Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model

Round 1

Reviewer 1 Report

The paper proposes a data grouping approach-based nonlinear grey Bernoulli model which can effectively predict the seasonal fluctuations of quarterly sales of the new energy industry in China. A few suggestions:

1. The language of this manuscript should be polished. The current version is not reader friendly. What does the title “Underground and Motivation” mean?

2. Policy implications should be mentioned in the abstract. The conclusion should also be expanded.

3. The authors can generalize the situations when this new model is a good choice.                         

4. Since the Sustainability is an international journal, the wording of the authors should be different comparing to submiting to a domestic journal.

Author Response

Reviewer 1

The paper proposes a data grouping approach-based nonlinear grey Bernoulli model which can effectively predict the seasonal fluctuations of quarterly sales of the new energy industry in China. A few suggestions:

1. The language of this manuscript should be polished. The current version is not reader friendly. What does the title “Underground and Motivation” mean?

Response: Thank you for your positive comment. We have revised the whole manuscript carefully and tried to avoid any grammar error. In addition, we have asked several colleagues who are native English-speaking professors and skilled authors of English language papers to check the English. We believe that the language is now acceptable for publication. The “Underground and Motivation” has been revised into the “Background and Motivation”.

2. Policy implications should be mentioned in the abstract. The conclusion should also be expanded.

Response: Many thanks for this comment. We have added policy implications in the abstract, and expanded the conclusion in revised manuscript.

3. The authors can generalize the situations when this new model is a good choice.  

Response: Thank you for this valuable comment. We have added the precondition of data for the DGA-based NGBM(1,1) model in the first paragraph in Section 4 “Empirical analysis” of the revised paper. It is suitable to use DGA-based NGBM(1,1) model for forecasting when the time series has quarterly characteristics and is not affected by unexpected policies.

4. Since the Sustainability is an international journal, the wording of the authors should be different comparing to submitting to a domestic journal.

Response: Thank you very much for your constructive comment. We have read some papers published in Sustainability and other international journals, such Energy, Journal of cleaner production, and divided the full text into four parts:1. Introduction (including 1.1 Background and motivation, 1.2. Literature review of NEVs’ market, 1.3. The development of grey theory model and 1.4 Contribution and organization), 2. Methodology (including 2.1. Data grouping approach-based nonlinear grey Bernoulli model, 2.2. Parameters optimization in the DGA-based NGBM (1,1), 2.3. Model evaluation criteria) 3. Empirical analysis and discussion (including 3.1. The construction of the two models, 3.2. The comparison between DGA-based GM (1,1) and DGA-based NGBM (1,1), 3.3. Out-of-sample forecasting and discussion) and 4. Conclusions.

We thank the Reviewers once again for their valuable comments which we have used to strengthen the accuracy and precision of the paper’s content. The authors deeply appreciate the Editor’s and Reviewers ’dedicated work, and hope that the revisions we have made will meet with your approval.

Once again, thank you very much for your valuable comments and suggestions.

Reviewer 2 Report

The article tries to forcast sales of New Energy Vehicles (NEVs) in China. First of all, I am not a native English speaker. However, some phrases sound awkward. Examples: 1.1 Underground and Motivation. I think it should read Background and Motivation. Sale Volume should be sales volume. I suggest to let the article undergo a language editing.

To be honest, I could not follow the Nonlinear Gray Bernoulli Model in such a short period of time. The methodology seems to be explained adequately, however, I have to trust in the authors' skills. A review of a specialist who is familiar with the DGA-based NGBM(1,1) could be advisable.

However, there is another concern. I have worked quite extensively with sales figures of EVs and PHEVs (which, I think, are addressed by the authors as NEVs) and I relied on the data from EV-Volumes in Sweden (http://www.ev-volumes.com/). Sales are reported by manufacturer and type which makes the data quite reliable. I found similar numbers of actual sales in China in Q1 and Q2 2017 and those predicted by the procedure described. For 2018, however, there exist strong discrepancies:

                Predicted by the authors          Actual Sales from EV-Volumes

2017 Q1         56,000                                               62,000

2017 Q2       139,000                                             130,000

2018 Q1         24,000                                             134,000

2018 Q2         86,000                                             261,000

The authors should check these discrepancies before publication.

Author Response

Response to Referee’s comments on the paper submitted to Sustainability entitled:

“Forecasting quarterly sales of the new energy vehicle industry in China using a data grouping approach-based nonlinear grey Bernoulli model”

We thank the Reviewers for these comments which provide useful guidance for the revision of our paper. All of your suggestions have been incorporated into the revised paper as explained below on a point-by-point basis, and all new changes are highlighted in yellow in the revised manuscript. Please find below our point-to-point response to the reviewers’ comments, which are first reproduced italic followed by our detailed response.

Reviewer 2

1. The article tries to forecast sales of New Energy Vehicles (NEVs) in China. First of all, I am not a native English speaker. However, some phrases sound awkward. Examples: 1.1 Underground and Motivation. I think it should read Background and Motivation. Sale Volume should be sales volume. I suggest to let the article undergo a language editing.

Response: Many thanks for your kind suggestion. The “Underground and Motivation” and “Sale Volume” have been revised. The language originally was revised by a native English-speaker engaged through the auspices of a professional proofreading service; based on their comments, the usage has been carefully checked and revised again. We now believe that the manuscript should meet the standards required for publication in this journal.

2. To be honest, I could not follow the Nonlinear Gray Bernoulli Model in such a short period of time. The methodology seems to be explained adequately, however, I have to trust in the authors' skills. A review of a specialist who is familiar with the DGA-based NGBM(1,1) could be advisable.

However, there is another concern. I have worked quite extensively with sales figures of EVs and PHEVs (which, I think, are addressed by the authors as NEVs) and I relied on the data from EV-Volumes in Sweden (http://www.ev-volumes.com/). Sales are reported by manufacturer and type which makes the data quite reliable. I found similar numbers of actual sales in China in Q1 and Q2 2017 and those predicted by the procedure described. For 2018, however, there exist strong discrepancies:

The authors should check these discrepancies before publication.

Response:

Thank you for this valuable comment. Considering the availability of the quarterly data in 2017, this paper updates the data during 2013 and 2017 as sample set to forecast the sales volume of NEVs in 2018 in Section 3.3 in revised manuscript, and the forecasted results are compared with the actual data. The out-of-sample values predicated in 2018 are finally acquired, as displayed in Table 1.

Table 1. Forecasting values of the sales volume of NEVs in 2018 by the modified DGA-based NGBM(1,1)

The prediction accuracy of the first and second quarters is poor. This can be explained by the unexpected policy was released in February 2018. The Ministry of Finance and the Ministry of Industry and Information Technology of China jointly issued the "Notice on Adjusting and Improving the Financial Subsidy Policy for the Promotion and Application of New Energy Vehicles ". The subsidy standard for 2018 is divided into three phases. The subsidy will be based on the standard of subsidy in 2017 during January 1st to February 11^th. There is a transition period from February 12 to June 11, the subsidy standard for new energy passenger cars and buses is 0.7 times that of the standard in 2017, while the new energy trucks and special vehicles is 0.4 times. The new subsidy standard will be implemented after June 12 in 2018. The sales volume of NEVs in the first and second quarters of 2018 increased by 155.68% and 93.423% respectively compared with 2017 because of the adjusted subsidy standard. This research use the Pauta criterion to judge the abnormality of data, and the results show that the data in the first and second quarters of 2018 are outliers. This is inconsistent with the assumptions of the data in this paper, which leads to poor prediction accuracy. To further verify the applicability of the DGA-based NGBM (1,1) model to quarterly data, this paper updates the dataset with quarterly data for 2014-2018 again, which including the outliers in 2018 to forecast the sales volume of NEVs from 2019-2020. The MAPE value of fitting result of DGA-based NGBM (1,1) model is 6.03%, which is a high-level prediction accuracy. The predicted values for 2019-2010 are shown in the table, which belongs to the high prediction accuracy, the predicted values for 2019-2010 are shown in the table 2.

Table 2. Forecasting values of the sales of new energy vehicle in 2019-2020 by the DGA-based NGBM(1,1)

As shown in Table 1, the sales volume of NEVs in China will maintain seasonal fluctuation from 2019 to 2020, with the highest sales volume in the fourth quarter and the lowest in the first quarter. The growth rate in the first quarter is the largest, and the third quarter is the lowest. The growth rate of the total annual sales volume remains at 57%. In 2020, the annual sales volume will reach 3115,062, which more than 2 million.

We thank the Reviewers once again for their valuable comments which we have used to strengthen the accuracy and precision of the paper’s content. The authors deeply appreciate the Editor’s and Reviewers ’dedicated work, and hope that the revisions we have made will meet with your approval.

Once again, thank you very much for your valuable comments and suggestions.

Author Response File: Author Response.pdf

Reviewer 3 Report

The objective of the paper “Forecasting quarterly sales of the new energy vehicle industry in China using a data grouping approach-based nonlinear grey Bernoulli model” is good and the research up to date. But the paper is very poorly written and the work poorly presented. The hypotheses are not strong enough and results do not much the intended objectives.

Author Response

Response to Referee’s comments on the paper submitted to Sustainability entitled:

“Forecasting quarterly sales of the new energy vehicle industry in China using a data grouping approach-based nonlinear grey Bernoulli model”

We thank the Reviewers for these comments which provide useful guidance for the revision of our paper. All of your suggestions have been incorporated into the revised paper as explained below on a point-by-point basis, and all new changes are highlighted in yellow in the revised manuscript. Please find below our point-to-point response to the reviewers’ comments, which are first reproduced italic followed by our detailed response.

Reviewer 3

The objective of the paper “Forecasting quarterly sales of the new energy vehicle industry in China using a data grouping approach-based nonlinear grey Bernoulli model” is good and the research up to date. But the paper is very poorly written and the work poorly presented. The hypotheses are not strong enough and results do not much the intended objectives.

Response: We thank the Reviewer for another valuable comment which is important in helping us improve the precision of our study. We have added the hypothesis of new energy vehicle development in the first paragraph in Section 4 “Empirical analysis and discussion” of the revised paper. The forecasted results in this paper show that the sales volume of NEVs in China still maintains seasonal fluctuation from 2019 to 2020, with the highest sales volume in the fourth quarter and the lowest in the first quarter. The growth rate in the first quarter is the largest, and the third quarter is the lowest. The growth rate of the total annual sales volume has remained at 57%. In 2020, the annual sales volume reached 3115,062, which more than 2 million. To achieve this goal in 2020, compound annual growth rate must reach 41.4%. According to the predicted results of this paper, if the government continues to issue policies to stimulate the consumption of new energy vehicles, the annual growth rate will reach more than 50%, and the annual sales volume will reach 2 million before 2020. The development of the NEVs includes the growth of sales volume, but is not limited to it. The data from China Electric Vehicle Charging Infrastructure Promotion Alliance indicates that 266231 public charging piles have been installed. However, there are 1.8 million NEVs at least while on average every six cars are equipped with a public charging pile, which leads to the problem of insufficient supply of charging piles. In addition, the "Interim Measures for the Management of Recycling and Utilization of Power Battery for New Energy Vehicles" was officially implemented on August 1, 2018. The government has not yet completed a complete system for the recycling and harmless disposal of NEVs. The sales volume of NEVs is increasing, and the problems of the after-sales and emergency support need to be solved urgently. The government should pay more attention to the infrastructure construction of the NEVs, and create a favorable environment for the development of it.

We thank the Reviewers once again for their valuable comments which we have used to strengthen the accuracy and precision of the paper’s content. The authors deeply appreciate the Editor’s and Reviewers ’dedicated work, and hope that the revisions we have made will meet with your approval.

Once again, thank you very much for your valuable comments and suggestions.

Round 2

Reviewer 1 Report

1. The Figures such as Figure 1 and Figure 4 should be more precise and reader-friendly.

2. The wording of the text should be more precise.

3. Line 147-Line 152: The description about the structure of this manuscript is not clearly described.

4.The authors should demonstrate the assumptions between Line 252-Line 259 are reasonable.

5. The conclusion still need to be expanded. A further discussion and application about your new method will improve your manuscript.

Author Response

Response to Referee’s comments on the paper submitted to Sustainability entitled:

“Forecasting quarterly sales volume of the new energy vehicles industry in China using a data grouping approach-based nonlinear grey Bernoulli model”

We thank the Reviewers for these comments which provide useful guidance for the revision of our paper. All of your suggestions have been incorporated into the revised paper as explained below on a point-by-point basis, and all new changes are highlighted in yellow in the revised manuscript. Please find below our point-to-point response to the reviewers’ comments, which are first reproduced italic followed by our detailed response.

Reviewer 1

1. The Figures such as Figure 1 and Figure 4 should be more precise and reader-friendly.

Response: Many thanks for your kind suggestion. The more information has been added in the Figure 1, Figure 3 and Figure 4 in revised manuscript, so the Figures can be more precise and reader-friendly.

2. The wording of the text should be more precise.

Response: Thank you for this valuable comment. We have revised the whole manuscript carefully and tried to avoid any grammar error. In addition, we have asked several colleagues who are native English-speaking professors and skilled authors of English language papers to check the English. We believe that the language is now acceptable for publication.

3. Line 147-Line 152: The description about the structure of this manuscript is not clearly described.

Response: Many thanks for this comment. The description about the structure of this manuscript has been corrected in Line 147-Line 151 in the revised manuscript.

4.The authors should demonstrate the assumptions between Line 252-Line 259 are reasonable.

Response: Thank you very much for your constructive comment. The basis of assumptions has been added in Line 267-Line 269 in the revised manuscript. According to the “13th Five-Year Strategic Development Plan”. the sales volume of NEVs will increase to 2 million in 2020, and the actual quarterly sales volume of NEVs during 2013-2016, we assume that :(1) The sales volume of NEVs will continue to grow, and the annual sales volume will be close to 2 million in 2020. (2) The sales volume of NEVs still has significant quarterly fluctuation characteristics, and the sales volume in the fourth quarter is the highest.

5. The conclusion still need to be expanded. A further discussion and application about your new method will improve your manuscript.

Response: Thank you for your positive comment. we have discussed the application of DGA-based NGBM (1,1) in Line 414-Line 417 in the revised manuscript. When the time series has nonlinear characteristics of quarterly fluctuation, data grouping approach can effectively identify the quarterly difference, it can improve the fitting accuracy, at the same time, the PSO algorithm optimizes the power exponent and background value of the DGA-based NGBM (1,1) model, which can flexibly fit the nonlinear trend of data grouping approach-based GM (1,1) (DGA-based GM (1,1)).

We thank the Reviewers once again for their valuable comments which we have used to strengthen the accuracy and precision of the paper’s content. The authors deeply appreciate the Editor’s and Reviewers ’dedicated work, and hope that the revisions we have made will meet with your approval.

Once again, thank you very much for your valuable comments and suggestions.

Author Response File: Author Response.docx

Reviewer 2 Report

I just received the 2018 data from EV-volumes.com. 

1st Quarter: 133,000

2nd Quarter: 261,000

3rd Quarter: 288,000

4th Quarter: 500,000.

At least, for 2018, there is some consensus about the actual data (discrepancies may be due to slightly diverging definitions of BEV, FCEV (Fuel Cell), PHEV). However, it seems that the authors skipped the 2017 data. Table 3 ends in Q4 2016 and Table 6 starts in 2018. Is there any reason for this? 2017 could be included in Table 3. 

Overall, the method described seems to have some validity. I have calculated regression models for the four quarters from 2013 to 2018. The best fit is achieved with exponentional functions with e^b1*no_of_years (b1= .779 for the first quarter, .861 for the 2nd, .884 for 3rd, .859 for 4th, R-Squares are as high as .950!). This, of course, is much to optimistic due to saturation. The linear function, however, strongly underestimates. Thus, the predicitions of the authors may come close to reality. I have attached the plot of the Q4 curve estimation (SPSS)

As I stated in my first review, I am not familiar with the used model. The authors may discuss the advantage of their model over other prediction methods.   

Assumed that the model and its implementation has been validated by an expert and after minor modifications described above, I tend to accept the article. 

Comments for author File: Comments.pdf

Author Response

Response to Referee’s comments on the paper submitted to Sustainability entitled:“Forecasting quarterly sales volume of the new energy vehicles industry in China using a data grouping approach-based nonlinear grey Bernoulli model”

We thank the Reviewer for these comments which provide useful guidance for the revision of our paper. All of your suggestions have been incorporated into the revised paper as explained below on a point-by-point basis, and all new changes are highlighted in yellow in the revised manuscript. Please find below our point-to-point response to the reviewers’ comments, which are first reproduced italic followed by our detailed response.

#Reviewer 2

I just received the 2018 data from EV-volumes.com.

1st Quarter: 133,000

2nd Quarter: 261,000

3rd Quarter: 288,000

4th Quarter: 500,000.

At least, for 2018, there is some consensus about the actual data (discrepancies may be due to slightly diverging definitions of BEV, FCEV (Fuel Cell), PHEV). However, it seems that the authors skipped the 2017 data. Table 3 ends in Q4 2016 and Table 6 starts in 2018. Is there any reason for this? 2017 could be included in Table 3.

Overall, the method described seems to have some validity. I have calculated regression models for the four quarters from 2013 to 2018. The best fit is achieved with exponentional functions with e^b1*no_of_years (b1= 0.779 for the first quarter, 0.861 for the 2nd, 0.884 for 3rd, 0.859 for 4th, R-Squares are as high as 0.950!). This, of course, is much to optimistic due to saturation. The linear function, however, strongly underestimates. Thus, the predications of the authors may come close to reality. I have attached the plot of the Q4 curve estimation (SPSS)

As I stated in my first review, I am not familiar with the used model. The authors may discuss the advantage of their model over other prediction methods.  

Assumed that the model and its implementation has been validated by an expert and after minor modifications described above, I tend to accept the article.

Response: Thanks for your useful suggestions. The data in this paper obtained from the Wind database (https://www.wind.com.cn/ ),we have added the data of sales volume of NEVs in 2017 as raw data to conduct an empirical analysis in section 3.1, the data has been shown in the Table 3 and Fig 1. We have discussed the disadvantage of regression model in Line 62-64, and displayed the contributions of this paper in section 1.4 in revised manuscript.

Once again, thank you very much for your valuable comments and suggestions.

Author Response File: Author Response.docx

Reviewer 3 Report

The authors have improved the manuscript from the first submission. Nevertheless we still recommend important revision,particularly the English text in order to be considered for publication.

Author Response

Response to Referee’s comments on the paper submitted to Sustainability entitled:“Forecasting quarterly sales volume of the new energy vehicles industry in China using a data grouping approach-based nonlinear grey Bernoulli model”

We thank the Reviewers for these comments which provide useful guidance for the revision of our paper. All of your suggestions have been incorporated into the revised paper as explained below on a point-by-point basis, and all new changes are highlighted in yellow in the revised manuscript. Please find below our point-to-point response to the reviewers’ comments, which are first reproduced italic followed by our detailed response.

Reviewer

The authors have improved the manuscript from the first submission. Nevertheless, we still recommend important revision, particularly the English text in order to be considered for publication.

Response: We thank the Reviewer for another valuable comment which is important in helping us improve the precision of our study. We have revised the whole manuscript carefully and tried to avoid any grammar error. In addition, we have asked several colleagues who are native English-speaking professors and skilled authors of English language papers to check the English. We believe that the language is now acceptable for publication.

We thank the reviewer once again for their valuable comments which we have used to strengthen the accuracy and precision of the paper’s content. The authors deeply appreciate the Editor’s and Reviewers ’dedicated work, and hope that the revisions we have made will meet with your approval.

Once again, thank you very much for your valuable comments and suggestions.

Author Response File: Author Response.docx

Round 3

Reviewer 1 Report

The manuscript can be accepted for publication.

Author Response

The manuscript can be accepted for publication.

Response: Thank you for your recognition of the paper. 

Author Response File: Author Response.docx