Innovations in enterprises
1. Contact
Responsible agency
Unit
Contact person
Position
Email (agency)
Phone
2. Statistical presentation
Data description
Innovation is implementation of new or significantly improved product (good or service) or business process in the enterprise. Innovation is novelty in enterprise, however, the enterprise may not be the first to implement this innovation.
Data on innovation in enterprises are used to assess number of innovative active enterprises, their share among active enterprises, number of innovative active enterprises by kind of activity, turnover and number of employees in innovative active enterprises, number and share of innovative active enterprises by kind of innovation, as well as total expenditure on innovation.
Statistical concepts and definitions
Statistical unit
Enterprises.
Statistical population
All economically active statistical units – merchants (individual merchants and commercial companies) with 10 employees or more, and market activity enterprises in the NACE Rev. 2 sections B, C, D, E, H, J, K and in the NACE Rev. 2 division 46 and divisions 71, 72 and 73 are to be covered.
3. Institutional mandate
Legal acts and other agreements
Commission Implementing Regulation (EU) No 995/2012 laying down detailed rules for the implementation of Decision No 1608/2003/EC of the European Parliament and of the Council concerning the production and development of Community statistics on science and technology.
4. Accessibility and clarity
On-line database
5. Comparability
Comparability - geographical
EU data on Eurostat website
Section - Community innovation survey
Length of comparable time series
The methodology used to produce innovation statistics is based on the Oslo Manual updated in 2018, therefore not all statistics is comparable over time.
6. Coherence
Coherence- cross domain
N/A
7. Statistical processing (data source etc.)
Source data
Data source used to acquire the data is survey on innovations in enterprises (Community Innovation Survey questionnaire (2-innovations)).
Data collection
At the moment when sample is built, the sample frame includes all statistical units meeting the description of the target population. Sample frame was built with the help of Statistical Business Register information. Sample size was set by using Neyman's optimal allocation. The sample was built as stratified simple random sampling.
Number of respondents in the Community Innovation Survey:
Year | Sample size |
2018-2020 | 3 108 |
2016-2018 | 3 103 |
2014-2016 | 3 103 |
2012-2014 | 1 501 |
2010-2012 | 1 573 |
2008-2010 | 1 358 |
Data compilation
Community Innovation Survey in Latvia is conducted basing on common Eurostat methodology and is sample survey.
Information on respondents included in the business sector sample is extrapolated by using weight given to each sample unit.
Estimation calculations are based on the Horvitz-Thompson estimator.