Survey of Electronic Commerce and Technology (SECT)

Detailed information for 2000





Record number:


The objective of this survey is to measure the use of various technologies by Canadian businesses and the extent to which the Internet is used to buy and sell goods and services.

Data release - April 3, 2001


The Survey of Electronic Commerce and Technology (SECT) measures the use of various information and communications technologies (ICTs) by Canadian businesses and the extent to which the Internet is used to buy and sell goods and services. The survey also measures the perceived benefits of conducting business over the Internet.

The information collected provides categorical data on the use of information and communication technologies (ICTs) (including the use of computers, the Internet, web sites) and electronic commerce among private and public sector enterprises.

Electronic commerce represents more than a technology; it is a pervasive phenomenon built around the applications of ICTs and plays a catalytic role impacting on every aspect of the value chain for products and services. Issues related to electronic commerce pose numerous challenges to both businesses and policy makers.

The data from this survey are used by businesses and policy makers to monitor the performance of the various ICTs and assess their impact on the economy and international organizations such as the Organization for Economic Co-operation and Development (OECD) to study the development and the influence of this sector on the global information economies.

Statistical activity

Science and technology (S&T) and the information society are changing the way we live, learn and work. The concepts are closely intertwined: science generates new understanding of the way the world works, technology applies it to develop innovative products and services and the information society is one of the results of the innovations.

People are looking to Statistics Canada to measure and explain the social and economic impacts of these changes.

The purpose of this Program is to develop useful indicators of S&T activity in Canada based on a framework that ties them together in a coherent picture.

Reference period: 12 month fiscal period for which the final day occurs on or between January 1st and December 31st of the reference year.

Collection period: November to February


  • Business and government internet use
  • Information and communications technology

Data sources and methodology

Target population

This survey covers most industrial sectors with the exception of local governments. The collection entity for the survey is the enterprise which is the organizational unit of a business that directs and controls the resources relating to its domestic organization and for which consolidated financial and balance sheet accounts are maintained. The implication is that the survey collects data on transactions that occur between enterprises, while it specifically excludes intra-firm transactions, i.e. Internet transactions that may occur between two establishments or companies within the same enterprise.

The industrial classification assigned to the enterprise engaged in electronic commerce is the industrial classification of the establishment with the highest value-added within that enterprise. For instance, if an Internet transaction were conducted in a retail establishment within a manufacturing enterprise, that activity would be classified as a sale of the manufacturing sector.


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

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which 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.

Data for a specific industry or variable may be suppressed (along with that of a second industry or variable) if the number of enterprises in the population is too low.

Data accuracy

While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting SECT estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: non-sampling and sampling.

Non-sampling error is not related to sampling and may occur for many reasons. For example, non-response is an important source of non-sampling error. Population coverage, differences in the interpretations of questions and mistakes in recording, coding and processing data are other examples of non-sampling errors.

Coverage error results from inadequate representation of the intended population. This error may occur during selection of the survey population, or during data collection and processing. In order to avoid such errors, a number of sources describing the population of the industry are used and compared.

Response error may be due to many factors, including faulty design of the questionnaire, interviewers' or respondents' misinterpretation of questions, or respondents' faulty reporting. Frequent changes in company personnel may also lead to response error. Several features are in place to help respondents complete the questionnaire, including logic and consistency checks, and a glossary of terms and concepts. Responses are compared from year to year and any significant deviations are queried by analysts to ensure their accuracy. However, even with these checks, the quality of data depends on the respondent's willingness to consult their records.

Non-response error occurs because not all respondents cooperate fully. To alleviate the impact on the survey, respondents are usually asked to provide key variables and the others are estimated.

Sampling error occurs because population estimates are derived from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. The sampling error is measured by a quantity known as the standard deviation. The latter indicates the expected variability of the estimate that would be produced if we sampled repeatedly. The actual value of the standard deviation is unknown, but it can be estimated from the sample.

When the estimates are disseminated, a scale distinguishes between the various qualities of accuracy. It combines the effect of sampling (using the CV) and the imputation rate (each imputed value adds to the uncertainty of the results). The scale is presented in the table below.


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