1.1. Contact organisation
Statistical Office in Szczecin
Statistics Poland
1.2. Contact organisation unit
Centre for Science, Technology, Innovation and Information Society (Statistical Office in Szczecin)
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Aneta Malesza
Statistical Office in Szczecin
Matejki Str. 22
70-530 Szczecin
Poland
Joanna Piotrowska
Statistical Office in Szczecin
Matejki Str. 22
70-530 Szczecin
Poland
Karolina Warno
Central Statistical Office
00-925 Warsaw, Al. Niepodległości 208
Poland
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
30 May 2024
2.2. Metadata last posted
30 May 2024
2.3. Metadata last update
30 May 2024
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.
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.
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
CIS covers main economic sectors according to NACE Rev.2 broken down by size class of enterprises and type of innovation activity.
3.3.1. Main economic sectors covered - NACE Rev.2
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
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 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
3.3.2.1. Sector coverage - size class - national particularities
Persons employed instead of employees
3.4. Statistical concepts and definitions
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.
3.5. Statistical unit
Legal unit (as well as in the previous CIS waves for Poland)
3.6. Statistical population
Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employees.
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.
3.8. Coverage - Time
Several rounds of Community Innovation Survey have been conducted so far at two-year interval since end of 90’s.
3.8.1. Participation in the CIS waves
| CIS wave | Reference period | Participation | 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 |
*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 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).
6.1. Institutional Mandate - legal acts and other agreements
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.
6.1.1. National legislation
Programme of Statistical Surveys of Public Statistics for the year 2020, established by the Regulation of the Council of Ministers of October 11th, 2019 as amended (consolidated text published under JL 2021 item 698).
6.2. Institutional Mandate - data sharing
Not requested.
CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system.
7.1. Confidentiality - policy
The issue of statistical confidentiality in Poland is settled by the art. 10 and art. 38 of the Law on official statistics of June 29th 1995 (latest version: JL 2022, item 459) as amended.
7.2. Confidentiality - data treatment
National confidentiality rules: if the aggregate consist of less than 3 records or one record consist 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 2020 under surveys no 1.43.02 - industry and 1.43.13 - service sector (available only in Polish language: https://bip.stat.gov.pl/dzialalnosc-statystyki-publicznej/program-badan-statystycznych/pbssp-2020/)
- Editorial-Title plan: https://stat.gov.pl/en/questions-and-orders/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.
(available in Polish only: https://stat.gov.pl/obszary-tematyczne/nauka-i-technika-spoleczenstwo-informacyjne/nauka-i-technika/dzialalnosc-innowacyjna-przedsiebiorstw-w-polsce-w-latach-2018-2020,14,8.html).
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):
https://stat.gov.pl/en/topics/science-and-technology/science-and-technology/innovation-activities-of-enterprises-in-the-years-2018-2020,3,6.html
https://stat.gov.pl/en/topics/science-and-technology/science-and-technology/science-and-technology-in-2020,1,16.html
Databases:
https://bdl.stat.gov.pl/BDL/start
https://strateg.stat.gov.pl/#/
http://swaid.stat.gov.pl/EN/SitePagesDBW/NaukaTechnika.aspx
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.
CIS is conducted and disseminated at two-year interval in pair years.
In Poland innovation survey is annual, after CIS2022 we plan to change it and perform biannually only in CIS 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 (in Polish): https://stat.gov.pl/obszary-tematyczne/nauka-i-technika-spoleczenstwo-informacyjne/nauka-i-technika/dzialalnosc-innowacyjna-przedsiebiorstw-w-polsce-w-latach-2018-2020,14,8.html |
| Access to public free of charge | YES | |
| Access to public restricted (membership/password/part of data provided, etc) | NO |
10.2. Dissemination format - Publications
- Online database (containing all/most results) : Local Data Bank https://bdl.stat.gov.pl/BDL/start
- Analytical publication (referring to all/most results) : https://stat.gov.pl/en/topics/science-and-technology/science-and-technology/innovation-activities-of-enterprises-in-the-years-2018-2020,3,6.html
- 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: https://stat.gov.pl/en/topics/science-and-technology/science-and-technology/science-and-technology-in-2020,1,16.html , https://szczecin.stat.gov.pl/publikacje-i-foldery/nauka-technika/gospodarka-oparta-na-wiedzy-w-wojewodztwie-zachodniopomorskim-w-2021-r-,2,13.html
10.3. Dissemination format - online database
https://bdl.stat.gov.pl/BDL/start
https://strateg.stat.gov.pl/#/
http://swaid.stat.gov.pl/en/SitePagesDBW/NaukaTechnika.aspx
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
No
10.4.1. Dissemination of microdata
| Mean of dissemination | Availability of microdata | Comments, links, ... |
| Eurostat SAFE centre | NO | |
| National SAFE centre | NO | |
| 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: https://stat.gov.pl/en/topics/science-and-technology/science-and-technology/innovation-activities-of-enterprises-in-the-years-2018-2020,3,6.html). 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: https://stat.gov.pl/en/metainformation/glossary/ )
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
Quality reports performed in Poland are publicly accessible only partly. The quality reports for innovation surveys managing CIS 2020 are not published yet.
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): https://bip.stat.gov.pl/dzialalnosc-statystyki-publicznej/jakosc-w-statystyce/ocena-i-monitorowanie-jakosci-procesow-statystycznych/
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.
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.
12.1. Relevance - User Needs
The CIS2020 Polish questionnaires 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 and impact of COVID-19 situation on the enteprises' activities.
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) or as a current demand (e.g. questions on COVID-19 situation impact).
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 (DG ENTR) | European Innovation Scoreboard, Regional Innovation Scoreboard |
| 1 - Institutions - International organisations | OECD | Data used for analyses and international comparisons |
| 1 - Institutions - national level | Ministry of Economic Development, Labour and Technology; 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 Regulation 995/2012 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
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.
13.2.1. Sampling error - indicators
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
13.2.1.1. Coefficient of variations for key variables
Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 and more employees
| NACE |
Size class |
(1) |
(2) |
(3) |
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) |
Total |
1,98 |
1,42 |
3,52 |
| Core industry (B_C_D_E - excluding construction) |
Total |
1,66 |
1,40 |
2,96 |
| Core Services (46-H-J-K-71-72-73) |
Total |
3,89 |
1,49 |
7,21 |
[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).
13.2.1.2. Variance estimation method
Estimation of variance was based on linearization method for ratio of two variables and classical formulas used for variance of totals in stratified random sampling; practical computations were done in SAS using SURVEYMEANS procedure.
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 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.
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
Over-coverage was not observed. 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 persons employed
| 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) | 5549 | 21300 | 26,1 | 36,7 |
| Core industry (B_C_D_E - excluding construction) | 3663 | 15000 | 24,4 | 33,9 |
| Core Services (46-H-J-K-71-72-73) | 1886 | 6300 | 29,9 | 39,8 |
The number of eligible units is the number of sample units, which indeed belong to the target population.
13.3.3.1.2. Maximum number of recalls/reminders before coding
One e-mail reminder before the date of receipt, then after this date: 5 e-mail reminders for all non- responders 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 persons emloyed).
| Item non-response rate (un-weighted) | Imputation | If imputed, describe method used, mentioning which auxiliary information or stratification is used | |
| Turnover | 0.80% | 0.04% | Hot-deck - data drawn from one of similar units (randomly); similarity criteria: size, NACE class (or group if necessary), sector, type of property. |
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 employees)
| NEW QUESTIONS IN CIS 2020 | Inclusion in national questionnaire | Item non response rate (un-weighted) | Comments |
| 2.2 Market conditions faced by enterprise | YES | 0.07% | |
| 2.8 Factors related to climate change | YES | 0.09% | |
| 3.16 Innovations with environmental benefits | YES | 0.43% | |
| 3.17 Factors driving environmental innovations | YES | 0.35% |
13.3.4. Processing error
Insignificant. Most responses are received through online questionnaires. Manual data entry is used only in specific situations (when enterprise cannot fill the on-line questionnaire and sends paper one).
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
The date of release of national CIS2020 data is November 29th 2021.
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 data and 30 June 2022) : 30 th June 2022 (0)
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
No problem at national nad NUTS 2 level.
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 mandatory and voluntary variables were collected. | all questions were included |
| Changes in the filtering compared to HDC | Comment |
| none | the filters used were just as in HDC |
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 from sales of new or improved goods |
traditionally collected in Poland |
| Revenues from sales of goods | traditionally collected in Poland |
| COVID-19 situation impact | |
| Cluster cooperation | |
| In Q2.4 - dividing for question on "application" and "receiving" rights including number of them and distinction between Polish and foreign patent offices | inventions/patents, utility models, industrial designs, trademarks |
| Sources of funds on innovation expenditures | traditionally collected in Poland |
| questions (short) on using bio-, nano- and metrology in enterprise | |
| time for preparing data and filling the questionnaire | |
| Adding “other expenditures” to the list of innovation expenditures in Q3.8. | |
15.2. Comparability - over time
Due to important methodological changes driven by Oslo Manual 2018, CIS 2018 and CIS 2020 cannot be directly compared with previous CIS waves.
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 persons employed
IMPORTANT: Total Core NACE and Core services unable to compare in order to significant difference between SBS and CIS in surveing section K, data unweighted
| NACE | Size class | Number of enterprises (SBS/CIS)* | Number of persons employed (SBS/CIS)* | Total Turnover (SBS/CIS)* |
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | |||
| Core industry (B_C_D_E - excluding construction) | Total | 156.2 | 103.8 | |
| Core Services (46-H-J-K-71-72-73) | Total |
* 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 CIS2020 was performed as two surveys - PNT-02 - Innovation survey in industry and PNT-02/u - Innovation survey in service sector.
The source database for compliling CIS2020 aggregates is prepared by combining the eligibile records from both surveys.
18.1.1. Sampling frame (or census frame)
The official, up-to-date, statistical business register of the country was used.
18.1.2. Sampling design
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 intersections of NACE divisions, geographical regions (NUTS2 level voivodships) and enterprise sizes (10-49 persons employed, 50-249,250+).
The samples were allocated into strata using historical data from previous surveys and numerical optimisation methods. Samples were allocated in such a way to meet the precision criteria from Eurostat's methodological recommendations.
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
| Target population | 63981 |
| Sample | |
| In case of combination sample/census: | |
| Sampled units | 12201 |
| Enumerated units/census | 9099 |
| Overall sample rate (overall sample/target population) | 33,3% |
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 lack of this variable in CIS data | SBS | 2020 |
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 enterprise in the frame corrected by the number of non-responses due to inactivity or non-eligibility |
| Variables used for weighting | The number of enterprises in the frame and in the realised sample, and information about reasons of non-response were used for weighting process. |
18.2. Frequency of data collection
According to the Commission Regulation (UE) 995/2012, the innovation statistics shall be provided to Eurostat every two years in each even year t+18.
Data for Poland provided with no deviations.
Generally in Poland innovation survey is performed annually. It will change after CIS2022 - it will be biannual, performed in CIS years.
18.3. Data collection
In Poland CIS2020 was performed as two surveys - PNT-02 - Innovation survey in industry and PNT-02/u - Innovation survey in service sector.
18.3.1. Survey participation
The survey was mandatory
18.3.2. Survey type
The survey was realised as a combination of sample survey and census.
18.3.3. Combination of sample survey and census data
The census was applied for the subpopulation of industrial enterprises (NACE sections B, C, D and E) with more than 49 persons employed and sample survey was used for industrial enterprises with 10-49 persons employed and for the service sector.
18.3.4. Census criteria
- NACE (industry)
- size class (50 and more persons employed)
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 web survey eg. because it was too late or 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 persons employed:
| 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 | 0.1 | 0.1 | 0.9 | 0.7 | 0.2 | 0.3 |
| Core industry (B_C_D_E - excluding construction) | Total | 0.1 | 0.1 | 1.0 | 0.8 | 0.2 | 0.5 |
| Core Services (46-H-J-K-71-72-73) | Total | 0.0 | 0.1 | 0.8 | 0.7 | 0.0 | 0.0 |
(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)
18.5.2. Weights calculation
Weights calculation method for sample surveys
| Method | Selected applied method | Comments |
| Inverse sampling fraction | ||
| Non-respondent adjustments | 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. 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.
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.
30 May 2024
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.
Legal unit (as well as in the previous CIS waves for Poland)
Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employees.
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.
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).
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 CIS2020 was performed as two surveys - PNT-02 - Innovation survey in industry and PNT-02/u - Innovation survey in service sector.
The source database for compliling CIS2020 aggregates is prepared by combining the eligibile records from both surveys.
CIS is conducted and disseminated at two-year interval in pair years.
In Poland innovation survey is annual, after CIS2022 we plan to change it and perform biannually only in CIS years.
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
No problem at national nad NUTS 2 level.
Due to important methodological changes driven by Oslo Manual 2018, CIS 2018 and CIS 2020 cannot be directly compared with previous CIS waves.
