Survey of Intellectual Property Awareness and Use (IPAU)

Detailed information for 2019




One Time

Record number:


This survey measures the general familiarity of owners and managers of enterprises across selected industries with intellectual property (IP). The purpose of collecting this information is to help evaluate impacts of Canadian Government programs to educate and raise awareness on the value of intellectual property.

Data release - February 18, 2021


This survey will provide statistically valid data on awareness and use of intellectual property. These data will be available by enterprise size (five size categories for all enterprises with employees), industry sector (15 sectors) and geography (Canada and four provinces or regions). The data provided will indicate the extent of awareness and use of intellectual property by demographic characteristics (such as gender and aboriginal status) of the business owner and/or senior executive managers.

These data will be used by the federal government to develop programs and policies to enhance awareness of intellectual property and to determine if particular demographics should be targeted for outreach.

These data could also be used by researchers, alone or added to other data files, to conduct research on the impact of the use of IP as a business strategy.

Reference period: Calendar year 2019; Period of 2017 to 2019

Collection period: Pre-contact: September 2019, Main survey: November 2019 to mid-February 2020


  • Science and technology

Data sources and methodology

Target population

The target population for the Intellectual Property Awareness and Use survey is limited to enterprises within the following 15 sectors defined according to the North American Industry Classification System (NAICS, Statistics Canada, 2017):

- Agriculture, forestry, fishing and hunting (11)
- Mining, quarrying, and oil and gas extraction (21)
- Utilities (22)
- Construction (23)
- Manufacturing (31-33)
- Wholesale trade (41)
- Retail trade (44-45)
- Transportation and warehousing (48-49)
- Information and cultural industries (51)
- Finance and insurance (52)
- Real estate and rental and leasing (53)
- Professional, scientific and technical services (54)
- Management of companies and enterprises (55)
- Administrative and support, waste management and remediation services (56)
- Information and Communication Technology (ICT)

Instrument design

The IPAU uses an electronic questionnaire (EQ). The questionnaire was developed in collaboration with subject matter experts at the Canadian Intellectual Property Office (CIPO). EQs are the principal mode of collection, and these were tested with enterprise respondents in English and French to confirm respondents' understanding of terminology, concepts and definitions, as well as their ability to provide the requested data and to navigate the EQ applications. Questionnaire content testing occurred in March 2019 in English in Ottawa and Toronto and in French in Gatineau and Montreal. This testing concentrated on validating respondents understanding of concepts, questions, terminology, the appropriateness of response categories and the availability of requested information.


This is a sample survey with a cross-sectional design.

The sample size for the survey is around 11,700 enterprises that is selected from a target population of approximately 600,000 enterprises, with an expected response rate of 50% by stratum. The target standards errors (S.E.) for the calculation of proportions are defined as follows:

- S.E. of 5.5% for 2-digit NAICS (11; 21; 22; 23; 31-33; 41; 44-45; 48; 49; 51; 52 excluding 521; 53; 54; 55; 56) by business size
- S.E. of 7.5% for 2-digit NAICS (11; 21; 22; 23; 31-33; 41; 44-45; 48; 49; 51; 52 excluding. 521; 53; 54; 55; 56) by economic region

An independent sample within units from the Information and Communications Technologies (ICT) population is selected at the national level. The sample is around 160 enterprises.

Another independent sample of approximately 160 units is selected among the population of "clean technology" enterprises.

Sampling unit

Stratification method

- Industry groups: NAICS 11, 21, 22, 23, 31-33, 41, 44-45, 48-49, 51, 52 (excluding 521), 53, 54, 55 and 56
- Size: 1 to 4 employees, 5 to 19 employees, 20 to 99 employees, 100 to 499 employees, 500 or more employees
- Geography: Atlantic Canada, Quebec, Ontario, the rest of Canada

Data sources

Data collection for this reference period: 2019-11-06 to 2020-02-21

Responding to this survey is mandatory.

Data are collected directly from survey respondents and extracted from administrative files.

The data will be collected through an electronic questionnaire (EQ), with non-response follow-up and failed edit follow-up for priority questions.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Error detection is an integral part of both data collection and data processing activities. Automated edits are applied to data records during collection to identify reporting errors. During data processing, other edits are used to automatically detect errors or inconsistencies that remain in the data following collection. Incoherent data are corrected based on responses to key "gate" questions.


In the case of partial non-response, imputation is used to fill in information not provided by the respondent. Imputation makes it possible to have a complete set of data that were provided by respondents during the collection period.

The imputation of non-response is performed using the Banff generalized system, a set of specialized SAS procedures developed at Statistics Canada, to satisfy the edit and imputation requirements of a survey.

Random donor imputation is performed within classes defined by a combination of industry groups, enterprise size and region in up to four rounds.

In cases where random donor imputation is not appropriate deterministic imputation is used where missing values are replaced with pre-determined values from external sources, or logically imputed by the questionnaire flow.


The response values for sampled units were multiplied by a final weight in order to provide an estimate for the entire population. The final weight was calculated using a certain number of factors, such as the probability for a unit to be selected in the sample, and adjustment of the units that could not be contacted or that refused to respond. Using a statistical technique called calibration, the final set of weights is adjusted in such a way that the sample represents as closely as possible the entire population.

Sampling error was measured by the standard error (SE) for proportions and by the coefficient of variation (CV) which represents the proportion of the estimate that comes from the variability associated to it. The SEs and CVs were calculated and are indicated in the data tables by quality flags.

Quality evaluation

Prior to publication, quality assurance measures were followed at each stage of data collection and analysis to monitor the quality of the data.

All tables were examined for anomalies and inconsistencies, and quality indicators (quality rating code) are published with data.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

Errors may occur for various reasons during the collection and processing of the data. For example, non-response is one possible source of error. Under or over-coverage of the population, differences in interpretation of questions and mistakes in recording and processing data are other possible errors. To the maximum extent possible, these errors are minimized through careful design of the survey questionnaire and verification of the survey data.

The data accuracy indicators used are the standard error and the coefficient of variation. The standard error is a commonly used statistical measure indicating the error of an estimate associated with sampling. The coefficient of variation is the standard error expressed as a percentage of the estimate.

Sampling error, response rate and imputation rate are combined into one quality rating code. This code uses letters that range from A to F, where A means the data is of excellent quality and F means it is unreliable. Estimates with a quality of F will not be published. Details on these quality rating codes can be requested and should always be taken into consideration when analyzing the data.

Response rates
The overall unweighted response rate for this survey was 80.3%.

Non-response bias
In addition to increasing variance, non-response can result in biased estimates if non-respondents have different characteristics from respondents. Non-response is addressed through survey design, respondent follow-up, reweighting, and verification and validation of microdata. Other indicators of quality such as the response rate are also provided.

Coverage error
Coverage errors consist of omissions, erroneous inclusions, duplications and misclassifications in the survey frame.

The Business Register (BR) was used as the frame. The BR is a data service centre updated through a number of sources including administrative data files, feedback received from conducting Statistics Canada business surveys and profiling activities including direct contact with companies to obtain information about their operations and Internet research findings.

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