Statistical Office of the Slovak Republic

Department of Cross-sectional Statistics

Statistical Office of the Slovak Republic

Lamacska cesta 3/C

840 05 Bratislava

Slovakia

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

Covered NACE activities beyond the CR No. 995/2012
- construction (NACE 41-43)

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 particularities.

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.

Entitiy for which the information is sought is the legal unit. 

Entity for which statistics are ultimately compiled is the legal unit. 

Legal units include legal persons whose existence is recognized by law independently of the individuals or institutions which may own them or are members of them.

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

The measured statistical phenomenon relates to the total country SLOVAKIA. The regional dimension of national data is available at NUTS 2 level.

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 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.

Act No. 540/2001 Coll. on State Statistics, as amended - adopted by the National Council of the Slovak Republic.

https://slovak.statistics.sk/wps/wcm/connect/938bf3c4-f9f2-450d-80e1-18f0bedcb8f0/act_540_2001_en.pdf?MOD=AJPERES

Program of State Statistical Surveys, published for three years in the Collection of Laws of the SR. 

https://slovak.statistics.sk/wps/portal/ext/aboutus/national/programme/

Not requested.

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

Act No. 540/2001 on State Statistics as amended and Internal Directive on the Protection of Confidential Statistical Data (regulates the method of management and implementation of activities related to ensuring the protection of confidential statistical data in the Statistical Office of the Slovak Republic).

We have applied local suppression (primary and secondary), dominance rule (1, 90) (i.e. the turnover of the largest enterprise exceeds 90 % of the cell value) and minimum frequency rule (n=3).

The Catalog of Publications is publicly available on the website of the Statistical Office of the Slovak Republic and it contains basic information on the issued titles, issue dates, periodicity and language version.

https://slovak.statistics.sk/wps/portal/ext/products/publikacie/

 Information on all new released publications is available on the website of the Statistical Office of the Slovak Republic. The release policy determines the availability of statistical data to all users at the same time. 

CIS is conducted at two-year interval in even years and disseminated in odd 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

https://slovak.statistics.sk/wps/portal/ext/Databases/DATAcube_sk

-              Analytical publication (referring to all/most results) : Yes:  Innovation activity of enterprises in the Slovak Republic 2018-2020

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : Yes: 1 table in the Statistical Yearbook of the Statistical Office of the Slovak Republic

https://slovak.statistics.sk/wps/portal/ext/Databases/DATAcube_sk

Not requested.

Micro-data are not disseminated. Micro-data are provided only for scientific purposes according to the stated rules. Conditions for granting access to confidential statistical data for scientific purposes are provided on the website of the Statistical Office of the Slovak Republic.

No other forms of disseminations.

Not requested.

Meta-information is available in on-line publication and on-line database, which includes  description of indicators, definitions,  survey methodology etc.

Not requested.

Quality reports for users are available on the website of the Statistical Office of the Slovak Republic, specifically at: https://slovak.statistics.sk/wps/portal/ext/metadata/qreports/

Statistical Office of the SR has established the system of quality management. Quality manual contains description of system of quality management and fulfillment of requirements of standard ISO 9001.

The application of the Quality manual in practice ensures that all activities with impact on the quality of statistical products are planned, managed, examined, evaluated and meet the requirements accepted in the customer order. Quality manual is available at: https://slovak.statistics.sk/wps/wcm/connect/9ca43aa4-bfaf-4101-9dae-5263aa834df7/ Prirucka_kvality.pdf?MOD=AJPERES&CVID=mu8R9IM&CVID=mu8R9IM

The basis of the whole system of quality management is the European Statistics Code of Practice.

The data quality of the CIS 2020 survey is considered to be good. Coverage of the survey, reference period, used methodology for sampling, data collection, checking and data processing followed the Eurostat methodology and recommendations. Results of the survey were transmitted to Eurostat in required SDMX forms via EDAMIS (tabulated data, most of which going beyond the CR No. 995/2012) by the stated deadline.
Improvement was realised in calibration of weights, we have used the application Calif 4.0 for the calibration. As all given indicators (for which the CV should be calculated) are non-linear, we used the linearization method using Taylor expansion series.

Main strengths of the survey:
- In all necessary cases, enterprises were contacted to consult errors and missing variables
- Eurostat checks were incorporated into the software for data recording and checking and preparation of results.

Weaknesses of the survey:
- No user satisfaction survey specifically for CIS 2020 was undertaken. There was a satisfaction survey conducted in our office in 2020 covering several statistical areas. Area of innovation was together with R&D, energy and environment statistics. Average rate of satisfaction with these four statistical areas was 68,9 %.

Assessment of the CIS 2020 according to particular quality criteria is as follows:

Relevance
- User needs are known and satisfied
- No compulsory cells are missing from the output tabulation
- Data at NUTS2 level are available

Subject covered by the CIS 2020 survey is highly relevant; obligatory modules and also most of voluntary modules were included.

Accuracy
- Overall unit response rate (un-weighted unit response rate in Core NACE) was 84,9 %, so the non-response analysis was not carried out
- Item non-response was not recorded.

Timeliness and punctuality
- Results from the CIS 2020 survey will be published in the second half of 2022
- CIS 2020 data were transmitted to Eurostat in the scheduled date, after 15 months the key outputs (“Fast Track“) and 18 months all other required outputs.

Accessibility and clarity
Results of the CIS 2020 survey will be published in national electronic publication on the web site of the Statistical Office of the Slovak Republic. Innovation data will be also available in the public database. Data will be accompanied with methodological description and made available for users in all forms of dissemination.

Comparability
Comparability over time (with CIS 2018 survey) and accros EU countries is ensured by using of the common questionnaire worked out by Eurostat in cooperation with member states.

Coherence
Coherence of data on turnover and employed persons from the innovation survey with data from the SBS survey is ensured by comparison of data from these two surveys during the processing procedure. Enterprises were contacted in the case of big difference and data were corrected.

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 in order to achieve comparable, harmonised and high quality results for EU Member States, EFTA countries, Candidates and Associated countries.

The content of the survey meets the needs of users. When deciding on the inclusion of indicators in the survey, the standard procedure used in the Statistical Office of the Slovak Republic is applied. We send information on the content of the survey for comments and for completion to individual central authorities and members of the Statistical Council. The suggestions obtained in this process are taken into account when creating the final questionairre. Consultations with specific users on their requirements for specific outputs show that the content of the survey is relevant.

No user satisfaction survey specially for CIS 2020 was undertaken. The content of the innovation survey follows the common methodology of European countries. As no additional requests were addressed to the Statistical Office of the Slovak Republic to extend the content of the innovation survey.  Communication with customers in case of specific requirements implies that users of innovation statistics are satisfied.

Since 2009, the Statistical Office of the Slovak Republic has carried out an overall customer satisfaction survey at two-year intervals. The purpose of the survey is to obtain information on users interest and opinion regarding provision and quality of statistical products and services. Result of the survey in 2020 is published on the website of the Statistical Office of the SR. https://slovak.statistics.sk/wps/portal/ext/aboutus/marketing/survey.of.satisfaction

In this user satisfaction survey, innovation has been linked with areas of R&D, energy and environment. Average rate of satisfaction with these statistical areas was 68,9 %, but it does not accurately reflect the satisfaction with innovation statistics. 

All compulsory and most of voluntary cells are provided in the output tabulation.

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).

The linearization method using Taylor expansion series was used for variance estimation.

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.

Un-weighted over-coverage rate for Core NACE: 3,16 %

Weighted over-coverage rate for Core NACE: 3,35 %

Not requested.

Exact information on under-coverage is not available. We assume that the under-coverage could be slight only.

Effects of the overcoverage errors were taken into consideration when the updated weights were calculated. So, indirectly the CV (which use weights) incorporate affects of overcoverage 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.

All errors caused by recording were corrected.

Additional methodological explanations for respondents were included in the on-line questionnaire and also automatic controlls to alert respondents about wrong data or logical inconsistencies

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.

Generally, number of maximum reminders were 2 phone calls. In several cases more than 2 phone calls were conducted

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).

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)
 

Number of coding errors is 0.

Processing errors were corrected during the editing procedure. So, CVs do not incorporate the effects of 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 : 18 months after the end of reference period

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) : 

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 problems of comparability between regions of the country.

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 driven by Oslo Manual 2018, CIS 2018 and CIS 2020 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)

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below.

The national statistical business register was used.

Sample design is stratified with SRS in particular strata. The whole sample is divided into strata by crossing the number of employees (3 size groups – 10 to 49, 50 to 249, 250 or more), NACE 2 codes (NACE classification at the two digit level) and NUTS2 level. It gives a number of 660 strata, from which 452 are non-empty. These have to be divided into domains to calculate the proper sample sizes. We obtained 30 domains at NACE 1 level. There are 3 key indexes in CIS 2020 and the sample design must have taken into account all three to follow required precision of key estimates.
We calculated domain sizes for all three key indexes and then made a maximum value from each table for each domain. After obtaining the appropriate domain sizes, we used proportional allocation technique to spread these counts into particular strata. It was not necessary in strata consisted of the companies with more than 250 employees because these are selected exhaustively. In the next step, the numbers were then multiplied, if possible, by an inverse non-response rate obtained from CIS 2018. If some strata consisted of less than 6 respondents and the target population for this strata was greater or equal than the threshold, final number was raised to 6.

The overal sample rate was 45,27 %. The initial weights were calculated as Nh/nh, where Nh was the total number of enterprises in stratum h of the population and nh was the number of enterprises in the sample in stratum h, assuming that each unit in the stratum had the same inclusion probability. Initial weights were updated after collection of questionnaires. 

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 t+18.

See below.

Mandatory survey included in the Program of State Statistical Surveys.

Combination of sample survey and census.

Census for enterprises with 250 and more employees (i.e. for large enterprises) and sample survey for enterprises with 10-249 employees (i.e. for small and medium enterprises).

The criterion to conduct a census is a size class (250 and more employees – large enterprises). However, if a particular stratum has less than six enterprises, then all the enterprises in this stratum are selected for the survey.

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)

Weights calculation method for sample surveys

The calibration software itself is the Calif 4.0 application, which offers advanced web-designed graphical user interface. It is a powerful open-source tool which incorporates all current calibration methodologies. The NSI staff is encouraged to use this tool for calibration.

For details see: https://slovak.statistics.sk/wps/portal/ext/products/software.tools

https://github.com/SO-SR/Calif

Inputs to the program body are: data themselves, specification of variables (which are categorical or numerical), marginal values which we want to calibrate on, degree of stratification, iteration method, lower and upper bounds for weights ratio, maximum number of iterations and a feasible tolerance. The program can stratify the calibration procedure according to defined stratification key. For this purpose we used stratification to NACE2 and size class levels (2D classification). For the calibration procedure variables turnover, number of employed persons and number of enterprises were used.

Not requested.