Thematic map of the business register (URS). The number of holdings per 10.000 inhabitants is divided by type of operation, the holdings are divided according to the number of employees employed as a percentage of all enterprises (circle and community level) as well as the dependent employees divided according to the number of employees of the Bertieb as a share of all employees in percent (only district level).: enterprises of the manufacturing industry, per 10.000 inhabitants, district level

This dataset represents the entire Industrial PinPointer database of manufacturing companies. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. This dataset covers manufacturing locations in the State of Alabama. Homeland SecurityThis dataset includes the entire Industrial PinPointer database of manufacturing companies, which includes the 2009 D2 of 2 update. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. SIC codes are not provided for 125 companies in the US territories. Where an employee count is available, only locations employing fifteen (15) or more people are included. All text fields were set to upper case, leading and trailing spaces were trimmed from all text fields, and non-printable and diacritic characters were removed from all text fields per NGA's request.Metadata

Displays a representation of where all the surveyed businesses across York Region are located. This data is collected through the Region’s annual comprehensive employment survey and each record contains employment and business contact information about each business with the exception of home and farm-based businesses. Home-based businesses are not included as they are distributed throughout residential communities within the Region and are difficult to survey. Employment data for farm-based businesses are collected through the Census of Agriculture conducted by Statistics Canada, and are not included in the York Region Employment Survey dataset.Update Frequency: Not PlannedDate Created: 17/03/2023Date Modified: 17/03/2023Metadata Date: 17/03/2023Citation Contacts: York Region, Long Range PlanningAttribute DefinitionsBUSINESSID: Unique key to identify a business.NAME: The common business name used in everyday transactions. FULL_ADDRESS: Full street address of the physical address. (This field concatenates the following fields: Street Number, Street Name, Street Type, Street Direction)STREET_NUM: Street number of the physical addressSTREET_NAME: Street name of the physical addressSTREET_TYPE: Street type of the physical addressSTREET_DIR: Street direction of the physical addressUNIT_NUM: Unit number of the physical addressCOMMUNITY: Community name where the business is physically locatedMUNICIPALITY: Municipality where the business is physically locatedPOST_CODE: Postal code corresponding to the physical street addressEMPLOYEE_RANGE: The numerical range of employees working in a given firm. PRIM_NAICS, PRIM_NAICS_DESC: The Primary 5-digit NAIC code defines the main business activity that occurs at that particular physical business location.SEC_NAICS, SEC_NAICS_DESC: If there is more than one business activity occurring at a particular business location (that is substantially different from the primary business activity), then a secondary NAIC is assigned.PRIM_BUS_CLUSTER, SEC_BUS_CLUSTER: A business cluster is defined as a geographic concentration of interconnected businesses and institutions in a common industry that both compete and cooperate. As defined by York Region, this field indicates the primary business cluster that this business belongs to.BUS_ACTIVITY_DESC: This is a comment box with a detailed text description of the business activity.TRAFFIC_ZONE: Specifies the traffic zone in which the business is located. MANUFACTURER: Indicates whether or not the business manufactures at the physical business location. CAN_HEADOFFICE: The business at this location is considered the Canadian head office.HEADOFFICEPROVSTATE: Indicates which state or province the head office is located if the head office is located in Canada (outside of Ontario) or in the United StatesHEADOFFICECOUNTRY: Indicates which country the head office is locatedYR_CURRENTLOC: Indicates the year that the business moved into its current address.MAIL_FULL_ADDRESS: The mailing address is the address through which a business receives postal service. This may or may not be the same as the physical street address.MAIL_STREET_NUM, MAIL_STREET_NAME, MAIL_STREET_TYPE, MAIL_STREET_DIR, MAIL_UNIT_NUM, MAIL_COMMUNITY, MAIL_MUNICIPALITY, MAIL_PROVINCE, MAIL_COUNTRY, MAIL_POST_CODE, MAIL_POBOX: Mailing address fields are similar to street address fields and in most cases will be the same as the Street Address. Some examples where the two addresses might not be the same include, multiple location businesses, home-based businesses, or when a business receives mail through a P.O. Box.WEBSITE: The General/Main business website.GEN_BUS_EMAIL: The general/main business e-mail address for that location.PHONE_NO: The general/main phone number for the business location.PHONE_EXT: The extension (if any) for the general/main business phone number.LAST_SURVEYED: The date the record was last surveyedLAST_UPDATED: The date the record was last updatedUPDATEMETHOD: Displays how the business was last updated, based on a predetermined list.X_COORD, Y_COORD: The x,y coordinates of the surveyed business locationFrequently Asked Questions How many businesses are included in the 2022 York Region Business Directory? The 2022 York Region Business Directory contains just over 34,000 business listings. In the past, businesses were annually surveyed, either in person or by telephone to improve the accuracy of the directory. Due to the COVID-19 Pandemic, a survey was not complete in 2020 and 2021. The Region may return to annual surveying in future years, however the next employment survey will be in 2024. This listing also includes home-based businesses that participated in the 2022 employment survey. What is a NAIC code? The North American Industrial Classification (NAIC) coding system is a hierarchical classification system developed in Canada, Mexico and the United States. It was developed to allow for the comparison of business and employment information across a variety of industry categories. The NAICS has a hierarchical structure, designed as follows: Two-digits = sector (e.g., 31-33 contain the Manufacturing sectors) Three-digits = subsector (e.g., 336 = Transportation Equipment Manufacturing) Four-digits = industry group (e.g., 3361 = Motor Vehicle Manufacturing) Five-digits = industry (e.g., 33611 = Automobile and Light Duty Motor Vehicle Manufacturing) For more information on the NAIC coding system click here How do I add or update my business information in the York Region Business Directory? To add or update your business information, please select one of the following methods: • Email: Please email businessdirectory@york.ca to request to be added to the Business Directory. • Online: Go to www.york.ca/employmentsurvey and participate in the employment survey - note, this will only be active in 2024 when the Region performs its next employment survey There is no charge for obtaining a basic listing of your business in the York Region Business Directory. How up-to-date is the information? This directory is based on the 2022 York Region Employment Survey, a survey of businesses which attempts to gather information from all businesses across York Region. In instances where we were unable to gather information, the most recent data was used. Farm-based businesses have not been included in the survey and home-based businesses that participated in the 2022 survey are included in the dataset. The date that the business listing was last updated is located in the LastUpdate column in the attached spreadsheet. Are different versions of the York Region Business Directory available? Yes, the directory is available in two online formats: • An interactive, map-based directory searchable by company name, street address, municipality and industry sector. • The entire dataset in downloadable Microsoft Excel format via York Region's Open Data Portal. This version of the York Region Business Directory 2022 is offered free of charge. The Directory allows for the detailed analysis of business and employment trends, as well as the construction of targeted contact lists. To view the map-based directory and dataset, go to: 2022 Business Directory - Map Is there any analysis of business and employment trends in York Region? Yes. The "2022 Employment and Industry Report" contains information on employment trends in York Region and is based on results from the employment survey. please visit www.york.ca/york-region/plans-reports-and-strategies/employment-and-industry-report to view the report. What other resources are available for York Region businesses? York Region offers an export advisory service and a number of other business development programs and seminars for interested individuals. For details, consult the York Region Economic Strategy Branch. Who do I contact to obtain more information about the Directory? For more information on the York Region Business Directory, contact the Planning and Economic Development Branch at: businessdirectory@york.ca.

This dataset includes the entire Industrial PinPointer database of manufacturing companies, which includes the 2009 D2 of 2 update. Eighteen (18) states have been updated in this delivery: Alaska, Arizona, Hawaii, Idaho, Massachusetts, Missouri, Nevada, New Hampshire, New York, Ohio, Oklahoma, Oregon, South Carolina, South Dakota, Tennessee, Utah, Wisconsin, and Wyoming. In addition to American Samoa, Guam, and the Commonwealth of the Northern Mariana Islands, two (2) US territories have been added to the dataset from the 2009 D1 of 2 update: Puerto Rico, and US Virgin Islands. This totals 48,930 companies. The database decreased by 65 companies from the 2009 D1 of 2 update. This dataset covers manufacturing locations in the 50 states, the District of Columbia, and US territories. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. SIC codes are not provided for 125 companies in the US territories. Where an employee count is available, only locations employing fifteen (15) or more people are included. Employee count is not available for the US territories; therefore, all locations primarily engaged in manufacturing are included for these territories. All text fields were set to upper case, leading and trailing spaces were trimmed from all text fields, and non-printable and diacritic characters were removed from all text fields per NGA's request.

This map is a visualization of the MAA projects on the Department of Economic and Community Development - Business Assistance Portfolio dataset. This map is updated in accordance with with the schedule of that dataset.

Thematic map on the business register (URS). Einwohner unterteilt nach Betriebsart, die Betriebe unterteilt nach der Anzahl der abhängig Beschäftigten

This provides information on the registration status of manufacturing companies in Paju-si, Gyeonggi-do, including business name, location map address, location number address, latitude, longitude, industry name (offset printing, wood furniture manufacturing, concrete product manufacturing, sanitary paper product manufacturing, etc.), and first registration date.

The "Taiwan Industrial Land Supply and Demand Service Network" mainly provides industrial areas nationwide, including industrial parks completed by the Industrial Development Bureau, industrial areas developed by central ministries (such as science parks, biotechnology parks, agricultural biotechnology parks, environmental protection parks, and processing and export zones), as well as industrial areas developed by local governments and the private sector. The network establishes an industrial land database, designs a multifunctional information platform, actively promotes it to business owners, and provides high-quality, convenient, and innovative industrial land supply information services. To provide the public and relevant authorities with a channel to understand the relevant data on the manufacturing industry's establishment areas in industrial areas under the jurisdiction of the ministry, the Industrial Development Bureau has specially set up the "Taiwan Industrial Zone Map" dataset. This provides the public with complete information for easy access, facilitates various forms of information dissemination, enhances the transparency of industrial land information, and further assists in the promotion of relevant policies. Therefore, in line with the government's promotion of open data measures, the Industrial Development Bureau of the Ministry of Economic Affairs has opened the Taiwan Industrial Zone Map (http://idbpark.moeaidb.gov.tw/Policy/Show?id49) for download, classified by designated industrial areas, processing and export zones, and science parks. Everyone is welcome to make full use of it.

The China Location-Based Services Market report segments the industry into By Component (Hadware, Software, Services), By Location (Indoor, Outdoor), By Application (Mapping and Navigation, Business Intelligence and Analytics, Location-based Advertising, Social Networking and Entertainment, Others), and By End User (Transportation and Logistics, IT and Telecom, Healthcare, Government, BFSI, Hospitality, Manufacturing, Others).

Abstract

The survey data accompanies the working paper, "Mapping the Landscape of Transactions the Governance of Business Relations in Latin America”. This paper provides a picture of the landscape of transactions and one of the central motivations for this analysis is to ascertain whether there are meaningful patterns that emerge from datasets on how firms make agreements with their suppliers and customers.

A new set of survey questions is used to map governance structures that firms employ to support the successful implementation of transactions. Without imposing any a priori model, latent class analysis (LCA) discovers meaningful patterns of governance structures that readily match constructs in the literature. All governance structures use bilateralism. Bilateralism and formal institutions are sometimes complemented but never substitutes. For each firm, LCA provides estimates of the posterior probability that the firm uses each of the discovered governance structures.

These estimates can be used by researchers to go further, testing their own hypotheses relevant to Williamson’s discriminating alignment agenda using additional data from the Enterprise Surveys or elsewhere. Variations in the effectiveness of different governance structures across countries and across different types of firms and transactions are explored. Regional variation within countries is greater than cross-country variation. Foreign-owned firms, exporters, larger firms, and better-managed ones are more likely to use governance structures that complement bilateralism with use of the legal system or with the help of paid third-parties.

The responses were used to a unique set of questions posed in 2017 and 2018 as part of the ES implemented in six Latin American countries: Argentina, Bolivia, Ecuador, Paraguay, Peru, and Uruguay. The surveys are based on interviews with business owners and top managers in a sample of officially registered firms with at least five employees in the manufacturing and services sectors. The surveys are designed to be nationally representative, using a stratified survey design.

Geographic coverage

The surveys are designed to be nationally representative (implemented in Argentina, Bolivia, Ecuador, Paraguay, Peru, and Uruguay).

Analysis unit

The primary sampling unit of the study is the establishment.

Universe

The surveys are based on interviews with business owners and top managers in a sample of officially registered firms with at least five employees in the manufacturing and services sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling methodology of the World Bank’s Enterprise Survey generates sample sizes appropriate to achieve two main objectives: first, to benchmark the investment climate of individual economies across the world and, second, to conduct firm performance analyses focusing mainly on how investment climate constraints affect productivity and job creation in selected sectors.

To achieve both objectives the sampling methodology:

• Generates a sample representative of the whole non-agricultural private economy that substantiates assertions about this part of the economy, not only about the manufacturing sector. The overall sample should include, in addition to selected manufacturing industries, services industries and other relevant sectors of the economy; and

• Generates large enough sample sizes for selected industries to conduct statistically robust analyses with levels of precision at a minimum 7.5% precision for 90% confidence intervals about:

i. Estimates of population proportions (percentages), at the industry level; and

ii. Estimates of the mean of log of sales at the industry level.

STRATIFICATION

The population of industries to be included in the Enterprise Surveys and Indicator Surveys, the Universe of the study, includes the following list (according to ISIC, revision 3.1): all manufacturing sectors (group D), construction (group F), services (groups G and H), transport, storage, and communications (group I), and subsector 72 (from Group K). Also, to limit the surveys to the formal economy the sample frame for each country should include only establishments with five (5) or more employees. Fully government owned firms are excluded as the Universe is defined as the non-agricultural private sector.

SAMPLE SIZE

Overall sample sizes for both Enterprise Surveys and Indicator Surveys are determined by the degree of stratification of the sample. The overall sample size depends on the decision of the sample size for each level of stratification. In all ES and IS the objectives of stratification are to allow an acceptable level of precision for estimates, at, first, different first, within size levels (small, medium, and large), second, at the different levels of regional stratification, and third, for the different sectors of stratification (which, as explained before, are chosen depending on the size of the economy).

Given that both the Enterprise Survey and the Indicator Survey include more than 100 indicators the computation of the minimum sample size required is complicated since it depends on the variance of each indicator. However, many of the indicators computed from the survey are proportions, such as percentage of firms that engage in X activity or chose Y action. In this case the computation of the sample size is simplified by the fact that the variance of a proportion is bounded. Assuming the maximum variance (0.5) the minimum level of precision is guaranteed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

As part of the implementation of the surveys, twelve newly designed questions were administered, six concerning interactions with the firms’ suppliers and six on customer interactions. These questions were on the effectiveness of various methods of preventing or resolving problems when implementing agreements. When designing questions to be administered in a long survey and addressed to firms of all types, in different institutional settings, both conceptual and practical issues immediately arise.

Cleaning operations

The model parameters that authors use to estimate posterior probabilities are obtained from the software Latent GOLD (Vermunt and Magidson 2016), which does not provide exact parameters and applies some rounding (See the Excel file with estimated model parameters, attached as Related Material). As a result, the estimates of posterior probabilities calculated from the estimated model parameters differ somewhat from the estimates that are obtained directly from the Latent GOLD output.

Response rate

Non-response rates due to respondents spontaneously answering “Don’t Know” (which was not displayed as a possible option in the ‘show card’ listing possible responses). Fewer than 3% of the respondents chose at least one “Don’t Know” across the six questions about the methods of governing relations with suppliers and customers. The question with the most frequent occurrence of “Don’t Know” on relations with suppliers is on paid private dispute resolution (1.4% of the sample); for relations with customers, the question about personal trust had the highest item non-response (1.2% of the sample). Given the low item non-response rates, in our application of LCA we drop observations that have at least one “Don’t Know” in the relevant series of questions. This leaves 3,350 observations on relations with suppliers (97.7% of the sample), and 3,339 observations on relations with customers (97.3% of the sample).

Credit report of Burn Manufacturing Usa Llc Ke New Horizon Business Park Go Downs 1 8 contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

The global data visualization market, valued at $9.84 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various industries necessitates effective visualization tools for insightful analysis and decision-making. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, driving market growth. Advances in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly with data visualization platforms, enhancing automation and predictive capabilities, further stimulating market demand. The BFSI (Banking, Financial Services, and Insurance) sector, along with IT and Telecommunications, are major adopters, leveraging data visualization for risk management, fraud detection, customer relationship management, and network optimization. However, challenges remain, including the need for skilled professionals to effectively utilize these tools and concerns regarding data security and privacy. The market segmentation reveals a strong presence of executive management and marketing departments across organizations, highlighting the strategic importance of data visualization in business operations. The market's competitive landscape is characterized by established players like SAS Institute, IBM, Microsoft, and Salesforce (Tableau), along with emerging innovative companies. This competition fosters innovation and drives down costs, making data visualization solutions more accessible to a broader range of businesses and organizations. Regional variations in market penetration are expected, with North America and Europe currently holding significant shares, but Asia Pacific is poised for substantial growth, driven by rapid digitalization and technological advancements in the region. The on-premise deployment mode still holds a considerable market share, though the cloud/on-demand segment is experiencing faster growth due to its inherent advantages. The ongoing trend towards self-service business intelligence (BI) tools is empowering end-users to access and analyze data independently, increasing the overall market demand for user-friendly and intuitive data visualization platforms. Future growth will depend on continued technological advancements, expanding applications across diverse industries, and addressing the existing challenges related to data skills gaps and security concerns. This report provides a comprehensive analysis of the Data Visualization Market, projecting robust growth from $XX Billion in 2025 to $YY Billion by 2033. It covers the period from 2019 to 2033, with a focus on the forecast period 2025-2033 and a base year of 2025. This in-depth study examines key market segments, competitive landscapes, and emerging trends influencing this rapidly evolving industry. The report is designed for executives, investors, and market analysts seeking actionable insights into the future of data visualization. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Lack of Tech Savvy and Skilled Workforce/Inability. Notable trends are: Retail Segment to Witness Significant Growth.

Medical technology: locations of manufacturing companies, dealers and service providers. Map type: Symbols. Spatial extent: Switzerland. Time: 2021

Asia Pacific Digital Maps Market size was valued at USD 19.2 Billion in 2024 and is projected to reach USD 67.8 Billion by 2032, growing at a CAGR of 14.1% from 2026 to 2032.

Asia Pacific Digital Maps Market Overview

In recent years, geospatial information has experienced growth due to its broad range of applications in various sectors and businesses such as risk and emergency management, marketing, urban planning, infrastructure management, resource management (oil, gas, mining), and business planning, logistics, and many others. In the Asia Pacific region, geospatial technologies are utilized for rural and agricultural development. In this region, companies are involved in engineering and construction, mining and manufacturing, insurance, and agriculture.

A printable map of the Technology Zones in the City of Newport News, Virginia. Virginia Technology Zones encourage the development of commercial and industrial businesses engaged in technological research, design and manufacturing. For more information, visit the city's website.

This feature service provides the current Priority Production Areas (PPAs) for the San Francisco Bay Region. PPAs identify clusters of industrial businesses and prioritize them for economic development investments and protection from competing land uses. These districts are already well-served by the region’s goods movement network.Typical businesses in PPAs include manufacturing, distribution, warehousing and supply chains.Jobs in PPAs enable the industrial sector to thrive and grow. They also improve the lives of workers by making the basic costs of living more affordable. Many middle-wage PPA jobs do not require four-year college degrees, and they are close to more-affordable housing.PPAs are nominated by local governments and adopted by the Association of Bay Area Governments. PPAs must be:Zoned for industrial use or have predominantly industrial usesOutside Priority Development Areas and other areas within walking distance of a major rail commute hub (such as BART, Caltrain, Amtrak or SMART)Located in jurisdictions with a certified housing element

The high-precision mapping market for self-driving cars is experiencing explosive growth, projected to reach $2122 million in 2025 and exhibiting a remarkable Compound Annual Growth Rate (CAGR) of 34.3%. This expansion is fueled by the burgeoning autonomous vehicle industry's increasing reliance on highly accurate map data for safe and efficient navigation. Key drivers include advancements in sensor technology (LiDAR, radar, cameras), the rising demand for advanced driver-assistance systems (ADAS), and the ongoing development of Level 4 and 5 autonomous vehicles. The market is segmented by application (passenger and commercial vehicles) and map type (embedded and cloud-based). Embedded systems offer real-time processing but require significant onboard storage, while cloud-based solutions leverage remote servers for processing and updating, optimizing cost and storage. The competitive landscape is fiercely contested, with major players such as NVIDIA, TomTom, Baidu, and Mobileye vying for market share, alongside several emerging technology companies specializing in HD map creation and maintenance. Geographic distribution reflects the concentration of automotive manufacturing and technological advancement, with North America and Asia-Pacific anticipated to dominate market share, driven by strong government support and technological innovation in these regions. Continued growth in the high-precision mapping market for self-driving cars hinges on several factors. The successful deployment of autonomous vehicles on a large scale is intrinsically linked to the accuracy and reliability of underlying map data. Overcoming challenges such as data acquisition costs, map updates in dynamic environments, and ensuring data security are crucial for sustained market expansion. Furthermore, regulatory frameworks and standardization efforts are pivotal for facilitating widespread adoption. The development of robust and scalable solutions capable of handling massive datasets and ensuring seamless integration with autonomous driving systems will be key differentiators for market players. The market is expected to see further consolidation as companies seek strategic partnerships to leverage expertise and expand their geographic reach. Expansion into developing markets will also contribute to the overall market expansion.

Credit report of Khatraco Manufacturing Business Corporation contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

The global market size of Mobile Phone Map is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Mobile Phone Map Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Mobile Phone Map industry. The key insights of the report:
1.The report provides key statistics on the market status of the Mobile Phone Map manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Mobile Phone Map industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Mobile Phone Map Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Mobile Phone Map as well as some small players. At least 7 companies are included:
* Here
* TomTom
* Google
* Alibaba?AutoNavi?
* Navinfo
* mobileye
For complete companies list, please ask for sample pages.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Mobile Phone Map market
* Ordinary Map
* HD Map
For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Route Query
* Navigation
* Positioning

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
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* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.