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Data (439)

Data (439) (0 to 10 of 439 results)

  • Table: 33-10-0822-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Technologies the business or organization plans to adopt or incorporate over the next 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0823-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Challenges faced by business or organization when adopting or incorporating technologies, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0825-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Use of artificial intelligence (AI) by businesses and organizations in producing goods or delivering services over the last 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0826-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Extent to which artificial intelligence (AI) has reduced tasks previously performed by employees and the impact of AI use on total employment, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0827-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Changes made by business or organization when using artificial intelligence (AI) to produce goods or deliver services, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0828-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: New or significantly improved goods or services brought onto the market from 2020 to 2023, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Table: 33-10-0829-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description: Innovation of new products or services and most significant recent product innovation was new to its market, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.
    Release date: 2024-05-27

  • Data Visualization: 71-607-X2022018
    Description: This dashboard shows traffic count data that is obtained from traffic camera imagery using a computer vision-based system developed at the Data Exploration and Integration Lab (DEIL) at Statistics Canada. The system periodically pulls traffic imagery from the Application Programmable Interfaces (APIs) of municipal and provincial traffic camera programs. Vehicle detection was implemented using the open source You Only Look Once version 3 (YOLOv3) object detection model that was trained on the Common Objects in Context (COCO) dataset. The output of the model is used to generates real-time counts of the detected vehicles (cars, trucks, buses, motorcycles).
    Release date: 2024-05-15

  • Table: 27-10-0367-01
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Occasional
    Description:

    Percentage of enterprises that used specific types of advanced or emerging technologies, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Advanced technologies include material handling, supply chain or logistics technologies; design or information control technologies; processing or fabrication technologies; clean technologies; security or advanced authentication systems; business intelligence technologies; and other types of advanced technologies. Emerging technologies include nanotechnology, biotechnology, geomatics or geospatial technologies, artificial intelligence (AI), integrated Internet of Things (IoT) systems, blockchain technologies, and other types of emerging technologies.

    Release date: 2024-04-30

  • Table: 27-10-0368-01
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Occasional
    Description:

    Percentage of enterprises that did not adopt or use advanced technologies for specific reasons, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Reasons for not adopting or using advanced technologies include not convinced of economic benefit; difficulty in obtaining financing; high cost of advanced technologies; investment not necessary for continuing operations; lack of technical skills required to support this type of investment; organizational culture too inflexible; decisions made by parent, affiliates or subsidiary businesses; lack of technical support or services (from consultants or vendors); lack of information regarding advanced technology; difficulty in integrating new advanced technologies with existing systems, standards and processes; other reasons for not adopting or using advanced technologies; and adoption or use of advanced technologies not applicable to this business’s activities.

    Release date: 2024-04-30
Analysis (44)

Analysis (44) (30 to 40 of 44 results)

  • Articles and reports: 11-633-X2020004
    Description:

    Recent advances in artificial intelligence have rekindled ancient fears that robots will replace humans in the economy. Previous waves of automation changed but did not reduce labour’s role, but robots’ human-like flexibility could make this time different. Whether or not it will is an empirical question that has lacked suitable data to answer. This paper describes the creation of a dataset to fill the evidence gap in Canada. Robots! is firm-level panel data on robot adoption created using Canadian import data. The data identify a substantial amount of the robot investment in the Canadian economy from 1996 to 2017. Although many robots are imported by robotics wholesalers or programmers for resale, the majority of them can be attributed to their final (direct) adopting firm. The data can be used to study the impact of robot adoption at the economic region, industry or firm-level.

    Release date: 2020-11-02

  • Articles and reports: 11F0019M2020017
    Description:

    This study examines how employment and organizations have changed in response to robot adoption. As robotics and artificial intelligence (AI) become increasingly used by firms as the next engine of innovation and productivity growth, their effects on labour, firm practices and productivity have become a subject of growing importance. The study provides the most comprehensive evidence possible at the level of individual businesses on the employment and organizational effects of robot investments.

    Release date: 2020-11-02

  • Articles and reports: 11F0019M2020015
    Description:

    Recent advances in artificial intelligence and machine-learning technologies have fuelled fears of potential job losses among some workers. While the net impact of new technology on total jobs can be negative, positive or neutral, some workers may be more affected than others depending on how easily robots and algorithms can replace them, or how easily their skills complement the new technology. In the case of women and men, it is not clear who is likely to be most affected. This study estimates the risk of job transformation as a result of automation technology faced by women and men.

    Release date: 2020-09-24

  • Articles and reports: 11F0019M2020011
    Description:

    The recent development of several artificial intelligence applications—such as driverless vehicles, robo-writers and computer-aided medical diagnostics—has led to concerns about the role of human workers in the future workforce. The COVID-19 pandemic has added to these concerns, as businesses may turn to new artificial intelligence technologies to perform work activities not traditionally regarded as automatable, such as social tasks. While previous studies have estimated the share of Canadian workers at high risk of automation-related job transformation, this study is the first to examine in great detail the automation risks faced by different groups of workers.

    Release date: 2020-06-29

  • Articles and reports: 11F0019M2020009
    Description:

    The main objective of this paper is to determine whether the immigration status of the owner of a small or medium-sized enterprise (SME) affects the likelihood of a company implementing an innovation. This paper uses data from a survey of Canadian small and medium-sized enterprises (SMEs) in 2011, 2014 and 2017, and asks whether immigrant-owned SMEs were more likely to innovate during the three years prior to the survey than those owned by Canadian-born individuals.

    Release date: 2020-06-09

  • Articles and reports: 11F0019M2020008
    Description:

    Multinationals play an important role in the world economy because they are larger, innovate more, are more productive and pay higher wages compared with non-multinationals. Multinationals (i.e., firms that have established affiliates or subsidiaries in other countries) have played an increasingly important role in many economies. In Canada, multinationals accounted for only 0.8% of all enterprises in 2016, but they held 67% of all assets in the Canadian economy (Schaffter and Fortier-Labonté 2019). Given the importance of multinationals to the Canadian economy, it is essential for policy makers to understand the economic performance and productivity advantage of multinationals operating in Canada.

    To address policy-relevant research questions, a rich micro dataset covering all industries from 2000 to 2014 has been constructed for this study, using several administrative microdata files at Statistics Canada. This dataset is used to delve deeper into and estimate the productivity advantage of multinationals, including the selection and learning effects associated with multinationality. In addition, this study investigates whether and how research and development (R&D) investment contributes to the superior productivity performance of multinationals.

    Release date: 2020-05-26

  • Articles and reports: 11F0019M2020002
    Description:

    Labour productivity growth in the business sector in Canada started to decline in 2000, from 2.3% per year in the period from 1991 to 2000 to 1.0% per year in the period from 2000 to 2015. This paper examines how innovation, innovation diffusion across firms, and business dynamism affected the productivity slowdown.

    Release date: 2020-01-17

  • Articles and reports: 16-002-X201900100001
    Description: The manner in which Canadians conduct their daily activities can have a profound impact on their surroundings thereby compelling them to adapt their practices to be less harmful to the environment. This is even more of a reality for Canadian businesses as their operations are significant contributors to the amount of pollution and environmental pressures generated each year in Canada. For this reason, it is important to monitor the amount and the type of environmental protection that Canadian industry has undertaken over the years. The article highlights expenditures made by Canadian industry to protect the environment from industrial activities between 2006 and 2016. The main data source for this paper is the Environmental Protection Expenditures Survey (EPES), which is conducted every two years. Several graphs and a summary of findings are included.
    Release date: 2019-12-18

  • Articles and reports: 13-604-M2015078
    Description:

    The increased pace of globalization has brought about many changes in both the Canadian and world economies. One important change has been the increased prevalence of global value chains which sees production processes spread out around the globe, across vertically integrated multinationals or via arm’s length trade. This paper focuses on two types of global production arrangements, namely, the case of merchanting and of goods send abroad for processing, with the limiting case of factoryless goods producers. Using the results of the 2009 and 2012 Survey of Innovation and Business Strategy, this report aims to provide an indication of the degree and nature of outsourcing among Canadian firms, with respect to these global production arrangements.

    Release date: 2015-05-22

  • Journals and periodicals: 88-202-X
    Description:

    This on-line report summarizes research and development (R&D) activities performed and funded by Canadian business enterprises and industrial research institutes and associations. The data are used, for instance, to plan and evaluate R&D tax incentive programs, to provide indicators of the state of industrial innovation and to complement national aggregates for scientific R&D expenditures and personnel. Among the topics covered are current and capital expenditures on research and development, energy R&D expenditures by area of technology, R&D expenditures as a percentage of company revenues, sources of funds for intramural R&D, personnel engaged in R&D, and foreign payments made and received for technological services. Most historical tables are presented for the latest five years and disaggregated by 46 industrial groupings, size of R&D program, employment size, revenue size, country of control, and by province.

    Release date: 2015-04-27
Reference (35)

Reference (35) (0 to 10 of 35 results)

  • Classification: 89-26-0004
    Description: This classification system was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect, and disseminate data related to research and development in Canada. The Canadian Research and Development Classification (CRDC) first official version was the 2020 Version 1.0, now being replaced by CRDC Version 2.0. The CRDC is revised within 2 years for minor changes, and every five years for major revisions. CRDC 2020 Version 2.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1,671 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).
    Release date: 2024-04-30

  • Classification: 12-604-X
    Description:

    The concordance table provides a link between data tables and the survey questions from the Survey of Innovation and Business Strategy (SIBS).

    Release date: 2021-07-30

  • Surveys and statistical programs – Documentation: 2936
    Description: This survey was sponsored by the Ontario Ministry of Economic Development and Trade.

  • Surveys and statistical programs – Documentation: 4201
    Description: The Annual Survey of Research and Development in Canadian Industry collects research and development (R&D) expenditures and personnel data used to monitor science and technology related activities of businesses and industrial non-profit organizations in Canada.

  • Surveys and statistical programs – Documentation: 4204
    Description: The Annual Survey of Research and Development of Canadian Private Non-Profit Organizations produces useful statistical information to monitor science and technology activities in Canada and to support the development of science and technology policy.

  • Surveys and statistical programs – Documentation: 4205
    Description: This survey collects in-house and outsourced research and development expenditures on energy-related technology of businesses and industrial non-profit organizations in Canada.

  • Surveys and statistical programs – Documentation: 4206
    Description: This annual survey collected data in all areas of technology, by Canadian firms operating in the petroleum industries.

  • Surveys and statistical programs – Documentation: 4208
    Description: This survey collects detailed expenditure and full-time equivalent personnel data on the scientific activities of provincial research organizations.

  • Surveys and statistical programs – Documentation: 4209
    Description: These statistical estimates cover scientific and technological (S&T) activities of the provincial government sector, except for provincial research organizations (PRO) which are surveyed separately (see record number 4208).

  • Surveys and statistical programs – Documentation: 4210
    Description: These statistical estimates cover scientific and technological (S&T) activities of the provincial government sector, except for provincial research organizations (PRO) which are surveyed separately (see record number 4208).
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