Survey of Knowledge Management Practices

Detailed information for 2001

Status:

Inactive

Frequency:

One Time

Record number:

5001

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

Data release - March 21, 2002

Description

The primary objectives of this new survey are to determine what business practices are used to support the sharing, transfer, acquisition and retention of knowledge by Canadian firms and whether firms find these practices effective.

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.

Subjects

  • Business adaptation and adjustment
  • Business performance and ownership
  • Innovation
  • Science and technology

Data sources and methodology

Target population

The Universe comprises of Canadian Enterprises in the following North American Industry Classification System (NAICS) sectors:
113: Forestry and Logging
325: Chemical Manufacturing
336: Transportation Equipment Manufacturing
417: Machinery Equipment and Supplies Wholesaler- Distributors, and
5416: Management, Scientific and Technical Consulting Services

Instrument design

Statistics Canada conducted this pilot survey on Knowledge Management Practices as part of an international initiative headed by the Organisation for Economic Co-operation and Development. Canada was the lead country piloting this survey. Other countries that in 2001 undertook pilot surveys based on the contents of the Knowledge Management Practices' questionnaire were Denmark and Germany.

The questionnaire for the Knowledge Management Practices Survey was designed by the Science, Innovation and Electronic Information Division of Statistics Canada in collaboration with: the Centre for Educational Research and Innovation (Organisation for Economic Co-operation and Development); the Ministry of Trade and Industry and the Center for Ledelse (Denmark); the Fraunhofer Institute for Systems and Innovation Research (Germany); Service des études et des statistiques industrielles and Institut national de la statistique et des études économiques (France); the Office of National Statistics (the United Kingdom); Innovazione tecnologica e ricerca scientifica (Italy); Statistics Netherlands (The Netherlands); Statistics Sweden (Sweden); and the Institute for Knowledge Management (United States of America).

Statistics Canada undertook cognitive testing of the questionnaire through extensive interviews with individual firms in both official languages to ensure that the questions were well understood. Feedback from respondents was incorporated into the questionnaire design.

Respondents completed paper and pencil questionnaire mail-out / mail- or fax- back with some questionnaire completed over the telephone by interviewers.

Questions on use/planned use of management practices; opinion using scales; mainly closed with opportunity provided for respondents to comment.

Questionnaire was tested with 30 firms in May/June 2001 and revised following questionnaire testing. Pilot survey completes the questionnaire testing.

Sampling

This is a sample survey.

Data sources

Data collection for this reference period: September 2001 to December 2001

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Pre-contact with sample to ensure contact name, title and industrial classification occurred in September 2001. Mail-out to 405 firms started late September 2001. Interviewer follow-up began in October with interviewers offering to complete the questionnaire over the telephone.

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

Error detection

Edits established to verify the consistency of the data once it was received were applied at the microdata level.

Imputation

Given that this is a pilot survey, imputation was used only for mandatory questions, which makes the questionnaire easier to evaluate. Donor imputation (hot deck method) was used in connection with the above-mentioned edits. Each question was imputed independently.

Estimation

Since this was a two-phase sample design, adjustment for non-response was carried out in two phases. Reweighting took place for each phase. The weight share method was used to obtain estimates at the enterprise level, since the statistical units for the first phase were at the enterprise level. Estimates and variances were calculated using direct methods associated with this type of sample design.

Quality evaluation

The imputation rate for each question is available.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.

Microdata is available to Statistics Canada employees only. A flat file from which all respondent identifiers have been removed is available for tabulation purposes.

Respondents are protected by the data release rules in place concerning data quality and number of unweighted enterprises required per cell to release information.

Data accuracy

Variance was calculated for each estimate produced. A quality rating was derived from this variance.

Data reliability

The reliability of the data has been assessed using the following convention:

Code Rating Standard Error
A Very good < 2.5%
B Good > 2.5% and < 7.5%
C Good to poor - use with caution > 7.5% and < 15.0%
D Very poor - may not be acceptable > 15.0%

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