CZECH STATISTICAL OFFICE

Research, Development and Information Society Statistics Unit

Czech Statistical Office

Society Development Statistics Department

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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)

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 national particularities.

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

Person employed used instead of employee as classification unit for size class of enterprises.

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.

The statistical unit is an enterprise which corresponds to the legal unit with the identification number given by the Business Register.

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

The geographic area to which the measured statistical phenomenon relates is Czechia (NUTS1) for all variables (data) and NUTS2 for selected (main) variables (data).

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

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 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.

There is no specific Czech legislation for the production of CIS statistics. The European Legislation applies.

The Law on Statistics of the Czech Republic is the main national legal act regarding official statistics. Production of CIS statistics as well as other official statistics is included in the annual Official Statistics Work Programme.

Not requested.

See the Framework Security Policy in tha annexed document.

In producing the standard statistical outputs, a number of procedures were implemented to prevent the release of information that identified characteristics about an enterprise.

1) Modifying some of the data before the statistics were released.

2) Restricting the number of output categories into which a variable may be classified.

3) Where the number of enterprises in a group fell below a minimum threshold, the statistical output is not published.

The rule concerning the confidentiality applied for treating the tabular data is following: less than 3 enterprises or at least 85% of turnover for one enterprise.

The main indicators were released in a press release in April 2020.

All indicators (data) were published in the regular publication Innovation activities of enterprises during 2016-2018 in June 2020.

https://www.czso.cz/csu/czso/catalogue-of-products

The CIS data are disseminated to all users through the Official Statistics Portal. The data are released simultaneously to all interested parties by issuing a news release. At the same time the news release is also e-mailed to the media. The news release is issued in Czech only. All published CIS data are available for users for free. Special datasets made ad hoc for researches/students are chargeable. Anonymized microdata are available at the Safe Centre of CZSO. The access to these microdata is paid.

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) : No

-              Analytical publication (referring to all/most results) : Yes : https://www.czso.cz/csu/czso/inovacni-aktivity-podniku-20162018

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : No

Not available.

Not requested.

Microdata are accessible only at the National SAFE centre and Eurostat SAFE centre.

No other means of dissemination.

Not requested.

The complete meta-information (methodology of survey, definition of variables) on the CIS is available for users on the website of CZSO.

https://www.czso.cz/csu/czso/statistika_inovaci

Not requested.

Quality related documents (quality reports, studies, etc) are not publicly available. Only selected indicators are published (e.g. overall non-response rate).

See attached annex.

Assessment of the quality uses the following components:

1) Standard STS compliance assessments carried out by Eurostat. This assessment is used internally as well.

2) Regular response rate measurement.

3) Regular methodological update and ad hoc methodological audit carried out every 10 years.

The overall quality of the national methodology is good. Improving of the national methodology regarding CIS and data quality is ongoing process in line with ICT development.

The CZSO primarily fulfils its commitments towards the European Commission, which represents the high priority user. However, depending on the capacity available the CZSO treats all the users equally.

The relevance of an instrument has to be assessed in the light of the needs of its users. As for EU Statistics on innovations in enterprises (CIS) the main users are the following:

1) Institutional users having access to aggregative data for policy-making;

2) Statistical users in Eurostat or in National Statistical Institutes to feed sectorial or transversal publications;

3) Researchers having access to microdata;

4) End users – including the media - interested in innovations in the EU area.

No user satisfaction survey is carried out exclusively for CIS indicators on the national level. However, CZSO is constantly in contact with different groups of users, e.g. Ministry of Industry and Trade, Czech National Bank, different associations, internal users etc. Formal meeting with users is organized regularly by the General Methodology Department. Data users are asked for a potential feedback if they receive data, publications or special outputs.

Every 5 years, CZSO organises the national user satisfaction survey. Last one was carried out in 2015.

All compulsory CIS 2018 variables (expect for COOP_OTH) according to the Commission Regulation No 995/2012 are implemented.

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 persons employed

[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).

See the annex 1.

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.

Because the corresponding list of units with the number social of insurance policyholders, is handed over with monthly periodicity with about a two-month delay after the end of the reference period, some coverage errors can occur at time of sampling.

The coefficient of variation reported under 13.2.1.1 incorporates the effects of coverage errors.

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.

Regarding overvalued innovation expenditure the following ratio is calculated as innovation expenditures in the given year/ turnover in the given year which should be lower than 1. Innovation expenditures on in-house research and development is also compared with research and development expenditures in Annual Research and Development Survey. A special training is organized for staff that process the questionnaires and transfer data from printed questionnaires to databases (data entry).

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)

The overall unit non-response rate is very good with low values. The weighted unit non-response rate and un-weighted unit non-response rate are both around 11 %.

No imputation regarding a non-responding unit is applied.

See below.

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

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

Two reminders are sent and also telephone follow-ups are carried out if it is needed.

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 persons employed).

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 persons employed)
 

Main data entry methods are: data scanning or keying for the printed questionnaire (1/3 of all) and CASI/e-PDF for the electronic questionnaire (2/3 of all). The errors’ catching is maintained by programming tools which identify hard and soft errors. Programming tools find incomplete answers and warn of the given type of error. Errors which were found during this checking process are corrected manually.

Processing errors are not significant.

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 : 16 months after the reference year

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) : 3 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.

No significant problems of comparability between regions at the level NUTS 2 of Czechia. The stratification of the sample is set to eliminate possible problems regarding comparability between regions at the NUTS 2.

Data collected by this survey are internationally comparable because this survey respects standards described in Oslo manual (OECD, 2018) and Commission Implementing Regulation (EU) No 995/2012 of 26 October 2012, laying down detailed rules for the implementation of Decision No 1608/2003/EC of the European Parliament and of the Council concerning the production and development of Community statistics on science and technology.

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 persons employed

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

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below:

The frame population is the same as the one for the Structural Business Survey (SBS). Following ESA 2010 sectors are included: S.11+S.12+S.141.

Sampling design is a combination of stratified random sampling (enterprises with 10-249 employees of selected two-digit NACE industries) and census (see 12.3.3). Two-digit NACE, NUTS2 and size-class according to the Business Register were used for stratification. The sample was designed with no reference to any other survey. Following ESA 2010 sectors are covered: S.11+S.12+S.141. The total number of strata is 1320 including special strata for units with unknown NACE.

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.

CZ-CIS survey in the Czech Republic is a combination of computer assisted filling in and paper questionnaires. There is a possibility for enterprises to fill in PDF format of questionnaire or online questionnaire available to fill in the special application especially developed for the purpose of this survey. Respondents receive instructions (via a message in their data mailbox) describing how to get the online questionnaire (computer assisted) or have an opportunity to download the online questionnaire from the CZSO website. We send paper questionnaires to enterprises that do not own data mailboxes (approximately 1000 enterprises a year). Paper questionnaires are sent and returned by post. 

During the data collection, checking and processing period all received data are checked primarily by junior statisticians (secondary by the Project manager). Online questionnaires (computer assisted) includes all necessary consistency checks (controls). There are approximately 150 of them every year. Inconsistencies in controls notify junior statisticians of necessity to check answers. Phone calls are used for validation of the data (corrections) and quality improvement if necessary. The year-to-year checks in the aggregate data (before data delivery to Eurostat) are made.

No imputation for item non-response will be used except of imputation of some background information that will not be available in SBS database.

The survey is mandatory.

Data are collected through the combination of a census and sample survey.

Covered by Census:
- Number of employees according to the Business Register >=250 of ALL CORE NACE
- Number of employees according to the Business Register =50-249 of NACE=5-9, 12, 19, 37, 39, 50-51, 53, 59-60

Covered by sample survey:

- Number of employees according to the Business Register =50-249 of NACE=10-11, 13-18, 20-36 , 38, 46, 49, 52, 58, 61-66, 71-73

- Number of employees according to the Business Register =10-49 of all NACE

Covered by Census:
- Number of employees according to the Business Register >=250 of ALL CORE NACE
- Number of employees according to the Business Register =50-249 of NACE=5-9, 12, 19, 37, 39, 50-51, 53, 59-60

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 persons employed:

(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

No procedures employed to modify statistical data are applied.

Not relevat for yearly data.