Statistics Finland

Economic statistics

FI-00022 Statistics Finland

The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on different types of innovation,  various aspects of the development of an innovation, objectives of innovation activities, sources of information, public funding or expenditure on innovation.  It is aim is to measure the innovativeness of sectors and enable the analysis of the factors of innovation.

 The CIS provides statistics by type of innovators, economic activities 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 developed a Harmonised Data Collection (HDC) questionnaire accompanied by a set of definitions and methodological recommendations.

CIS 2018 concepts and its underlying methodology are based on the Oslo Manual (2018) 4th Edition. 

New review of the CIS2018  aims to meet several objectives :

1: Reduce subjectivity and biases in the main CIS indicators

2: Improve reporting about innovation activities and capabilities in the firm

3: Ensure international comparability (including compliance with the OM4)

4: Broaden the basis CIS information on enterprise management

5: Take better account the diversity of enterprises in the EU

6: Improve reporting about external drivers and enablers of innovation

7: Improve timeliness

8: Ensure the feasibility of data collection

9: Ensure continuity with the CIS 2016

10: Improve reporting about the output and impact of innovation

CIS2018 is conducted under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE economic sectors (see section 3.3.) with at least 10 employees. 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 consider CIS t to be the survey that refers to the same year of the quality report and CIS t-2 to be the previous survey e.g.: CIS  2018= CIS t then, CIS t-2=CIS 2016

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 product or business process innovation, had ongoing innovation activities, abandoned innovation activities or was 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)

B: MINING AND QUARRYING

C: MANUFACTURING

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

No deviation.

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 2018 European metadata file (ESMS) Results of the community innovation survey 2018 (CIS2018) (inn_cis11) in Eurostat database.

Enterprise, most often referring to legal unit, in some cases group or part of a group operating nationally

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

National data for Finland. No NUTS 2 level data available.

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

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

Not relevant.

CIS indicators are available according to 3 units of measure:

NR: 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 2018, the time covered by the survey is the 3-year period from the beginning of 2016 to the end of 2018.

Some questions and indicators refer to one year — 2018.

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.

Statistics Act (280/2004), https://www.finlex.fi/fi/laki/ajantasa/2004/20040280 (Finnish/Swedish), http://tilastokeskus.fi/meta/lait/statistics-act-2802004_en.html

Not requested.

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

In Finland, the data protection of data collected for statistical purposes is absolutely guaranteed in accordance with the Statistics Act (280/2004), the Personal Data Act (532/1999) and the Act on the Openness of Government activities (621/1999), as well as the requirements of the EU's General Data Protection Regulation (2016/679). The data materials are protected at all stages of processing with the necessary physical and technical solutions. Statistics Finland has compiled detailed directions and instructions for confidential processing of the data. Employees have access only to the data essential for their duties. The premises where unit-level data are processed are not accessible to outsiders. Members of the personnel have signed a pledge of secrecy upon entering the service. Wilful breaching of data protection is punishable.

Statistics Finland's official guidelines on the protection of tabulated business data are applied in protecting innovation survey data. As in sample surveys, the basis for publishing the data is to not publish data on the statistical units belonging to the sample. In terms of protection, compliance with the threshold rule (3) is the primary procedure. In addition, the dominance rule is applied to data in euros.

Industry-specific data are mainly published on the 2-digit level. However, some of the most sensitive industries from the point of data protection have been combined with other industries. If there is need for protection after possible aggregations, or for some other reason, the cells to be protected are hidden.

In the tabulations submitted to Eurostat, sensitive cells are indicated as protected (also secondary protection), in which case Eurostat does not publish these data. However, the data can be used in calculating sum data at the EU level. Protection is indicated in accordance with instructions given by Eurostat.

The innovation data - without identification data - are also submitted to Eurostat's SafeCenter for research use.

Statistics Finland's release calendar lists all the statistical data and publications to be released over the year.

The statistics on innovation activity are nationally published in the spring around 16 months from the end of the statistical reference year. The release date is announced in Statistics Finland's release calendar. All statistical data can be found on the home page of the statistics http://tilastokeskus.fi/til/inn/index_en.html.

http://tilastokeskus.fi/ajk/julkistamiskalenteri/index_en.html#?langs=fi

The data of the statistics on innovation activity are released to all data users simultaneously according to the date given in Statistics Finland's release calendar. All statistical data are available free-of-charge on the home page of the statistics http://tilastokeskus.fi/til/inn/index_en.html.

Assignments can be commissioned from the statistical data, that is, small free-of-charge or extensive charged reports can be ordered, for example from tiede.teknologia@stat.fi. Further information about the charges payable for Statistics Finland's services is available at https://www.stat.fi/tup/hinnat/index_en.html.

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.

See below.

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

http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__ttt__inn/?tablelist=true

-              Analytical publication (referring to all/most results) : Yes

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : 

Available http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__ttt__inn/?tablelist=true

Not requested.

Innovation microdata are available in Eurostat and at national level in SAFE Centre.

No other dissemination formats.

Not requested.

The implementation of the innovation survey follows the methodological recommendations issued by Eurostat, the Statistical Office of the European Communities.

The concepts are based, inter alia, on the OECD/Eurostat Oslo Manual.

Not requested.

Statistic's webpage covers national quality report. National quality report mainly covers same items than Eurostat's quality reporting included in this metadata description.

When compiling statistics, Statistics Finland observes the European Statistics Code of Practice (CoP) and the Quality Assurance Framework (QAF) based on them. The Code of Practice concerns the independence and accountability of statistical authorities and the quality of processes and data to be published. The principles are in line with the Fundamental Principles of Official Statistics approved by the United Nations Statistics Division and are supplementary to them. The quality criteria of Official Statistics of Finland are also compatible with the European Statistics Code of Practice. The principles are also compatible with those of the European Foundation for Quality Management (EFQM).

More information about this is available on Statistics Finland's quality management pages.

Every year Statistics Finland conducts statistical auditing that helps to ensure the quality of statistics.

Quality issues are critical and controlled at every stage of stastistical production process of innovation data -- in data collection, in data editing and in validating the final data.

In the acquisition of innovation data, the aim is to attain an adequate response rate (target 70 per cent) for the data to be representative and for high-quality answers. All the illogicalities, shortcomings, faults and other types of errors are tried to be corrected. Data are corrected by various means, and the final data validated in multiple ways, such as
- identifying deficiencies and internal illogicalities in the data as well as other possible errors (checking of observation units, errors regarding thousands in the euro data and so on) and by correcting and supplementing them and
- by examining distributions of variables and comparing data and distributions with previous data and with existing comparison data (research and development activity and other business data).

Following Eurostat's methodological recommendations and using multiple ways of controlling the quality at every stage of the statistical process quarantees reliable and as unbiased and correct data as possible for enterprises innovation activity.

CIS data covers however difficult items, such as innovation expenditure, which are very challenging for respondents to be provided. It is important to take this into account when using the data in order to avoid misinterpretation of the data.  

Key users of innovation data and innovation statistics are invited to discuss (meetings or other contacts) about the content of the forthcoming survey and about current information (user) needs before each survey round. At that time, the content of forthcoming survey, i.e. the EU CIS Harmonised Data Collection, is discussed and analysed together, and it is assessed whether there are themes and subjects, in addition to the harmonised data content, that should be covered in the national survey. This is a key tool for monitoring users' information needs and user satisfaction along with other user meetings.

Key users of innovation data and innovation statistics (such as the Ministry of Economic Affairs and Employment, Business Finland or research institutes) are invited to discuss the content of the forthcoming survey and current information (user) needs before each survey round. At that time, the content of forthcoming survey and of the EU CIS Harmonised Data Collection is discussed and analysed together, and it is assessed whether there are themes, in addition to the harmonised data content, that should be covered in the national survey. This is a key tool for monitoring users' information needs and user satisfaction along with other user meetings.

Actual user satisfaction surveys have not been made concerning the innovation statistics.

Actual and separate user satisfaction surveys have not been implemented for CIS. User satisfaction is tried to be quaranteed by discussing about the content of statistics with users already before every survey round (meetings with users described under 12.1). About satisfaction towards published information and accessibility to that based on previous rounds is also asked from main users at that same occasion. 

Also, if other feedback received, it is taken into account when surveys and publishing planned.

The data are available on all legislated or otherwise desired indicators by industry and size category according to the EU recommendation. Industry data are presented mainly on the 2-digit level with the exception of industries that for data protection reasons have to be described as aggregated, for example.

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 (ENT18)
[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 [TUR18,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).

ETOS and SAS procedures

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.

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 number of enterprises included in over-coverage was 62. These were distributed over different strata both in total industry and in service sector.

Over coverage units are eliminated from the estimation and the calculation of coefficient of variation.

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.

Training of personnel working with data collection and data editing, profound studying the concepts and the content of the survey resulting in ability to help respondents when difficulties with responding.

CIS2018 HDC questionnaire was also tested as part of the implementation of new content.

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 13.3.3.1. and 13.3.3.2.

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.

Three reminder letters, two email reminders and reminder calls by CATI (Computer Assisted Telephone Interviews) personnel.

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).

Information on turnover is missing only for marginal number of respondents. If missing, the SBS data is used.

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)
 

 By multiple ways of controlling, editing and analysing the data it is targeted to the finalised data that does not cover any processing errors. 

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 : 23/04/2020

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 2020) : -1

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.

No deviations from ESS/international standards, concepts and definitions (OM4 and Eurostat guidelines).

Not requested.

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Methodological deviations from the CIS Harmonised Data Collection (HDC)

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

Not requested.

See the comparison between SBS and CIS data in the section 15.3.3 below.

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

Comparison between SBS and CIS data (relative difference) by NACE categories and for enterprises with 10 or more employees

* Numbers are to be provided for the last year of the reference period (t)

Data not fully comparable due to minor differences in statistical units (legal units/enterprise units/groups). Data without K.

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below:

National business register (BR)

Census for enterprises with 250 employees or more and simple random sampling for enteprises with 10 to 249 employees. NACE and size class as stratifiying variables. 

Total frame of CIS2018 covering 8 840 enteprises and overall sampling rate 41 per cent -- 33 per cent for enterprises with 10 to 49 employees and 58 per cent for medium size enterprises (census for large enterprises).

Variables and indicators filled or prefilled from other sources.

According to the Commission Regulation (UE) 995/2012, 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.

See below.

Mandatory

Combination of census and sample survey.

Census for 250+ employees and sample survey for enterprises with 10 to 249 employees.

250 employees

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:

(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)

Total turnover: missing information replaced by the data from SBS.

Weights calculation method for sample surveys

None

Not requested.