Research to Insights: Challenges and Opportunities in Innovation, Technology Adoption and Productivity

Release date: July 24, 2024

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About Research to Insights

The Research to Insights series of presentations features a broad range of findings on selected research topics. Each presentation draws from and integrates evidence from various studies that use innovative and high-quality data and methods to better understand relevant and complex policy issues.

Based on applied research of valuable data, the series is intended to provide decision makers, and Canadians more broadly, a comprehensive and horizontal view of the current economic, social and health issues we face in a changing world.

Context

Figure 1 Framework: Innovation, productivity growth and living standards

Description for Figure 1

The title of Figure 1 is Framework: Innovation, productivity growth and living standards. There are 3 circles, the first one is labelled A and says “Capital intensity (investment per worker), the second one is labelled B and says “Labour composition (skills upgrading)” and the third one labelled C says “Growth in multifactor productivity”. All A, B and C circles have a red arrow that points to a box that says “Labour productivity growth”. The box for “Labour productivity growth” has a red arrow that points to another box that says “GDP per capita”. On top of The box for “Labour productivity growth” there is a circle that says “Work intensity (hours per employee)”. On the bottom of the box for “Labour productivity growth” there is a circle that says “Employment rate (percentage of the population that is employed)”. Both of these top and bottom circles have red arrows that point to the box that says “GDP per capita”.

There is a note at the bottom of the figure that relates to the “C” circle, it says “The residual portion of labour productivity growth that is not attributable to gains in capital intensity (A) and skills upgrading (B) is called growth in multi-factor productivity (C). It measures the efficiency with which inputs are used in production. Growth in multi-factor productivity is often associated with innovation and technological progress”.

Less productivity growth from capital investment coupled with low contributions from multifactor productivity, which partly reflect modest returns from innovation and technology

Chart 1 Contributions to labour productivity growth, selected periods

Data table for Chart 1 
Data table for Chart 1
Table summary
This table displays the results of Data table for Chart 1 1980 to 2000, 2000 to 2015, 2015 to 2022 and 2019 to 2022, calculated using percentage point contributions to the average annual growth in labour productivity units of measure (appearing as column headers).
1980 to 2000 2000 to 2015 2015 to 2022 2019 to 2022
percentage point contributions to the average annual growth in labour productivity
Capital intensity 0.9 0.9 0.4 0.5
Labour Composition 0.4 0.3 0.3 0.3
Multifactor productivity growth 0.5 -0.2 0.1 -0.1
Labour productivity growth 1.8 1.0 0.8 0.8

Over the past two decades, increases in multifactor productivity—which are improvements in business efficiency that stem from innovation and technology use, organizational change, and scale economies—have not translated into sustained improvements in labour productivity.

For more information: The Daily—Multifactor productivity growth estimates and industry productivity database, 2022.

Gap in labour productivity growth between Canada and the United States reflects lower productivity north of the border in several high-tech sectors

Chart 2 Labour productivty growth, Canada and the United States

Data table for Chart 2 
Data table for Chart 2
Table summary
This table displays the results of Data table for Chart 2 United States and Canada, calculated using index (1980=100) units of measure (appearing as column headers).
United States Canada
index (1980=100)
1980 100.00 100.00
1981 102.13 101.99
1982 101.55 104.56
1983 105.01 108.00
1984 108.00 111.50
1985 110.47 112.83
1986 113.58 112.02
1987 114.19 112.99
1988 115.91 114.78
1989 117.23 115.34
1990 119.56 115.40
1991 121.46 115.25
1992 127.10 117.90
1993 127.22 119.86
1994 127.95 122.81
1995 128.84 124.03
1996 131.98 123.38
1997 134.83 127.24
1998 139.44 130.43
1999 145.12 135.54
2000 149.68 141.62
2001 153.62 143.87
2002 160.12 146.00
2003 166.23 146.58
2004 171.45 147.45
2005 175.28 150.58
2006 177.01 152.98
2007 179.91 153.37
2008 182.37 151.76
2009 189.83 150.22
2010 195.95 152.32
2011 195.59 155.83
2012 196.95 155.73
2013 199.06 158.79
2014 200.58 164.55
2015 203.00 164.31
2016 204.58 165.57
2017 207.30 168.46
2018 210.35 169.04
2019 214.71 169.90
2020 225.68 185.45
2021 229.79 175.09
2022 225.43 173.94
2023 228.67 170.19

For more information: The post-2001 productivity growth divergence between Canada and the United States: The role of the information and cultural services industry.

Opportunities to improve productivity through investment and innovation

Chart 3 Average entry and exit rates in Canadian industries, 2000 to 2021

Data table for Chart 3 
Data table for Chart 3
Table summary
This table displays the results of Data table for Chart 3 Average entry rate and Average exit rate, calculated using percent units of measure (appearing as column headers).
Average entry rate Average exit rate
percent
2000 14.60 10.26
2001 14.70 10.29
2002 11.86 9.59
2003 10.90 9.37
2004 12.96 9.36
2005 12.34 8.62
2006 11.85 9.42
2007 12.94 8.75
2008 10.79 9.27
2009 9.98 9.57
2010 9.60 8.63
2011 9.69 8.58
2012 10.21 7.88
2013 9.54 8.13
2014 9.42 8.80
2015 9.06 8.91
2016 8.75 9.14
2017 9.24 10.15
2018 9.37 9.04
2019 9.57 9.35
2020 7.75 10.68
2021 7.34 12.17

For more information: Competition Bureau report finds Canada’s competitive intensity in decline and The Daily—Survey of Innovation and Business Strategy, 2022.

Businesses invest in innovation and technology adoption—especially in response to competition

Chart 4 Innovation rates, 2020 to 2022

Data table for Chart 4 
Data table for Chart 4
Table summary
This table displays the results of Data table for Chart 4 percentage of businesses reporting innovations (appearing as column headers).
percentage of businesses reporting innovations
Users of advanced technology 85.2
All businesses 71.9
Non-users of advanced technology 60.0

For more information: The Daily—Survey of Innovation and Business Strategy, 2022 and Aspects that improved the ability of business or organization to operate efficiently over the last 12 months, second quarter of 2024.

Business research and development spending is ramping up, but overall R&D intensity remains well below that of other major industrial economies

Chart 5 Growth in business research and development spending, by expenditure groups

Data table for Chart 5 
Data table for Chart 5
Table summary
This table displays the results of Data table for Chart 5 2016, 2017, 2018, 2019, 2020 and 2021, calculated using index (2016=1) units of measure (appearing as column headers).
2016 2017 2018 2019 2020 2021
index (2016=1)
Less than $500,000 1.00 0.90 0.91 0.89 1.11 0.99
$500,000 to $9,999,999 1.00 1.02 1.18 1.22 1.29 1.32
$10,000,000 and more 1.00 1.04 1.11 1.20 1.28 1.65

For more information: The Daily—Industrial research and development, 2021 (actual), 2022 (preliminary) and 2023 (intentions) and Activities of multinational enterprises in Canada, Canadian and foreign multinationals, as a share of the Canadian economy.

Many businesses benefited from federal support for innovation and growth during the recovery from the COVID-19 pandemic

Chart 6 Business innovation and growth support by employment size, 2021

Data table for Chart 6 
Data table for Chart 6
Table summary
This table displays the results of Data table for Chart 6 Enterprises and Total value of support, calculated using percent units of measure (appearing as column headers).
Enterprises Total value of support
percent
Small- and medium-sized enterprises 96 77
Large enterprises 4 23

For more information: The Daily—Business innovation and growth support, 2021.

Patent activity scaled back prior to the COVID-19 pandemic

Chart 7 Number of patents

Data table for Chart 7 
Data table for Chart 7
Table summary
This table displays the results of Data table for Chart 7 2001 to 2005, 2006 to 2010, 2011 to 2015 and 2016 to 2019, calculated using number of patents units of measure (appearing as column headers).
2001 to 2005 2006 to 2010 2011 to 2015 2016 to 2019
number of patents
CIPO 2,914 3,004 3,038 2,625
USPTO 2,569 3,458 5,217 5,133
Other international patent office 4,538 4,758 3,834 2,631

For more information: The Daily—Survey of Innovation and Business Strategy, 2022 and Innovation in focus: Exploring trends in the development of advanced technology through patent applications.

Adoption of disruptive technologies is in its early stages

Chart 8 Share of capital expenditures on advanced technology by type of technology, 2020 to 2022

Data table for Chart 8 
Data table for Chart 8
Table summary
This table displays the results of Data table for Chart 8 percentage of advanced technology spending (appearing as column headers).
percentage of advanced technology spending
Advanced design and information control technologies 23.4
Additional advanced technologies 15.2
Advanced business intelligence technologies 14.9
Clean technologies 11.7
Advanced processing and fabrication technologies 11.4
Advanced material handling, supply chain and logistics technologies 8.0
Internet-connected smart devices or systems 5.5
Other 4.7
Robotics 3.9
Artificial intelligence technologies 1.3

For more information: The Daily—Survey of Advanced Technology, 2022.

Comparatively low spending on advanced technologies 

For more information: The Daily—Survey of Advanced Technology, 2022, The Daily—Non-residential capital and repair expenditures, 2022 (revised), 2023 (preliminary) and 2024 (intentions), Reasons for not investing capital expenditures in advanced technologies, by industry and enterprise size, Technologies the business or organization plans to adopt or incorporate over the next 12 months, second quarter of 2024 and Analysis on artificial intelligence use by businesses in Canada, second quarter of 2024.

Impacts of artificial intelligence on the workforce may be more far-reaching than earlier technological transformations

Artificial intelligence is expected to have far-reaching impacts on business productivity and the nature of work  

Figure 2 Potential artificial intelligence occupational exposure and complementarity in Canada

Description for Figure 2

This chart shows a scatter plot with the AI occupational exposure index ranging from 5 to 7 on the horizontal axis and the complementarity index ranging from 0.4 to 0.8 on the vertical axis. There are 490 data points. Each data point represents an occupation as per the 4-digit National Occupation Classification version 2016 and are colour-coded with three different colours. The colours are used to distinguish the occupations according to their minimum educational requirement. Occupations requiring a bachelor's degree or higher are represented by blue, occupations requiring some postsecondary education below bachelor's degree are represented by green, and occupations requiring high school or less education are represented by red. The chart shows the relationship between AI occupational exposure and the extent to which AI can play a complementary role in a given occupation. A higher AI occupational exposure index is associated with greater potential occupational exposure to AI. A higher complementarity index is associated with greater potential complementarity with AI. The median AI occupational exposure index score of 6 and the median complementarity index score of 0.6 are used to group the various occupations into four quadrants. The top-left quadrant contain data points representing occupations which might be relatively less exposed to AI and highly complementary with AI. The majority of occupations in that quadrant require some postsecondary education below bachelor's degree but there are also a few which require high school or less education. Some examples include firefighters, plumbers, and carpenters. The bottom-left quadrant contain data points representing occupations which might also be relatively less exposed to AI but also less complementary with AI. The majority of occupations in that quadrant require high school or less education but there are also a few which require some postsecondary education below bachelor's degree. Some examples include food and beverage servers, labourers in processing, manufacturing and utilities, and welders and related machine operators. The top-right quadrant contain data points representing occupations which might be highly exposed to AI and highly complementary with AI. The majority of occupations in that quadrant require a bachelor's degree or higher education but there are a few which require some postsecondary education below bachelor's degree. Some examples include general practitioners and family physicians, secondary school teachers, and electrical engineers. The bottom-right quadrant contain data points representing occupations which might be highly exposed to AI but less complementary with AI. This quadrant has fewer data points than the other quadrants and the occupations represented by the data points have a mixture of educational requirements. Some examples include data entry clerks, economists, computer network technicians, and computer programmers and interactive media developers.

Takeaways

For more information, please contact
analyticalstudies-etudesanalytiques@statcan.gc.ca

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