1.1. Contact organisation
National Statistics Office (NSO) - Malta
1.2. Contact organisation unit
Business Register, Research and Innovation Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
National Statistics Office (NSO),
Lascaris, Valletta VLT 2000, Malta.
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
25 October 2022
2.2. Metadata last posted
25 October 2022
2.3. Metadata last update
8 October 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.
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
Data for this study is collected through a census of enterprises employing 10 or more persons.
NACE Rev. 2 Sections A to N are covered by the CIS.
Size classes are based on the number of employees: 10-49 employees, 50-249 employees, 250+ employees.
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
NACE Rev. 2 Sections A to N are covered by the CIS.
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
Grouping of size classes is according to the regulation.
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
The enterprise
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: Only one unit is selected as 'representative' and data provided is based on answers given by the 'representative' unit.
- For quantitative variables: Data is collected from the representative unit and added with data from other units within 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 CIS survey covers enterprises located in Malta and Gozo NUTS 1 and 2.
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 | ||
| CIS3 | 1998-2000 | x | |
| CIS light | 2002-2003* | ||
| CIS4 | 2002-2004 | x | |
| CIS2006 | 2004-2006 | x | |
| CIS2008 | 2006-2008 | x | |
| CIS2010 | 2008-2010 | x | |
| CIS2012 | 2010-2012 | x | |
| CIS2014 | 2012-2014 | x | |
| CIS2016 | 2014-2016 | x | |
| CIS2018 | 2016-2018 | x | |
| CIS2020 | 2018-2020 | x | |
| CIS2022 | 2020-2022 | x |
*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
The Malta Statistics Authority Act 2000
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
At National level:
The confidentiality policy of the NSO can be accessed through this website.
At European level:
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Confidential data sent to Eurostat is flagged to prevent publishing. Furthermore, if any requested data is identified as confidential, this will not be provided. Primary and secondary confidentiality rules are applied. That is for information which is being requested by NACE, if the number of units is below the value of 3 will not be released. Furthermore, any kind of information on individual units may not be given to other individuals or entities requesting the data. Confidential data sent to Eurostat is flagged to prevent publishing.
8.1. Release calendar
An advance release calendar is maintained by the NSO and published on the NSO website.
8.2. Release calendar access
8.3. Release policy - user access
National Statisitcs Office’s primary channel of dissemination for official statistics is the NSO website on which official statistics are published and made available to the public free of charge. The Office also makes use of social media venues as a platform to communicate with its users and to present its output. The public is free to use, copy and quote the information published provided that the NSO is quoted as the source. It should be understood, however, that any calculations and conclusions drawn by users on the basis of the NSO data are the intellectual product of themselves.
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 | x | 17th September 2024 - NSO website - business-innovation. |
| Access to public free of charge | x | 17th September 2024 |
| Access to public restricted (membership/password/part of data provided, etc) |
10.2. Dissemination format - Publications
- Online database (containing all/most results): yes.
- Analytical publication (referring to all/most results).
- Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect).
10.3. Dissemination format - online database
The link for the Innovation Database can be found at this website: Database.
The following path needs to be followed to access the database - Database by themes; Science, technology, digital society; Science and technology; Community Innovation Survey (CIS).
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
Micro data is provided to Eurostat.
10.4.1. Dissemination of microdata
| Mean of dissemination | Availability of microdata | Comments, links, ... |
| Eurostat SAFE centre | ||
| National SAFE centre | ||
| Eurostat: partially anonymised data (SUF) | x | Community innovation survey. |
| National: partially anonymised data |
10.5. Dissemination format - other
No other means of dissemination.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
Data is given on request and accompanying information to the data and assistance is directly linked to the requested data.
11.1. Quality assurance
The NSO ensures the accuracy of data released to the public and prepares clear methodological notes which explain the processes involved in the collection and production of official statistics.
The NSO has developed an internal Quality Management Framework (QMF) which is built on common requirements of the ESS Code of Practice (ESS CoP). A document was prepared to include a set of general quality guidelines spanning over all statistical domains. Assuring methodological soundness is an integral part of the QMF, nonetheless, the document spans also on other areas related to institutional aspects.
Every five to seven years, the NSO participates in a Peer Review exercise through which the compliance of its operations with principles of the ESS CoP is assessed by an expert team. Peer Reviews are indeed part of the European Statistical System (ESS) strategy to implement the ESS CoP. Each NSI is expected to provide information as requested by a standard self-assessment questionnaire. Following this an expert team visits the office to meet NSI representatives and main stakeholders. Peer Reviews result in a compliance report and the listing of a set of Improvement Actions which need to be followed up by the NSI.
11.2. Quality management - assessment
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. Comparability of data with previous years based on the same methodology is the main assessment for quality.
12.1. Relevance - User Needs
Insitutions both at European and national levels, researchers and students, and enterprises and businesses
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 | DG ENTR | European Innovation Scoreboard |
| 1. Institutions - National Level | Malta Council for Science and Technology (MCST) | Satisfy international requirements as well as to produce national policy |
| 4. Researchers and students | Researchers and students | To substantiate their studies |
| 5. Enterprises or businesses | Various |
12.2. Relevance - User Satisfaction
No user satisfaction survey was undertaken specific on innovation data.
12.3. Completeness
Data is fully complete since all requested data is provided. There were no missing cells.
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 |
|
||
| Core industry (B_C_D_E - excluding construction) |
Total |
|
||
| Core Services (46-H-J-K-71-72-73) |
Total |
|
(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
Not applicable. The innovation survey is a census.
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
The difference between the target population and the frame population is of 142 enterprises. This was mainly due to closures, inactive enterprises and less than 10 employed persons.
13.3.1.4. Coverage errors in coefficient variation
Not applicable
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
Data are collected via email and vetting is done by trained and experienced staff. Data inputting software was created to facilitate the use of uploading the received excel questionnaires in the system, without having to input each variable manually, as it was the case in previous years. The software contains validation checks catering for the logic of the questionnaire to ensure that measurement errors are minimal.
13.3.3. Non response error
Certain enterprises might consider the survey as not applicable for them especially if they have few employees on their books. Additionally, such enterprises might consider this survey as time consuming due to its length.
Item non-response is usually associated with sensitive questions, such as turnover and expenditure figures.
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) | 366 | 1318 | 27.77% | 27.77% |
| Core industry (B_C_D_E - excluding construction) | 104 | 360 | 28.89% | 28.89% |
| Core Services (46-H-J-K-71-72-73) | 262 | 958 | 27.35% | 27.35% |
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
Two reminder emails were sent, and another final reminder was sent by post. Following the second reminder by email, a contact was made with the enterprise to notify the enterprise that the questionnaire was still pending and that they will be receiving a final letter should it remain not received.
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 | Not available | Yes |
If turnover is not given in the survey, it is taken from the Statistical Business Register (SBR) during the vetting process. Turnover at t-2 given in the survye is always checked with that of SBR during the vetting process. |
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 | |
| 3.10 Reasons for having no innovation activities | Yes | 0 |
13.3.4. Processing error
Data entry method: questionnaires in excel format are automatically uploaded in an application created by our IT unit
Editing process and method: prior to uploading the questionnaire in the system, validations on the data of each variable are in place to highlight any processing errors immediately
Coding errors: not applicable
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: 17th September 2024
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) : 28th June 2024 (no delays)
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
The same international standards, concepts and definitions according to the Oslo Manual and the Harmonized CIS questionnaire are used in Malta and Gozo NUTS 1 and 2.
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 |
| Age of enterprise | Taken directly from the Business Statistical Register |
| Changes in the filtering compared to HDC | Comment |
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 |
|---|---|
| If enterprise operates through more than branch/premises | Question was used to populate local units due to a lack of national administrative register |
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 | 100.99% | 100.46% | 95.59% |
| Core industry (B_C_D_E - excluding construction) | Total | 98.06% | 97.58% | 102.98% |
| Core Services (46-H-J-K-71-72-73) | Total | 102.09% | 101.89 % | 93.93% |
* 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
See below:
18.1.1. Sampling frame (or census frame)
A census is carried out using the national business register for the population source
18.1.2. Sampling design
A census is carried out
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
|---|---|
| Target population (A) (*) | 3018 |
| Sample (B = C+D) | 3018 |
| In case of combination sample/census: | |
| Sampled units (C) | 0 |
| Enumerated units/census (D) | 3018 |
| Overall sample rate (E = 100*B/A) | 100% |
(*) 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 |
|---|---|---|
| Age of enterprise | Statistical Business Register | 2022 |
18.1.5. Data source and variables used for derivation and weighting
| Item | Response |
|---|---|
| Data source used for deriving population totals | Statistical Business Register |
| Variables used for weighting | Not applicable |
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.
18.3. Data collection
See below
18.3.1. Survey participation
Survey is mandatory
18.3.2. Survey type
A census for all enterprises with 10 emplyed persons or more and according to the activity classification.
18.3.3. Combination of sample survey and census data
Not applicable
18.3.4. Census criteria
Not applicable
18.3.5. Data collection method
Data collection method
| Survey method | Yes/No | Comment |
|---|---|---|
| Face-to-face interview | No | |
| Telephone interview | See comment in 'Other' | |
| Postal questionnaire | Yes | Only to a few enterprises for which we did not have an email address |
| Electronic questionnaire (format Word or PDF to send back by email) | Yes | Electronic questionnaire in Excel format sent automatically by email through an application created by IT. The email also included a covering letter indicating that the questionnaire shall be sent back by email in the same format. |
| Web survey (online survey available on the platform via URL) | No | |
| Other | Enterprises were contacted via telephone after 2 reminder emails were sent and before sending out a final reminder. |
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 | n.a. | n.a. | 0% | 0% | 1% | 1% |
| Core industry (B_C_D_E - excluding construction) | Total | n.a. | n.a. | 0% | 0% | 0.6% | 0.6% |
| Core Services (46-H-J-K-71-72-73) | Total | n.a. | n.a. | 0% | 0% | 0.4% | 0.4% |
Legend: n.a. = not applicable
Note: Turnover data are taken directly from administrative sources and are not requested from respondents.
(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 | Not applicable | |
| Non-respondent adjustments | Not applicable | |
| Other | Not applicable |
18.6. Adjustment
Not applicable
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).
8 October 2024
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.
The enterprise
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: Only one unit is selected as 'representative' and data provided is based on answers given by the 'representative' unit.
- For quantitative variables: Data is collected from the representative unit and added with data from other units within 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 CIS survey covers enterprises located in Malta and Gozo NUTS 1 and 2.
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.
See below:
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.
The same international standards, concepts and definitions according to the Oslo Manual and the Harmonized CIS questionnaire are used in Malta and Gozo NUTS 1 and 2.
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.
