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Global In-vehicle Payment Services Market to reach USD 11.21 billion by 2028.

Global In-vehicle Payment Services Market Size study, by Mode of Payment (NFC, QR Code/RFID, App/e-wallet, Credit/Debit card) by Application (Parking, Gas/charging stations, Shopping, Food/Coffee, Toll Collection, Others) and Regional Forecasts 2022-2028

Product Code: ALTST-57708650
Publish Date: 13-06-2022
Page: 200

Global In-vehicle Payment Services Market is valued approximately USD 4.08 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 15.53 % over the forecast period 2022-2028. In-vehicle payment services enable drivers to order and pay for food, coffee, gasoline, groceries, parking spaces, and tolls without ever leaving their vehicle. Over the projected period, advances in Internet of Things (IoT) technology and strong efforts by various automakers to integrate new, advanced infotainment solutions into their vehicle models are expected to fuel market expansion. The rising use of contactless payment methods in the aftermath of the COVID-19 pandemic, as well as further advancements in smart vehicles, augur well for the market’s growth. Automobile makers are concentrating their efforts on developing built-in technology, such as voice-based controls, that might allow drivers to shop while on the road without jeopardizing road safety. Given the potential for a voice-activated dashboard to divert the driver’s attention, drivers must always prioritise road safety when shopping while driving. MasterCard, Visa, and PayPal are among the payment solution providers collaborating with automakers around the world to create and integrate new payment processes and techniques in vehicles. Similarly, Visa announced a partnership with SiriusXM in January 2019 to launch a vehicle-based payments platform. Volkswagen AG, Honda Motor Co. Ltd., and Ford Motor Co. are among the companies that have created in-vehicle payment solutions and platforms. Over the forecast period, the market for in-vehicle payment services is expected to rise due to the increasing usage of driver assistance systems. Driver assistance systems assist drivers in a variety of ways, including hassle-free parking and making purchases directly from the control panel without the use of any extra devices or cards. However, risks of cyber threats impede the growth of the market over the forecast period of 2022-2028.

The key regions considered for the Global In-vehicle Payment Services Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America accounted for largest market share. The region has the highest percentage of connected vehicles. Furthermore, technological businesses situated in North America, such as Apple Inc. and Google Inc., have entered the automobile market with their ability to develop and compete with automotive companies. From 2022 to 2028, the Asia Pacific regional market is expected to grow at the fastest rate. The expansion is projected to be aided by a growing population and rising levels of disposable income. Over the projection period, adoption of the most advanced technology and further improvements in the way payments are made and processed will also play a key role in driving growth.

Major market player included in this report are:
BMW AG
Daimler AG
Ford Motor Co.
General Motors Co.
Honda Motor Co. Ltd.
Hyundai Motor Co.
Jaguar Land Rover Automotive PLC
Volkswagen AG
ZF Friedrichshafen AG
Google
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Mode of Payment:
NFC
QR Code/RFID
App/e-wallet
Credit/Debit card
By Application:
Parking
Gas/charging stations
Shopping
Food/Coffee
Toll Collection
Others
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global In-vehicle Payment Services Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. In-vehicle Payment Services Market, by Region, 2020-2028 (USD Billion)
1.2.2. In-vehicle Payment Services Market, by Mode of Payment, 2020-2028 (USD Billion)
1.2.3. In-vehicle Payment Services Market, by Application, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global In-vehicle Payment Services Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global In-vehicle Payment Services Market Dynamics
3.1. In-vehicle Payment Services Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Surging demand for Contactless payment methods
3.1.1.2. Growing adoption of Driver Support Systems
3.1.2. Market Challenges
3.1.2.1. Increasing threat of cyberattacks
3.1.2.2. Disruption in global supply chain.
3.1.3. Market Opportunities
3.1.3.1. Advancements in Internet of Things Technology
3.1.3.2. Increasing penetration of Connected Cars
Chapter 4. Global In-vehicle Payment Services Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global In-vehicle Payment Services Market, by Mode of Payment
6.1. Market Snapshot
6.2. Global In-vehicle Payment Services Market by Mode of Payment, Performance – Potential Analysis
6.3. Global In-vehicle Payment Services Market Estimates & Forecasts by Mode of Payment 2018-2028 (USD Billion)
6.4. In-vehicle Payment Services Market, Sub Segment Analysis
6.4.1. NFC
6.4.2. QR Code/RFID
6.4.3. App/e-wallet
6.4.4. Credit/Debit card
Chapter 7. Global In-vehicle Payment Services Market, by Application
7.1. Market Snapshot
7.2. Global In-vehicle Payment Services Market by Application, Performance – Potential Analysis
7.3. Global In-vehicle Payment Services Market Estimates & Forecasts by Application 2018-2028 (USD Billion)
7.4. In-vehicle Payment Services Market, Sub Segment Analysis
7.4.1. Parking
7.4.2. Gas/charging stations
7.4.3. Shopping
7.4.4. Food/Coffee
7.4.5. Toll Collection
7.4.6. Others
Chapter 8. Global In-vehicle Payment Services Market, Regional Analysis
8.1. In-vehicle Payment Services Market, Regional Market Snapshot
8.2. North America In-vehicle Payment Services Market
8.2.1. U.S. In-vehicle Payment Services Market
8.2.1.1. Mode of Payment breakdown estimates & forecasts, 2018-2028
8.2.1.2. Application breakdown estimates & forecasts, 2018-2028
8.2.2. Canada In-vehicle Payment Services Market
8.3. Europe In-vehicle Payment Services Market Snapshot
8.3.1. U.K. In-vehicle Payment Services Market
8.3.2. Germany In-vehicle Payment Services Market
8.3.3. France In-vehicle Payment Services Market
8.3.4. Spain In-vehicle Payment Services Market
8.3.5. Italy In-vehicle Payment Services Market
8.3.6. Rest of Europe In-vehicle Payment Services Market
8.4. Asia-Pacific In-vehicle Payment Services Market Snapshot
8.4.1. China In-vehicle Payment Services Market
8.4.2. India In-vehicle Payment Services Market
8.4.3. Japan In-vehicle Payment Services Market
8.4.4. Australia In-vehicle Payment Services Market
8.4.5. South Korea In-vehicle Payment Services Market
8.4.6. Rest of Asia Pacific In-vehicle Payment Services Market
8.5. Latin America In-vehicle Payment Services Market Snapshot
8.5.1. Brazil In-vehicle Payment Services Market
8.5.2. Mexico In-vehicle Payment Services Market
8.6. Rest of The World In-vehicle Payment Services Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. BMW AG
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments

9.2.2. Daimler AG
9.2.3. Ford Motor Co.
9.2.4. General Motors Co.
9.2.5. Honda Motor Co. Ltd.
9.2.6. Hyundai Motor Co.
9.2.7. Jaguar Land Rover Automotive PLC
9.2.8. Volkswagen AG
9.2.9. ZF Friedrichshafen AG
9.2.10. Google
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
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Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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