Design and Application of Experience Management Tools from the Perspective of Customer Perceived Value: A Study on the Electric Vehicle Market
Abstract
:1. Introduction
1.1. Background
1.2. Research Gap
1.3. Objectives
1.4. Methodology
1.5. Significance
2. Literature Review
2.1. Customer Perceived Value
2.2. Customer Experience Management
2.3. Customer Experience Management in the Automotive Industry
2.4. Experience Management Tools
2.5. Research Gap in Customer Experience Management Tools for Electric Vehicles
3. Methodology
3.1. Research through Design (RtD)
3.2. Empirical Research and Factor Analysis
3.3. Fuzzy-Set Qualitative Comparative Analysis (fsQCA)
3.4. Semi-Structured Interviews
3.5. Expert Reviews and the Delphi Method
3.6. Usability Testing with the System Usability Scale (SUS)
3.7. Overview of Case Studies
4. Case Study 1: Identifying Key Factors Influencing Electric Vehicle Purchase Decisions
4.1. Hypotheses
4.2. Methodology
4.3. Results
4.3.1. Reliability and Validity of the Sample
4.3.2. Descriptive Statistics and Correlations
4.3.3. fsQCA Factor Combination Analysis
4.3.4. Hypothesis Testing and Analysis Results
4.4. Conclusions
- User willingness to purchase new energy vehicles (NEVs) does not require any prerequisite conditions. Previous research, such as Kowalska-Pyzalska et al. (2021), identified significant positive impacts and the absence of negative impacts as influencing purchase intention [53,54]. However, our study shows that no single factor is absolute; negative factors can persist, and positive factors may disappear. This suggests that automotive companies can focus on market breakthrough strategies to optimize resource use in NEV design and sales.
- Quality value is a key factor influencing users’ willingness to purchase NEVs. Using the fsQCA method, we identified four configurations that enhance purchase intentions, emphasizing quality value. These insights guide the design and planning of offline experience spaces, optimizing R&D investment. Future research should include additional indicators like vehicle models and brand recognition to enrich the model’s complexity.
4.5. Discussion
5. Case Study 2: In-Depth Interview Analysis of Customer Experience Management Tool Users
5.1. Methodology
5.2. Result
5.3. Conclusions and Discussion
6. Case Study 3: Validation and Optimization of the Prototype
6.1. Methodology
6.1.1. Research Objectives and Participants
6.1.2. Testing Process
6.2. Results
6.2.1. On-Site Observation Analysis
- Three users experienced hesitation during Task 5 when saving and locating the user journey map in data analysis.
- Two users had difficulty finding the data dissection button for perceived value analysis during Task 7.
6.2.2. SUS Scores and User Feedback Analysis
7. Case Study 4: Usability Testing and Optimization of the Customer Experience Management Tool
7.1. Methodology
7.1.1. Testing Methods and Objectives
7.1.2. Test Participants
7.1.3. Testing Procedures and Content
7.1.4. Experimental Procedures
7.2. Results
7.3. Conclusions
8. Discussion
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Variable | Item | Source |
---|---|---|
Use Value | Travel efficiency | Sheth et al. (1991) [56,57] |
Driving mileage | ||
Structural safety | ||
Good performance | ||
Easy operation | ||
Stability and comfort | ||
Price Value | Policy subsidies | Sweeney and Soutar (2001) [14] |
Loan discounts | ||
Low cost | ||
Affordable maintenance | ||
Cost performance | ||
Emotional Value | Pleasant mood | Chen Jie (2015) [58] |
Fashionable and trendy | ||
Green and environmentally friendly | ||
Environmental contribution | ||
Social recognition | ||
Social Value | Low carbon and dual reduction | Chen et al. (2019) [59] |
Petroleum consumption | ||
Environmental protection | ||
Social responsibility | ||
Purchase Intention | Desire to purchase | Dodds et al. (1991) [60]; Ng et al. (2018) [61] |
Priority purchase | ||
Recommend purchase |
Characteristic | Category | Frequency | Percentage (%) |
---|---|---|---|
Gender | Male | 165 | 55.00 |
Female | 135 | 45.00 | |
Age | Under 18 | 11 | 3.66 |
19–28 | 104 | 34.67 | |
29–45 | 93 | 31.00 | |
46–59 | 72 | 24.00 | |
Over 60 | 20 | 6.67 | |
Education | Middle school or below | 12 | 4.00 |
High school or technical school | 28 | 9.33 | |
Junior college | 76 | 25.33 | |
Bachelor’s degree | 158 | 52.67 | |
Master’s degree or above | 26 | 8.67 | |
Occupation | Ordinary workers or service personnel | 58 | 19.33 |
Staff of government organizations, institutions, and state-owned enterprises | 92 | 30.67 | |
Staff in education, research, and healthcare | 56 | 18.67 | |
Private enterprise owners or employees | 50 | 16.67 | |
Self-employed | 32 | 10.66 | |
Student | 12 | 4.00 | |
Monthly Income | Less than 3000 RMB | 15 | 5.00 |
3000–5500 RMB | 101 | 33.67 | |
5501–8000 RMB | 92 | 30.66 | |
8001–10,000 RMB | 51 | 17.00 | |
More than 10,000 RMB | 41 | 13.67 | |
Household Registration | Urban household | 158 | 52.67 |
Rural household | 142 | 47.33 | |
Have you purchased a new energy vehicle? | Yes | 36 | 12.00 |
No | 264 | 88.00 | |
Car Ownership | 0 | 61 | 20.33 |
1 | 197 | 65.67 | |
2 | 38 | 12.67 | |
3 | 4 | 1.33 | |
Annual Mileage | Less than 15,000 km | 80 | 26.67 |
15,000–30,000 km | 62 | 20.66 | |
30,001–40,000 km | 92 | 30.67 | |
More than 40,001 km | 66 | 22.00 | |
Awareness of New Energy Vehicles | Never heard of it | 0 | 0.00 |
Heard only in the news or other channels | 30 | 10.00 | |
Slightly familiar | 129 | 43.00 | |
Quite familiar | 101 | 33.67 | |
Very familiar | 40 | 13.33 | |
Do you own any new energy vehicles? | Yes | 115 | 38.33 |
No | 185 | 61.67 |
Appendix B. Questionnaire
- Gender: [single choice]
- Male
- Female
- Age: [single choice]
- Under the age of 18
- 19 to 28 years old
- 29 to 45 years old
- 46 to 59 years old
- Over 60 years old
- Educational background: [single choice]
- Junior high school and below
- High school or technical secondary school
- Junior college
- Undergraduate
- Master’s degree or above
- Occupation [single choice]
- General workers or service personnel
- Staff of government organizations, institutions, and state-owned enterprises
- Staff in the fields of education, scientific research, or health
- Owners or employees of private enterprises
- Self-employed person
- Student
- Monthly income [single choice]
- Below CNY 3000
- CNY 3000–5500
- CNY 5501–8000
- CNY 8001–10,000
- Over CNY 10,000
- Your household registration type is [single choice]
- Urban
- Rural
- Have you bought a vehicle [single choice]
- Purchased
- Not purchased
- The number of vehicles you own is [single choice]
- 0
- 1
- 2
- 3
- Your annual mileage is approximately (km/year) [single choice]
- Less than 15,000 km
- 15,000–30,000 km
- 30,001–40,000 km
- Longer than 40,001 km
- Do you know or hear about new energy vehicles [single choice]
- Never heard of
- Only heard of it over the news or by other means
- Know a little
- Better understanding
- Very well
- Do you own any NEVs? [single choice]
- Yes
- No
- New energy vehicles can improve driving efficiency
- The driving range of new energy vehicles can meet the requirements of driving distance
- The design and body structure of new energy vehicles are safer
- The power performance of new energy vehicles is good and the speed is fast
- The driving and operation of new energy vehicles are simple and convenient
- New energy vehicles have low driving noise and are stable and comfortable when driving
- Large subsidies for new energy vehicles
- New energy vehicles have preferential loan and tax policies
- Low use cost of new energy vehicles (electricity price lower than oil price)
- The late maintenance of new energy vehicles is economical and practical
- The purchase of new energy vehicles is cost effective
- Buying or driving new energy cars can make me happy
- Buying or driving a new energy car fits my fashionable image
- Buying or driving a new energy car fits my green image
- Buying or driving a new energy car makes me feel like I’m contributing to the environment
- Buying or driving new energy vehicles can gain more social recognition
- Buying or driving new energy vehicles is in response to the country’s low-carbon double reduction policy
- Buying or driving new energy vehicles reduces oil consumption in the long run
- Buying or driving new energy vehicles helps protect the environment
- Buying or driving new energy vehicles is a socially responsible act
- I want to buy a new energy car
- When buying a car, I will give priority to new energy vehicles
- I would like to recommend my friends to buy new energy vehicles
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Stages | Activities | Objectives |
---|---|---|
Awareness | Marketing, Social Media Engagement | Increase Brand Awareness, Educate Customers |
Consideration | Test Drives, Product Comparisons | Provide Information, Build Trust |
Purchase | Sales Process, Financing Options | Ensure Smooth Purchase Experience, Close Sales |
Service | Maintenance, Customer Support | Provide Excellent Service, Address Issues |
Loyalty | Feedback, Loyalty Programs | Foster Loyalty, Encourage Repeat Purchases |
Case Study | Purpose | Objective | Method | Results |
---|---|---|---|---|
Case Study 1 | Identifying Factors Influencing EV Purchases | Identify key factors influencing EV purchase decisions | Surveys analyzed with fsQCA | Identified price, quality, and brand image as key factors |
Case Study 2 | Interview Analysis of CEM Tool Users | Understand workflows of CEM tool users | Semi-structured interviews | Identified issues in time management and communication |
Case Study 3 | Prototype Validation through Expert Reviews | Validate research findings and prototype design | Expert reviews using Delphi method | Validated hypotheses and suggested prototype improvements |
Case Study 4 | Usability Testing of CEM Tool | Evaluate effectiveness of CEM tool | Usability testing with SUS | Identified strengths and weaknesses, guiding optimization |
Variable | Cronbach’s α |
---|---|
Purchase Intention | 0.921 |
Use Value | 0.894 |
Price Value | 0.873 |
Emotional Value | 0.898 |
Social Value | 0.971 |
Measure | Value |
---|---|
Kaiser–Meyer–Olkin Measure | 0.983 |
Bartlett’s Test of Sphericity | |
Approx. Chi-Square | 7412.743 |
Degrees of Freedom (df) | 531 |
Significance (p-value) | 0.000 |
Variable | Mean | Std. Dev | Quality Value | Price Value | Emotional Value | Social Value | Purchase Intention |
---|---|---|---|---|---|---|---|
Quality Value | 3.7855 | 0.78123 | 0.815 | ||||
Price Value | 3.8968 | 0.77234 | 0.432 ** | 0.873 | |||
Emotional Value | 3.8872 | 0.76532 | −0.012 | −0.035 | 0.781 | ||
Social Value | 3.6712 | 0.82134 | −0.051 | −0.039 | 0.497 ** | 0.769 | |
Purchase Intention | 3.6515 | 0.82467 | 0.435 ** | 0.548 ** | −0.232 ** | −0.114 | 0.812 |
Antecedent Condition | Purchase Intention | Non-Purchase Intention | ||
---|---|---|---|---|
Consistency | Coverage | Consistency | Coverage | |
Use Value | 0.759795 | 0.753630 | 0.469121 | 0.615996 |
-Use Value | 0.612822 | 0.466725 | 0.814764 | 0.819815 |
Price Value | 0.731932 | 0.723492 | 0.484774 | 0.633137 |
-Price Value | 0.628611 | 0.479989 | 0.791001 | 0.799102 |
Emotional Value | 0.621032 | 0.486147 | 0.729022 | 0.753901 |
-Emotional Value | 0.670453 | 0.652923 | 0.502991 | 0.637035 |
Social Value | 0.648611 | 0.658902 | 0.654774 | 0.746269 |
-Social Value | 0.702932 | 0.604766 | 0.615269 | 0.699869 |
Condition | Config 1 | Config 2 | Config 3 | Config 4 |
---|---|---|---|---|
Use Value | O | O | O | |
Price Value | O | • | O | |
Emotional Value | • | • | • | |
Social Value | x | x | • | |
Original Coverage | 0.451406 | 0.555453 | 0.417559 | 0.398906 |
Unique Coverage | 0.0524269 | 0.0410322 | 0.0746638 | 0.0713743 |
Consistency | 0.869756 | 0.918945 | 0.939575 | 0.882943 |
Overall Solution Coverage | 0.710585 | |||
Overall Solution Consistency | 0.837724 |
No. | Position | Location | Gender | Age | Job Responsibilities |
---|---|---|---|---|---|
S1 | Sales | Beijing | Male | 28 | Communicate with potential customers, understand their needs, and provide product information. Maintain a professional image to ensure customer trust. |
S2 | Sales | Shanghai | Male | 25 | |
C1 | UX Designer | Beijing | Female | 25 | Design user interfaces and experiences to enhance customer satisfaction. |
C2 | UX Designer | Shenzhen | Male | 32 | |
T1 | Product Manager | Shanghai | Female | 35 | Develop product strategies, plan roadmaps, and collaborate with teams to improve product quality. |
T2 | Product Manager | Chengdu | Male | 28 | |
M1 | Marketing | Shanghai | Female | 25 | Develop marketing strategies and conduct market analysis to ensure product market entry and recognition. |
M2 | Marketing | Shanghai | Female | 29 | |
O1 | Service Supervisor | Nanjing | Male | 30 | Ensure efficient operation and high service quality of the customer service team. |
O2 | Service Supervisor | Shanghai | Female | 37 |
Interview Phase | Interview Content |
---|---|
Phase 1 | Action: Ice breaking, introduction to the study background, and ethical principles based on the Helsinki Declaration. |
Goal: Establish trust and rapport with the interviewees and ensure they understand the importance of the research. | |
Phase 2 | Action: Collect basic information about the interviewees, such as age, gender, education, occupation, etc. |
Goal: Better understand the interviewees’ backgrounds and personal characteristics. | |
Phase 3 | Action: Understand the current customer experience management tools used by the interviewees and how they use these tools to manage customer relationships. |
Goal: Identify the problems and challenges faced by the interviewees in using these tools to better understand their needs and expectations. | |
Phase 4 | Action: Explore the interviewees’ work experiences, such as how they manage time, communicate with colleagues, handle tasks, and interact with customers. |
Goal: Gain a deeper understanding of the interviewees’ work scenarios, workflows, and work requirements. |
Pain Points | Impact on Perceived Customer Value | Innovation Design Opportunities |
---|---|---|
1. Limited offline experience maps | Reduces use and emotional value due to lack of reuse and coordination | Implement online experience map creation |
2. No visualization of customer footprints | Lowers emotional and social value, causing dissatisfaction | Add visualization of customer footprints and profiles |
3. Absence of component libraries | Complicates design, affecting use and emotional value | Introduce customizable component libraries |
4. No multi-channel surveys | Misses changes in emotional value, reducing loyalty | Deploy multi-channel experience surveys |
5. Undefined customer journey metrics | Hinders understanding of product value | Define clear customer journey metrics |
6. Inconsistent metrics across departments | Varies service quality, impacting perceived value | Integrate operational metrics tracking |
Task Number | Task Content |
---|---|
1 | Find and enter the workstation to select and open a recent project. |
2 | Locate the most recent project in project management and open the user profile. |
3 | Edit the user’s name, age, and notes in the profile and save the changes. |
4 | Find and open the user’s journey map to edit user tags. |
5 | Save the user journey map and find it in data analysis. |
6 | Locate and open multidimensional data analysis in the data analysis section. |
7 | Open the user perceived value analysis, dissect the data, and find the source file. |
8 | Use the data annotation function to upload a test file and perform data annotation. |
9 | Free exploration phase, allowing participants to explore the prototype as they wish. |
Expert Name | Position | Company | Responsible Product | Industry Experience |
---|---|---|---|---|
Zhang Kai | Senior Customer Experience Researcher | Shanghai Automotive Group | Electric Vehicle Intelligent Connectivity System | Over 10 years in EV customer experience, specializing in user research, needs analysis, and experience design. |
Li Ming | Senior Interaction Designer | Beijing Automotive Group | EV Infotainment System | Over 7 years in EV customer experience design, experienced in user research, interaction design, and usability testing. |
Wang Qiang | Senior Systems Engineer | Guangzhou Tesla Center | EV Intelligent Driving Assistance System | Extensive experience in EV customer experience management tools, specializing in systems engineering design and intelligent control algorithms. |
Chen Jing | Senior Software Engineer | Shenzhen BYD | EV Intelligent Charging System | Over 10 years in EV customer experience management tools, specializing in software development, experience design, and testing. |
Participant | Q1 | Q2 | Q3 | Q4 | Q5 | Q6 | Q7 | Q8 | Q9 | Q10 | Total Score | SUS Score |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 5 | 3 | 4 | 2 | 5 | 4 | 3 | 4 | 4 | 5 | 39 | 78 |
2 | 4 | 2 | 3 | 5 | 4 | 3 | 5 | 5 | 3 | 4 | 38 | 76 |
3 | 3 | 4 | 4 | 3 | 4 | 4 | 5 | 3 | 4 | 4 | 38 | 76 |
4 | 4 | 2 | 3 | 2 | 4 | 2 | 2 | 4 | 3 | 4 | 30 | 60 |
5 | 5 | 4 | 4 | 4 | 5 | 4 | 4 | 4 | 3 | 5 | 42 | 84 |
6 | 3 | 5 | 5 | 5 | 4 | 2 | 5 | 3 | 3 | 3 | 38 | 76 |
7 | 4 | 3 | 4 | 3 | 4 | 5 | 3 | 4 | 5 | 4 | 39 | 78 |
8 | 2 | 2 | 2 | 2 | 2 | 4 | 2 | 4 | 5 | 2 | 27 | 54 |
9 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 5 | 2 | 3 | 31 | 62 |
10 | 4 | 4 | 3 | 4 | 4 | 5 | 5 | 4 | 3 | 4 | 40 | 80 |
Average | 4 | 3.2 | 3.5 | 3.3 | 3.9 | 3.6 | 3.7 | 4 | 3.5 | 3.8 | 36.2 | 72.4 |
No. | Name | Company | Role |
---|---|---|---|
1 | Karen Lee | N | Sales |
2 | Michael Chen | N | UX Designer |
3 | Michelle Wang | N | Product Manager |
4 | Sophie Liu | P | Service Manager |
5 | John Wu | P | Marketing |
6 | Jessica Zhang | S | B2B UX Designer |
7 | Alex Wang | S | B2B Product Manager |
8 | Jane Li | S | Marketing |
9 | Eric Li | C | Service Manager |
10 | Emily Wang | C | Marketing |
11 | Kevin Chen | B | B2B UX Designer |
12 | Lily Zhang | B | B2B Product Manager |
13 | Tony Chen | B | Operations |
14 | Grace Zhou | A | Service Manager |
15 | Michael Liu | A | Marketing |
16 | Sarah Wu | A | B2B UX Designer |
17 | Jason Chen | D | Product Manager |
18 | Steven Zhang | D | Service Manager |
Category | Experimental Group | Control Group | X2 | p-Value |
---|---|---|---|---|
Age | 0.083 | 0.773 | ||
25 and under | 7 (70%) | 6 (67%) | ||
26–35 | 2 (20%) | 2 (22%) | ||
36 and over | 1 (10%) | 1 (11%) | ||
Gender | 0.000 | 1.000 | ||
Male | 6 (60%) | 5 (56%) | ||
Female | 4 (40%) | 4 (44%) |
Task Stage | Task Details |
---|---|
Data Collection | Task 1: Open the questionnaire collection feature |
Task 2: Find and view data from the “Metaverse Virtual Space” survey | |
Task 3: Publish the completed “Experience Design Questionnaire A” | |
Task 4: Select the app delivery method for the questionnaire | |
Task 5: Change Q2 trigger to “phone screen off” | |
Task 6: Save and send the questionnaire | |
Action Improvement | Task 7: Open the welcome page of the workstation |
Task 8: Search for the warning center in the search box | |
Task 9: View the warnings in the warning center | |
Task 10: Track a low-score experience | |
Task 11: Trace the customer journey to find issues | |
Data Annotation | Task 12: Upload “demo.3ds” model to the annotation interface |
Task 13: Add and rename a point of interest (POI) | |
Task 14: Add paths between POI A and B | |
Task 15: View and delete POI C in the global view | |
Task 16: Save the model annotations |
Step | Time | Experimental Group | Control Group |
---|---|---|---|
Pre-experiment | 10 min | Introduce objectives, background, and methods | Fill out basic information |
Sign informed consent | |||
Experiment | 20 min | Introduce prototype and usage | Introduce Beisite XM and usage |
Complete tasks using prototype | Complete tasks using Beisite XM | ||
Post-experiment | 10 min | Fill out questionnaire | |
Participant interviews | |||
End of experiment, gift distribution |
Job Function | Experimental Group | Control Group |
---|---|---|
Marketing | 2 | 1 |
Service Manager | 2 | 2 |
Product Manager | 2 | 2 |
Sales | 2 | 2 |
UX Design | 2 | 2 |
X2 | 0.500 | |
p | >0.05 |
Metric | Experimental Group | Control Group | Difference | t | p |
---|---|---|---|---|---|
Usability | 4.2 ± 0.3 | 3.7 ± 0.3 | 0.5 ± 0.4 | 2.33 | 0.033 |
Understandability | 3.5 ± 0.2 | 3.0 ± 0.2 | 0.5 ± 0.28 | 2.83 | 0.012 |
Efficiency | 4.0 ± 0.3 | 3.7 ± 0.3 | 0.3 ± 0.4 | 1.50 | 0.148 |
Effectiveness | 4.1 ± 0.2 | 3.8 ± 0.2 | 0.3 ± 0.3 | 1.74 | 0.096 |
Aesthetics | 3.25 ± 0.27 | 2.75 ± 0.27 | 0.50 ± 0.38 | 5.111 | 0.002 |
Metric | Experimental Group | Control Group | Difference | t | p |
---|---|---|---|---|---|
Usability | 3.5 ± 0.2 | 3.0 ± 0.2 | 0.5 ± 0.4 | 2.83 | 0.012 |
Understandability | 3.2 ± 0.3 | 2.8 ± 0.3 | 0.4 ± 0.4 | 2.33 | 0.033 |
Efficiency | 3.2 ± 0.2 | 3.6 ± 0.2 | 0.4 ± 0.3 | 2.83 | 0.012 |
Effectiveness | 3.8 ± 0.3 | 3.5 ± 0.3 | 0.3 ± 0.4 | 1.74 | 0.096 |
Aesthetics | 3.7 ± 0.3 | 3.3 ± 0.3 | 0.4 ± 0.4 | 2.33 | 0.033 |
Metric | Experimental Group | Control Group | Difference | t | p |
---|---|---|---|---|---|
Usability | 3.2 ± 0.3 | 2.8 ± 0.3 | 0.4 ± 0.4 | 2.33 | 0.003 ** |
Understandability | 3.0 ± 0.2 | 3.5 ± 0.2 | 0.5 ± 0.3 | 2.83 | 0.004 ** |
Efficiency | 3.1 ± 0.3 | 2.8±0.3 | 0.3 ± 0.4 | 2.33 | 0.029 |
Effectiveness | 3.7 ± 0.2 | 3.3±0.2 | 0.4 ± 0.3 | 2.83 | 0.045 |
Aesthetics | 3.4 ± 0.3 | 2.8 ± 0.3 | 0.6 ± 0.4 | 2.33 | 0.001 ** |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Xu, Y.; Shan, X.; Guo, M.; Gao, W.; Lin, Y.-S. Design and Application of Experience Management Tools from the Perspective of Customer Perceived Value: A Study on the Electric Vehicle Market. World Electr. Veh. J. 2024, 15, 378. https://doi.org/10.3390/wevj15080378
Xu Y, Shan X, Guo M, Gao W, Lin Y-S. Design and Application of Experience Management Tools from the Perspective of Customer Perceived Value: A Study on the Electric Vehicle Market. World Electric Vehicle Journal. 2024; 15(8):378. https://doi.org/10.3390/wevj15080378
Chicago/Turabian StyleXu, Yuanyuan, Xinyang Shan, Mingcheng Guo, Weiting Gao, and Yin-Shan Lin. 2024. "Design and Application of Experience Management Tools from the Perspective of Customer Perceived Value: A Study on the Electric Vehicle Market" World Electric Vehicle Journal 15, no. 8: 378. https://doi.org/10.3390/wevj15080378