New Energy Vehicle Consumer Demand Mining Research Based on Fusion Topic Model: A Case in China

Round 1

Reviewer 1 Report

The review of manuscript sustainability-1612852 prepared by Xiaoguang Wang , Tao Lv * , Lei Fan

The manuscript extracted the demand preference topic words of new energy vehicle consumers with the help of the topic model, calculated the similarity between the word vectors and the topic keywords and expanded the topic keywords, analyzed and compared the demand topics and feature expansion words of different car models, and summarized the demand differences of other consumer groups. Thus the topic aims and content of the manuscript are actual and worth to be published in a scientific journal. It suites to Sustainability journal scope.

Section 1 is a brief introduction to the problems discussed in the paper. It's correct. I have no recommendation to extend it.

Section 2 discuss literature in two subsections "Customer demands" and "Consumer demands for the automotive industry ". This division is clear and correct. But the number of investigated references is not sufficient. Also, there is a lack of actual positions. So Recommendation 1 - please extend the literature review with at least 8 positions from 2020-2022 year range.

Section 3 "Methodology and Model" is presented in a comprehensive manner. Hovewer I suggest adding the adequate literature to the mentioned in the paper equation (recommendation #2). Also for line 132-133 "According to the results of literature research" please add the adequate references that justify this sentence (Recommendation #3).

Section 4 "Results" is well presented. However, I suggest an extension to Table 1 with prices in dollars or euros to be easier for the reader '' (recommendation #4).

Section 5 " Discussions and Conclusion" also need an extension. Please add an additional paragraph with future research directions (recommendation #5).

Best regards,

Reviewer

 

Author Response

Response to Reviewer 1 Comments

 

The manuscript extracted the demand preference topic words of new energy vehicle consumers with the help of the topic model, calculated the similarity between the word vectors and the topic keywords and expanded the topic keywords, analyzed and compared the demand topics and feature expansion words of different car models, and summarized the demand differences of other consumer groups. Thus the topic aims and content of the manuscript are actual and worth to be published in a scientific journal. It suites to Sustainability journal scope.

 

Section 1 is a brief introduction to the problems discussed in the paper. It's correct. I have no recommendation to extend it.

 

Section 2 discuss literature in two subsections "Customer demands" and "Consumer demands for the automotive industry ". This division is clear and correct. But the number of investigated references is not sufficient. Also, there is a lack of actual positions. So Recommendation 1 - please extend the literature review with at least 8 positions from 2020-2022 year range.

 

Response 1:  We extended the literature review with:

1. Al-Mahish, M.; AlDossari, N.; Almarri, A. Consumer's demand for Disinfectants and Protective Gear from COVID-19 infection in Al-Hofuf, Saudi. Infect. Dev. Ctries. 2021, 11, 1618-1624.
2. Baarsma, B.; Groenewegen, J. COVID-19 and the Demand for Online Grocery Shopping: Empirical Evidence from the Netherlands. Economist-Netherlands. 2021, 4, 407-421.
3. Wu, ; Wang, Y. Discovery of associated consumer demands: Construction of a co-demanded product network with community detection. Expert Syst. Appl. 2021, 178, 115038.
4. Park, M.; Kim, M.; Ryu, S. The relationship between network governance and unilateral governance in dynamic consumer demand. Mark. Manage. 2020, 84, 194-201.
5. Pallant, J.; Sands, S.; Karpen, I. Product customization: A profile of consumer demand. Retail. Consum. Serv. 2020, 54, 102030.
6. Dertwinkel-Kalt, M.; Koster, M.; Sutter, M. To buy or not to buy? Price salience in an online shopping field experiment. Econ. Rev. 2020, 130, 103593.
7. Singh, A.; Jenamani, M.; Thakkar, J.; Rana, N. Propagation of online consumer perceived negativity: Quantifying the effect of supply chain underperformance on passenger car sales. Bus. Res. 2021, 132, 102-114.
8. Hee, H. A Study on the Consumer Behaviors and Satisfaction Toward Hybrid Cars: Focused on Consumers’ Perceived Cost and Consumption Values. Korean Journal of Human Ecology. 2021, 5, 783-801.
9. Galarraga, I.; Kallbekken, S.; Silvestri, A. Consumer purchases of energy-efficient cars: How different labeling schemes could affect consumer response to price changes. Energy Policy. 2020, 137, 111181.
10. ALGANAD, A.; ISA, N.; FAUZI, W. Boosting green cars retail in Malaysia: The influence of conditional value on consumer’s behavior. Journal of Distribution Science. 2021, 7, 87-100.
11. Jiang, Z.; Dennis, Z.; Tat, C. How Do Bonus Payments Affect the Demand for Auto Loans and Their Delinquency? Mark. Res. 2021, 3, 476-496.

 

Section 3 "Methodology and Model" is presented in a comprehensive manner. Hovewer I suggest adding the adequate literature to the mentioned in the paper equation (recommendation #2). Also for line 132-133 "According to the results of literature research" please add the adequate references that justify this sentence (Recommendation #3).

 

Response 2:  We added the literature to the mentioned in the paper equation with:

12. Wu, Y.; Huang, K.; Wang, X. Method of Emotional Classification in Short Texts Combined with LDA Models. Journal of Chinese Computer Systems. 2019, 10, 2082-2086.
13. Zeng, Q.; Hu, X.; Li, C. Extracting Keywords with Topic Embedding and Network Structure Analysis. Data Analysis and Knowledge Discovery. 2019, 7, 52-60.

 

Response 3:  We added references with:

14. Ha, T.; Lee, J.; chang-hoan, L.; Coh, B. The Prediction of Long-Term Survival of Artificial Intelligence Patents Based on Deep-Learning and Latent Dirichlet Allocation Modeling. International Telecommunications Policy Review. 2021, 1, 27-50.
15. Edison, H.; Carcel, H. Text data analysis using Latent Dirichlet Allocation: an application to FOMC transcripts. Econ. Lett. 2020, 1, 38-42.
16. Ozyurt, B.; Akcayol, M. A new topic modeling based approach for aspect extraction in aspect based sentiment analysis: SS-LDA. Expert Syst. Appl. 2021, 168, 114231.
17. Ekinci, E.; Omurca, SI. Concept-LDA: Incorporating Babelfy into LDA for aspect extraction. Inf. Sci.2020, 3, 406-418.
18. Joung, J.; Kim, H. Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews. Mech. Des. 2021, 8, 084501.

 

Section 4 "Results" is well presented. However, I suggest an extension to Table 1 with prices in dollars or euros to be easier for the reader '' (recommendation #4).

 

Response 4:  We extended to Table 1 and certain paragraphs with prices in dollars.

 

A(below CNY100,000/USD 15,830)

B(CNY100,000-200,000/USD 15,830-31,660)

C(CNY200,000-300,000/USD31,660-47,490)

D(overCNY300,000/USD 47,490)

 

Section 5 " Discussions and Conclusion" also need an extension. Please add an additional paragraph with future research directions (recommendation #5).

 

Response 5：We separated the “Discussions and Conclusion”, and added an additional paragraph with future research directions.

 

Further research regarding possible improvements should be carried out based on the customer demand from the traditional fuel vehicle and new energy vehicle. On the one hand, traditional fuel vehicles are still sought after by consumers because of their endurance and service life; on the other hand, new energy vehicles are gradually becoming a new hot spot in the auto market because of their energy-saving and environmental protection, low maintenance costs, and significant purchase discounts. Further study will focus on how consumers choose to buy fuel or new energy vehicles, the similarities and differences in consumer demand between the two types of cars, and what the differences in consumer demand tell us about the marketing of automotive companies.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript is basically well written, but the following points must be improved.

• Title: What is "new energy vehicle?" Please specify it (in the title or in the text). Also, because the target of this study is China, so include "China" in the title (and emphasize in the text).
• Literature review and dicussion: these part should be revised to add more about international perspectives as this is an international journal.
• Methods: Some part of results should be in the method section, including data.
• Results: Add numerical results, so that the authors can interpret the results and discussion.
• Discussion and conclusion: these sections must be separated.

Some minor comments are as follows:

• What is this sign "￥"? Yuan? If so, explain it and also add conversion to US dollar.
• What is LDA? Write the full spell for it.
• If the authors used Chinese data/information, please clearly state it.

 

Author Response

Response to Reviewer 2 Comments

 

The manuscript is basically well written, but the following points must be improved.

 

Title: What is "new energy vehicle?" Please specify it (in the title or in the text). Also, because the target of this study is China, so include "China" in the title (and emphasize in the text).

 

Response 1:  We quote the definition of the “new energy vehicle” in the text.

New energy vehicle refers to the vehicles which use unconventional vehicle fuel or use conventional fuel but adopt new vehicle power unit, integrate the advanced technologies of power control and drive of the vehicle with new technology, new structure and new theory. New energy vehicles can be broadly divided into four categories: pure electric vehicles, hybrid vehicles, fuel cell vehicles and solar electric vehicles.

 

We include "China" in the title and emphasize in the text.

Title: New Energy Vehicle Consumer Demand Mining Research Based on Fusion Topic Model: A case in China

Text: According to the report "Economic Operation of the Automotive Industry in December 2020" published by the Ministry of Industry and Information Technology, China's auto sales reached 25.311 million units in 2020, the world's first for 12 consecutive years.

 

Literature review and dicussion: these part should be revised to add more about international perspectives as this is an international journal.

 

Response 2:  We added several references about international perspectives.

1. Al-Mahish, M.; AlDossari, N.; Almarri, A. Consumer's demand for Disinfectants and Protective Gear from COVID-19 infection in Al-Hofuf, Saudi. Infect. Dev. Ctries. 2021, 11, 1618-1624.
2. Baarsma, B.; Groenewegen, J. COVID-19 and the Demand for Online Grocery Shopping: Empirical Evidence from the Netherlands. Economist-Netherlands. 2021, 4, 407-421.
3. Wu, ; Wang, Y. Discovery of associated consumer demands: Construction of a co-demanded product network with community detection. Expert Syst. Appl. 2021, 178, 115038.
4. Park, M.; Kim, M.; Ryu, S. The relationship between network governance and unilateral governance in dynamic consumer demand. Mark. Manage. 2020, 84, 194-201.
5. Pallant, J.; Sands, S.; Karpen, I. Product customization: A profile of consumer demand. Retail. Consum. Serv. 2020, 54, 102030.
6. Dertwinkel-Kalt, M.; Koster, M.; Sutter, M. To buy or not to buy? Price salience in an online shopping field experiment. Econ. Rev. 2020, 130, 103593.
7. Singh, A.; Jenamani, M.; Thakkar, J.; Rana, N. Propagation of online consumer perceived negativity: Quantifying the effect of supply chain underperformance on passenger car sales. Bus. Res. 2021, 132, 102-114.
8. Hee, H. A Study on the Consumer Behaviors and Satisfaction Toward Hybrid Cars: Focused on Consumers’ Perceived Cost and Consumption Values. Korean Journal of Human Ecology. 2021, 5, 783-801.
9. Galarraga, I.; Kallbekken, S.; Silvestri, A. Consumer purchases of energy-efficient cars: How different labeling schemes could affect consumer response to price changes. Energy Policy. 2020, 137, 111181.
10. ALGANAD, A.; ISA, N.; FAUZI, W. Boosting green cars retail in Malaysia: The influence of conditional value on consumer’s behavior. Journal of Distribution Science. 2021, 7, 87-100.
11. Jiang, Z.; Dennis, Z.; Tat, C. How Do Bonus Payments Affect the Demand for Auto Loans and Their Delinquency? Mark. Res. 2021, 3, 476-496.
12. Ha, T.; Lee, J.; chang-hoan, L.; Coh, B. The Prediction of Long-Term Survival of Artificial Intelligence Patents Based on Deep-Learning and Latent Dirichlet Allocation Modeling. International Telecommunications Policy Review. 2021, 1, 27-50.
13. Edison, H.; Carcel, H. Text data analysis using Latent Dirichlet Allocation: an application to FOMC transcripts. Econ. Lett. 2020, 1, 38-42.
14. Ozyurt, B.; Akcayol, M. A new topic modeling based approach for aspect extraction in aspect based sentiment analysis: SS-LDA. Expert Syst. Appl. 2021, 168, 114231.
15. Ekinci, E.; Omurca, SI. Concept-LDA: Incorporating Babelfy into LDA for aspect extraction. Inf. Sci.2020, 3, 406-418.
16. Joung, J.; Kim, H. Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews. Mech. Des. 2021, 8, 084501.

 

Methods: Some part of results should be in the method section, including data.

 

Response 3:  “Data sources” is adjusted to section ”Results”.

 

Results: Add numerical results, so that the authors can interpret the results and discussion.

 

Response 4:  We added numerical results.

“The aggregated results are shown in Tables 2 - 5. Among them, group A has 5 demand topics and 82 topic feature expansion words, group B has 4 demand topics and 57 topic feature expansion words, group C has 4 demand topics and 68 topic feature expansion words, and group D has 5 demand topics and 75 topic feature expansion words”

 

Discussion and conclusion: these sections must be separated.

 

Response 5:  We separated the Discussion and Conclusion.

 

Some minor comments are as follows:

 

What is this sign "￥"? Yuan? If so, explain it and also add conversion to US dollar.

 

Response 6:  "￥" means CNY.  We added conversion to US dollar.

 

A(below CNY100,000/USD 15,830)

B(CNY100,000-200,000/USD 15,830-31,660)

C(CNY200,000-300,000/USD31,660-47,490)

D(overCNY300,000/USD 47,490)

 

What is LDA? Write the full spell for it.

 

Response 7:  LDA means Latent Dirichlet Allocation. We write the full spell in the text.

 

If the authors used Chinese data/information, please clearly state it.

 

Response 8:  We state that we used Chinese data/information.

“Auto Home is a Chinese version of the website, so we collected 18,484 Chinese online reviews of the four groups through the self-coded crawler…”

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The manuscript is suitable for publication in the present form.