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Description: This study compares the Government of Canada’s direct and indirect measures to support R&D, as captured by business innovation and growth support (BIGS) programs and the Scientific Research and Experimental Development (SR&ED) tax incentive program. BIGS and SR&ED are two central instruments that the Canadian government uses to stimulate R&D expenditures in the business sector.

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).

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.

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.

Description: Percentage of enterprises where the use of clean technologies was related to environmental protection, sustainable resource management or adapted goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Environmental protection includes air and environment protection or remediation; waste management, reduction or recycling; and water or wastewater treatment. Sustainable resource management includes alternative fuels; non-emitting energy supply; bio-products; smart grid; energy storage; energy management and efficiency improvements; water management or recycling; agriculture, aquaculture, forestry or biodiversity improvements; and sustainable mining. Adapted goods include energy-efficient transportation, energy-efficient equipment or appliances, and advanced or lightweight materials.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

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).

Description:

Percentage of enterprises for which specific long-term strategies were the most important, by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. The most important long-term strategies include main focus on good or service positioning, main focus on low-price and cost leadership, and good or service positioning and low-price and cost leadership are equally important.

Description:

Percentage of enterprises for which specific statements best described their strategic focus regarding goods or services (products), by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. Statements that best described enterprises’ strategic focus regarding goods or services (products) include maintain sales of existing goods or services, expand the sales of existing goods or services, introduce new or significantly improved goods or services regularly, and don’t know.

Description:

Percentage of enterprises that sold only goods, only services or both goods and services, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

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).

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.

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.

Description: Percentage of enterprises where the use of clean technologies was related to environmental protection, sustainable resource management or adapted goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Environmental protection includes air and environment protection or remediation; waste management, reduction or recycling; and water or wastewater treatment. Sustainable resource management includes alternative fuels; non-emitting energy supply; bio-products; smart grid; energy storage; energy management and efficiency improvements; water management or recycling; agriculture, aquaculture, forestry or biodiversity improvements; and sustainable mining. Adapted goods include energy-efficient transportation, energy-efficient equipment or appliances, and advanced or lightweight materials.

Description:

Percentage of enterprises for which specific long-term strategies were the most important, by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. The most important long-term strategies include main focus on good or service positioning, main focus on low-price and cost leadership, and good or service positioning and low-price and cost leadership are equally important.

Description:

Percentage of enterprises for which specific statements best described their strategic focus regarding goods or services (products), by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. Statements that best described enterprises’ strategic focus regarding goods or services (products) include maintain sales of existing goods or services, expand the sales of existing goods or services, introduce new or significantly improved goods or services regularly, and don’t know.

Description:

Percentage of enterprises that sold only goods, only services or both goods and services, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that produced or manufactured any of the goods that they sold, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that offered specific services to complement the sale of goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Complementary services include after-sales maintenance or repair, installation or implementation, training or technical support, after-sales condition monitoring or quality control, customization, distribution or transportation, leasing or rental agreements, and other services.

Description:

Percentage of enterprises that expanded capacity for specific services to complement the sale of goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a three-year observation period. Complementary services include after-sales maintenance or repair, installation or implementation, training or technical support, after-sales condition monitoring or quality control, customization, distribution or transportation, leasing or rental agreements, and other services.

Description:

Micro-level information on buildings and physical infrastructure is increasing in relevance to social, economic and environmental statistical programs. Alternative data sources and advanced analytical methods can be used to generate some of this information. This paper presents how multiple convolutional neural networks (CNNs) are finetuned to classify buildings into different types (e.g., house, apartment, industrial) using their street-view images. The CNNs use the structure of the façade in the building’s image for classification. Multiple state-of-the-art CNNs are finetuned to accomplish the classification task. The trained models provide a proof of concept and show that CNNs can be used to classify buildings using their street-view imagery. The training and validation performance of the trained CNNs are measured. Furthermore, the trained CNNs are evaluated on a separate test set of street-view imagery. This approach can be used to augment the information available on openly accessible databases, such as the Open Database of Buildings.

Description:

The entrepreneurship indicator database provides data describing the dynamics of a subset of Canadian enterprises, such as the number of active enterprises with one or more employees, the number of high-growth enterprises, the number of births and deaths of active enterprises with one or more employees, the survival of newly created enterprises, and more.

Description:

This study examines the economic footprint created by the Canadian research and development pharmaceutical sector on the Canadian economy in 2018, including a focus on the contribution of Innovative Medicines Canada’s members. While the impact of the sector’s medical research is well known, less known are the economic impacts of the sector on the Canadian economy, such as the value generated, the jobs supported and the investments made.

Description:

The federal government offers business innovation and growth support through program streams managed by its departments and agencies. In 2017, enterprises in the manufacturing sector accounted for almost one-quarter of the beneficiaries of this support and received almost one-third of the total value of support (Statistics Canada, 2020). The objective of this analysis is to assess the impact of federal growth and innovation support on the employment and revenue of beneficiary enterprises in the manufacturing sector between 2007 and 2017. This analysis suggests that enterprises that received federal support for growth and innovation experienced stronger employment and revenue growth relative to non-beneficiary enterprises. Over the three years following receipt of support, employment growth for beneficiary enterprises averaged 1.8% per year while, on average, enterprises that did not receive support experienced employment declines. Over the same period, the average annual revenue growth of beneficiary enterprises was higher than that of non-beneficiary enterprises by 4.6 percentage points.

Description:

Over the past two decades, Canadians have embraced digital technologies at an unprecedented pace and breadth. The objective of this study is to develop statistical indexes to measure the intensity of digitalization in Canadian industries. Because of the ubiquitous presence of digitalization and businesses’ and individuals’ increasing reliance on digital products and services, it is essential to measure the digitalization in the Canadian economy to better understand its impact so that governments, businesses and other stakeholders can make informed decisions.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

In recent years, technological advancements in artificial intelligence and machine learning have broadened the realm of tasks that have the potential to be accomplished through automation technology. Consequently, these developments have raised questions about the future of work. Debate on this issue has focused primarily on the risk of job loss attributable to automation, with less attention given to how automation may change the nature of workers’ jobs. This study employs a task-based approach that shifts the focus from job replacement to changes in the nature of Canadians’ work. This approach views occupations as a set of tasks, allowing researchers to assess the effects of automation in the context of changes in occupational tasks.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.

Description: The purpose of this survey was to measure and develop a better understanding of the emerging contribution of biotechnology to the Canadian economy.

Description: The objective of the survey is to assure the availability of pertinent information to monitor science and technology related activities and to support the development of science and technology policy.

Description: The objective of the Survey of Advanced Technology is to collect important information about the extent to which Canadian enterprises use advanced technologies.

Description: The objective of the survey is to provide information on innovation, advanced technology and advanced practices being used in the construction and related industries.

Description: The survey provides information on companies developing new products and processes using biotechnologies.

Description: This survey is being conducted to measure the extent to which knowledge management practices are used or will be used by Canadian businesses.

Description: The objective of the survey is to produce new statistical information on the collection, use and disclosure of human genetic material in Canada.

Description: The objectives of the survey are to produce statistical information on the functional food and natural health product sector and a profile of firms engaged in functional food and/or natural health product related activities in Canada.

Description: The objective of this survey is to collect new statistical information on the nature and extent of product, process, marketing and organizational innovations in the Canadian food processing industry and on other emerging issues in the food processing industry;

Description: The 2015 Bioproducts Production and Development Survey collects information on the characteristics and activities of businesses in Canada that develop and/or produce bioproducts and that collect, separate or refine biomass used in bioproducts.