Getting a Broad View of Constructing the Built Environment

A Satellite Account for Built Environment Industries

 

 

How the built environment is created and maintained through project initiation, design, fabrication and construction to operation, repair and maintenance is an ongoing process. The network of firms involved includes construction contractors and subcontractors, property management and real estate services, manufacturers of fittings, finishings, plant and equipment, suppliers of building materials, and professional services. All these firms belong to industries that are part of the process of producing and maintaining the built environment. 

 

National agencies collect data and present it in tables following the format given in the System of National Accounts (SNA) published by the UN. The national accounts present highly aggregated estimates of expenditure, output and income based on the detailed data collected on the economic activities of households, firms, non-profits and government. That data is collected using the methods, definitions and categories provided in the SNA, ISIC and other publications. Firms and other organizations are assigned ISIC codes on the basis of common characteristics in products, services, production processes and logistics, and collects companies and other organizations into groups with similar characteristics.

 

Industries as defined by SIC classifications cannot capture all their associated economic activities, and when economic activities involve a range of different industries the contribution of a sector is not obvious, despite its importance. Because the ISIC system puts strict boundaries around an industry, what is included or left out of the definition of an industry determines its extent. However, inclusions and exclusions vary greatly between industries and there are many anomalies. Examples are:

·      Health insurance is included in Insurance not in health expenditure

·      Retail sales by chemists is included in Pharmaceutical expenditure as well as manufacturing and R&D

·      Research is classified to industries not by purpose, and often done by institutions

·      Automobile manufacture includes design, Construction does not 

 

The solution to the issues raised by narrow SIC industry definitions is a satellite account that reclassifies expenditures from different industry groupings into a single sector. Satellite accounts have been produced for many sectors that are made up of several industries, such as health, the digital economy, the environment, R&D, the space industry, and infrastructure. They have also been produced for non-profit institutions, volunteering, education and training, and unpaid household activities. They are used to provide more detail on sectors that are not visible in current statistics, following guidelines provided by the SNA for their preparation. The most widely found satellite account is for tourism, so far produced at various times for over 50 countries. This brings together the contributions of industries like travel, accommodation, hospitality, tour operators and entertainment to estimate their total output and employment.

 

The primary purpose of satellite accounts is to improve policy-making by providing better, more granular data, and demand for satellite accounts has increased as their usefulness has been shown. A 2019 survey by the UN found 80 countries had produced 241 satellite accounts covering over 20 different topics, with 148 of those done since 2000, mainly on health, tourism and the environment. The number produced by country varied from one to 15, the median number of satellite accounts in production was 2 and the average was 4. As a result, there are many guidelines for producing a satellite account available, usually produced through international collaboration, and the methodology has been adapted to a wide variety of sectors. 

 

 

Figure 1. Number of satellite accounts by sector

Source: Conference of European Statisticians, 2019: 11. In-depth review of satellite accounting, Paris: UNECE.

 

 

Preparation of a satellite account requires significant research and development. Different data sources have to be harmonized and measurement challenges met. The OECD published A System of Health Accounts in 2000 (updated 2011) after 15 years of development of the concepts and methods needed for a health satellite account, and the US Bureau of Economic Analysis (BEA) worked on their R&D satellite account for over a decade. However, the research is being done and more satellite accounts are being produced, such as the 2020 estimates for The Small Business Economy, and the Space Economy. In 2021 the OECD published the first Working Paper on a Transport satellite account.

 

A built environment sector satellite account would restrict its scope to relevant activities, and would therefore remain within the production, consumption and asset boundaries of the SNA framework, a type of satellite account known as a thematic account. Some examples of thematic accounts are agriculture, tourism, culture, and sport and recreation. Developing a sector based thematic account involves regrouping, re-arranging and re-packaging existing national accounts data by creating definitions of the economic activities, products, suppliers and users involved.[i] In some cases the national accounts data is supplemented by other sources, such as surveys of household activities or expenditure, that collect data on the use of products and supply of services not otherwise available. 

 

Despite issues of data quality and availability, bringing together the range of industries that contribute to the production, maintenance and management of cities, infrastructure and buildings in a satellite account would improve our understanding of both the sector and the wider economy. For example, urban development and city policies involve significant infrastructure spending, which is often their main focus. However, it is the associated induced industrial, commercial and residential development around the new infrastructure that drives longer-term growth. A satellite account captures that activity. 

---

[i] In selecting a number of industries of special interest ‘It is common practice to refer to such groupings of industries as “sectors” even though they do not constitute institutional sectors as the term is used in the SNA. The SNA does not try to provide specific and precise criteria for the definition of what identifies a key sector or activity….. in some important cases, such as tourism and environmental protection activities, the process of identification of characteristic and connected products is complex because not all the relevant activities and products appear in the central framework classifications.’ OECD, 2000. A System of Health Accounts, OECD Publishing, Paris. 

     Characteristic products are those that are typical of the field, for construction characteristic products are buildings and structures, project management and other professional services. Connected goods and services includes expenditure on products that are not typical and are classified to other product categories.  In construction quarrying, manufactured products and transportation of materials and components may be considered connected.

Australian Built Environment: Output and Employment

 

Industries are groups of firms with common characteristics in products, services, production processes and logistics, subdivided by the SIC into a four-level structure. The highest level is alphabetically coded divisions such as Agriculture, forestry and fishing (A), Manufacturing (C) and Information and communication (J). The classification is then organized into two-digit subdivisions, three-digit groups, and four-digit classes. SIC codes are therefore two, three and four-digit numbers representing industries, defined as firms with shared characteristics.

The SIC definition of the construction industry captures the onsite activities of contractors and subcontractors, and this data on building and construction work is taken to represent the industry. However, onsite work brings together suppliers of services, materials, machinery and equipment, products, components and other inputs required to deliver the buildings and structures that make up the built environment. When enough firms share sufficient characteristics they are often described as an industry cluster or sector.

The data used here is provided in the Australian Bureau of Statistics annual publication Australian Industry (ABS 8155), produced using a combination of data from the annual Economic Activity Survey and Business Activity Statement data provided by the Australian Taxation Office. The data includes all operating business entities and Government owned or controlled Public Non-Financial Corporations. Australian Industry excludes the finance industry and public sectors, but includes non-profits in industries like health and education and government businesses providing water, sewerage and drainage services. The industries included account for around two-thirds of GDP and the data is presented at varying levels for industry divisions, subdivisions and classes. The most recent issue is for 2020-21.

There is data at the two digit subdivision level for the Construction services and Property operators and real estate services industries. For the subdivisions in Professional, scientific and technical services and Building cleaning, pest control and other services the data includes contributions from other classes outside the built environment. Therefore, for these industries the two digit subdivision estimates have to be weighted using the four digit class data for the built environment component. These proportions are released as supplementary tables and provide data at the class level. Professional, scientific and technical services were included in 2015-16, and in 2016-17 this data was provided for two divisions: Rental, hiring and real estate services, with subdivisions Rental and hiring services (except real estate), and Property operators and real estate services; and Administrative and support services, with subdivisions Administrative services and Building cleaning, pest control and other support services.

The data is not complete because some industries cannot be separated into the relevant classes from Australian Industry. For example, rental of heavy machinery and scaffolding (class 6631) is in subdivision 66 but the data is not available to separate it from the other classes. Also, services such as marketing, legal, insurance and financial are important inputs, but again are not identifiable. Government spending on infrastructure and investment in departments like health and education is included through supply industries, although any maintenance and work done internally will generally not be included. That also applies in industries like retailing and transport where some unknown proportion of work is done in-house.

There is also leakage around the boundaries of industry statistics: some glass is used in mirrors, some in car windscreens; textiles are used in buildings; architects design furniture; engineers repair machines as well as structures, and so on. Because Australian Industry uses tax and business register data, it is the self-classification of firms to SIC industry classes that fundamentally determines the structure and scope of that data. Needless to say, such classifications are not perfect, particularly in regard to large multi-unit or multi-divisional organisations. The data here includes sixteen industries that together form one of the largest and most important industrial sectors in the economy.

Table 1. Australian Built Environment Industries

Supply industries Demand industries              Maintenance industries

Quarrying             Residential property Water, sewerage and drainage

Building construction     Non-residential property Waste collection, and disposal

Heavy and civil engineering     Real estate services          Building and industrial cleaning

Construction services                 Building pest control services

Architectural services                 Gardening services

Surveying and mapping services

Engineering design and consulting

Manufacturing industries

Figure 1.

Table 2. Economic Contribution of Australian Built Environment Industries 2020-21

                                                Employment IVA $billion

Total Australian Built Environment Industries 2,228,000 282

Total Australia Employment and GDP              12,369,000 2,069,178

Built Environment share of Australia total          16.9% 13.6%

Sources: ABS 8155, ABS 5206, ABS 6202.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

The IVA of the sixteen built environment industries contributed 13.6 percent to Australian GDP in 2018-19, within a long-run range between 13 and 15 percent of GDP since 2006-07. The sixteen built environment industries share of total employment was 16.9 percent, and its long-run range was between 16.5 and 17.5 percent of total employment.

Figure 6.

Figure 7.

Employment Trends in Australian Built Environment Industries

 Record High in Built Environment Employment

The number of people employed in the 16 industries that make up the Australian Built Environment Sector reached 2.23 million in 2020-21, an increase of nearly 10 percent over the previous year, contributing 17 percent to total employment in Australia. 

Figure 1

The largest industry is Construction, which employed 1.2 million people (54%), followed by Property and real estate with 333,000 (15%), Professional services 269,000 (12%) and Building services 206,000 (9%). These four industries include a dozen smaller industry groups, and account for 90 percent of persons employed in construction and maintenance of Australia’s built environment. 

 

Figure 2

The big increase in 2021 was a rebound after the 1.3 percent fall in total BES employment in 2019-20. In all industries, with the exception of Water and Waste, employment fell in 2020, and by over three percent in Property and real estate services. In the post-lockdown recovery employment growth in 2020-21 was strong, at over eight percent in Construction and over six percent in both Building services and Professional services. 

 

Figure 3

In the decade from 2007 to 2017 there was a small increase in total built environment employment, however the rate of employment growth since 2018 has been much stronger. The only industry that has not increased employment is Property and real estate services, but in 2020-21 the other industries all had record numbers of people employed after a significant increase in employment. However, this was an unusually large upturn and much larger than the annual increase in output for these industries. 

 

Figure 4

The average growth rate of total employment in the five years to 2021 has been one percent higher than the 15 year average, at 2.5 percent a year. The highest 5 year average rates of growth in employment were five percent a year in the combined Water supply, sewerage and drainage services and Waste collection, treatment and disposal services, and over four percent a year in Professional services. Also of note is the growth in manufacturing employment after a decade of decline. 

 

Figure 5

The Australian Built Environment Sector

 

The Australian Built Environment Sector uses data provided in the Australian Bureau of Statistics annual publication Australian Industry, produced from a combination of directly collected data from the annual Economic Activity Survey conducted by the ABS, and Business Activity Statement data provided by businesses to the Australian Taxation Office. The data includes all operating business entities and Government owned or controlled Public Non-Financial Corporations. Australian Industry excludes the finance industry and public sector, but includes non-profits in industries like health and education and government businesses providing water, sewerage and drainage services. The industries included account for around two-thirds of GDP. Industries are groups of firms with common characteristics in products, services, production processes and logistics.

 

Figure 6

Data on the construction industry captures the onsite activities of contractors and subcontractors. However, onsite work brings together suppliers of materials, machinery and equipment, products, components and other inputs required to deliver the buildings and structures that make up the built environment. Consultants provide professional services such as design, engineering, urban planning, cost planning and project management as inputs into building and construction projects. There are also inputs from transport, finance and legal services, although data for these services is not available. 

 

Other industries like tourism and defence are structured around such value chains and production networks, and when firms from different industries share sufficient characteristics they are described as an industry cluster or sector. In the case of tourism an annual satellite account that combines the industries involved is produced by the ABS.

 

Table 1. Industries included in the Australian Built Environment Sector

Supply industries	Demand industries	Maintenance industries
Non-metallic mining and quarrying	Residential property	Water, sewerage and drainage
Building construction	Non-residential property	Waste collection, and disposal
Heavy and civil engineering	Real estate services	Building and industrial cleaning
Construction services		Building pest control services
Architectural services		Gardening services
Surveying and mapping services
Engineering design and consulting
Manufacturing industries

 

 

Digitization and advanced business technologies in industry

Data on the technology frontier at the industry level

 

 

There is a commonly held view that construction is a digital laggard.  A widely cited McKinsey report in 2016 argued: “the construction sector has been slow to adopt process and technology innovations …. The industry has not yet embraced new digital technologies that need up-front investment, even if the long-term benefits are significant. R&D spending in construction runs well behind that of other industries: less than 1 percent of revenues, versus 3.5 to 4.5 percent for the auto and aerospace sectors. This is also true for spending on information technology, which accounts for less than 1 percent of revenues for construction, even though a number of new software solutions have been developed for the industry.”

 

Technology use and diffusion is an important dynamic in industry development, but good data is rare. Most surveys are of specific industries or selected firms (typically large ones), and surveys with large samples that would be more representative of firms across the economy by including small and medium size firms are scarce. This particularly affects built environment industries like construction and professional services because of the large number of small firms in those industries. 

 

The United States Census Bureau conducts an Annual Business Survey (ABS), and in 2018 the ABS included a technology module with three questions about the extent of technology use between 2015 and 2017: the availability of information in digital format (digitization), expenditure on cloud computing services, and use of a range of advanced business technologies. The survey was a partnership between the Census Bureau and the National Center for Science and Engineering Statistics, and the first results have been released in a working paper from the National Bureau of Economic Research. The results are summarized below.

 

The survey data is at a high level of generality, to make the questions relevant across the variety of firms and industries included. There are also issues around how the data has been modelled and analysed, and the adjustments for high counts for firms that minimally use or are not using advanced business technologies at all. Importantly, the survey shows construction is not significantly lagging other industries in the US in digitization and use of cloud services, however it is doing less testing and development of advanced business technologies. 

 

The main finding of the survey was “Despite increasingly widespread discussion in the press of machine learning, robotics, automated vehicles, natural language processing, machine vision, voice recognition and other advanced technologies, we find that their adoption rates are relatively low. Furthermore, adoption is quite skewed, with heaviest concentration among a small subset of older and larger firms. We also find that technology adoption exhibits a hierarchical pattern, with the most sophisticated technologies being present most often only when more-basic applications are as well.” 

 

There were 583.000 responses to the survey. Two thirds of the firms employed under 10 people and were less than 20 years old, making this the most comprehensive survey of diffusion of advanced business technologies done so far. The industry breakdown of firms is in Table 1, with the built environment industries of construction, real estate and professional services well represented. This makes the data particularly interesting. 

 

Table 1. Industry breakdown of firms

Sector	Distribution %
Agriculture, Mining, Utilities	2
Construction	10
Education	1
Finance, Insurance, Real Estate	10
Health Care	9
Information	2
Management & Administrative	5
Manufacturing	8
Other (Arts, Food, Other Services)	14
Professional Services	17
Retail Trade	13
Transportation & Warehousing	4
Wholesale Trade	5

 

Following are extracts from the NBER paper on the results of the survey on the three technology questions: the availability of information in digital format, expenditure on cloud computing services, and use of advanced business technologies with a focus on the use of AI. The next post will discuss the survey and its implications for construction. 

 

 

Digital Share of Information by Business Activity 

 

The first question in the 2018 ABS technology module queried firms on the type of information stored digitally. In all sectors, financial and personnel information are the most likely to be digitized, followed by customer feedback and marketing. This is the case for Construction, with financial, personnel and marketing digitized. The lowest rates of adoption are in production and supply chain activities.

 

Figure 2 is a butterfly chart of adoption and use rates for digital information by sector, where the ranking of sectors by adoption and intensity of use rates parallel each other. The right panel of the chart represents, by sector, the adoption rates of digital information across all surveyed information types. The segments within each bar in the chart capture adoption rates by the number of information types in digital format. In all sectors, a large share of adopters report having three or more types of information digitized. 

 

The left panel of Figure 2 represents intense use of digitization. Most firms report digitizing at least two types of information, regardless of sector, the fraction of firms digitizing only one type of information intensively is relatively small in each sector. Overall, digitization appears to be highly prevalent across sectors. Manufacturing, Information and Professional Services are among the highest adopters of digitization, with size being a primary correlate of adoption. 

 

Figure 2: Extensive and Intensive Margin Measures of Digitized Information by Sector

 

Cloud Service Purchases by IT Function 

 

This section describes the adoption patterns for cloud service purchases across size, age and sector. Like digitization, the highest adoption and intensive-use rates are in Information, followed closely by Professional Services and Education. The lowest rates are in Agriculture, Mining, Utilities, Retail Trade, and Transportation and Warehousing, and the Other category. Figure 4 reveals that cloud services purchases have much lower diffusion rates compared to those for digital information in any given sector. 

 

Billing and Security are the most common IT functions for most sectors, with certain sectors, including Construction, predominantly relying on the cloud to perform collaborative or synchronized tasks. The Data Analysis function has the lowest number of firms reporting some cloud purchase, Billing and Account Management has the highest number of firms, closely followed by Security or Firewall and Collaboration and Synchronization functions. 

 

Although the adoption rates for business IT functions in the cloud is significantly lower than the adoption rates of storing information digitally, this technology is widespread across various applications, with nearly a third of each different type of IT function being performed in the cloud and being used intensively. 

 

Figure 4: Extensive and Intensive Margin Measures of Use Rates for Cloud Service Purchases by Sector - Conditional 

Advanced Business Technologies 

 

In this section we analyze firm responses to the business technologies question. Due to their wide technological scope, we link the responses here with the previous technology adoption questions and perform a deeper set of analyses assessing the range of response categories. Very few firms use the business technologies included in the module, and many answered, “Don’t know”. Based on our tabulation weights, only 10.3% (8.5% non-imputed) of firms adopt at least one of the listed advanced business technologies. 

 

The highest use frequencies are in touchscreens and machine learning. For touchscreens the adoption rate is 6.1% of firms. Machine learning comes second but the rate is low at 2.9%. Voice Recognition and Machine Vision, which are can be considered examples of Machine Learning applications, have the next two highest use rates. 

 

The overall diffusion of robotics is very low across firms in the U.S. The use rate is only 1.3%, concentrated in large, manufacturing firms. The distribution of robots among firms is highly skewed toward larger firms. The least-used technologies are RFID (1.1%), Augmented Reality (0.8%), and Automated Vehicles (0.8%). 

 

Looking at the most common types of business technologies adopted by sector in Table 2 there is substantial variation. All sectors (except Manufacturing adopt Touchscreens followed by Machine Learning or Voice Recognition. Manufacturing is most likely to adopt Machine Learning followed by Touchscreens and Robotics. RFID technology is most commonly used in the Retail, Wholesale, and Transportation and Warehousing sectors, consistent with these industries tracking physical goods through supply chains. 

 

 Table 2. Top Use Sub-Categories for Business Technologies by Sector (p. 60).                                     

Sector	1st	2nd	3rd
Agriculture, Mining, Utilities	Touchscreens	Machine Learning	Automated vehicles
Construction	Touchscreens	Machine Learning	Voice Recognition
Education	Touchscreens	Machine Learning	Voice Recognition
Finance, Insurance, Real Estate	Touchscreens	Voice Recognition	Machine Learning
Health Care	Touchscreens	Voice Recognition	Machine Learning
Information	Touchscreens	Machine Learning	Voice Recognition
Management & Administrative	Touchscreens	Machine Learning	Voice Recognition
Manufacturing	Machine Learning	Robotics	Touchscreens
Other Arts, Food, Other Services	Touchscreens	Machine Learning	Machine Vision
Professional Services	Touchscreens	Voice Recognition	Machine Learning
Retail Trade	Touchscreens	Machine Learning	RFID
Transportation & Warehousing	Touchscreens	Machine Learning	RFID
Wholesale Trade	Touchscreens	Machine Learning	RFID

 

The testing-versus-use rates across different technologies are used to assess which technologies are in earlier phase of diffusion, that is, where testing is high relative to use. In Figure 6, the vertical axis represents the ratio of the fraction of firms testing to the fraction of firms using. The technologies are represented by the circles. The size of each circle corresponds to the use rate for that technology with larger circles representing higher rates of use. Technologies are ordered in the figure by usage rate, low to high. 

As shown in panel a, the technology with the highest testing-to-use ratio is Augmented Reality, where nearly half as many firms as those using the technology report testing it. The next highest ratios are observed in RFID and Natural Language Processing and the lowest ratios are in technologies that are relatively more diffused (and hence, used), such as Touchscreens, Machine Learning and Machine Vision. For Touchscreens, for instance, only about 15 firms report testing the technology for every 100 that use it. It is notable that most testing-to-use ratios are below 0.3, indicating that there are fewer than 30 firms testing the technology for every 100 using it. 

The remaining panels of Figure 6 plot the testing-to-use ratio for technologies by firm size, age, and manufacturing status. Panel b displays ratios by firm size, where small firms are defined as those with 1-9 employees and large firms are those with at least 250 employees. The blue circles capture usage among large firms and the orange circles represent usage among small firms. The sizes of the circles are smaller for small firms for each technology, consistent with the earlier finding that larger firms tend to use the business technologies at a higher rate, in general. 

 

Figure 6: Testing-to-Use Ratios 

a. Testing-to-Use Ratios for all Business Technologies (All Firms) 

 

b. Testing-to-Use Ratios for all Business Technologies (By Size) 

 

c. Testing-to-Use Ratios for all Business Technologies (By Age) 

 

d. Testing-to-Use Ratios for all Business Technologies (By Manufacturing Status)

 

The butterfly chart in Figure 7 provides sectoral diffusion rates for all business technologies considered together. Manufacturing leads with about 15% of firms indicating use of at least one business technology, followed by Health Care (14%), Information (12%), Education (11%) and Professional Services (10%). The lowest diffusion rates for the technologies are in Construction, Agriculture, Mining and Utilities, Management and Administrative, and Finance, Insurance and Real Estate sectors. 

 

Figure 7: Extensive and Intensive Margin Measures of Use and Testing Rates for Business Technologies by Sector 

 

The third question asked directly about the use of advanced “business technologies,” including those typically categorized as “AI.” These technologies include automated guided vehicles, machine learning, machine vision, natural language processing, and voice recognition software. Respondents are presented with a list that covers robotics (i.e., “automatically controlled, reprogrammable, and multipurpose machines”), various cognitive technologies (i.e., applications that help machines to “perceive, analyze, determine response and act appropriately in [their] environment”, a standard definition of AI), radio frequency identification, touchscreens/kiosks for customer interface, automated storage and retrieval systems, and automated guided vehicles. 

 

Across all AI-related technologies, the aggregate adoption rate for all firms in the economy is 6.6% meaning that approximately 1 in 16 firms in the US are utilizing some form of AI in the workplace. This adoption rate is significantly lower than the adoption rate highlighted in the AI survey by the European Commission and other private surveys by McKinsey, Deloitte, and PwC. However, it is important to consider the sampling methods of those surveys. None of the other surveys claim to be nationally representative and tend to focus on larger, publicly traded companies. In contrast, the ABS sample includes many small firms where AI adoption is very low. This is important because AI adoption rate varies greatly by firm size. Adoption rates (defined as usage or testing) increase from 5.3% for the group of firms with the smallest number of employees to 62.5% for firms with 10,000+ employees. 

 

In other words, scale appears to be a primary correlate of AI usage, likely due to both the large quantities of data and computing power required to fully realize the most popular types of AI currently available. This may potentially have far-reaching implications on topics such as inequality, competition and the rise of “superstar” firms, especially if AI is shown to have widespread productivity benefits. If only a select group of firms are able to fully realize the benefits of AI, we can expect further divergence for the “frontier” and most productive set of firms. 

 

Our data and explanatory variables are simply too crude to provide a reliable predictor for the precise types of firms that adopt certain technologies and those that do not. While we can claim that size is a reliable predictor of adoption, even amongst large firms, we see heterogeneous patterns of adoption depending on the technology type. In other words, there are simply too many unknown factors that cannot be measured by traditional metrics (such as firm size, age and industry) that appear to drive technology adoption. 

 

 

Conclusion 

 

We have provided an introduction to the technology module in the 2018 ABS and placed it in the larger context of related work at the Census Bureau to collect comprehensive data on technology adoption and use by U.S. firms in order to provide a more accurate picture of the state of advanced technology use in the U.S. economy. Because of the large pool of respondents (about 850,000 firms) in the 2018 ABS, the module represents a unique opportunity to offer insights on technology adoption and use across all sectors of the economy and across a variety of key firm characteristics. The same technology module is expected to be a part of the 2021 Annual Business Survey.

 

A primary contribution for the paper is to develop a nationally representative set of technology adoption and use measures based on the survey results, which in public use tabulations report aggregate response counts for each technology question (see public use tabulations at: https://www.census.gov/data/tables/2018/econ/abs/2018-abs-digital-technology-module.html ). 

 

Advanced Technologies Adoption And Use By U.S. Firms: Evidence From The Annual Business Survey, by  Nikolas Zolas, Zachary Kroff, Erik Brynjolfsson, Kristina McElheran, David N. Beede, Cathy Buffington, Nathan Goldschlag, Lucia Foster and Emin Dinlersoz. 2020. National Bureau of Economic Research, Cambridge, MA Working Paper 28290 http://www.nber.org/papers/w28290