Modeling and Evaluation of Market Incentives for Battery Electric Vehicles
Round 1
Reviewer 1 Report
The presented study is related to the very important issue of the influence of various factors on the share of battery electric vehicles on the market.
To solve this problem, it is proposed to use a generalized linear mode
The variables include those related to infrastructure, taxes, and other areas. In the case of such a wide group of variables, perhaps we should consider using a slightly more advanced model - however, it is a question of a debatable nature
Nevertheless, such a choice of the model proposed by the authors can be accepted as a preliminary approach to the subject matter under consideration.
However, the following additions are proposed:
- detailed presentation of empirical values ​​that were used in model 1 and model 2 - this will enable a wider analysis and comparison of the results also for other evolution periods than 2010 - 2018 in the future
-outline the differences between the two models in more detail by adding their mathematical description
- removal of redundant in my opinion information included on lines 64-67 (in the case of the total text containing only 9-10 pages),
- deletion of lines 88-89 as duplicate information placed earlier on lines 74-75
- information about some parameters in table 5 is not consistent with the information in the text (line 170), coefficient R2 -(the value in the text is 0.768 and in table 5 is 0.801), it is also proposed to change the notation of the coefficient instead of R2 to R2
-detailing the text of the abstract and summary so that it is more related to the results obtained
Author Response
Dear Editor and reviewers:
We greatly appreciate the opportunity to submit a revised draft of our manuscript. In addition, we are grateful for the time and effort dedicated to providing a thorough review of the manuscript, particularly the reviewers' valuable feedback and insightful comments. As a result, we have made changes to the manuscript to reflect the suggestions provided by the reviewers and believe the manuscript has been greatly improved.
The corresponding changes and refinements made in the revised paper are summarized in our response below, with our answers shown in blue font colour. We will be glad to address further questions or concerns about the manuscript if any.
Thank you.
Best regards,
The Authors
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper concerns the modelling and evaluation of market incentives for battery electric vehicles. This phase of the research aims to identify the effective market influencing factors/measures with statistical analysis (the authors need to stick with one word, factors or measures).
The data used is from 15 countries across Europe between 2010 and 2018 with a good range of sources. It would have been useful to have bit more policy context between the countries, for example which of the EU countries are more advanced in terms of BEV policy measures implemented and what is the take-up in these countries.
There is a logical progression with the model development, investigating correlation before running the Generalised Linear Model (GLM). There is a good discussion of the significant variables in order of their influences and there are some interesting findings.
The main finding of this study as outlined in the Abstract are too vague: specify the unambiguously positive factors that encourage the BEVs market, outline how they contribute, and state the policy guidance. The Conclusions section also needs improvement along the same lines. It is quite a laborious summary and I typically look for 2-3 key findings in a paper which I can take away. The final paragraph does appropriately state the impacts after the COVID, but I would like a further 2-3 sentences on how BEV levels and policy have developed after the data period (i.e. from 2019 onwards).
The language needs to be improved and some parts are very clumsy. Not keen on the use of “Authors” at the start of sentences. Other words are over-stated (e.g. “unambiguously” in the Abstract). There is inconsistent use of capital letters in Table 1. Finally, the Section headings were a bit odd to me, as I prefer results presented in a Results rather than Discussion section.
Author Response
Dear Editor and reviewers:
We greatly appreciate the opportunity to submit a revised draft of our manuscript. In addition, we are grateful for the time and effort dedicated to providing a thorough review of the manuscript, particularly the reviewers' valuable feedback and insightful comments. As a result, we have made changes to the manuscript to reflect the suggestions provided by the reviewers and believe the manuscript has been greatly improved.
The corresponding changes and refinements made in the revised paper are summarized in our response below, with our answers shown in blue font colour. We will be glad to address further questions or concerns about the manuscript if any.
Thank you.
Best regards,
The Authors
Author Response File: Author Response.pdf
Reviewer 3 Report
Title: Modelling and Evaluation of Market Incentives for Battery 2
Electric Vehicles
Major:
- The methods used in this paper seems trivial and common. It is difficult to see the contribution of this paper. What is the difference between this paper and previous works? As reviewer know, there are many similar works that addressed about incentive on using BEV. However, authors are only addressing very small portions of the previous works.
- Authors need to specify how to build the model 1 and model 2 (Line 142 – 149). Without any mathematical expressions, the statement would be only an expression which is difficult to verify.
- In the conclusion, authors mentioned that the study was to investigate the relationship between the socio-economic, socio-demographic with technological factors and incentives offered. However, the manuscript has lack of explanation on those factors. For example, how did authors specify those factors as shown in Table 1? What are the technological factors? How did the incentives data contribute to this factor?
- The relevant lists of financial and non-financial incentives are unclear. Authors claimed that the other studies [15-18] used dummy variables (1, 0). Meanwhile, this paper also does not clearly mention what is the real meaning of incentive. And, what is the range of values of incentives?
- Reviewer cannot see that the incentives contribute to the performance measures (refer to Table 4). It contradicts with the statement in Line 13 (Page 1) which is addressing the lack of other works on investigating different policy incentives. What does it mean?
- Authors select the Model 2 due to the lower AIC than the Model 1. Meanwhile, there are many other Goodness of Fit (Table 3). What is the reason on choosing only AIC? It is also a bit strange to see some of the goodness of fit show the same values. For example, the Deviance, Pearson Chi-Square showed the same value. And, the scaled deviance and the scaled Pearson chi square also showed the same values. It also noted that the discussion address R2 (Line 170, Page 6).
- (Line 226, Page 8) It is interesting to see the contrary statements with the early studies. First, which early studies did author mention? There is no reference about it. Second, did the previous work use the same dataset as authors? What is the basis on mentioning about the contrary?
- The discussion in Line 226 – 244) did not include any references so it is difficult to verify authors’ arguments.
Minor:
Page 4. Line 118 and Line 119. One statement mentioned “Generalised Linear Model” while the other statement mentioned “Generalized Linear Model”.
Page 8 (Line 220). Aren’t --> are not.
Author Response
Dear Editor and reviewers:
We greatly appreciate the opportunity to submit a revised draft of our manuscript. In addition, we are grateful for the time and effort dedicated to providing a thorough review of the manuscript, particularly the reviewers' valuable feedback and insightful comments. As a result, we have made changes to the manuscript to reflect the suggestions provided by the reviewers and believe the manuscript has been greatly improved.
The corresponding changes and refinements made in the revised paper are summarized in our response below, with our answers shown in blue font colour. We will be glad to address further questions or concerns about the manuscript if any.
Thank you.
Best regards,
The Authors
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Thank you for submit a revised draft of your manuscript
Author Response
Dear Editor and reviewer:
We are thankful for your continuous interest in improving our manuscript. greatly appreciate the opportunity to submit a revised draft of our manuscript. We have made further changes to improve the manuscript as recommended.
We will be glad to address further questions or concerns about the manuscript, if any.
Thank you.
Best regards,
The Authors
Reviewer 3 Report
Title: Modelling and Evaluation of Market Incentives for Battery Electric Vehicles
The authors have attempted to address most of the reviewer’ comments. However, there are still missing comments on some sections.
- The revision on the abstract can be followed by elaborating the contents on the Introduction section. In this manuscript, the introduction section is still vague although the abstract has been extended. For example, the abstract mentioned about the varieties of incentives with less analytical research. Meanwhile, the introduction mentioned “…. But defining their extend needs further quantitative analysis.”. Authors can elaborate more on the meaning of the analytical and the quantitative since it is too broad. One suggestion is to adopt more contents on GLM, as one of the approaches on the analysis.
- Authors attempted to extend the previous work [3]. However, authors have not addressed similar works on GLM to model the incentives on BEV.
For example:
- Alan Jenn, et al. 2018, Effectiveness of electric vehicle incentives in the United States
- Kim, Heo, 2019, Key Drivers behind the Adoption of Electric Vehicle in Korea:An Analysis of the Revealed Preferences
- Z. Lu, Y Yuan, W. Tong, 2020, Optimal Driving Range for Battery Electric Vehicles Based on Modeling Users’ Driving and Charging Behavior
Minor.
- The abstract mentioned “generalized linear modeling” instead of “generalized linear model”.
Author Response
Dear Editor and reviewer:
We are thankful for your continuous interest in improving our manuscript. greatly appreciate the opportunity to submit a revised draft of our manuscript. We have made further changes to improve the manuscript as recommended.
We will be glad to address further questions or concerns about the manuscript, if any.
Thank you.
Best regards,
The Authors
