1.1. Contact organisation
Statistics Sweden
1.2. Contact organisation unit
Economic Statistics Department
Section for Innovation, Business production and Research
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
SCB
Solna strandväg 86
171 54 Solna, Sweden
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
1 December 2025
2.2. Metadata last posted
1 December 2025
2.3. Metadata last update
1 December 2025
3.1. Data description
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – design improvement in 2018.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
3.2. Classification system
Indicators related to the enterprises are classified by country, economic activity (NACE Rev. 2), size class of enterprises and type of innovation.
The main typology of classification of enterprises in reference to innovation is the distinction between innovation-active enterprises (INN) and not innovation-active enterprises (NINN).
The enterprise is considered as innovative (INN) if during the reference period it successfully introduced a a) product or a) business process innovation, c) completed but not yet implemented the innovation, d) had ongoing innovation activities, e) abandoned innovation activities or was f) engaged in in-house R&D or R&D contracted out. Non-innovative (NINN) enterprises had no innovation activity mentioned above whatsoever during the reference period.
3.3. Coverage - sector
CIS covers main economic sectors accordning to NACE Rev.2 broken down by size class of enterprises and type of innovation activity.
3.3.1. Main economic sectors covered - NACE Rev.2
In accordance with the Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, the following sectors of the economic activity are included in the core target population: NACE Sections B, C, D, E, H, J, K, and Divisions 46, 71, 72 and 73.
3.3.1.1. Main economic sectors covered - NACE Rev.2 - national particularities
The following NACE are additionally covered in the Swedish CIS: NACE section F (41-43) construction, NACE division 85 Education and 86 Human health services.
3.3.2. Sector coverage - size class
In accordance with Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, only the enterprises with 10 or more employed persons (sum of employees and self-employed persons) are included in the core target population.
3.3.2.1. Sector coverage - size class - national particularities
No deviations.
3.4. Statistical concepts and definitions
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
3.5. Statistical unit
Data is produced for the statistical unit enterprise. Sweden has implemented the representative approach, where we pick a representative (legal unit) from complex enterprises in the sample. The legal unit is the reporting unit for the enterprise, and the answers from the reporting unit is assumed to correctly represent the values for the entire enterprise.
The representative unit is chosen based on specific criteria in three steps. Firstly, the legal unit with the NACE category closest to the enterprise is chosen. Secondly, if there are several legal units with the same NACE category the unit with the highest number of employed persons is chosen. Thirdly, if there still is more than one legal unit left for an enterprise the unit with the highest turnover is chosen.
The observation unit was the legal unit, while sampling was carried out at Statistical Unit Enterprise level.
3.6. Statistical population
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
3.7. Reference area
Sweden SE. Stratification on NUTS2 (only enterprises with less than 250 employees) has been conducted, regional statistics is available.
The CIS2022 regional data are calibrated at the legal unit level.
3.8. Coverage - Time
Several rounds of Community Innovation Survey have been conducted so far at two-year interval since the end of the 90’s.
3.8.1. Participation in the CIS waves
| CIS wave | Reference period | Participation (Yes/No) | Comment (deviation from reference period) |
|---|---|---|---|
| CIS2 | 1994-1996 | Yes | |
| CIS3 | 1998-2000 | Yes | |
| CIS light | 2002-2003* | Yes | |
| CIS4 | 2002-2004 | Yes | |
| CIS2006 | 2004-2006 | Yes | |
| CIS2008 | 2006-2008 | Yes | |
| CIS2010 | 2008-2010 | Yes | |
| CIS2012 | 2010-2012 | Yes | |
| CIS2014 | 2012-2014 | Yes | |
| CIS2016 | 2014-2016 | Yes | |
| CIS2018 | 2016-2018 | Yes | |
| CIS2020 | 2018-2020 | Yes | |
| CIS2022 | 2020-2022 | Yes |
*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003
3.9. Base period
Not relevant.
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
6.1. Institutional Mandate - legal acts and other agreements
The CIS is based on the Commission Implementing Regulation (EU) 2022/1092, implementing Regulation (EU) 2019/2152 of the European Parliament and of the Council on the production and development of Community statistics on science and technology.
This Regulation establishes innovation statistics on a statutory basis and makes the delivery of certain variables compulsory e.g. innovation activities, cooperation, development, expenditures and turnover (see the Regulation). Each survey wave may additionally include further variables.
In addition, the Regulation defines the obligatory cross-coverage of economic sectors and size class of enterprises.
6.1.1. National legislation
In addition to the resulation and implementeting decision described above the CIS is a part of the Swedish Official Statistics. Quality and availability of the CIS is therefore regulated in the Law of Official Statistics of Sweden (2001:99).
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
Confidentiality is regulated in the 24th chapter, 8 paragraph of the Swedish Public Access to Information and Secrecy Act (2009:400). To protect enterprises confidential information in the official statistics, Statistics Sweden is obliged to ensure the nondisclosure of these enterprises, directly and indirectly.
7.2. Confidentiality - data treatment
For frequency tables, the rule applied is the value of a cell should be above a certain value n, othervise the cell is considered sensitive.
For magnitude tables, the rule applied is the p% rule. The formula for the p% rule is as follows:
The cell is considered as sensitive if X-x2-x1
8.1. Release calendar
Release dates for CIS2022:
- National publication: 09 November 2023
- National report publication: 05 June 2024
- National microdata: 04 January 2024
The planned releases of statistics in Sweden is available in the publication calendar as well on the product page for the specific product, in this case the CIS.
8.2. Release calendar access
- The national publishing calendar: Publishing calendar (scb.se).
- The product page for the CIS: Community Innovation Survey (scb.se).
8.3. Release policy - user access
Statistics Sweden releases data on the planned dissemination date in the publishing calender at 8 am. Data is made available to all users at the same time. The publication of data in the statistical database is accompanied with a short statistical news article. Users are able to subscribe to our statistical news, they then receive an email when something regarding that product is released.
CIS is conducted and disseminated at two-year interval in pair years.
Accessibility and clarity refer to the simplicity and ease for users to access statistics using simple and user-friendly procedure, obtaining them in an expected form and within an acceptable time period, with the appropriate user information and assistance: a global context which finally enables them to make optimum use of the statistics.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Dissemination and access | Availability | Comments, links, ... |
|---|---|---|
| Press release | X | A statistical news was published 09 November 2013, free of charge.
|
| Access to public free of charge | X | Access to articles, press releases/statistical news, statistical database and other publications are available free of charge on the product page |
| Access to public restricted (membership/password/part of data provided, etc) | X | Microdata is restricted from public access. Microdata is only available in the Swedish microdata database (MONA - Microdata Online Access). After granted application through Mona microdata is available. MONA – Statistics Sweden’s platform for access to microdata (scb.se) |
10.2. Dissemination format - Publications
- Online database (containing all/most results): X
All official statistics are available in the statistical database. Statistical database - Select table (scb.se)
- Analytical publication (referring to all/most results): X
There is a report available analysing the general results of the CIS2022 survey. The report is written in Swedish with an English summary. Large enterprises in the industry sector the most innovative in 2020-2022 (scb.se)
- Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect): X
An analytical report on the results of the CIS2022 was published 05 June 2024. The report is written in Swedish with an English summary. Community Innovation Survey in Sweden 2020-2022 (scb.se).
A report on regional CIS statistics will be published during fall 2024.
10.3. Dissemination format - online database
The statistical database is available free of charge Statistical database - Select table (scb.se).
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
At national level, microdata is available in the MONA-database MONA – Statistics Sweden’s platform for access to microdata (scb.se)
The MONA system provides secure access to microdata at Statistics Sweden via password. This service is not free of charge.
Microdata is also transmitten to Eurostat, and there made available via Eurostat SAFE center.
10.4.1. Dissemination of microdata
| Mean of dissemination | Availability of microdata | Comments, links, ... |
|---|---|---|
| Eurostat SAFE centre | X | |
| National SAFE centre | X* | MONA – Statistics Sweden’s platform for access to microdata (scb.se) |
| Eurostat: partially anonymised data (SUF) | ||
| National: partially anonymised data |
*Microdata is availabe to researchers using MONA-database (Microdata Online Access). The MONA system provides secure access to microdata at Statistics Sweden. Not free of charge.
10.5. Dissemination format - other
No other means of dissemination.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
Statistics Sweden provides documents on the statistics and microdata by describing the quality as well as the producing and processing of data. Along with the semiannual dissemination of the CIS, a report on the methodology of the CIS is published.
“The Process of Producing the Statistics” (Statistikens framställning -Innovation i företagssektorn -Community Innovation Survey (CIS) (scb.se)), a description of the process of producing the Community Innovation Survey. Only available in Swedish.
All documents can be found at the Community Innovation Survey’s homepage (only in Swedish - Innovation i företagssektorn (scb.se)).
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
Statistics Sweden provides documents on the statistics and microdata by describing the quality as well as the producing and processing of data. Along with the semiannual dissemination of the CIS, a report on the quality of the CIS is published.
“Quality Declaration and Description of the Statistics” (Kvalitetsdeklaration, Innovation i företagssektorn - Community Innovation Survey (CIS) (scb.se)), a description of the quality of the CIS statistics in accordance with the Swedish Law of Official Statistics (2001:99). Only available in Swedish.
All documents can be found at the Community Innovation Survey’s homepage (only in Swedish -Innovation i företagssektorn (scb.se)).
11.1. Quality assurance
The Swedish quality assurance framework is based on the Regulation No 223/900 of the European Parliament and of the Council. The regulation specifies seven quality criteria which the European statistic should follow to ensure coherence and comparability in the ESS (European Statistical System). The Swedish Law of Official Statistics (2001:99), under which the CIS is regulated, specifies the same quality criteria. The seven criteria are:
- Relevance;
- Accuracy;
- Timeliness;
- Punctuality;
- Accessibility and clarity;
- Comparability;
- Coherence.
To uphold high quality in the Swedish CIS the NSI follows the principles listed above by reducing uncertainties, such as sampling error, measurement error, unit- and item non-response, amongst other things. Statistics Sweden follows the European Statistics Code of Practice.
In addition, the Swedish NSI evaluates the quality of each survey round in a national quality report, which is then published on the CIS homepage (Kvalitetsdeklaration, Innovation i företagssektorn - Community Innovation Survey (CIS) (scb.se)). Only available in Swedish.
11.2. Quality management - assessment
The overall quality is considered good.
The methodology used is based on the recommendations given in the fourth edition of the Oslo Manual. The quality is also assured by following the European Statistics Code of Practice as well as the laws and regulations stated above (11.1 Quality assurance).
For the CIS2022 we have updated the national questionnaire to minimize deviations from the HDC. Currently we have a project to ensure harmonisation between CIS and R&D in the business enterprise sector in regards to R&D expenditure.
12.1. Relevance - User Needs
User needs and requests are mostly voiced by the User Council for Statistics on Research and Development in Sweden (Användarrådet för FoU-statistik (scb.se)). The council consists of representatives from universities, research institutes as well as Swedish authorities and ministries, which represents some of the users of the Community Innovation Survey. The council is primarily for the R&D statistics but requests on Innovation statistics are also collected through this forum.
Specific requests from users are collected, within and outside the council, and thereafter analysed based on user demand, cost, and relevance.
12.1.1. Needs at national level
| User group | Short description of user group | Main needs for CIS data of the user group Users’ needs |
|---|---|---|
| 1. Institutions - European level | The European comission (DG RI) | Innovation Scoreboard Regional Innovation Scoreboard |
| 1. Institutions - International organisations | OECD | |
| 1. Institutions - National level | Ministry of finance | |
| 1. Institutions - Regional level | Municipalities and regional councils | |
| 2. Social actors | ||
| 3. Media | International, national or regional media specialised or for the general public | Key indicators |
| 4. Researchers and students | Researcers | Microdata |
| 5. Enterprises or businesses |
12.2. Relevance - User Satisfaction
Statistics Sweden has not conducted a user satisfaction survey since 2012. User satisfaction and needs are discussed within the User Council for Statistics on Research and Development in Sweden, mentioned in 12.1 Relevance - User Needs.
12.3. Completeness
All mandatory indicators are included and published in national CIS as well as transmitted to Eurostat. Voluntary indicators that have been included in the national CIS are also published nationally and transmitted to Eurostat.
12.3.1. Data completeness - rate
Not requested.
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
13.2. Sampling error
Restricted from publication
13.2.1. Sampling error - indicators
The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).
CV= Coefficient of variation (%) = 100 * (Square root of the estimate of the sampling variance) / (Estimated value)
Formula:
where
and
13.2.1.1. Coefficient of variations for key variables
Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 or more employed persons
| NACE | Size class |
(1) |
(2) |
(3) |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total |
1.8% |
2.9% |
0.3% |
| Core industry (B_C_D_E - excluding construction) | Total |
2% |
2.4% |
0.4% |
| Core Services (46-H-J-K-71-72-73) | Total |
2.5% |
4.4% |
0.4 % |
(1) = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT)
(2) = Coefficient of variation for the turnover of product innovative enterprises with new or improved products (TUR_PRD_NEW_MKT), as a percentage of total turnover of product innovative enterprises [TOVT,INNO_PRD].
(3) = Coefficient of variation for percentage of product and/or process innovative enterprises (incl. enterprises with abandoned and or on-going activities) involved in any innovation co-operation arrangement [COOP_ALL,INN], as a percentage of innovative enterprises (INN).
13.2.1.2. Variance estimation method
Horvitz-Thompson is used for variance estimation. The sample weights Nh/nh has been adjusted with nh/nhR in each stratum.
For quantitative variables, the GREG estimator is used for variance estimation.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors (or frame errors) are due to divergences between the target population and the frame population. The frame population is the set of target population members that have a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under covered groups of the target population
The target population is collected from the National Business Register and is placed in a system for coordinated sampling (SAMU). From the frame population in SAMU the sample for the CIS is drawn. The frame population constitutes as a snapshot of the National Business Register when the system (SAMU) is updated. - Therefore, under coverage or over coverage may occur. Under covered groups of the target population consists of newly established enterprises, that weren’t registered when the system (SAMU) was updated.
Over coverage in the target population is the inclusion of enterprises that, after the target population was established, has abandoned or shut down their operations. In the CIS2022 sample (core NACE) 15 enterprises were registered as over coverage.
13.3.1.4. Coverage errors in coefficient variation
The effects of coverage errors due to the over coverage is not incorporated in the coefficient variations (see table in 13.2.1.1).
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.
13.3.2.1. Measures for reducing measurement errors
Statistics Sweden has taken several measures to reduce measurement errors. Definitions, questions, question related information and filters from the Oslo manual and the HDC has been incorporated in the national questionnaire. Further measures to increase the harmonisation between the HDC and the national questionnaire has been taken for CIS2022 by, among other things, adding a yes and no alternative to each question.
Every year the national questionnaire is tested by experts on survey methodology.
The web-questionnaire have controls for inconcistent answer, and in the processing of data we remove incostistent answers. The biggest enterprises are controlled separately and follow up contact is taken if necessary. After the CIS round is completed evaluation of the results and the data collection process is conducted to decrease the risk of measurement error in later CIS rounds.
13.3.3. Non response error
The CIS is mandatory in Sweden, all enterprises have an obligation to answer the survey. Statistics Sweden has the authority to fine enterprises who, without valid reasons, don’t answer the survey. Because of the survey being mandatory, the unit non-response is generally low. Statistics Sweden sends out two reminders via letter and contact chosen enterprises via email or phone. This reduces the non response.
Unit non-response is in the data processing assumed to be represented by the responding units within the same strata because of weight adjustment. This type of non response can cause bias. The random uncertainty is captured in the confidence interval, but the systematic uncertainty is unknown since we have not conducted a non response survey.
All questions in the CIS are mandatory, therefor, controls and filters are used to eliminate item non-response. An error in the system used for data collection created item non-response in questions that were subject to filters. For example follow up questions on product or process innovation and expenditure on R&D and innovation. To complete missing information the enterprises was initially contacted via email. Since we did not have the resources to contact all enterprises with item non-response Statistics Sweden used BANFF, created by Statistics Canada. Item non-response regarding variables on expenditure were manually imputed where the basis for imputation was the enterprises previously reported values from CIS2020 and Research and development in the business enterprise sector 2021.
13.3.3.1. Unit non-response - rate
See below.
13.3.3.1.1. Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
| NACE | Number of eligible units with no response | Total number of eligible units in the sample | Un-weighted unit non-response rate (%) | Weighted unit non-response rate (%) |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | 1107 | 5882 | 18.8 % | 20.9% |
| Core industry (B_C_D_E - excluding construction) | 527 | 2806 | 18.8% | 20.9% |
| Core Services (46-H-J-K-71-72-73) | 580 | 3076 | 18.9% | 20.9% |
The number of eligible units is the number of sample units, that ultimately indeed belong to the target population.
13.3.3.1.2. Maximum number of recalls/reminders before coding
Two reminders were sent via letter to the enterprises before they were coded as non-responding.
13.3.3.2. Item non-response - rate
See below.
13.3.3.2.1. Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons).
There were no item non-response for turnover in CIS2022 since it was collected from the National Business Register.
| Item non-response rate (un-weighted) (%) |
Imputation (Yes/No) |
If imputed, describe method used, mentioning which auxiliary information or stratification is used | |
|---|---|---|---|
| Turnover | n.a. |
n.a.=not applicable
Note: Turnover data are taken directly from administrative sources and are not requested from respondents.
13.3.3.2.2. Item non response rate for new questions
Item non-response rate for new questions in CIS t (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
| NEW QUESTIONS IN CIS 2022 | Inclusion in national questionnaire (Yes/No) | Item non response rate (un-weighted) (%) | Comments |
|---|---|---|---|
| 3.9 -- Reasons for not having more innovation activities | Yes | 0.2% | |
| 3.10 -- Reasons for having no innovation activities | Yes | 0.7% |
13.3.4. Processing error
For the CIS2022 there were two significant processing errors that resulted in revision of published data on a national level. Both of these errors were corrected before the tansmission of data to Eurostat.
The first error was related to the imputation for item non-response for the variables on turnover from product innovations. Statistics Sweden uses Banff for imputations. When imputing missing values for all three variables the system uses the same donor to ensure that it sums upp correctly. In this process the variable TUR_PRD_NINN was left out, resulting in it receiving a different donor. This resulted in an incorrect summation. The imputation step was corrected and the published table was revised. The impact of the error is difficult to asess, the table with incorrect data for TUR_PRD_NINN was published for four months before it was corrected. However, the main indicator used in this table is TUR_PRD_INN which was correct.
The second error was related to the logical corrections concerning indicators for cooperation and location of cooperation on innovation activities. An incorerct order of logical corrections in the data process led to inconsistent answer which also were published in the national database. The program was corrected and a new table was published approximately 6 months after publication. As for the previous described error the impact is difficult to asess.
All processing errors that occurred have been thouroghly documented and incorporated in the CIS2024 working process.
13.3.5. Model assumption error
Not requested.
Timeliness and punctuality refer to time and dates, but in a different manner.
14.1. Timeliness
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
14.1.1. Time lag - first result
Timeliness of national data – date of first release of national level:
- 09 November 2023 (9 November 2023)
- T+11
14.1.2. Time lag - final result
Not requested.
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Date of transmission of complete and validated data to Eurostat (Number of days between that date and 30 June 2024) : 29 May 2014 (29 May 2024), 31 days before 30 June 2024.
Comparability aims at measuring the impact of differences in applied statistical concepts and definitions on the comparison of statistics between geographical areas, non-geographical domains, or over time.
The coherence of statistical outputs refers to the degree to which the statistical processes by which they were generated used the same concepts (classifications, definitions, and target populations) and harmonised methods. Coherent statistical outputs have the potential to be validly combined and used jointly.
15.1. Comparability - geographical
Regional Statistics are produced for enterprises with less than 250 employees. Large enterprises, with 250 or more employees are not included in the regional statistics. The regional statistics is produced on NUTS 2 level.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. National questionnaire – compliance with Eurostat model questionnaire
In question 6.1 on environmental innovations, no distinction was made between ‘yes, significant’ and ‘yes, but insignificant’. Both answers are included as ‘yes, significant’.
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Questions not included in national questionnaire compared to HDC | Comment |
|---|---|
| 4.3 Tax incentives and allowances | Not included |
| 5.2 Purchase of machinery, equipment or software | Not included |
| 5.3 User requirements | Not included |
| 5.4 Fundamental changes to business model | Not included |
| 7.2 Teriary degree of persons employed | Not included |
| 7.4 Percentage of turnover | Not included |
| 7.5 Age of enterprise | Not included in the questionnaire, administrative data for 7.5A2 collected from BD. |
| 7.6 Enterprise expenditure | Not included |
| 7.7 Enterprise group | Not included in the questionnaire, administrative data collected from the National Business Register. |
| 7.8 Activities in the enterprise group | Not included |
| 7.9 Intra-group loans | Not included |
| Changes in the filtering compared to HDC | Comment |
|---|---|
| Not available. | Not available. |
15.1.3. National questionnaire – additional questions
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Additional questions in national questionnaire (not included in HDC) | Comment |
|---|---|
| Intramural R&D expenditures for energy research | In cooperation with the Swedish Energy Agency, Statistics Sweden included a question on intramural R&D expenditures for energy related R&D in the 2022 survey round of CIS. This question has now been implemented in the R&D in the business enterprise sector survey. |
15.2. Comparability - over time
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
For CIS2022 changes in the statistical unit ‘Enterprise’ has been implemented. The number of enterprises with more than one legal unit has increased from approximately 30 to over 50 000. The structure of the population of enterprises has therefor changed, now containing fewer but larger enterprises. This will decrease the double count for some variables, since the internal flows are considered and removed. It also effects the composition of the enterprise population with respect to sector. The implementation of the statistical unit enterprise has caused a break in time series, which effects the comparability with previous survey rounds. For the Swedish CIS2022 the number of voluntary sectors according to NACE Rev.2 has decreased to keep the sample to an acceptable amount of enterprises.
15.2.1. Length of comparable time series
Not requested.
15.3. Coherence - cross domain
See the comparison between SBS and CIS data in the section 15.3.3 below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Not requested.
15.3.3. Coherence – Structural Business Statistics (SBS)
This part compares key variables for aggregated CIS data with SBS data
Definition of relative difference between CIS and SBS data: DIFF = (SBS/CIS)*100
Comparison between SBS and CIS data (relative difference) by NACE categories and for enterprises with 10 or more employed persons
| NACE | Size class | Number of enterprises (SBS/CIS)* | Number of employed persons (SBS/CIS)* | Total Turnover (SBS/CIS)* |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | 104.1% | 96.5% | 114.8% |
| Core industry (B_C_D_E - excluding construction) | Total | 101.5% | 103.9% | 112.6% |
| Core Services (46-H-J-K-71-72-73) | Total | 105.4% | 91.0% | 116.6% |
* Numbers are to be provided for the last year of the reference period (t)
15.4. Coherence - internal
Not requested.
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
See below
18.1.1. Sampling frame (or census frame)
For the sampling frame the National Business Register was used.
18.1.2. Sampling design
Statistic Sweden has a system for coordinated sampling (SAMU) which is a frame population consisting of active enterprises in the National Business Register when the frame is created. The frame population (SAMU) is updated two times per year. The frame population for the CIS2022 was created from the coordinated sampling frame (SAMU) created in November the last year of the reference period.
A sample of enterprises with less than 200 employees is then drawn from the frame population. Enterprises with at least 200 employees, enterprises in NACE 72, enterprises with expenditure for intramural or extramural R&D in the survey R&D in the business enterprise sector 2021 as well as industrial research institutes are completely enumerated. The stratification variables are NACE (two-digit level), size class (10-49 emp, 50-199 emp, 200-249 emp, 250-499 emp, 500- emp) and NUTS2 (only for enterprises with less than 250 employees).
For CIS2022 this formed 1 121 strata and a sample size of 6 855 enterprises, nationally. When only accounting for Core NACE there were 1 003 strata and a sample size of 5 888 enterprises.
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
|---|---|
| Target population (A) (*) | 16 024 |
| Sample (B = C+D) | 5 888 |
| In case of combination sample/census: | |
| Sampled units (C) | 4 192 |
| Enumerated units/census (D) | 1 696 |
| Overall sample rate (E = 100*B/A) | 37% |
(*) CIS core population, i.e. NACE Rev.2 B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons.
18.1.4. Data source for pre-filled variables
Variables and indicators filled or prefilled from other sources.
There were no filled or prefilled variables or indicators in the CIS2022 questionnaire. However, the variables intramural R&D expenditure and extramural R&D expenditure had prefilled examples of the enterprise's value in R&D in the business enterprise sector 2021.
| Variables/Indicators | Source | Reference year |
|---|---|---|
| Not available. | Not available. | Not available. |
18.1.5. Data source and variables used for derivation and weighting
| Item | Response |
|---|---|
| Data source used for deriving population totals | National Business Register |
| Variables used for weighting | The number of enterprises in each strata and turnover |
18.2. Frequency of data collection
According to the Commission Implementing Regulation (EU) 2022/1092, the innovation statistics shall be provided to Eurostat every two years in each even year. The data collection takes place every second year in year t-2 preceding the data provision.
18.3. Data collection
Data is collected online through a web-based questionnaire.
18.3.1. Survey participation
The CIS is a mandatory survey.
18.3.2. Survey type
Data are collected through a combination of census and sample survey.
18.3.3. Combination of sample survey and census data
A sample is drawn for enterprises with 10-199 employees. For enterprises with 200 or more employees, enterprises in NACE 72, industrial research institutes and enterprises with expenditure for intramural or extramural R&D in the R&D in the business sector survey 2021, a census was used.
18.3.4. Census criteria
The critera for a census was size class, sector, type of organisation and previous information about R&D expenditure.
For enterprises with 200 or more employees, enterprises in NACE 72, industrial research institutes and enterprises with expenditure for intramural or extramural R&D in the R&D in the business sector survey 2021, a census was used.
18.3.5. Data collection method
Data collection method
| Survey method | Yes/No | Comment |
|---|---|---|
| Face-to-face interview | No | |
| Telephone interview | Yes | Only to confirm or revise details in a filled out web questionnaire. |
| Postal questionnaire | No | |
| Electronic questionnaire (format Word or PDF to send back by email) | No | |
| Web survey (online survey available on the platform via URL) | Yes | The only method for data collection in the CIS. |
| Other |
18.4. Data validation
Not requested.
18.5. Data compilation
Operations performed on data to derive new information according to a given set of rules.
18.5.1. Imputation - rate
Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition of imputation rate:
Imputation rate (for the variable x) (%) = 100 * (Number of replaced values) / (Total number of values for a given variable)
Definition of weighted imputation rate:
Weighted imputation rate= 100 * (Number of total weighted replaced values) / (Total number of weighted values for a given variable)
18.5.1.1. Imputation rate for metric variables
Imputation rate (%) for metric variables by NACE categories and for enterprises with 10 or more employed persons:
Zero imputation rate for turnover since information on enterprises turnover is collected from the national business register.
| NACE | Size class | Total Turnover (1) | Turnover from products new to the market (2) | R&D expenditure in-house (3) | |||
|---|---|---|---|---|---|---|---|
| Unweighted | Weighted | Unweighted | Weighted | Unweighted | Weighted | ||
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | n.a. | n.a. | 0.29% | 0.33% | 0.4% | 0.35% |
| Core industry (B_C_D_E - excluding construction) | Total | n.a. | n.a. | 0.18% | 0.32% | 0.6% | 0.44% |
| Core Services (46-H-J-K-71-72-73) | Total | n.a. | n.a. | 0.44% | 0.33% | 0.18% | 0.19% |
n.a.=not applicable
(1) = Imputation rate (%) for the total turnover in the last year of the reference period (t) (TUR)
(2) = Imputation rate (%) for the share of the turnover in the last year of the reference period (t) due to new or improved product new to the market in the total turnover for product innovative enterprises TUR_PRD_NEW_MKT/TOVT(INNO_PRD)
(3) = Imputation rate (%) for the R&D expenditure performed in-house (EXP_INNO_RND_IH)
18.5.2. Weights calculation
Weights calculation method for sample surveys
| Method | Selected applied method | Comments |
|---|---|---|
| Inverse sampling fraction | ||
| Non-respondent adjustments | X | For qualitative variables the weight is calculated as the total number of enterprises in the population per strata divided by the number of enterprises answering the questionnaire per strata: Nh/nh . Nh is the total number of enterprises in stratum h of the population. |
| Other | X | For quantitative variables the weight is calculated as the total turnover for all enterprises in the population per strata divided by the total turnover for enterprises answering the questionaire per strata. |
18.6. Adjustment
For calibration Statistics Sweden uses Etos as software. The method for calibration for quantitaitve variables is deriving weights from responding units total turnover in relation to the strata's total fram turnover. Non response adjusted weights are used for qualitative variables.
18.6.1. Seasonal adjustment
Not requested.
No further comments.
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – design improvement in 2018.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
1 December 2025
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
Data is produced for the statistical unit enterprise. Sweden has implemented the representative approach, where we pick a representative (legal unit) from complex enterprises in the sample. The legal unit is the reporting unit for the enterprise, and the answers from the reporting unit is assumed to correctly represent the values for the entire enterprise.
The representative unit is chosen based on specific criteria in three steps. Firstly, the legal unit with the NACE category closest to the enterprise is chosen. Secondly, if there are several legal units with the same NACE category the unit with the highest number of employed persons is chosen. Thirdly, if there still is more than one legal unit left for an enterprise the unit with the highest turnover is chosen.
The observation unit was the legal unit, while sampling was carried out at Statistical Unit Enterprise level.
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
Sweden SE. Stratification on NUTS2 (only enterprises with less than 250 employees) has been conducted, regional statistics is available.
The CIS2022 regional data are calibrated at the legal unit level.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
Operations performed on data to derive new information according to a given set of rules.
See below
CIS is conducted and disseminated at two-year interval in pair years.
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
Regional Statistics are produced for enterprises with less than 250 employees. Large enterprises, with 250 or more employees are not included in the regional statistics. The regional statistics is produced on NUTS 2 level.
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
For CIS2022 changes in the statistical unit ‘Enterprise’ has been implemented. The number of enterprises with more than one legal unit has increased from approximately 30 to over 50 000. The structure of the population of enterprises has therefor changed, now containing fewer but larger enterprises. This will decrease the double count for some variables, since the internal flows are considered and removed. It also effects the composition of the enterprise population with respect to sector. The implementation of the statistical unit enterprise has caused a break in time series, which effects the comparability with previous survey rounds. For the Swedish CIS2022 the number of voluntary sectors according to NACE Rev.2 has decreased to keep the sample to an acceptable amount of enterprises.
