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Bizwit Research & Consulting LLP is a global provider of business intelligence & consulting services. We have a strong primary base of key industry leaders along with the chain of industry analysts to analyze the market trends and its future impact in order to estimates and forecast different business segments and markets. 

Global In-car apps Market to reach USD XX billion by the end of 2029.

Global In-car apps Market Size study & Forecast, by Application (ADAS & Safety System, Body Control & Comfort System, Powertrain System, Infotainment System, Communication System, Vehicle Management & Telematics, Connected Services, Others), By Vehicle Type (Passenger car, LCV, HCV), By Software Layer (Operating System, Middleware, Application software) and Regional Analysis, 2022-2029

Product Code: ICTEITS-94973412
Publish Date: 25-01-2023
Page: 200

Global In-car apps Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. In-car apps are third-party application software that offers the car driver to control different features in the vehicle such as infotainment systems, cruise control, lane keep assist system, and telematics management among others. These apps also assist in vehicle monitoring and diagnosis features. The required updates and new feature additions in the applications are provided over the air that can be downloaded via an internet connection. The growing expansion of automobile industry and increasing adoption of autonomous vehicles as well as strategic initiatives from leading market players are key factors accelerating the market growth.

The growing expansion of automotive sector and increasing penetration of autonomous cars is contributing to the growth of the Global In-car apps Market. For instance, as per International Energy Agency estimates – in 2020, globally around 3 million electric vehicles (EVs) were sold, and in 2021 this number becomes more than double to reach 6.6 million units. Furthermore, in the first quarter of 2022 more than 2 million units of EVs have been sold. Also, rising technological advancements in the automotive sector and rapid emergence of connected cars would create a lucrative growth prospectus for the market over the forecast period. However, high deployment costs and rising concerns over risk associated with use of third-party applications impede the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global In-car apps Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is the leading region in terms of global market share owing to presence of key market players and rising adoption of autonomous & semiautonomous vehicles in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rising penetration of leading market players coupled with favorable initiatives from government authorities to promote automotive sector & rapid emergence of connected cars in the region.

Major market players included in this report are:
Robert Bosch GmbH
NXP Semiconductors N.V.
Renesas Electronics Corporation
BlackBerry Limited
Nvidia Corporation
Microsoft Corporation
Airbiquity Inc.
Elektrobit Automotive GmbH
Green Hills Software
Wind River Systems

Recent Developments in the Market:
 In June 2020, Ford commercial solutions rolled out Ford TelematicsTM platform. This new web-based software platform and subscription service would facilitate commercial vehicle customers to manage and optimize the efficiency of their fleets. For the first six months, the customers would get complimentary access and after that, a subscription would be levied.

Global In-car apps Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Application, Vehicle Type, Software Layer, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential 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 Application
ADAS & Safety Systems
Body Control & Comfort System
Powertrain System
Infotainment System
Communication System
Vehicle Management & Telematics
Connected Services

By Vehicle Type
Passenger car

By Software layer
Operating System
Application software

By Region:
North America
Asia Pacific
South Korea
Latin America
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. In-car apps Market, by Region, 2019-2029 (USD Billion)
1.2.2. In-car apps Market, by Application, 2019-2029 (USD Billion)
1.2.3. In-car apps Market, by Vehicle Type, 2019-2029 (USD Billion)
1.2.4. In-car apps Market, by Software Layer, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global In-car apps 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-car apps Market Dynamics
3.1. In-car apps Market Impact Analysis (2019-2029)
3.1.1. Market Drivers Growing expansion of automobile industry Increasing adoption of autonomous vehicles Strategic initiatives from leading market players
3.1.2. Market Challenges High deployment cost Rising concern over cybersecurity
3.1.3. Market Opportunities Growing technological advancements in automotive sector Rising emergence of connected cars
Chapter 4. Global In-car apps 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
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global In-car apps Market, by Application
6.1. Market Snapshot
6.2. Global In-car apps Market by Application, Performance – Potential Analysis
6.3. Global In-car apps Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
6.4. In-car apps Market, Sub Segment Analysis
6.4.1. DAS & Safety Systems
6.4.2. Body Control & Comfort System
6.4.3. Powertrain System
6.4.4. Infotainment System
6.4.5. Communication System
6.4.6. Vehicle Management & Telematics
6.4.7. Connected Services
6.4.8. Others
Chapter 7. Global In-car apps Market, by Vehicle Type
7.1. Market Snapshot
7.2. Global In-car apps Market by Vehicle Type, Performance – Potential Analysis
7.3. Global In-car apps Market Estimates & Forecasts by Vehicle Type 2019-2029 (USD Billion)
7.4. In-car apps Market, Sub Segment Analysis
7.4.1. Passenger car
7.4.2. LCV
7.4.3. HCV
Chapter 8. Global In-car apps Market, by Software Layer
8.1. Market Snapshot
8.2. Global In-car apps Market by Software Layer, Performance – Potential Analysis
8.3. Global In-car apps Market Estimates & Forecasts by Software Layer 2019-2029 (USD Billion)
8.4. In-car apps Market, Sub Segment Analysis
8.4.1. Operating System
8.4.2. Middleware
8.4.3. Application software
Chapter 9. Global In-car apps Market, Regional Analysis
9.1. In-car apps Market, Regional Market Snapshot
9.2. North America In-car apps Market
9.2.1. U.S. In-car apps Market Application breakdown estimates & forecasts, 2019-2029 Vehicle Type breakdown estimates & forecasts, 2019-2029 Software Layer breakdown estimates & forecasts, 2019-2029
9.2.2. Canada In-car apps Market
9.3. Europe In-car apps Market Snapshot
9.3.1. U.K. In-car apps Market
9.3.2. Germany In-car apps Market
9.3.3. France In-car apps Market
9.3.4. Spain In-car apps Market
9.3.5. Italy In-car apps Market
9.3.6. Rest of Europe In-car apps Market
9.4. Asia-Pacific In-car apps Market Snapshot
9.4.1. China In-car apps Market
9.4.2. India In-car apps Market
9.4.3. Japan In-car apps Market
9.4.4. Australia In-car apps Market
9.4.5. South Korea In-car apps Market
9.4.6. Rest of Asia Pacific In-car apps Market
9.5. Latin America In-car apps Market Snapshot
9.5.1. Brazil In-car apps Market
9.5.2. Mexico In-car apps Market
9.5.3. Rest of Latin America In-car apps Market
9.6. Rest of The World In-car apps Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Robert Bosch GmbH Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.2.2. NXP Semiconductors N.V.
10.2.3. Renesas Electronics Corporation
10.2.4. BlackBerry Limited
10.2.5. Nvidia Corporation
10.2.6. Microsoft Corporation
10.2.7. Airbiquity Inc.
10.2.8. Elektrobit Automotive GmbH
10.2.9. Green Hills Software
10.2.10. Wind River Systems
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. 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.
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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:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
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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