Statistics Sweden

Economic Statistics Department

Section for Innovation, Business production and research

SCB
Solna strandväg 86
171 54 Solna, Sweden

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. 

CIS 2020 is a second in a row to implement concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes in the CIS driven by the revision of the manual and their impact on collected indicators are described in the Statistics Explained article: Community Innovation Survey – new features. 

The legal framework for CIS since 2012 is the Commission Regulation No 995/2012 that establishes the quality conditions for the data collection and transmission and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population are enterprises with at least 10 employees 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). Please refer to the Annex section of the European metadata (ESMS) for details of the time coverage of collected indicators.

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.

CIS covers main economic sectors according to NACE Rev.2 broken down by size class of enterprises and type of innovation activity.

In accordance with Commission Regulation 995/2012 on innovation statistics, the following industries and services are included in the core target population. Results are made available with these following breakdowns :

All NACE – Core NACE (NACE Rev. 2  sections & divisions B-C-D-E-46-H-J-K-71-72-73 )

CORE INDUSTRY (excluding construction) (NACE Rev. 2 SECTIONS B_C_D_E)

10-12: Manufacture of food products, beverages and tobacco

13-15: Manufacture of textiles, wearing apparel, leather and related products

16-18: Manufacture of wood, paper, printing and reproduction

20: Manufacture of chemicals and chemical products

21: Manufacture of basic pharmaceutical products and pharmaceutical preparations

19-22: Manufacture of petroleum, chemical, pharmaceutical, rubber and plastic products

23: Manufacture of other non-metallic mineral products

24: Manufacture of basic metals

25: Manufacture of fabricated metal products, except machinery and equipment

26: Manufacture of computer, electronic and optical products

25-30: Manufacture of fabricated metal products (except machinery and equipment), computer, electronic and optical products, electrical equipment, motor vehicles and other transport equipment

31-33: Manufacture of furniture; jewellery, musical instruments, toys; repair and installation of machinery and equipment

D: ELECTRICITY, GAS, STEAM AND AIR CONDITIONING SUPPLY

E: WATER SUPPLY; SEWERAGE, WASTE MANAGEMENT AND REMEDIATION ACTIVITIES

36: Water collection, treatment and supply

37-39: Sewerage, waste management, remediation activities

CORE SERVICES (NACE Rev. 2 sections & divisions 46-H-J-K-71-72-73)(NACE code in the tables = G46-M73_INN)

46: Wholesale trade, except of motor vehicles and motorcycles

H: TRANSPORTATION AND STORAGE

49-51: Land transport and transport via pipelines, water transport and air transport

52-53: Warehousing and support activities for transportation and postal and courier activities

J: INFORMATION AND COMMUNICATION

58: Publishing activities

61: Telecommunications

62: Computer programming, consultancy and related activities

63: Information service activities

K: FINANCIAL AND INSURANCE ACTIVITIES

64: Financial service activities, except insurance and pension funding

65: Insurance, reinsurance and pension funding, except compulsory social security

66: Activities auxiliary to financial services and insurance activities

M: PROFESSIONAL, SCIENTIFIC AND TECHNICAL ACTIVITIES

71: Architectural and engineering activities; technical testing and analysis

72: Scientific research and development

73: Advertising and market research

71-73: Architectural and engineering activities; technical testing and analysis; Scientific research and development; Advertising and market research

The following NACE are covered in addition: NACE 41-43 Construction, NACE 45 Wholesale and retail trade and repair of motor vehicles and motorcycles, NACE 47 Retail and trade, except of motor vehicles and motorcycles, NACE 55-56 Accommodation and food service activities, NACE 69 Legal and accounting activities, NACE 70 Activities of head offices; management consultancy activities, NACE 74 Other professional, scientific and technical activities, NACE 77-82 Administrative and support service activities, NACE 85 Education and NACE 86 Human health services.

In accordance with Commission Regulation 995/2012 on innovation statistics, the following size classes of enterprises according to number of employees are included in the core target population of the CIS:

• 10 - 49 employees
• 50 - 249 employees
• 250 or more employees

No deviations

The description of concepts, definitions and main statistical variables is available in CIS 2020 European metadata file (ESMS) Results of the community innovation survey 2020 (CIS2020) (inn_cis12) in Eurostat database.

Enterprise

Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employees.

CIS Sweden. Stratification on NUTS2 (only enterprises with less than 200 employees) has been conducted, regional statistic is available. 

Several rounds of Community Innovation Survey have been conducted so far at two-year interval since end of 90’s.

*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003

** No deviations from reference 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 2020, the time covered by the survey is the 3-year period from the beginning of 2018 to the end of 2020.

Some questions and indicators refer to one year — 2020.

The list of indicators covering the 3-year period and referring to one year according to the HDC is available in the Annex section of the European metadata (ESMS). 

CIS surveys are based on the Commission Regulation No 995/2012, implementing Decision No 1608/2003/EC 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.

In addition to the regulation and implementing decision described above the CIS is a part of the Swedish official Statistics. The quality and availability of the CIS is regulated in the Law of Official Statistics of Sweden (2001:99).

Not requested.

CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system.

Confidentiality is regulated in the 24^th 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. 

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 p% rule. The formula for p% rule is as following:

The cell is considered as sensitive if X-x2-x1>p%*x1, where X=cell total, x1=biggest contributor to the cell, x2=second biggest contributor to the cell.

National publication: 2021-11-11

Report publication, national: 2022-06-01

National microdata: 2022-02-24, Revised: 2022-06-09

Community Innovation Survey (scb.se)

Microdata is available in Statistics Sweden microdata database (MONA – Microdata Online Access). Users can access data by applying for and receiving permission through MONA (MONA – Statistics Sweden’s platform for access to microdata (scb.se)).

CIS is conducted and disseminated every other year.

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.

See below.

-              Online database (containing all/most results): Yes

Community Innovation Survey (scb.se)

-              Analytical publication (referring to all/most results): Yes, report in Swedish (English summary)

More than half of Swedish enterprises conducted innovation activities in 2016-2018 (scb.se)

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect): Yes, article on innovation in the welfare sector, a comparison between the public and private health (86) and education (85) sector. Only available in Swedish.

Innovation in the welfare sector (scb.se)

Free access, Community Innovation Survey (scb.se)

Not requested.

Available via Eurostat SAFE center. 

At national level microdata is transmitted to research projects using 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 protected passwords. Not free of charge.

*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. 

No other means of dissemination.

Not requested.

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)).

Not requested.

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)).

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.

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 2022 CIS, Statistics Sweden intends to minimize the deviations of the national questionnaire to the core questionnaire. This is done to reduce the risk of measurement errors as well as item non-response.

Relevance is the degree to which statistics meet current and potential users’ needs. It includes the production of all needed statistics and the extent to which concepts used (definitions, classifications etc.) reflect user needs. The aim is to describe the extent to which the statistics are useful to, and used by, the broadest array of users. For this purpose, statisticians need to compile information, firstly about their users and their needs.

The CIS is based on a common questionnaire and a common survey methodology, as laid down in the 3rd edition of Oslo Manual (2005 edition), in order to achieve comparable, harmonised and high quality results for EU Member States, EFTA countries, Candidates and Associated countries.

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 analyzed based on user demand, cost, and relevance.

No user satisfaction survey has been conducted since 2012 but continuous evaluation of user needs, and satisfaction is done at the R&D/innovation council in Sweden.

Since 2012 measures have been taken to increase user satisfaction. An example of such measures is the increase in the number of reported industries, specifically in the service sector. For the 2020 CIS, Sweden included NACE 85 Education and NACE 86 Human health services.

All mandatory indicators are included and published in national CIS as well as transmitted to Eurostat. Both regarding mandatory NACE, size classes and variables. 

Not requested.

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).

That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.

The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).

Coefficient of Variation= (Square root of the estimate of the sampling variance) / (Estimated value)

Formula:

where

Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 and more employees

[1] = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT20)
[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 [TUR20,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).

Horvitz-Thompson is used for variance estimation. The sample weights Nh/nh  has been adjusted with nh/nhR  in each stratum.

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.

No reports have been issued attempting to quantify the non-sampling error for CIS t=2018. 

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 has 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.

Not requested.

Not requested.

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 CIS2020 sample (Core Nace) 7 enterprises were registered as over coverage.

The effects of coverage errors due to the over coverage is not incorporated in the coefficient variations (see table in 13.2.1.1).  

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.

Statistics Sweden has taken on several measures to reduce measurement errors. Definitions and question related information in the core questionnaire has been incorporated in the national questionnaire. The filters in the core questionnaire have also been incorporated in the national web-based questionnaire. The national questionnaire has also been tested by experts on survey methodology.

In the web-questionnaire there are controls for inconsistent answers. The controls generate an error message to the answering unit which must change or comment their answer. A selection of answering units, based on the activated controls are later revised. Follow up contact with the enterprise is conducted via telephone or email if necessary. The aggregated results are later analyzed broken down into different domains (size class, NACE).

Evaluation is conducted after each CIS round to decrease the risk of occurring measurement error.

Non-response occurs when a survey fails to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

There are two types of non-response:

1) Unit non-response, which occurs when no data (or so little as to be unusable) are collected about a population unit designated for data collection.

a) Un-weighted unit non-response rate (%) = 100*(Number of units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)

b) Weighted unit non-response rate (%) = 100*(Number of weighted units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)

2) Item non-response, which occurs when only data on some, but not all survey data items are collected about a population unit designated for data collection.                                       

a) Un-weighted item non-response rate (%) = 100*(Number of units with no response at all for the item) / (Total number of eligible, for the item, units in the sample i.e. filters have to be taken into account) 

See below.

Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employees

The number of eligible units is the number of sample units, which indeed belong to the target population.

A total amount of two reminders were sent to non-responding enterprises before they were coded as non-responding.

See below.

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 employees).

There were no item non-response for Turnover in the CIS2020 since it was collected from the SBS survey (Structural Business Statistics)

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 employees)
 

For the CIS2020 round there were three significant processing errors that resulted in revision of transmitted data.

Firstly, no imputation of expenditures in the CIS2020 round were conducted. This processing error was discovered when analyzing the differences in the CIS2018, definitive statistics, and the CIS2020 fast track (preliminary statistics). Imputation for the quantitative variables were then conducted and a new fast track was transmitted, as well as corrected national dissemination.

Secondly, the incorrect variables for turnover and employment were used in the fast track delivery of the CIS2020 data. The variables used did not follow the specifications in the Commission Implementing Regulation (2020/1197). The variables were revised, and all disseminated statistics were updated.

Thirdly, incorrect filtering and too few logic checks led to enterprises estimating turnover from products new to the market and new to the firm, respectively, even though they did not introduce products new to the market or new to the firm, respectively. This caused an overestimate of turnover from products new to the market and new to the firm. The processing error was solved by adding a logical correction in the programming. The variables were then revised, and corrected data was transmitted and disseminated.

All processing errors that occurred have been thoroughly documented and incorporated in the working process of the CIS2022 survey round.

Not requested.

Timeliness and punctuality refer to time and dates, but in a different manner.

The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.

Timeliness of national data – date of first release of national level: 2021-11-11 (11th of November 2021). 

T+11 months.

Not requested.

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.

Date of transmission of complete and validated data to Eurostat (Number of days between that data and 30 June 2022): 7 days

Revised data sent 05/10/2022 (73 days).

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.

The regional statistics are produced for enterprises with less than 200 employees. Large enterprises (200 or more employees) are not a part of the regional statistics.

Not requested.

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Methodological deviations from the CIS Harmonised Data Collection (HDC)

There were no additional questions in the national questionnaire that were not included in the HDC.

Due to important methodological changes driven by Oslo Manual 2018, CIS 2018 and CIS 2020 cannot be directly compared with previous CIS waves.

Not requested.

There are difficulties in assessing the coherence across domains. For 2020 other surveys or statistical domains have implemented the new statistical unit 'Enterprise', which is not implemented in the CIS2020.

Not requested.

Not requested.

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

Not available. There are difficulties to the task of comparing the key variables for aggregated CIS data and SBS data. For 2020 the SBS has implemented the new statistical unit 'Enterprise', this is not implemented in the CIS2020.

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below:

National Business Register was used.

The frame population consists of enterprise units that are registered as active in the National Business Register. These units are then placed in a system for coordinated sampling (SAMU) at Statistics Sweden. The system is updated two times per year. A sample of enterprises with less then 200 employees is then drawn from the frame population in the system for coordinated sampling (SAMU). Enterprises with at least 200 employees, enterprises in NACE 72 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 size classes 10-49 emp and 50-199 emp).

For CIS2020 this formed 1064 strata and a sample size of 9939 enterprises, nationally. When only counting for Core NACE there were 740 strata and a sample size of 6368 in the CIS2020.

Variables and indicators filled or pre-filled from other sources.

There were no filled or prefilled variables or indicators in the CIS2020 questionnaire. However, the variables expenditure for R&D in house, expenditure for R&D contracted out and expenditure for innovation had pre-filled examples of what the answering unit had stated in earlier survey rounds (R&D 2019 and CIS2018).

According to the Commission Regulation (UE) 995/2012, the innovation statistics shall be provided to Eurostat every two years in each even year t+18.

Data is primarily collected via a web-based questionnaire. It is also possible for enterprises to answer the questionnaire on paper. The data is then collected online or scanned into the database. 

The CIS is a mandatory survey.

Data is collected through census and sample survey. 

Sample survey for enterprises with 10-199 employees. For enterprises with 200 employees or more, enterprises in NACE 72 and industrial research institutes, a census was used.

Size class, specific sector (NACE 72) as well as type of organization (industrial research institutes).

For enterprises with 200 employees or more, enterprises in NACE 72  and industrial research institutes, a census was used.

Data collection method

Not requested.

Operations performed on data to derive new information according to a given set of rules.

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)

Imputation rate for metric variables by NACE categories and for enterprises with 10 or more employees: 

No imputation for Total Turnover (1). The imputation for R&D expenditure in-house (3) was less than 1 percent. 

(1) = Total turnover in the last year of the reference period (t) (TUR)

(2) = 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/TUR(INNO_PRD)

(3) = R&D expenditure performed in-house (EXP_INNO_RND_IH)

Weights calculation method for sample surveys

For estimates SAS and CLAN was used.

Not requested.