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1 | 1 | In the last two weeks, did this business use Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 1 | Yes | 5.0% | 0.05% |
1 | 1 | In the last two weeks, did this business use Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 2 | No | 84.2% | 0.08% |
1 | 1 | In the last two weeks, did this business use Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 3 | Do not know | 10.8% | 0.08% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 1 | Machine learning | 1.2% | 0.02% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 2 | Natural language processing | 1.7% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 3 | Virtual agents or chat bots | 1.9% | 0.04% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 4 | Speech/voice recognition using AI | 1.4% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 5 | Recommendation systems based on AI | 0.8% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 6 | Large language models | 1.0% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 7 | Text analytics using AI | 1.5% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 8 | Data analytics using AI | 1.5% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 9 | Neural networks | 0.2% | 0.01% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 10 | Augmented reality | 0.1% | 0.01% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 11 | Decision making systems based on AI | 0.5% | 0.01% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 12 | Deep learning | 0.3% | 0.02% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 13 | Image/pattern recognition | 0.7% | 0.02% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 14 | Machine/computer vision | 0.5% | 0.02% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 15 | Robotics process automation | 0.3% | 0.01% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 16 | Biometrics | 0.3% | 0.02% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 17 | Marketing automation using AI | 2.5% | 0.04% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 18 | Other | 1.4% | 0.03% |
1 | 2 | In the last six months, what types or applications of Artificial Intelligence (AI) did this business use in producing goods or services? | 19 | null | 91.2% | 0.08% |
2 | 3 | In the last six months, did this business use Artificial Intelligence to perform tasks previously done by employees in producing goods or services? | 1 | Yes | 26.6% | 0.38% |
2 | 3 | In the last six months, did this business use Artificial Intelligence to perform tasks previously done by employees in producing goods or services? | 2 | No | 65.2% | 0.46% |
2 | 3 | In the last six months, did this business use Artificial Intelligence to perform tasks previously done by employees in producing goods or services? | 3 | Do not know | 8.1% | 0.23% |
3 | 4 | In the last six months, how many tasks previously done by employees were instead performed by Artificial Intelligence? | 1 | A small number | 84.6% | 0.49% |
3 | 4 | In the last six months, how many tasks previously done by employees were instead performed by Artificial Intelligence? | 2 | A moderate number | 13.0% | 0.54% |
3 | 4 | In the last six months, how many tasks previously done by employees were instead performed by Artificial Intelligence? | 3 | A large number | 2.4% | 0.24% |
2 | 5 | In the last six months, did this business use Artificial Intelligence to perform operations previously performed by existing equipment or software in producing goods or services? | 1 | Yes | 19.6% | 0.37% |
2 | 5 | In the last six months, did this business use Artificial Intelligence to perform operations previously performed by existing equipment or software in producing goods or services? | 2 | No | 68.9% | 0.41% |
2 | 5 | In the last six months, did this business use Artificial Intelligence to perform operations previously performed by existing equipment or software in producing goods or services? | 3 | Do not know | 11.5% | 0.32% |
2 | 6 | In the last six months, how did the use of Artificial Intelligence affect this business’s total employment? | 1 | Increased | 2.8% | 0.23% |
2 | 6 | In the last six months, how did the use of Artificial Intelligence affect this business’s total employment? | 2 | Decreased | 2.6% | 0.13% |
2 | 6 | In the last six months, how did the use of Artificial Intelligence affect this business’s total employment? | 3 | Did not change | 94.6% | 0.32% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 1 | Trained current staff to use AI | 20.8% | 0.34% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 2 | Hired staff trained in AI | 2.0% | 0.10% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 3 | Purchased computing power or specialized equipment | 5.9% | 0.18% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 4 | Purchased cloud services or cloud storage | 12.4% | 0.26% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 5 | Changed data collection or data management practices | 8.0% | 0.21% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 6 | Developed new workflows | 19.7% | 0.40% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 7 | Used vendors or consulting services to install or integrate AI | 7.8% | 0.16% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 8 | Other | 7.6% | 0.13% |
2 | 7 | In the last six months, to use Artificial Intelligence (AI), what changes did this business make? | 9 | null | 50.5% | 0.40% |
1 | 8 | During the next six months, do you think this business will be using Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 1 | Yes | 6.5% | 0.07% |
1 | 8 | During the next six months, do you think this business will be using Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 2 | No | 70.6% | 0.16% |
1 | 8 | During the next six months, do you think this business will be using Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.) | 3 | Do not know | 22.9% | 0.17% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 1 | Machine Learning | 22.1% | 0.32% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 2 | Natural language processing | 26.6% | 0.42% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 3 | Virtual agents or chat bots | 28.2% | 0.61% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 4 | Speech/voice recognition using AI | 22.2% | 0.54% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 5 | Recommendation systems based on AI | 16.8% | 0.32% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 6 | Large language models | 15.5% | 0.29% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 7 | Text analytics using AI | 23.0% | 0.44% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 8 | Data analytics using AI | 29.8% | 0.56% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 9 | Neural networks | 3.7% | 0.21% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 10 | Augmented reality | 3.3% | 0.13% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 11 | Decision making systems based on AI | 14.1% | 0.27% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 12 | Deep learning | 7.3% | 0.17% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 13 | Image/pattern recognition | 13.3% | 0.37% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 14 | Machine/computer vision | 7.0% | 0.29% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 15 | Robotics process automation | 5.2% | 0.19% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 16 | Biometrics | 3.8% | 0.21% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 17 | Marketing automation using AI | 36.5% | 0.57% |
4 | 9 | During the next six months, what types or applications of Artificial Intelligence (AI) do you think this business will use in producing goods or services? | 18 | Other | 12.4% | 0.31% |
4 | 10 | During the next six months, do you think this business will use Artificial Intelligence to perform tasks currently done by employees in producing goods or services? | 1 | Yes | 34.4% | 0.41% |
4 | 10 | During the next six months, do you think this business will use Artificial Intelligence to perform tasks currently done by employees in producing goods or services? | 2 | No | 51.2% | 0.43% |
4 | 10 | During the next six months, do you think this business will use Artificial Intelligence to perform tasks currently done by employees in producing goods or services? | 3 | Do not know | 14.4% | 0.38% |
5 | 11 | During the next six months, how many tasks currently done by employees will instead be performed by Artificial Intelligence? | 1 | A small number | 79.2% | 0.60% |
5 | 11 | During the next six months, how many tasks currently done by employees will instead be performed by Artificial Intelligence? | 2 | A moderate number | 17.7% | 0.51% |
5 | 11 | During the next six months, how many tasks currently done by employees will instead be performed by Artificial Intelligence? | 3 | A large number | 3.1% | 0.28% |
4 | 12 | During the next six months, do you think this business will use Artificial Intelligence to perform operations currently performed by existing equipment and software in producing goods or services? | 1 | Yes | 33.5% | 0.39% |
4 | 12 | During the next six months, do you think this business will use Artificial Intelligence to perform operations currently performed by existing equipment and software in producing goods or services? | 2 | No | 46.1% | 0.45% |
4 | 12 | During the next six months, do you think this business will use Artificial Intelligence to perform operations currently performed by existing equipment and software in producing goods or services? | 3 | Do not know | 20.4% | 0.46% |
4 | 13 | During the next six months, how do you think the use of Artificial Intelligence will affect this business’s total employment? | 1 | Increase | 6.5% | 0.21% |
4 | 13 | During the next six months, how do you think the use of Artificial Intelligence will affect this business’s total employment? | 2 | Decrease | 6.1% | 0.17% |
4 | 13 | During the next six months, how do you think the use of Artificial Intelligence will affect this business’s total employment? | 3 | Will not change | 87.4% | 0.26% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 1 | Train current staff to use AI | 41.9% | 0.58% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 2 | Hire staff trained in AI | 8.0% | 0.15% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 3 | Purchase computing power or specialized equipment | 12.2% | 0.35% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 4 | Purchase cloud services or cloud storage | 18.6% | 0.22% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 5 | Change data collection or data management practices | 20.7% | 0.46% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 6 | Develop new workflows | 37.6% | 0.59% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 7 | Use vendors or consulting services to install or integrate AI | 16.7% | 0.30% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 8 | Other | 6.9% | 0.27% |
4 | 14 | During the next six months, to use Artificial Intelligence, what changes do you think this business will make? | 9 | null | 26.7% | 0.58% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 1 | Too expensive | 4.1% | 0.07% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 2 | AI is not a mature enough technology yet | 6.1% | 0.09% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 3 | Lack of knowledge on the capabilities of AI | 7.3% | 0.06% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 4 | Concerns about privacy/security | 6.6% | 0.05% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 5 | Concerns about bias | 2.8% | 0.04% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 6 | Lack of skilled workforce | 2.9% | 0.05% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 7 | Lack of required data | 2.2% | 0.03% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 8 | Laws and regulations prevent or restrict use of AI | 1.2% | 0.04% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 9 | Previous or current use of AI did not meet expectations | 0.9% | 0.02% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 10 | Other | 4.5% | 0.07% |
6 | 15 | Why does this business not plan to use Artificial Intelligence (AI) during the next six months in producing goods or services? | 11 | AI is not applicable to this business | 80.9% | 0.14% |
null | null | null | null | null | null | null |
null | null | null | null | null | null | null |
Source: U.S. Census Bureau, Business Trends and Outlook Survey (BTOS). The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data. | null | null | null | null | null | null |
(Project No. P-7529868, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0162) | null | null | null | null | null | null |
Dataset Card for AI Use in Business from US Census Bureau
This dataset is from the US Census Bureau and contains the segment about AI use in businesses.
Dataset Details
The BTOS questionnaire defines AI as computer systems and software able to perform tasks normally requiring human intelligence, such as decision-making, visual perception, speech recognition and language processing.
Examples of AI technologies and applications include machine learning, natural language processing, virtual agents, predictive analytics, machine vision, voice recognition, decision-making systems, data analytics, text analytics and image processing.
While it may seem like AI is everywhere, BTOS shows the opposite. Based on survey responses, only an estimated 3.9% of businesses used AI to produce goods or services between Oct. 23 and Nov. 5, 2023. However, this usage varied widely among economic sectors.
Dataset Description
The BTOS asks a series of qualitative questions about business conditions in the last two weeks and expectations about future business conditions. These qualitative questions result in response share estimates, the percent of businesses which have selected each possible answer. For most questions, an index is produced to create one estimate per question for easier comparison over time.
Source: U.S. Census Bureau, Business Trends and Outlook Survey (BTOS). The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data. (Project No. P-7529868, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0162)
- Curated by: U.S. Census Bureau
- Funded by: U.S. Census Bureau, Business Trends Outlook Survey
- Shared by: U.S. Census Bureau
- Language(s) (NLP): English
- License: Public Domain (U.S. Government Work)
Dataset Sources
https://www.census.gov/hfp/btos/data_downloads
Repository: U.S. Census Bureau - Business Trends Outlook Survey Direct link to dataset Survey Supplement Table https://www.census.gov/hfp/btos/downloads/Supplement%20Table.xlsx
Paper: Business Trends and Outlook Survey Begins
https://www.census.gov/newsroom/press-releases/2022/business-trends-and-outlook-survey-begins.html
Uses
The Business Trends and Outlook Survey (BTOS) provides insight into the state of the economy by providing timely data for key economic measures and business expectations about future conditions. By providing detailed geographic and subsector data, BTOS provides local, state, and federal officials near real-time data for policy and decision-making including after natural disasters or during economic crises. The BTOS also provides insight into recovery after these events.
Direct Use
This dataset from the U.S. Census Bureau can be used for various purposes, including:
Demographic Analysis: Understanding population distribution, age, gender, and other demographic characteristics.
Economic Research: Analyzing economic trends, employment statistics, and business dynamics.
Policy Making: Informing government policies and programs based on population and economic data.
Academic Research: Supporting studies in sociology, economics, public health, and other fields.
Market Research: Assisting businesses in market analysis and strategic planning.
Out-of-Scope Use
This dataset is not suitable for:
Personal Identification: The data is anonymized and should not be used to identify individuals.
Real-Time Decision Making: The dataset is not updated in real-time and may not reflect the most current information.
Misuse or Malicious Use: Any use that violates privacy, promotes discrimination, or is intended to harm individuals or groups.
Dataset Structure
An example can provide some insight into the interpretation of the index. Businesses are asked how revenue has changed in the last two weeks and can answer either increased, decreased, or no change. The following formula is used throughout the example.
Index = 100*(1Increased + ½NoChange + 0Decreased) (1) Assume that 10% of businesses reported an increase in revenue, 60% reported no change, and 30% reported a decrease in revenue. Using the following formula gives an estimate of Index = 100(10% + ½60% + 030%) = 40
(2) In the next period 20% of businesses report an increase in revenue, 50% report no change, and 30% report a decrease in revenue. Using the following formula gives an estimate of Index = 100*(20% + ½50% + 030%) = 45
(3) In the next period 5% of businesses report an increase in revenue, 70% report no change, and 25% report a decrease. Using the formula gives an estimate of 100*(5% + ½70% + 025%) = 40. (4) In the next period 5% of businesses report an increase in revenue, 85% report no change, and 10% report a decrease. Using the formula gives an estimate of 100*(5% + ½85% + 010%) = 47.
Moving from period (1) to (2), the revenue index improves, capturing the improvement of businesses from the “no change” to “increased” positions. Note that the index improves even though there is no improvement for the 30% of businesses that report decreases in revenue.
Moving from period (2) to (3), the revenue index declines. This reflects the larger weight given to increases (versus no change and decreases) as well as the magnitude of the change.
Moving from period (3) to (4), the revenue index again improves this time reflecting a move away from “decreased” to “no change” while there is no change in the share reporting increases.
These indexes measure the breadth of change for the variable of interest. They capture the extensive margin of change, in that an index moving toward 100 reflects the extent to which the situation for that variable is increasing and movement towards 0 reflects the extent to which the situation for that variable is decreasing while a value near 50 suggests a preponderance of businesses reporting no change such as in period 4. Depending on the question, increasing could have a negative connotation, such as the question on prices. The examples above are meant to illustrate that the index accounts for and simplifies the underlying dynamics of the variable of interest when the dynamics may be complex and difficult to summarize otherwise.
Dataset Creation
The dataset from the U.S. Census Bureau's Business Trends and Outlook Survey (BTOS) is created through a detailed and systematic process to ensure it provides accurate and timely data on business conditions. Here are the key steps involved:
Survey Design: The BTOS is designed to collect data on key economic measures and business expectations. The survey includes core questions and supplemental content as needed. Sampling: The sample consists of approximately 1.2 million businesses, divided into six panels of about 200,000 businesses each. These businesses are asked to report once every 12 weeks for a year. Data Collection: Data is collected every two weeks through online surveys. Businesses provide information on various aspects of their operations, including economic conditions and expectations for the future. Data Cleaning: The collected data undergoes a cleaning process to remove any inconsistencies, errors, or incomplete responses, ensuring the dataset's accuracy and reliability. Anonymization: To protect the privacy of respondents, all personally identifiable information is removed from the dataset. Data Aggregation: The cleaned and anonymized data is aggregated to provide insights at various geographic levels, including national, state, and metropolitan areas. Documentation: Detailed documentation is provided, including survey instruments, data dictionaries, and methodology reports, to help users understand the dataset's structure and variables. Quality Assurance: The dataset undergoes rigorous quality assurance checks to ensure its accuracy and reliability. This includes validation against known benchmarks and peer reviews. Publication: The final dataset is published on the U.S. Census Bureau's website, making it accessible to researchers, policymakers, and the public. Regular updates are provided to reflect the most current information. This comprehensive creation process ensures that the BTOS dataset is a valuable resource for understanding business trends and supporting informed decision-making.
Curation Rationale
The Business Trends and Outlook Survey (BTOS) provides insight into the state of the economy by providing timely data for key economic measures and business expectations about future conditions. This specific segment of the dataset is curated to discover how AI is being used in business or how it is affecting business operations.
Source Data
The BTOS sample consists of approximately 1.2 million businesses split into 6 panels (approximately 200,000 cases per panel). Businesses in each panel will be asked to report once every 12 weeks for a year. Data collection will occur every two weeks. The BTOS is comprised of a set of core questions and supplemental content, which is included as needed. The initial target population for BTOS is all nonfarm, employer businesses with receipts of $1,000 or more that are in the United States, District of Columbia, and Puerto Rico. The following industries were designated as out of scope for the BTOS:
Agriculture production (NAICS in [“110000,” “111,” “112”]) Railroads (NAICS = "482") U.S. Postal Service (NAICS = "491") Monetary Authorities – Central Bank (NAICS = "521") Funds, Trusts, and other financial vehicles (NAICS = "525") Religious grant operations and religious organizations (NAICS = "813") Private households (NAICS = "814") Public administration (NAICS = "92") Unclassified with legal form of organization as tax-exempt or unknown Businesses classified without a 2-digit NAICS (NAICS = "00") were not included.
Data Collection and Processing
The BTOS has a biweekly data collection schedule. The questionnaire for the BTOS contains approximately 25 core questions. The respondents are asked to report for the previous two weeks and looking forward six-months on numerous concepts.
Editing: Due to the nature of the survey questions and rapid cycle of data collection and release, the BTOS response data are not subjected to editing. Nonresponse: Nonresponse is defined as the inability to obtain requested data from an eligible survey unit. Two types of nonresponse are often distinguished. Unit nonresponse is the inability to obtain any of the substantive measurements about a unit. In most cases of unit nonresponse, the U.S. Census Bureau was unable to obtain any information from the survey unit after several attempts to elicit a response. Item nonresponse occurs when a particular question is unanswered. Nonresponse Adjustment: The BTOS nonresponse adjustment consists of two weighting class adjustment factors: NAF1 and NAF2. NAF1 uses adjustment cells defined by state and employment size class (EMPSIZE). EMPSIZE is a categorical version of the number of employees in the establishment and has three categories: four or fewer employees ("A"), between five and 19 employees ("B"), and 20 or more employees ("C"). NAF2 uses adjustment cells defined by 2-digit NAICS (sector) and EMPSIZE.
Who are the source data producers?
The source data producers for the Business Trends and Outlook Survey (BTOS) are the U.S. Census Bureau. The Census Bureau is responsible for designing, collecting, cleaning, and disseminating the data. They ensure the data is representative of U.S. businesses and provide detailed geographic and subsector information. The BTOS sample consists of approximately 1.2 million businesses and is a voluntary survey.
Annotations [optional]
There are no specific annotations of note.
Annotation process
The annotation process for this dataset involves several key steps to ensure the data is accurately labeled and useful for analysis:
Data Collection: The initial data is collected through surveys conducted by the U.S. Census Bureau. Data Cleaning: The collected data is cleaned to remove any inconsistencies, errors, or incomplete responses. Annotation Guidelines: Clear guidelines are established to ensure consistency in the annotation process. These guidelines include definitions, examples, and instructions for annotators. Annotation: Trained annotators label the data according to the established guidelines. This may involve categorizing responses, tagging specific data points, or adding metadata. Quality Control: The annotated data undergoes a quality control process to ensure accuracy and consistency. This may involve spot-checking annotations, double-checking by a second annotator, or automated validation checks. Final Review: The final annotated dataset is reviewed and approved before being made available for use.
Who are the annotators?
U.S. Census Bureau. Individual names are not listed.
Personal and Sensitive Information
Disclosure is the release of data that reveal information or permit deduction of information about a particular survey unit through the release of either tables or microdata. Disclosure avoidance is the process used to protect each survey unit’s identity and data from disclosure. Using disclosure avoidance procedures, the Census Bureau modifies or removes the characteristics that put information at risk of disclosure. Although it may appear that a table shows information about a specific survey unit,the Census Bureau has taken steps to disguise or suppress a unit’s data that may be “at risk” of disclosure while making sure the results are still useful.
Bias, Risks, and Limitations
BTOS estimates may be subject to nonresponse bias if businesses that respond to the survey are systematically different from businesses that do not. BTOS estimates may also be subject to other types of nonsampling error, such as coverage error, measurement error, and processing error.
Sampling Error: The sampling error of an estimate based on a sample survey is the difference between the estimate and the result that would be obtained from a complete census conducted under the same survey conditions. This error occurs because characteristics differ among sampling units in the population and only a subset of the population is measured in a sample survey. Sampling weights are used to ensure that the sample represents the entire in-scope population. The use of sampling weights also allows for the estimation of sampling variability of the survey estimates.
A common measure of sampling variability for percentage estimates is the standard error of the estimate. The standard error is the square root of the sampling variance, which is the squared difference, averaged over all possible samples of the same size and design, between the estimator and its average value. The standard errors for the BTOS estimates are calculated using a delete-a-group jackknife procedure, using 10 groups.
It is important to note that the sampling variance and standard error only measure sampling variability. They do not measure any systematic biases in the estimates.
The Census Bureau recommends that individuals using these estimates incorporate sampling error information into their analyses, as this could affect the conclusions drawn from the estimates.
Recommendations
The Census Bureau recommends that individuals using these estimates incorporate sampling error information into their analyses, as this could affect the conclusions drawn from the estimates.
Citation
US Census Bureau. (2022, July 15). Data collection begins for new business trends and outlook survey. Census.gov. https://www.census.gov/newsroom/press-releases/2022/business-trends-and-outlook-survey-begins.html
APA: US Census Bureau. (2022, July 15). Data collection begins for new business trends and outlook survey. Census.gov. https://www.census.gov/newsroom/press-releases/2022/business-trends-and-outlook-survey-begins.html
More Information
A copy of the questionnaire can be found at: https://www.census.gov/hfp/btos/downloads/BTOS%20Content%20V2%20Supplement%2011.29.2023_Watermarked.pdf
For the AI supplement used in this dataset, only questions #23-#37 are pertinent.
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