1.1. Contact organisation
Statistical Office in Szczecin
Statistics Poland
1.2. Contact organisation unit
Centre for Science, Technology, Innovation and Information Society Statistics
Department for Innovation
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Aneta Malesza, Joanna Piotrowska
Statistical Office in Szczecin
ul. Jana Matejki 22
70-530 Szczecin
Karolina Warno
Statistics Poland
Al. Niepodległości 208
00-925 Warszawa
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
7 February 2025
2.2. Metadata last posted
7 February 2025
2.3. Metadata last update
7 February 2025
3.1. Data description
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – new features.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
3.2. Classification system
Indicators related to the enterprises are classified by country, economic activity (NACE Rev. 2), size class of enterprises and type of innovation.
The main typology of classification of enterprises in reference to innovation is the distinction between innovation-active enterprises (INN) and not innovation-active enterprises (NINN).
The enterprise is considered as innovative (INN) if during the reference period it successfully introduced a a) product or a) business process innovation, c) completed but not yet implemented the innovation, d) had ongoing innovation activities, e) abandoned innovation activities or was f) engaged in in-house R&D or R&D contracted out. Non-innovative (NINN) enterprises had no innovation activity mentioned above whatsoever during the reference period.
3.3. Coverage - sector
3.3.1. Main economic sectors covered - NACE Rev.2
In accordance with the Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, the following sectors of the economic activity are included in the core target population: NACE Sections B, C, D, E, H, J, K, and Divisions 46, 71, 72 and 73.
3.3.1.1. Main economic sectors covered - NACE Rev.2 - national particularities
No deviations
3.3.2. Sector coverage - size class
In accordance with Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, only the enterprises with 10 or more employed persons (sum of employees and self-employed persons) are included in the core target population.
3.3.2.1. Sector coverage - size class - national particularities
No deviations
3.4. Statistical concepts and definitions
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
3.5. Statistical unit
Statistical unit enterprise (please take note that previous waves for Poland were presented for legal units).
The sampling was carried out at the level of the legal units. The observation unit was the legal unit.
Process for obtaining results at Statistical Unit Enterprise level in complex enterprises:
- For qualitative variables:
All the complex enterprises were analysed case-by-case. In most of the cases, the representative unit that has been chosen was the unit with the same NACE as the whole enterprise NACE and with the highest number of persons employed (ewentually turnover). In some cases due to lack of response, a unit not meeting these criteria had to be selected.
- For quantitative variables:
Two main methods were used depending on the variable:
- Persons employed and total turnover were derived from the business profiling data.
- The rest of variables were treated according to their characteristics (e.g. the share of persons employed with tertiary degree was calculated on the basis of all the legal units in the enterprise).
3.6. Statistical population
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
3.7. Reference area
The national CIS data is published in Poland for NUTS2 regions, however the breakdown is not the same as for the CIS data for Poland send to Eurostat.
NUTS2 was used as a geographical stratification dimension for the sampling.
The CIS2022 regional data are calibrated at the level of the legal units.
3.8. Coverage - Time
Several rounds of Community Innovation Survey have been conducted so far at two-year interval since the end of the 90’s.
3.8.1. Participation in the CIS waves
| CIS wave | Reference period | Participation (Yes/No) | Comment (deviation from reference period) |
|---|---|---|---|
| CIS2 | 1994-1996 | no | |
| CIS3 | 1998-2000 | yes | no deviations for industry, 1997-1999 for service sector |
| CIS light | 2002-2003* | no | |
| CIS4 | 2002-2004 | yes | no deviations for industry, 2001-2003 for service sector |
| CIS2006 | 2004-2006 | yes | no deviations |
| CIS2008 | 2006-2008 | yes | no deviations |
| CIS2010 | 2008-2010 | yes | no deviations |
| CIS2012 | 2010-2012 | yes | no deviations |
| CIS2014 | 2012-2014 | yes | no deviations |
| CIS2016 | 2014-2016 | yes | no deviations |
| CIS2018 | 2016-2018 | yes | no deviations |
| CIS2020 | 2018-2020 | yes | no deviations |
| CIS2022 | 2020-2022 | yes | no deviations |
*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003
3.9. Base period
Not relevant.
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
6.1. Institutional Mandate - legal acts and other agreements
The CIS is based on the Commission Implementing Regulation (EU) 2022/1092, implementing Regulation (EU) 2019/2152 of the European Parliament and of the Council on the production and development of Community statistics on science and technology.
This Regulation establishes innovation statistics on a statutory basis and makes the delivery of certain variables compulsory e.g. innovation activities, cooperation, development, expenditures and turnover (see the Regulation). Each survey wave may additionally include further variables.
In addition, the Regulation defines the obligatory cross-coverage of economic sectors and size class of enterprises.
6.1.1. National legislation
Programme of Statistical Surveys of Public Statistics for the year 2022, established by the Regulation of the Council of Ministers of November 19th, 2021 as amended (consolidated text JL 2022 item 436)
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
The issue of statistical confidentiality in Poland is settled by the art. 38 of the Law on official statistics of June 29th 1995 (consolidated text in JL of 2024 item 1799), as amended.
7.2. Confidentiality - data treatment
National confidentiality rules: if the aggregate consists of less than 3 records or one record consists over 75% of the whole aggregate, data is deemed confidential.
8.1. Release calendar
There is a calendar of main publications of the innovation data. Publicly accessible are:
- calendar included in the survey description in Programme of Statistical Surveys of Public Statistics (including publications, main databases and yearbooks)
- Editorial Title-Plan (annual), with publications only.
8.2. Release calendar access
Programme of Statistical Surveys of Public Statistics for the year 2022 under survey no 1.43.02 - Survey on innovations (available only in Polish language: Stat website.
Editorial-Title plan: Stat webiste - Editorial title plan of the statisics poland and rso.
8.3. Release policy - user access
The general rule for release the statistical data is that we are publishing the short information with the main indicators on the Statistics Poland website. Stat website - Innovation activities of enterprises in the years 2020 2022.
Then the more detailed publications are prepared and published - also on the Statistics Poland website as well as in the traditional, paper form (paper form is for fee): Stat website - Science and technology in 2022.
Databases:
All these releases are public, available for all users. Only publications in paper form are for fee, the electronic forms of publication are free.
The information about the publication is published on Statistics Poland and Statistical Office in Szczecin websites and social media accounts.
Please take note that results in Poland are published still for legal units in order to maintain the time series.
CIS is conducted and disseminated at two-year interval in pair years.
Accessibility and clarity refer to the simplicity and ease for users to access statistics using simple and user-friendly procedure, obtaining them in an expected form and within an acceptable time period, with the appropriate user information and assistance: a global context which finally enables them to make optimum use of the statistics.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Dissemination and access | Availability | Comments, links, ... |
|---|---|---|
| Press release | YES | Short release Stat webiste - Innovation activities of enterprises in poland in the years 2020-2022 (data for legal units) |
| Access to public free of charge | YES | (data for legal units) |
| Access to public restricted (membership/password/part of data provided, etc) | NO |
10.2. Dissemination format - Publications
- Online database (containing all/most results).
- Analytical publication (referring to all/most results).
- Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect): publications where innovation activity is only one of more themes of science and technology domain: Stat website - Science and technology in 2022, Stat website (PL).
10.3. Dissemination format - online database
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
Anonymised data available only on individual requests from researchers
10.4.1. Dissemination of microdata
| Mean of dissemination | Availability of microdata | Comments, links, ... |
|---|---|---|
| Eurostat SAFE centre | NO | |
| National SAFE centre | NO | anonymised data available only on individual requests from researchers |
| Eurostat: partially anonymised data (SUF) | NO | |
| National: partially anonymised data | NO |
10.5. Dissemination format - other
None
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
The most detailed meta-information is included in the main publication (in Polish language: Stat website - Innovation activities of enterprises in the years 2020-2022). It consists: Definitions of terms used, scope of surveyed population according to Nace Rev.2 (in Poland - PKD2007) - current and historical, brief presentation of used classifications.
The main definitions are also included in the Glossary of terms, being a part of Metainformation published on the Statistics Poland website (in Polish and English: Stat website glossary).
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
Quality reports performed in Poland are publicly accessible only partly.
There's no dedicated quality study for innovation statistics in Poland. We use general documents, as well as good practices. They're also internal documents, but based inter alia on international guidelines.
Publicly accessible is the Compendium of Knowledge from Quality in Statistics (available only in Polish): Stat website.
11.1. Quality assurance
Methodological concepts and definitions are based on Oslo Manual and Methodological recommendations.
Quality management is based on documents and guidelines mentioned in point 10.7.
Main strengths of Polish CIS:
- electronic form of collecting data (convenient for respondents, economical form of collecting data, data control during fulfilling questionnaires providing good quality data, built-in filters)
- high unit response rate,
- electronic and manual data checking (3 phases of checking)
- survey results including regional breakdown.
Main weaknesses of Polish CIS: not indicated.
11.2. Quality management - assessment
In every CIS wave we introduce new and improved validations, guideliness for enterprises, tools for statisticians etc. on the basis of previous experiences to improve the quality of the data.
12.1. Relevance - User Needs
The CIS2022 Polish questionnaire contains additional questions in the response to reported needs: the sale of goods (total and also new or improved), cluster cooperation, number of IPR applications and received protection rights.
The subject scope of survey on innovation in Poland is included in the Programme of Statistical Surveys of Public Statistics, which is a legal act implemented in the form of a regulation of the Council of Ministers. Like every legal act in Poland, the draft of this regulation is subject to interdepartmental agreements, opinions and public consultations. Some additional questions in Polish CIS questionnaire are therefore the result of comments and suggestions submitted as part of the consultation. Some institutions also submit their proposals on other occasions, e.g. meetings on a broader subject than CIS (e.g. questions on IPR agreed with the Polish Patent Office).
12.1.1. Needs at national level
| User group | Short description of user group | Main needs for CIS data of the user group Users’ needs |
|---|---|---|
| 1 - Institutions - European level | The European Commission | European Innovation Scoreboard, Regional Innovation Scoreboard |
| 1 - Institutions - International organisations | OECD | Data used for analyses and international comparisons |
| 1 - Institutions - national level | The Ministry of Economic Development and Technology; The Ministry of Industry, The Ministry of Development Funds and Regional Policy; Polish Agency for Enterprise Development, Narodowy Bank Polski (National Polish Bank) | Data used for conducting innovation policy (evaluation and monitoring of special programmes and strategies) |
| 1 - Institutions - regional level | Units of Territorial Self-government | Data used for conducting innovation policy (evaluation and monitoring of special programmes and strategies) |
| 3 - Media | International, national and regional press-economic, technical and for the general public | Data used for analyses and comments |
| 4 - Researchers and students | Public and private research institutes (e. g. Center for Social and Economic Research), Universities (higher education institutions, students and postgraduate students) | Data used for research projects, analyses, scientific publications, studies, diploma works |
12.2. Relevance - User Satisfaction
No user satisfaction survey has been undertaken
12.3. Completeness
All mandatory sectors and indicators required by the Commission Implementing Regulation (EU) 2022/1092 are covered in Polish CIS. Missingness in data is only due to Polish coverage of the survey - in Poland only core CIS coverage is surveyed.
12.3.1. Data completeness - rate
Not requested.
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
13.2. Sampling error
Restricted from publication
13.2.1. Sampling error - indicators
The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).
CV= Coefficient of variation (%) = 100 * (Square root of the estimate of the sampling variance) / (Estimated value)
Formula:
where
and
13.2.1.1. Coefficient of variations for key variables
Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 or more employed persons
| NACE |
Size class |
(1) |
(2) |
(3) |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) |
Total |
Not available. |
Not available. | Not available. |
| Core industry (B_C_D_E - excluding construction) |
Total |
Not available. |
Not available. | Not available. |
| Core Services (46-H-J-K-71-72-73) |
Total |
Not available. |
Not available. | Not available. |
(1) = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT)
(2) = Coefficient of variation for the turnover of product innovative enterprises with new or improved products (TUR_PRD_NEW_MKT), as a percentage of total turnover of product innovative enterprises [TOVT,INNO_PRD].
(3) = Coefficient of variation for percentage of product and/or process innovative enterprises (incl. enterprises with abandoned and or on-going activities) involved in any innovation co-operation arrangement [COOP_ALL,INN], as a percentage of innovative enterprises (INN).
13.2.1.2. Variance estimation method
Estimation of variance was based on classical formulas used for variance of totals in stratified random sampling. For ratio of two variables linearization method was used.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors (or frame errors) are due to divergences between the target population and the frame population. The frame population is the set of target population members that have a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under covered groups of the target population
We try to eliminate under coverage at the sampling stage - breakdowns with small number of enterprises are selected for the sample as a whole.
13.3.1.4. Coverage errors in coefficient variation
Coverage errors were not considered in calculation of the CVs.
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.
13.3.2.1. Measures for reducing measurement errors
On-line questionnaire with built-in validations and filters reduce bias. Questionnaire is tested by statistitians before the beginning if the data collection.
We have exhaustive explanatory notes attached to the questionnaire. Before every survey we perform training for statistitians.
13.3.3. Non response 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)
In Polish CIS survey occured unit non-responses as well as item non-responses.
13.3.3.1. Unit non-response - rate
See below.
13.3.3.1.1. Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
| NACE | Number of eligible units with no response | Total number of eligible units in the sample | Un-weighted unit non-response rate (%) | Weighted unit non-response rate (%) |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | 5408 | 19933 | 27.1% | 39.4% |
| Core industry (B_C_D_E - excluding construction) | 3730 | 14056 | 26.5% | 36.5% |
| Core Services (46-H-J-K-71-72-73) | 1678 | 5877 | 28.6% | 42.4% |
The number of eligible units is the number of sample units, that ultimately indeed belong to the target population.
13.3.3.1.2. Maximum number of recalls/reminders before coding
Can’t provide the maximum. The minimum is: one e-mail reminder before the date of receipt, then after this date: 5 e-mail reminders for all non-respondents and additionally urging notes, e-mails and phone calls for still non-responders.
13.3.3.2. Item non-response - rate
See below.
13.3.3.2.1. Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons).
| Item non-response rate (un-weighted) (%) |
Imputation (Yes/No) |
If imputed, describe method used, mentioning which auxiliary information or stratification is used | |
|---|---|---|---|
| Turnover | 1.3% | Y | Imputation was used only for part of missing values, for which data from other sources were unavailable. The method was hot-deck within strata (randomly). Stratification criteria: 2-digit NACE (even 3-digit where possible), size class and ownership sector. For turnover an additional criterion was used, i.e. ranges of quintile groups according to the value in the previous year. |
13.3.3.2.2. Item non response rate for new questions
Item non-response rate for new questions in CIS t (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
| NEW QUESTIONS IN CIS 2022 | Inclusion in national questionnaire (Yes/No) | Item non response rate (un-weighted) (%) | Comments |
|---|---|---|---|
| 3.9 -- Reasons for not having more innovation activities | YES | 0.2% | |
| 3.10 -- Reasons for having no innovation activities | YES | 0.1% | |
| 5.4 - Fundamental changes to business model | YES | 0.2% |
13.3.4. Processing error
Insignificant. Most responses are received through on-line questionnaires. manual data entry is used only in specific situations. Variables for the whole ENT (TURN and EMP) are obtained from a source common to economic surveys.
13.3.5. Model assumption error
Not requested.
Timeliness and punctuality refer to time and dates, but in a different manner.
14.1. Timeliness
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
14.1.1. Time lag - first result
Timeliness of national data – date of first release of national level: 209
14.1.2. Time lag - final result
Not requested.
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Date of transmission of complete and validated data to Eurostat (Number of days between that date and 30 June 2024) : 68
Comparability aims at measuring the impact of differences in applied statistical concepts and definitions on the comparison of statistics between geographical areas, non-geographical domains, or over time.
The coherence of statistical outputs refers to the degree to which the statistical processes by which they were generated used the same concepts (classifications, definitions, and target populations) and harmonised methods. Coherent statistical outputs have the potential to be validly combined and used jointly.
15.1. Comparability - geographical
In Polish publications data for Poland and NUTS 2 regions are presented for legal units. For Eurostat data for Poland was presentes for statistical unit enterprise, while for NUTS2 regions - as before for legal units.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. National questionnaire – compliance with Eurostat model questionnaire
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Questions not included in national questionnaire compared to HDC | Comment |
|---|---|
| all were included |
| Changes in the filtering compared to HDC | Comment |
|---|---|
| none |
15.1.3. National questionnaire – additional questions
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Additional questions in national questionnaire (not included in HDC) | Comment |
|---|---|
| Revenues on sales of new or improved goods | traditionally collected in Poland |
| Revenues on sales of goods | traditionally collected in Poland |
| Cluster cooperation | |
| Question 2.4 is divided for "application" and "receiving" rights including | |
| Sources of funds on innovation expenditures | |
| Short questions on usage of bio-, nano- and metrology | |
| time for preparing data and filling the questionnaire |
15.2. Comparability - over time
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
15.2.1. Length of comparable time series
Not requested.
15.3. Coherence - cross domain
See the comparison between SBS and CIS data in the section 15.3.3 below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Not requested.
15.3.3. Coherence – Structural Business Statistics (SBS)
This part compares key variables for aggregated CIS data with SBS data
Definition of relative difference between CIS and SBS data: DIFF = (SBS/CIS)*100
Comparison between SBS and CIS data (relative difference) by NACE categories and for enterprises with 10 or more employed persons
| NACE | Size class | Number of enterprises (SBS/CIS)* | Number of employed persons (SBS/CIS)* | Total Turnover (SBS/CIS)* |
|---|---|---|---|---|
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | 102.2% | 88.6 % | 79.8% |
| Core industry (B_C_D_E - excluding construction) | Total | 103.3% | 74.0 % | 76.2% |
| Core Services (46-H-J-K-71-72-73) | Total | 102.7% | 82.2 % | 78.3% |
* Numbers are to be provided for the last year of the reference period (t)
15.4. Coherence - internal
Not requested.
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
In Poland CIS 2022 was performed as the PNT-02 – Survey on innovations. The previous edition was performed as two surveys – separate for industry and service sector, while now the surveys are combined into one.
18.1.1. Sampling frame (or census frame)
The official statistical business register of the country was used, including business profiling.
18.1.2. Sampling design
CIS 2022 was for the first time performed in Poland in a manner that ensures comparability with previous years at the national level using legal units and simultaneously allows preparation of the data for statistical unit enterprise.
This approach resulted in the need for a two-stage sample draw, as described below.
Stage 1 included sampling for industry and services under the existing rules.
The samples were drawn separately for industry and service sector by the method of simple random sampling, independently in every stratum. Strata were defined as the NACE intersections of NACE divisions, geographical regions (NUTS2 level) and enterprise sizes (10-49, 50-249 and 250+ persons employed). The samples were allocated into strata using historical data from previous surveys and numerical optimisation methods.
Stage 2 consisted of selecting units in a way that ensures presenting the data for the statistical unit enterprise. First, the sample was analysed in terms of affiliation of chosen legal units to the enterprises, which resulted in a list of enterprises in the sample. Then the sample was supplemented with the legal units belonging to the enterprises from the list. This stage was performed on the basis of business profiling.
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
| Target population (A) (*) | 63000 |
| Sample (B = C+D) | 20439 |
| In case of combination sample/census: | |
| Sampled units (C) | 12393 |
| Enumerated units/census (D) | 8046 |
| Overall sample rate (E = 100*B/A) | 32.4 % |
(*) CIS core population, i.e. NACE Rev.2 B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons.
18.1.4. Data source for pre-filled variables
Variables and indicators filled or prefilled from other sources.
| Variables/Indicators | Source | Reference year |
|---|---|---|
| Total turnover - in case of missing the variable in CIS data | SBS | 2022 |
18.1.5. Data source and variables used for derivation and weighting
| Item | Response |
|---|---|
| Data source used for deriving population totals | Total population is the number of enterprises in the frame corrected by the number of non-responses due to inactivity or non-eligibility. |
| Variables used for weighting | The number of enteprises in the frame and in the realised sample, and information about the reasons of non-response were used for weighting process. |
18.2. Frequency of data collection
According to the Commission Implementing Regulation (EU) 2022/1092, the innovation statistics shall be provided to Eurostat every two years in each even year. The data collection takes place every second year in year t-2 preceding the data provision.
Data for Poland with no deviations. Innovation survey in Poland is performed now every two years.
18.3. Data collection
CIS 2022 in Poland was performed as PNT-02 – Survey on innovations. Unlike the CIS 2020, it was only one survey and one questionnaire.
18.3.1. Survey participation
The survey was mandatory.
18.3.2. Survey type
The survey was realised as a combination of census and sample.
18.3.3. Combination of sample survey and census data
According to description in pt.18.1.2, works on the population consisted 2 stages: 1. stage for national needs on the basis of legal units, and 2. stage to ensure the ability to present data for statistical unit enterprise.
In the 1.stage, the census was applied for the subpopulation of industrial enterprises (NACE sections B-E) with more than 49 persons employed while sample survey was used for industrial units with 10-49 persons employed and whole service sector (procedure the same as in previous CIS rounds).
In the 2.stage, the list of units from the stage 1. was supplemented with the legal units belonging to the enterprises according to the list with business profiling.
18.3.4. Census criteria
- NACE (industry);
- Number of persons employed;
- Affiliation to an enterprise.
18.3.5. Data collection method
Data collection method
| Survey method | Yes/No | Comment |
|---|---|---|
| Face-to-face interview | NO | |
| Telephone interview | NO | |
| Postal questionnaire | NO | |
| Electronic questionnaire (format Word or PDF to send back by email) | NO | |
| Web survey (online survey available on the platform via URL) | YES | The main method. Other methods (telephone, electronic, postal) were used only in small number of cases (when the unit couldn’t use the web survey e.g. because it was too late or it didn’t want to). |
| Other | NO |
18.4. Data validation
Not requested.
18.5. Data compilation
Operations performed on data to derive new information according to a given set of rules.
18.5.1. Imputation - rate
Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition of imputation rate:
Imputation rate (for the variable x) (%) = 100 * (Number of replaced values) / (Total number of values for a given variable)
Definition of weighted imputation rate:
Weighted imputation rate= 100 * (Number of total weighted replaced values) / (Total number of weighted values for a given variable)
18.5.1.1. Imputation rate for metric variables
Imputation rate (%) for metric variables by NACE categories and for enterprises with 10 or more employed persons:
| NACE | Size class | Total Turnover (1) | Turnover from products new to the market (2) | R&D expenditure in-house (3) | |||
|---|---|---|---|---|---|---|---|
| Unweighted | Weighted | Unweighted | Weighted | Unweighted | Weighted | ||
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | 1.1% | 1.0% | 0.4% | 0.2% | 0.2% | 0.2% |
| Core industry (B_C_D_E - excluding construction) | Total | 1.2% | 1.3% | 0.4% | 0.3% | 0.2% | 0.2% |
| Core Services (46-H-J-K-71-72-73) | Total | 1.1% | 0.7% | 0.4% | 0.1% | 0.3% | 0.1% |
(1) = Imputation rate (%) for the total turnover in the last year of the reference period (t) (TUR)
(2) = Imputation rate (%) for the share of the turnover in the last year of the reference period (t) due to new or improved product new to the market in the total turnover for product innovative enterprises TUR_PRD_NEW_MKT/TOVT(INNO_PRD)
(3) = Imputation rate (%) for the R&D expenditure performed in-house (EXP_INNO_RND_IH)
18.5.2. Weights calculation
Weights calculation method for sample surveys
| Method | Selected applied method | Comments |
|---|---|---|
| Inverse sampling fraction | X | The base weights were calculated separately for strata as ratios: the number of enterprises of the frame population to the number of enterprises in the sample. |
| Non-respondent adjustments | X | The base weights were corrected for unit non-response by multiplying the base weight by adjustment factor. The non-response adjustment factors were computed using information from enterprise about reasons of non response (e.g. unit was inactive or there was incorrect contact information). |
| Other |
18.6. Adjustment
The calibration was not used.
18.6.1. Seasonal adjustment
Not requested.
No further comments.
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – new features.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
7 February 2025
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
Statistical unit enterprise (please take note that previous waves for Poland were presented for legal units).
The sampling was carried out at the level of the legal units. The observation unit was the legal unit.
Process for obtaining results at Statistical Unit Enterprise level in complex enterprises:
- For qualitative variables:
All the complex enterprises were analysed case-by-case. In most of the cases, the representative unit that has been chosen was the unit with the same NACE as the whole enterprise NACE and with the highest number of persons employed (ewentually turnover). In some cases due to lack of response, a unit not meeting these criteria had to be selected.
- For quantitative variables:
Two main methods were used depending on the variable:
- Persons employed and total turnover were derived from the business profiling data.
- The rest of variables were treated according to their characteristics (e.g. the share of persons employed with tertiary degree was calculated on the basis of all the legal units in the enterprise).
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
The national CIS data is published in Poland for NUTS2 regions, however the breakdown is not the same as for the CIS data for Poland send to Eurostat.
NUTS2 was used as a geographical stratification dimension for the sampling.
The CIS2022 regional data are calibrated at the level of the legal units.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
Operations performed on data to derive new information according to a given set of rules.
In Poland CIS 2022 was performed as the PNT-02 – Survey on innovations. The previous edition was performed as two surveys – separate for industry and service sector, while now the surveys are combined into one.
CIS is conducted and disseminated at two-year interval in pair years.
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
In Polish publications data for Poland and NUTS 2 regions are presented for legal units. For Eurostat data for Poland was presentes for statistical unit enterprise, while for NUTS2 regions - as before for legal units.
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
