered for improvement.
1. Abstract is too short and do not convey the main idea of the study.
2. Intentions of the users to use EVs are also one of the main dimension to be considered. Therefore, authors should add a dedicated section about it in the introduction section. Consider following works to be cited:
a) Extracting Travelers’ Preferences toward Electric Vehicles Using the Theory of Planned Behavior in Lahore, Pakistan
b) The impact of policy measures on consumer intention to adopt electric vehicles: evidence from China
c) Travelers’ Adoption Behavior towards Electric Vehicles in Lahore, Pakistan: An Extension of Norm Activation Model (NAM) Theory
d) Moving toward green mobility: overview and analysis of electric vehicle selection, Pakistan a case in point
3. Methods are not adequately described, need super improvement.
4. Reference to Figure 1 data?
5. Reference to Figure 2 data?
6. Notations and references needs a check.
7. Most of the references are old, consider adding latest research work in the revised version.
8. Limitations should be added at the end of the conclusions section. Research gap is also missing in the end of introduction section.
Author Response
Dear reviewer,
Thank you for your comments and recommendations. Please find below our corrections and responses.
- Abstract is too short and do not convey the main idea of the study.
Response 1: We tried hard to make our Abstract short and laconic. We believe that it properly describes motivation, mentions all three parts of our study, and reports about two main conclusions. Please let us know what important part of our research has been omitted and we will be happy to include it. But we hope that you will agree that our Abstract is acceptably short.
- Intentions of the users to use EVs are also one of the main dimension to be considered. Therefore, authors should add a dedicated section about it in the introduction section. Consider following works to be cited:
- a) Extracting Travelers’ Preferences toward Electric Vehicles Using the Theory of Planned Behavior in Lahore, Pakistan
- b) The impact of policy measures on consumer intention to adopt electric vehicles: evidence from China
- c) Travelers’ Adoption Behavior towards Electric Vehicles in Lahore, Pakistan: An Extension of Norm Activation Model (NAM) Theory
- d) Moving toward green mobility: overview and analysis of electric vehicle selection, Pakistan a case in point
Response 2: The consumer intention is an important subject to study EV market, but this is out of the scope of our work. We perform a statistical study of open market data and discuss the possibility of forecasting at various time scales. We don’t study driving forces. We have tried to find a place to discuss consumer intention but couldn’t find one. We fully agree that there are many important dimensions of EV market studies but only reviews can combine them all. Original research papers must focus on a specific subject. Also, please mention that we don’t discuss Pakistan in our manuscript, so we can’t cite the proposed papers. But thank you anyway, it would be interesting for us to study (later) the case of Pakistan and its national EV market.
- Methods are not adequately described, need super improvement.
Response 3: Well, since we introduce a new method, this section is rather small. But if you think the elaborated Method section will help to understand the results, why not. We have added a corresponding paragraph to the Methods.
- Reference to Figure 1 data?
Response 4: We added the sentence “The data are taken from open sources described in the first paragraph of the Methodology.” to captions for all figures. The list is rather large but the same for all the figures, so this relatively short sentence let us to avoid overloaded captions.
- Reference to Figure 2 data?
See Response 4.
- Notations and references needs a check.
We added 10 more recent publications to the list of references.
- Most of the references are old, consider adding latest research work in the revised version.
We added several recent articles:
https://doi.org/10.1016/j.eneco.2020.104773 (2020)
https://www.doi.org/10.1016/j.jclepro.2020.121038 (2020),
https://www.doi.org/10.1016/j.energy.2021.121932 (Jan 2022),
https://www.doi.org/10.3390/su14042206 (Feb 2022)
https://www.doi.org/10.1002/pam.22362 (spring 2022)
https://www.doi.org/10.1111/twec.13345 (Sept 2022)
- Limitations should be added at the end of the conclusions section. Research gap is also missing in the end of introduction section.
Response 8: We've improved the introduction by removing some redundant sentences and rewording the last (summary) paragraph. We don’t use the term “gap” but focus on the novelty of the proposed approach. We have the phrase “The applicability of this approach is limited only by the availability of monthly sales data”.
Author Response File: Author Response.docx
Reviewer 3 Report
The manuscript details historical sales of electric vehicles, a sustainability analysis, and short-term projections. The manuscript could merit favorable consideration following revisions based on the comments below.
1/ The authors’ main finding that “In the conditions when authorities and regulators are the main driving forces of changes, electric car market needs not forecasting, but proper goalsetting and timely published market data with open access” appears spot on. The authors are encouraged to emphasize that the IEA STEPS and APS scenarios are respectively based on implemented policies and pledged commitments.
2/ I was unable to comprehend the methodology of the assessment of sustainability based on the analysis of normalized monthly sales. The authors are urged to base the application of their methodology for studying sustainability on peer-reviewed literature. Or, as suggested later in the comments, simply frame the manuscript as a study of volatility, with the methodology appropriately grounded in published literature.
3/ On page 2, the authors state: “Only recently, the accumulated market data have reached some critical value enabling new wave of research papers focused on EV prospects and outlooks [14–17].” The authors are recommended to consider some of the recent literature looking at multiple major EV markets, including but not limited to:
https://doi.org/10.5547/01956574.44.2.tshe
https://doi.org/10.1016/j.eneco.2019.104493
4/ On page 6, the authors state: “Such a slowdown was rather expected, since the stagnation in sales was caused by a change in the national EV policy and it was planned years ago [25,27–31].” The authors are recommended to consider some of the recent literature looking at the impact of EV subsidies in China, including but not limited to:
https://doi.org/10.1016/j.eneco.2020.104773
https://doi.org/10.1002/pam.22362
5/ Sustainability and volatility were utilized interchangeably by the authors. It is unclear to me how volatility, which is designed for short-term analysis, can be used interchangeably with sustainability, which is designed for long-term analysis. The analysis presented using monthly sales is, in my opinion, more appropriate as a volatility measurement than as a sustainability measurement. The authors are encouraged to reframe the paper to examine volatility in electric vehicle market.
6/ I was unable to comprehend the rationale behind using the first three months of sales data as a proxy for a short-term annual sales forecast. If short-term forecasting is the objective, I believe time series data analysis techniques would be more beneficial. The authors are urged to investigate time series analysis techniques or omit this part.
Author Response
Dear reviewer,
Thank you for your valuable comments and recommendations. Please find below our corrections and responses.
1/ The authors’ main finding that “In the conditions when authorities and regulators are the main driving forces of changes, electric car market needs not forecasting, but proper goalsetting and timely published market data with open access” appears spot on. The authors are encouraged to emphasize that the IEA STEPS and APS scenarios are respectively based on implemented policies and pledged commitments.
Response 1: Thank you for this comment, we missed this point. We added a proposed paragraph to the section 3.4. Also, we decided to divide section 3.4 into two parts.
2/ I was unable to comprehend the methodology of the assessment of sustainability based on the analysis of normalized monthly sales. The authors are urged to base the application of their methodology for studying sustainability on peer-reviewed literature. Or, as suggested later in the comments, simply frame the manuscript as a study of volatility, with the methodology appropriately grounded in published literature.
Response 2: Thank you for this valuable recommendation. We were not sure that the word “sustainability” was used properly. We’ve significantly reduced its usage. In the case of short-term analysis, we used the proposed “volatility assessment”. In some other cases, the word "sustainable" has been replaced by "consistent". All corrections made are marked with a green highlight.
3/ On page 2, the authors state: “Only recently, the accumulated market data have reached some critical value enabling new wave of research papers focused on EV prospects and outlooks [14–17].” The authors are recommended to consider some of the recent literature looking at multiple major EV markets, including but not limited to:
https://doi.org/10.5547/01956574.44.2.tshe
Response 3.1: Unfortunately, we could not download this publication. We can’t cite an article without reading it first, but we’ve cited the article of the same authors, which you have recommended in the following comment (10.1016/j.eneco.2020.104773 – ref. [21] in the revised version).
https://doi.org/10.1016/j.eneco.2019.104493
Response 3.2: Thank you, this is an interesting paper. Unfortunately, it doesn’t fit well to this sentence because it doesn’t focus on outlook or forecasting. To meet your recommendation, we’ve cited three more recent articles more relevant for our statement:
https://www.doi.org/10.1016/j.jclepro.2020.121038 (2020),
https://www.doi.org/10.1016/j.energy.2021.121932 (Jan 2022),
https://www.doi.org/10.3390/su14042206 (Feb 2022)
https://www.doi.org/10.1111/twec.13345 (Sept 2022)
Since you’ve proposed us to cite more articles about governmental initiatives, we’ve cited this and ??? papers in new comments about goalsetting not forecasting
4/ On page 6, the authors state: “Such a slowdown was rather expected, since the stagnation in sales was caused by a change in the national EV policy and it was planned years ago [25,27–31].” The authors are recommended to consider some of the recent literature looking at the impact of EV subsidies in China, including but not limited to:
https://doi.org/10.1016/j.eneco.2020.104773
Response 4.1: thank you, this article is suitable here, so we’ve cited it (ref. [21] in the revised version).
https://doi.org/10.1002/pam.22362
Response 4.2: thank you, this article is suitable here, so we’ve cited it (ref. [39] in the revised version).
5/ Sustainability and volatility were utilized interchangeably by the authors. It is unclear to me how volatility, which is designed for short-term analysis, can be used interchangeably with sustainability, which is designed for long-term analysis. The analysis presented using monthly sales is, in my opinion, more appropriate as a volatility measurement than as a sustainability measurement. The authors are encouraged to reframe the paper to examine volatility in electric vehicle market.
Response 5: We have agreed and corrected the manuscript as described in Response 2.
6/ I was unable to comprehend the rationale behind using the first three months of sales data as a proxy for a short-term annual sales forecast. If short-term forecasting is the objective, I believe time series data analysis techniques would be more beneficial. The authors are urged to investigate time series analysis techniques or omit this part.
Response 6: The three-months cumulative EV sales is used only once to illustrate the possible implementation of the proposed assessment. We’ve checked the section once again and made sure that we don’t propose to use this time interval for further analysis. We don’t mind about time series analysis, but this will be another study. For this paper, we believe that the three-months cumulative EV sales is optimal choice for an illustration. Some open sources of information report about not monthly sales but quarterly ones, so the first three-months cumulative EV sales are equal to Q1 sales volumes.
We tried to justify this in the text and considered the option below, but later considered this wording redundant:
“In March 2021, the three-months cumulative EV sales (Q1 sales volumes) amounted 127 thousand units and Vest annual (2021)3 became 686 thousand, thus the assessment error decreased to about 2%.”
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
All my concerns have been addressed.
Reviewer 2 Report
The authors have addressed all the comments. The paper is accepted in the current form.
Reviewer 3 Report
Accept
