LinkedIn companies use datasets to access public company data for machine learning, ecosystem mapping, and strategic decisions. Popular use cases include competitive analysis, CRM enrichment, and lead generation.

Use our LinkedIn Companies Information dataset to access comprehensive data on companies worldwide, including business size, industry, employee profiles, and corporate activity. This dataset provides key company insights, organizational structure, and competitive landscape, tailored for market researchers, HR professionals, business analysts, and recruiters.

Leverage the LinkedIn Companies dataset to track company growth, analyze industry trends, and refine your recruitment strategies. By understanding company dynamics and employee movements, you can optimize sourcing efforts, enhance business development opportunities, and gain a strategic edge in your market. Stay informed and make data-backed decisions with this essential resource for understanding global company ecosystems.

Dataset Features

• timestamp: Represents the date and time when the company data was collected.
• id: Unique identifier for each company in the dataset.
• company_id: Identifier linking the company to an external database or internal system.
• url: Website or URL for more information about the company.
• name: The name of the company.
• about: Brief description of the company.
• description: More detailed information about the company's operations and offerings.
• organization_type: Type of the organization (e.g., private, public).
• industries: List of industries the company operates in.
• followers: Number of followers on the company's platform.
• headquarters: Location of the company's headquarters.
• country_code: Code for the country where the company is located.
• country_codes_array: List of country codes associated with the company (may represent various locations or markets).
• locations: Locations where the company operates.
• get_directions_url: URL to get directions to the company's location(s).
• formatted_locations: Human-readable format of the company's locations.
• website: The official website of the company.
• website_simplified: A simplified version of the company's website URL.
• company_size: Number of employees or company size.
• employees_in_linkedin: Number of employees listed on LinkedIn.
• employees: URL of employees.
• specialties: List of the company’s specializations or services.
• updates: Recent updates or news related to the company.
• crunchbase_url: Link to the company’s profile on Crunchbase.
• founded: Year when the company was founded.
• funding: Information on funding rounds or financial data.
• investors: Investors who have funded the company.
• alumni: Notable alumni from the company.
• alumni_information: Details about the alumni, their roles, or achievements.
• stock_info: Stock market information for publicly traded companies.
• affiliated: Companies or organizations affiliated with the company.
• image: Image representing the company.
• logo: URL of the official logo of the company.
• slogan: Company’s slogan or tagline.
• similar: URL of companies similar to this one.

Distribution

• Data Volume: 56.51M rows and 35 columns.
• Structure: Tabular format (CSV, Excel).

Usage

This dataset is ideal for:
- Market Research: Identifying key trends and patterns across different industries and geographies.
- Business Development: Analyzing potential partners, competitors, or customers.
- Investment Analysis: Assessing investment potential based on company size, funding, and industries.
- Recruitment & Talent Analytics: Understanding the workforce size and specialties of various companies.

Coverage

• Geographic Coverage: Global, with company locations and headquarters spanning multiple countries.
• Time Range: Data likely covers both current and historical information about companies.
• Demographics: Focuses on company attributes rather than demographics, but may contain information about the company's workforce.

License

CUSTOM

Please review the respective licenses below:

1. Data Provider's License
   • Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: For building models, conducting research, or enhancing machine learning algorithms with business data.
• Researchers: For academic analysis in fields like economics, business, or technology.
• Businesses: For analysis, competitive benchmarking, and strategic development.
• Investors: For identifying and evaluating potential investment opportunities.

Dataset Name Ideas

• Global Company Profile Database
• **Business Intellige

Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

Product contains one data file (.txt format) for each year from 1997-2023 containing 11-15 million records per year. Records provide information about business location (including address, census block, census tract & lat/long coordinates), number of employees, sales volume, NAICS & SIC codes, unique identifier across time for businesses and parent entities.

Xverum’s Point of Interest (POI) Data is a comprehensive dataset containing 230M+ verified locations across 5000 business categories. Our dataset delivers structured geographic data, business attributes, location intelligence, and mapping insights, making it an essential tool for GIS applications, market research, urban planning, and competitive analysis.

With regular updates and continuous POI discovery, Xverum ensures accurate, up-to-date information on businesses, landmarks, retail stores, and more. Delivered in bulk to S3 Bucket and cloud storage, our dataset integrates seamlessly into mapping, geographic information systems, and analytics platforms.

🔥 Key Features:

Extensive POI Coverage: ✅ 230M+ Points of Interest worldwide, covering 5000 business categories. ✅ Includes retail stores, restaurants, corporate offices, landmarks, and service providers.

Geographic & Location Intelligence Data: ✅ Latitude & longitude coordinates for mapping and navigation applications. ✅ Geographic classification, including country, state, city, and postal code. ✅ Business status tracking – Open, temporarily closed, or permanently closed.

Continuous Discovery & Regular Updates: ✅ New POIs continuously added through discovery processes. ✅ Regular updates ensure data accuracy, reflecting new openings and closures.

Rich Business Insights: ✅ Detailed business attributes, including company name, category, and subcategories. ✅ Contact details, including phone number and website (if available). ✅ Consumer review insights, including rating distribution and total number of reviews (additional feature). ✅ Operating hours where available.

Ideal for Mapping & Location Analytics: ✅ Supports geospatial analysis & GIS applications. ✅ Enhances mapping & navigation solutions with structured POI data. ✅ Provides location intelligence for site selection & business expansion strategies.

Bulk Data Delivery (NO API): ✅ Delivered in bulk via S3 Bucket or cloud storage. ✅ Available in structured format (.json) for seamless integration.

🏆Primary Use Cases:

Mapping & Geographic Analysis: 🔹 Power GIS platforms & navigation systems with precise POI data. 🔹 Enhance digital maps with accurate business locations & categories.

Retail Expansion & Market Research: 🔹 Identify key business locations & competitors for market analysis. 🔹 Assess brand presence across different industries & geographies.

Business Intelligence & Competitive Analysis: 🔹 Benchmark competitor locations & regional business density. 🔹 Analyze market trends through POI growth & closure tracking.

Smart City & Urban Planning: 🔹 Support public infrastructure projects with accurate POI data. 🔹 Improve accessibility & zoning decisions for government & businesses.

💡 Why Choose Xverum’s POI Data?

• 230M+ Verified POI Records – One of the largest & most detailed location datasets available.
• Global Coverage – POI data from 249+ countries, covering all major business sectors.
• Regular Updates – Ensuring accurate tracking of business openings & closures.
• Comprehensive Geographic & Business Data – Coordinates, addresses, categories, and more.
• Bulk Dataset Delivery – S3 Bucket & cloud storage delivery for full dataset access.
• 100% Compliant – Ethically sourced, privacy-compliant data.

Access Xverum’s 230M+ POI dataset for mapping, geographic analysis, and location intelligence. Request a free sample or contact us to customize your dataset today!

The Location Analytics Market size was valued at USD 18.30 USD Billion in 2023 and is projected to reach USD 48.68 USD Billion by 2032, exhibiting a CAGR of 15.0 % during the forecast period. The increasing adoption of location-based services (LBS) in various industries, the growing need for real-time data and insights, and the advancements in location-based technologies are driving the growth of the market. Location analytics is the practice of adding a layer of geographical data to a business’s data assets in order to extract more valuable insights. Across industries, business data, including data on people, events, transactions, assets, and more, often includes a geographic component, which when added to an analysis of performance may unlock new related insights. This allows for greater context when asking questions about different business processes, offering a new understanding of trends and relationships in the data. Location analytics provides everyone in an organization with spatial analytics and other analytics capabilities to understand the data through a location-specific perspective and make predictions and optimize business practices accordingly. Adding location to an organization’s analytics allows for greater context in decision making and drives greater insights that may not have been uncovered using traditional, flat business intelligence (BI) data. Recent developments include: January 2024 - ANYbotics and Cognite collaborated to provide integrated robotic inspection solutions. The solutions automate real-time data collection to facilitate location, analysis, and reporting and improve digital twin., November 2023 - Gravy Analytics, an enterprise location intelligence company, and Unacast, a location analytics and data company, announced a definitive merger agreement to create one of the largest and most comprehensive location analytics platforms in the industry. The merger would expand location intelligence for customers in the retail, telecommunications, real estate, and financial services., March 2023 - BetterMile, a company supplying smart spatial software for parcel delivery, announced an extended partnership with HERE Technologies to enhance its service. Drivers around the globe using BetterMile can now access complete location information and geocoding from HERE, customized for fleet delivery on their devices., September 2022 - TomTom introduced GO Navigation’s truck plan, which is curated to meet the needs of professional truck drivers. This allows drivers to plan their routes according to maximum speeds, vehicle dimensions, fuel needs, and cargo as well as GO Navigation's premium navigation features and abilities., July 2021 - INRIX, Inc., a leader in mobile analytic technology, unveiled a powerful new cloud LBS application called INRIX IQ, which provides retailers, investors, and other business people with information to open new stores, raise revenue, and achieve optimum returns on their investments.. Key drivers for this market are: Increasing Adoption of Location-based Applications among Several Industries to Favor Market Growth. Potential restraints include: Concerns Associated with Geo Privacy and Confidential Data to Limit Market Growth. Notable trends are: Artificial Intelligence (AI) and Machine Learning (ML) based Analytics Solutions to Propel Market .

ZIP Code business counts data for Maptitude mapping software are from Caliper Corporation and contain aggregated ZIP Code Business Patterns (ZBP) data and Rural-Urban Commuting Area (RUCA) data.

SafeGraph Places provides baseline location information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. B2B marketing dataset can be used to ingest a list of companies and information such as phone number for lead generation. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation.

According to a December 2020 survey of U.S. adults, only ten percent of respondents felt very comfortable with tech companies sharing their location data, including where they had traveled, with the government so that the government could better track Americans' locations. A total of 47 percent of respondents felt very uncomfortable with this idea.

Location Intelligence Market size was valued at USD 18.5 Billion in 2023 and is projected to reach USD 63.15 Billion by 2030, growing at a CAGR of 15.63% during the forecasted period 2024 to 2030.Global Location Intelligence Market DriversThe growth and development of the Location Intelligence Market drivers. These factors have a big impact on how Location Intelligence are demanded and adopted in different sectors. Several of the major market forces are as follows:Proliferation of Spatial Data: A rich source of data for location intelligence and analytics is made possible by the exponential increase of spatial data produced by sources including GPS-enabled devices, Internet of Things sensors, and geographic information systems (GIS). In order to extract meaningful insights, there is a growing need for sophisticated tools and technologies due to the volume and diversity of spatial data.Location-Based Services (LBS) are Growing: The demand for location intelligence and analytics solutions is fueled by the widespread use of location-based services including ride-sharing services, navigation apps, and location-based marketing. Companies use location data to target services based on local context, optimize operations, and improve customer experiences.Need for Real-time information: To make wise judgments swiftly in the hectic business world of today, businesses need to have real-time access to location-based information. Businesses may increase agility and responsiveness by using location intelligence and analytics solutions to monitor events, identify patterns, and react to changes in real-time.The amalgamation of location: intelligence and analytics with nascent technologies such as artificial intelligence (AI) and the Internet of Things (IoT) amplifies their potential and value proposition. Through the integration of sensor data, AI algorithms, and location data, enterprises may gain more profound understanding, anticipate future patterns, and streamline their decision-making procedures.Urbanization and Smart City Initiatives: The use of location intelligence and analytics solutions is fueled by the global trend toward urbanization and the growth of smart city initiatives. These technologies help municipalities, urban planners, and government agencies create sustainable and effective urban environments by optimizing infrastructure development, city planning, and service delivery.Cross-Industry Applications: Location analytics and intelligence are useful in a variety of industries, such as banking, logistics, healthcare, and retail. Businesses use location-based data to increase risk management, streamline supply chains, target customers more effectively, and increase operational efficiency across a range of company operations.Regulatory Compliance and Risk Management: The use of location intelligence and analytics solutions for regulatory compliance and risk management is influenced by compliance requirements relating to location-based data, such as privacy laws and geospatial standards. These products are purchased by organizations to guarantee data governance, reduce risks, and prove compliance with legal and regulatory obligations.The need for location-based: marketing is growing as companies use location analytics and intelligence to create more focused advertising and marketing campaigns. Organizations may increase customer engagement and conversion rates by providing tailored offers, promotions, and content depending on the geographic context of their customers by evaluating location data and consumer activity patterns.Emergence of Digital Twin Technology: This technology opens up new possibilities for location intelligence and analytics by building virtual versions of real assets or environments. Organizations can improve decision-making processes in a variety of fields, such as manufacturing, infrastructure management, and urban planning, by incorporating location data into digital twin models and simulating scenarios.

Location Intelligence Analytics Market Outlook

The global location intelligence analytics market size is projected to grow from USD 14.2 billion in 2023 to USD 31.7 billion by 2032, exhibiting a CAGR of approximately 9.4% during the forecast period. This robust growth is primarily driven by the increasing demand for spatial data and analytical tools across various industries to enhance decision-making processes and optimize business operations. As organizations increasingly recognize the value of location-based insights, they are investing in sophisticated analytics solutions that leverage geographic data to drive business outcomes and gain competitive advantages.

One of the primary growth factors for the location intelligence analytics market is the proliferation of IoT devices and the consequent surge in location-based data generation. With billions of connected devices expected to be operational in the coming years, the volume of location-specific data is set to explode. Businesses across industries are eager to harness this data to gain insights into consumer behavior, improve operational efficiency, and develop targeted marketing strategies. Moreover, advancements in AI and machine learning are enabling more sophisticated analysis of location data, providing deeper insights and predictive capabilities that are invaluable to enterprises.

Another significant driver for market growth is the growing adoption of smart city initiatives across the globe. Governments and municipalities are increasingly implementing location intelligence solutions to enhance urban planning, traffic management, and public safety. By leveraging location-based analytics, cities can optimize resource allocation, improve citizen services, and drive sustainable development. Furthermore, the integration of real-time data from various sources, such as sensors and social media, with geographic information systems (GIS) is facilitating more dynamic and responsive urban management systems, thus propelling the demand for location intelligence analytics.

The increasing emphasis on business intelligence and data-driven decision-making is also fueling the demand for location intelligence analytics. In today's competitive landscape, organizations are seeking to leverage every bit of data to gain actionable insights and stay ahead. Location intelligence provides a unique perspective by overlaying geographic data on traditional business data, offering a holistic view of trends and patterns. This capability is particularly valuable in sectors such as retail, transportation, and logistics, where location-based insights can directly impact revenue generation, cost savings, and customer satisfaction.

Regionally, North America is expected to hold the largest share of the location intelligence analytics market, driven by the presence of major technology companies and the rapid adoption of advanced analytics solutions across industries. The region's commitment to innovation and technological advancement is further supported by substantial investments in R&D activities. Additionally, Europe is anticipated to witness significant growth, influenced by stringent regulatory frameworks and a heightened focus on data privacy and security. In contrast, the Asia Pacific region is projected to demonstrate the highest growth rate, attributed to the rapid digital transformation and increasing investments in smart city projects across emerging economies like India and China.

Component Analysis

The location intelligence analytics market is broadly segmented into software and services. Software solutions are a critical component of this market, offering the necessary tools and platforms for collecting, analyzing, and visualizing geographic data. These software solutions are designed to process large volumes of spatial data, integrate various data sources, and provide users with intuitive and interactive interfaces for data exploration. The advancements in cloud computing and the increasing adoption of Software as a Service (SaaS) models are further driving the demand for location intelligence software, as they offer greater scalability, flexibility, and cost-effectiveness to organizations of all sizes.

Within the software segment, Geographic Information System (GIS) solutions are particularly prominent. GIS technology enables the mapping and analysis of spatial data, allowing users to visualize relationships, patterns, and trends in complex datasets. The ability to integrate GIS with other enterprise systems, such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP), enhances its ut

Veridion's Location Intelligence Data Suite provides a comprehensive view of where and how businesses operate globally. It delivers granular, structured intelligence across more than 130 million active business entities in 249+ countries and territories. This extensive global coverage includes emerging markets and regions where data from other vendors may be limited. Veridion's data universe covers all companies with a digital footprint.

The Location Intelligence data identifies and maps all operational locations linked to a business, regardless of its legal entity structure. This includes differentiating between the Headquarters (HQ) and all secondary physical locations. Beyond HQs and standard branches, it covers a wide range of specific facility types, including manned and unmanned operational locations. These facilities can be classified into 100+ categories, such as office, factory, warehouse, or retail outlet.

The data also covers subsidiaries and field offices. Veridion is capable of identifying facility types mapped to companies through its granular taxonomy of business activities. Examples of identified facility types include those in energy and utilities (power plants, renewable energy installations, oil and gas facilities), manufacturing hubs, tech centers, supply chain nodes, and specialized facilities like data centers. The classification of facility types is provided across multiple levels of detail, currently supporting Level 1 (L1) in production. Planned enhancements for 2025 include expanding the taxonomy to include Level 2 (L2) with more than 100 unique values and Level 3 (L3) classifications for more precise categorization.

For each location, Veridion provides detailed attributes: - Full Address: Including Country, Region, City, Postcode, Street, and Street Number. - Geo-coordinates: Precise Latitude and Longitude. - Location Type: Classification into 100+ categories. - Operating Metrics: Includes estimated Employee counts and Revenue at the location level. - Business Descriptions & Activity Tags: Descriptions of what is happening at each specific site, including key operations and detailed activity tags. - Operational Status: Tracking whether a location is active or inactive. - Industry Classifications: Location-specific NAICS, SIC, ISIC, and proprietary classifications.

Veridion's location data is built from first-party disclosed information from public web sources such as company websites, social media, press releases, regulatory filings, geolocation services, and media reports. Advanced AI and Natural Language Processing (NLP) technologies are used to extract and structure this information. Proprietary AI models and custom infrastructure process billions of data points. Data triangulation and advanced correlation techniques are employed to tie signals to legal and commercial entities and connect entities across different geographies.

A key differentiator is the High-Frequency Updates. Veridion's entire dataset, including location data, is refreshed weekly. This ensures companies consistently have access to the most accurate and reliable information. Weekly updates capture changes in business locations, operations, address types, functions, and operational status with exceptional speed. Ad hoc updates can also be performed based on specific customer requests.

Data Quality and Accuracy are ensured through a robust, multi-faceted methodology. Veridion consolidates data from multiple sources, resolves data conflicts, and infers missing information. Data is cross-referenced against multiple structured company information sources. Each data point is assigned a confidence score, reflecting the number and reliability of sources used. Only data with sufficient certainty in its accuracy is included. AI-driven models actively detect inconsistencies and refine datasets. Reliability scores for location-level data are assigned based on evaluation of multiple sources. Veridion is developing a system to make these reliability scores directly accessible to customers.

Veridion's location data is linked to the company level. Every operational location is linked to its ultimate parent company, delivering a unified and scalable enterprise hierarchy. This enables cross-border visibility and accurate entity resolution. Location data can be appended with additional company data such as revenue, employees, business description, and ESG data. Since data is collected at the individual entity and facility level, it can be aggregated at portfolio levels without compromising granularity.

Veridion's detailed locational data is critical for various use cases, including: - Supply Chain Risk Management: Provides crucial insights into the geographical distribution of suppliers for risk assessment, compliance checks, and strategic planning. It allows mapping the entire supply chain to identify regions with higher risks, such as areas prone to natural disasters or geopolitical issues. P...

Comprehensive dataset of 466 Sports activity locations in India as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Small Business Market Promotion Agency_Commercial Building (Commercial Area) Information Provides data on nationwide commercial establishments in operation. (Business name, industry code, industry name, address, road name address, longitude, latitude, etc.) [Data change notice] 1. Commercial area industry classification: Industry classification based on standard industrial classification 2. Industry classification system: Large classification (10), medium classification (75), small classification (247) 3. Standard industrial classification: 10th - The standard industrial classification may differ from the commercial area industry classification linkage table depending on the refinement of the industry classification. For more information, please check the Small Business 365 notice. https://bigdata.sbiz.or.kr/#/notice/267352041576902656

Academic and demographic information on co-located schools. Data in the Co-Location Report pertains to the 2019-20 school year except for Graduation rates, which pertain to the 2018-19 school year.

According to a December 2020 survey of U.S. adults, 26 percent of respondents with post-graduate education felt very comfortable with tech companies sharing their location data, including where they had traveled, with the government so that the government could better track Americans' locations. However, only seven percent of respondents with a Bachelor's degree felt equally comfortable with this idea.

Locations of corporate headquarters in Los Angeles CountyThis dataset is maintained through the County of Los Angeles Location Management System. The Location Management System is used by the County of Los Angeles GIS Program to maintain a single, comprehensive geographic database of locations countywide. For more information on the Location Management System, visit http://egis3.lacounty.gov/lms/.

Numbers of enterprises and local units produced from a snapshot of the Inter-Departmental Business Register (IDBR) taken on 8 March 2024.

Comprehensive dataset of 5 Sports activity locations in Province of Como, Italy as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Abstract

The study was conducted in Serbia between October 2008 and February 2009 as part of the first round of The Management, Organization and Innovation Survey. Data from 135 manufacturing companies with 50 to 5,000 full-time employees was analyzed.

The survey topics include detailed information about a company and its management practices - production performance indicators, production target, ways employees are promoted/dealt with when underperforming. The study also focuses on organizational matters, innovation, spending on research and development, production outsourcing to other countries, competition, and workforce composition.

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment is defined as a separate production unit, regardless of whether or not it has its own financial statements separate from those of the firm, and whether it has it own management and control over payroll. So the bottling plant of a brewery would be counted as an establishment.

Universe

The survey universe was defined as manufacturing establishments with at least fifty, but less than 5,000, full-time employees.

Kind of data

Sample survey data [ssd]

Sampling procedure

Random sampling was used in the study. For all MOI countries, except Russia, there was a requirement that all regions must be covered and that the percentage of the sample in each region was required to be equal to at least one half of the percentage of the sample frame population in each region.

In most countries the sample frame used was an extract from the Orbis database of Bureau van Dijk, which was provided to the Consultant by the EBRD. The sample frame contained details of company names, location, company size (number of employees), company performance measures and contact details. The sample frame downloaded from Orbis was cleaned by the EBRD through the addition of regional variables, updating addresses and phone numbers of companies.

Examination of the Orbis sample frames showed their geographic distributions to be wide with many locations, a large number of which had only a small number of records. Each establishment was selected with two substitutes that can be used if it proves impossible to conduct an interview at the first establishment. In practice selection was confined to locations with the most records in the sample frame, so the sample frame was filtered to just the cities with the most establishments.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys. For Serbia, the percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 26.7% (82 out of 307 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

Two different versions of the questionnaire were used. Questionnaire A was used when interviewing establishments that are part of multiestablishment firms, while Questionnaire B was used when interviewing single-establishment firms. Questionnaire A incorporates all questions from Questionnaire B, the only difference is in the reference point, which is the so-called national firm in the first part of Questionnaire A and firm in Questionnaire B. Second part of the questionnaire refers to the interviewed establishment only in both Questionnaire A and Questionnaire B. Each variation of the questionnaire is identified by the index variable, a0.

Response rate

Item non-response was addressed by two strategies: - For sensitive questions that may generate negative reactions from the respondent, such as ownership information, enumerators were instructed to collect the refusal to respond as (-8). - Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response.

Survey non-response was addressed by maximising efforts to contact establishments that were initially selected for interviews. Up to 15 attempts (but at least 4 attempts) were made to contact an establishment for interview at different times/days of the week before a replacement establishment (with similar characteristics) was suggested for interview. Survey non-response did occur, but substitutions were made in order to potentially achieve the goals.

Additional information about sampling, response rates and survey implementation can be found in "MOI Survey Report on Methodology and Observations 2009" in "Technical Documents" folder.

Comprehensive dataset of 36 Sports activity locations in Missouri, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.