1.1. Contact organisation
Statistical Service of Cyprus (CYSTAT)
1.2. Contact organisation unit
Science and Technology Statistics Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Statistical Service of Cyprus
CY-1444 Nicosia
Cyprus
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 October 2024
2.2. Metadata last posted
30 October 2024
2.3. Metadata last update
30 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
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 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
The entire core target population was covered. No non-core activities were added
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 national particularities.
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
It is the business enterprise.
Sampling was carried out at the level of the Statistical Unit Enterprise. The observation unit was the Statistical Unit Enterprise. For complex enterprises, the reporting unit was determined by contacting the decision making legal unit.
For quantitative variables, Structural Business Statistics (SBS) data were used. The SBS uses consolidated accounts to consolidate the accounts of the legal units in complex enterprises.
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
All statistical surveys in Cyprus cover all economic activities in the Government controlled area only.
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 | No | |
| CIS light | 2002-2003* | Yes | Reference period 2000-2002 |
| CIS4 | 2002-2004 | Yes | |
| CIS2006 | 2004-2006 | Yes | |
| CIS2008 | 2006-2008 | Yes | |
| CIS2010 | 2008-2010 | Yes | |
| CIS2012 | 2010-2012 | Yes | |
| CIS2014 | 2012-2014 | Yes | |
| CIS2016 | 2014-2016 | Yes | |
| CIS2018 | 2016-2018 | Yes | |
| CIS2020 | 2018-2020 | Yes | |
| CIS2022 | 2020-2022 | Yes |
*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
Article 3 of the national Official Statistics Law, No. 25(I) of 2021 defines the functions of the Statistical Service of Cyprus regarding the production and dissemination of official statistics. Moreover, Article 13, explicitly stipulates the mandate for data collection and introduces a mandatory response to statistical enquiries by stipulating the obligation of respondents to reply to surveys and provide the data required. This relates not only to national but also to European statistics which, by virtue of Article 8 of the said Law, are incorporated in the annual and multiannual programmes of work without any further procedure.
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
The survey was carried out in accordance with the Statistics Law, No. 25(I) of 2021. The Statistical Service is obliged, under the provisions of the Statistics Law, to treat all the information collected as confidential. All the information collected is used solely for statistical purposes. No data for any individual enterprise is published or disclosed to either public bodies or private individuals. Data which have been gathered from sources which are accessible to the public are not considered as confidential. All data collected remain confidential, even after the publication of results.
All members of staff have legal confidentiality commitments. They are required to take an oath, in accordance with the provisions of the Statistics Law, No. 25(I) of 2021, that they will not disclose information which they have received during the conduct of the survey. This obligation continues to exist after the termination of their professional relationship with the Statistical Service.
CIS data are transmitted to Eurostat via EDAMIS using Eurostat's consignment. This safe, secure procedure guarantees a method of tracking transmission. All necessary steps are taken to ensure that the EDAMIS system is working at national level.
Official statistics are released in accordance to all confidentiality provisions of the following:
- National Official Statistics Law No. 25(I) of 2021 (especially Article 16 on statistical confidentiality).
- Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality).
- European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
- CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.
Links to all of the above documents:
- Statistics Law No. 25(I) of 2021: https://www.cystat.gov.cy/en/StaticPage?id=1074
- Regulation (EC) No 223/2009 on European statistics (consolidated text): http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:02009R0223-20150608&qid=1504858409240&from=EN
- European Statistics Code of Practice: http://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-32-11-955
- Code of Practice for the Collection, Publication and Storage of Statistical Data: https://www.cystat.gov.cy/en/StaticPage?id=1066
7.2. Confidentiality - data treatment
Under the provisions of the Statistics Law, No. 25(I) of 2021, the statistics published should not allow for the direct or indirect identification of the sampling units. Cells with less than 3 enterprises are flagged as confidential. No dominance rule is applied for primary or secondary confidentiality. Data from sources accessible to the public are not considered as confidential.
The treatment of confidential data is regulated by CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.
Links to all of the above documents:
- Statistics Law No. 25(I) of 2021: https://www.cystat.gov.cy/en/StaticPage?id=1074
- Code of Practice for the Collection, Publication and Storage of Statistical Data: https://www.cystat.gov.cy/en/StaticPage?id=1066
8.1. Release calendar
Not applicable. No specific release policy or release calendar for the data set in question (CIS) exists.
8.2. Release calendar access
Not applicable. No specific release calendar for the data set in question (CIS) exists.
8.3. Release policy - user access
According to the Dissemination and Pricing Policy of the Statistical Service of Cyprus (section 2.3) CYSTAT΄s main channel for dissemination of statistics is the website, which offers the same conditions to everyone and is updated at the same time every working day (12:00 noon). Privileged pre-released access (of no more than 1 day in advance) has been granted to a few selected users for specific statistics. These are specified in the Dissemination Policy (section 2.3).
In addition to the annual release calendar, users are informed of the various statistical releases through the “Alert” service provided by CYSTAT.
Link to the Dissemination and Pricing Policy:
- Dissemination and Pricing Policy of the Statistical Service of Cyprus: https://library.cystat.gov.cy/NEW/Revision%5FPolicy%2DEN%2D090117.pdf
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.
10.1.1. Availability of the releases
| Dissemination and access | Availability | Comments, links, ... |
|---|---|---|
| Press release | Yes | |
| 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): No
- Analytical publication (referring to all/most results): General paper and online publications with key data included in the statistical yearbook entitled “Statistical Abstract” and in other multi-domain publications such as the pocketbook “Cyprus in Figures”
- Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect): No
10.3. Dissemination format - online database
No online database exists.
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below 10.4.1.
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 | Yes |
Statistical micro-data from CYSTAT’s surveys are accessible for research purposes only and under strict provisions as described below:
Under the provisions of the Statistics Law, CYSTAT may release microdata for the sole use of scientific research. Applicants have to submit the request form "APPLICATION FOR DATA FOR RESEARCH PURPOSES" giving thorough information on the project for which micro-data are needed.
The application is evaluated by CYSTAT’s Confidentiality Committee and if the application is approved, a charge is fixed according to the volume and time consumed for preparation of the data. Micro-data may then be released after an anonymisation process which ensures no direct identification of the statistical units but, at the same time, ensures usability of the data. The link for the application is attached below.
- Link to the application for access to microdata on CYSTAT's website: https://www.cystat.gov.cy/en/DataRequestContactForm?fid=7
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
Each data file loaded on the web site is accompanied by a press release and a comprehensive methodological note, giving information on the innovation survey and its scope, the concepts and definitions used, as well as assistance on how to interpret the tables published.
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
Users can download free of charge from the web site of the Statistical Service of Cyprus the key results (as MS Excel files) of the various rounds of innovation surveys carried out in Cyprus. Each data file is accompanied by a press release and a comprehensive methodological note, giving information on the surveys and their scope, concepts and definitions, as well as assistance on how to interpret the tables published. For any further information, users can address a request to the Statistical Service (by phone, mail, e-mail or via the enquiries facility on the web site). Users seem to be fully satisfied.
11.1. Quality assurance
The quality of statistics in CYSTAT is managed in the framework of the European Statistics Code of Practice which sets the standards for developing, producing and disseminating European Statistics as well as the ESS Quality Assurance Framework (QAF). CYSTAT endorses the Quality Declaration of the European Statistical System. In addition, CYSTAT is guided by the requirements provided for in Article 11 of the Statistics Law No. 25(I) of 2021 as well as Article 12 of Regulation (EC) No 223/2009 on European statistics, which sets out the quality criteria to be applied in the development, production and dissemination of European statistics.
Links to all of the above documents:
- European Statistics Code of Practice: http://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-32-11-955
- ESS Quality Assurance Framework (QAF): http://ec.europa.eu/eurostat/documents/64157/4392716/ESS-QAF-V1-2final.pdf/bbf5970c-1adf-46c8-afc3-58ce177a0646
- Quality Declaration of the European Statistical System: http://ec.europa.eu/eurostat/documents/4031688/8188985/KS0217428ENN_corr.pdf/116f7c85-cd3e-4bff-b695-4a8e71385fd4
- Statistics Law No. 25(I) of 2021: https://www.cystat.gov.cy/en/StaticPage?id=1074
- Regulation (EC) No 223/2009 on European statistics (consolidated text): http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:02009R0223-20150608&qid=1504858409240&from=EN
11.2. Quality management - assessment
The CIS 2022 carried out in Cyprus is assessed to have reached high levels of quality. To this effect, the mandatory nature of the survey (in accordance with the provisions of the national Statistics Law, No 25(I) of 2021) and the practice of carrying out face to face interviews at the enterprises premises played a vital and decisive role.
In addition of carrying out face to face interviews at the enterprises premises, all other auxiliary methods and tools for face to face interviews such as Skype and Viber were used.
The CIS2022 survey has been the fifth CIS (the first was CIS2014) to implement the Computer Assisted Personal Interviewing (CAPI) method. A specially developed BLAISE programme (enumerators version) was used for this survey for data entry and most consistency tests. Controls and consistency checks were included in the BLAISE programme in order to identify possible errors. Also, help screens and warning messages for data entry errors, internal inconsistencies or quality errors are provided by the programme, minimizing the possibility of having any such errors.
All enumerators employed attended a comprehensive training session, during which the questionnaire, the BLAISE program and the concepts involved were thoroughly explained, examples on what qualified as innovation were given and problems expected to be encountered in the field were identified. Consequently, they were skilled enough to properly guide the respondents through the questionnaire, to clarify concepts and definitions and to make sure that the possibility of having internal inconsistencies or quality errors in the questionnaires is kept to a minimum.
The use of skilled enumerators is the usual practice with all business surveys in Cyprus, resulting in extremely high unit response rates and negligible item nonresponse, thus rendering the conduct of a non-response analysis as unnecessary.
The electronically completed questionnaires were checked again in the office with the specially developed for this survey BLAISE programme (supervisors version). This included additional quality checking and correcting for any remaining logical inconsistencies, comparing with the responses provided by the same unit in the previous CIS 2020, consulting the respective structural business and R&D questionnaires, etc. Data analysis and processing was done using MS Excel spreadsheets. Additional controls and validation checks were included in order to identify any remaining errors. Also the SPSS statistical package programme and specified programming in R (which is a computer programming language) were used for the first time for further analysis and to identify any other remaining errors.
The Eurostat methodological guidelines and recommendations and the provisions of 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 were respected.
12.1. Relevance - User Needs
Up to now there is no involvement of users at national level in the final national questionnaire design. The questionnaire used at national level corresponds fully to the core questionnaire agreed at European level. For the time being, no unmet users’ needs at national level have come to our attention and thus no specific actions are planned to satisfy such needs.
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 |
|---|---|---|
| See in below table | See in below table | See in below table |
| See in below table | See in below table | See in below table |
| See in below table | See in below table | See in below table |
| See in below table | See in below table | See in below table |
| 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) | Innovation Union Scoreboard |
| 1. Institutions - National level | Ministry of Finance, Ministry of Energy, Commerce and Industry, Deputy Ministry Of Research, Innovation And Digital Strategy, Directorate General for European Programmes, Coordination and Development, Research and Innovation Foundation | Strategic programming, economic analysis and monitoring of national research policies and of the national Lisbon (Europe 2020) strategy programme |
| 2. Social actors | Cyprus Chamber of Commerce and Industry, various employers’ associations, trade unions and lobby groups | Economic analysis and monitoring, interested both in figures and comments |
| 3. Media | Economic and financial newspapers and web pages, TV channels | Interested in figures, comments and analyses |
| 4. Researchers and students | Higher education institutions, researchers, students, private individuals | Interested in figures, comments and analyses and access to micro data for research purposes |
| 5. Enterprises or businesses | Business enterprises, consultancy offices | Market analysis, marketing strategy, offering consultancy services |
12.2. Relevance - User Satisfaction
In the latest national user satisfaction survey, innovation statistics were listed down explicitly as one of the main statistical fields to be commented on. However, the number of questionnaires with relevant comments was extremely limited and does not allow for adequate conclusions to be made. No specific problems were reported.
Since 2008 (with the exception of 2010, 2013 and 2020) CYSTAT carries out an annual online “Users Satisfaction Survey”. The results of the surveys are available on CYSTAT’s website at the link attached below.
Overall, there is a high level of satisfaction of the users of statistical data published by CYSTAT.
- Results of CYSTAT’s User Satisfaction Surveys: https://www.cystat.gov.cy/en/StaticPage?id=1144
12.3. Completeness
The national standard CIS 2022 output tabulation is complete; there exist no missing cells, either compulsory or voluntary (for voluntary questions covered in national questionnaire).
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 |
1.321 | 1.226 | 1.371 |
| Core industry (B_C_D_E - excluding construction) | Total |
1.289 | 1.446 | 1.538 |
| Core Services (46-H-J-K-71-72-73) | Total |
1.335 | 1.102 | 1.268 |
(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
The variance was calculated using the formula given in section 13.2.1. Sample design and weighting were taken into account.
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
No coverage or frame errors exist.
13.3.1.4. Coverage errors in coefficient variation
Not applicable. No coverage or frame errors exist.
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
No measurement errors have been identified.
The CIS2022 survey has been the fifth CIS (the first was CIS2014) to implement the Computer Assisted Personal Interviewing (CAPI) method. A specially developed BLAISE programme (enumerator’s version) was used for this survey for data entry and most consistency tests. Controls and consistency checks were included in the BLAISE programme in order to identify possible errors. Also, help screens and warning messages for data entry errors, internal inconsistencies or quality errors are provided by the programme, minimizing the possibility of having any such errors.
All enumerators employed attended a comprehensive training session, during which the questionnaire, the BLAISE program and the concepts involved were thoroughly explained, examples on what qualified as innovation were given and problems expected to be encountered in the field were identified. Consequently, they were skilled enough to properly guide the respondents through the questionnaire, to clarify concepts and definitions and to make sure that the possibility of having internal inconsistencies or quality errors in the questionnaires is kept to a minimum.
The use of skilled enumerators is the usual practice with all business surveys in Cyprus.
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)
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) | 0 | 1673 | 0% | 0% |
| Core industry (B_C_D_E - excluding construction) | 0 | 568 | 0% | 0% |
| Core Services (46-H-J-K-71-72-73) | 0 | 1105 | 0% | 0% |
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
Not applicable. There exists no unit non-response.
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 | 0% | No |
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
Between data collection and the beginning of statistical analysis on the base of the statistics produced, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies in the data which usually represent errors.
13.3.4.1. Data entry method
Data collection was carried out by face to face interviewing at the enterprises’ premises, using the Computer Assisted Personal Interviewing (CAPI) method. In addition of carrying out face to face interviews at the enterprises premises, all other auxiliary methods and tools for face to face interviews such as Skype and Viber were used. For data entry and editing, the BLAISE program was used. Data were exported in MS Excel for further checks, analyses and first tabulations. The first data analysis and processing was done using MS Excel spreadsheets. Additional controls and validation checks were included in order to identify any remaining errors. Also the SPSS statistical package programme and specified programming in R (which is a computer programming language) were used for the first time for further analysis and to identify any other remaining errors. The tabulations were done using specified programming in R.
13.3.4.2. Editing process and method
During the face to face interview, respondents were instructed on what qualifies as innovation and were guided in completing the questionnaire in the best possible way thus ensuring that item non response was kept to a minimum. Using the Computer Assisted Personal Interviewing (CAPI) method all electronically completed questionnaires were thoroughly checked by controls and validation checks and corrected for any logical inconsistencies by the BLAISE data entry and editing programme. If required, respondents were contacted again over the phone. For the basic economic information (turnover and employment), auxiliary sources (such as the structural business and R&D surveys) were used.
For data analysis and processing, data from BLAISE were exported to MS Excel spreadsheets. Additional controls and validation checks were included in order to eliminate any remaining errors. The first data analysis and processing was done using MS Excel spreadsheets. Additional controls and validation checks were included in order to identify any remaining errors. Also the SPSS statistical package programme and specified programming in R (which is a computer programming language) were used for the first time for further analysis and to identify any other remaining errors. The tabulations were done using specified programming in R.
13.3.4.3. Coding errors
No coding errors have been identified.
13.3.4.4. Effect of processing errors in the coefficient of variation
The CVs reported in section 13.2.1 incorporate the effects of any processing errors.
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: December 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) : 1 day
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
This part focuses on reporting the deviations from the harmonised CIS questionnaire (see below).
Cypus followed the same international standards, concepts and definitions (Oslo manual and Eurostat guidelines) at the whole territory and there is not discrepancy at national level and in comparison to remaining EU countries.
Cyprus is one area in all NUTS levels.
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 |
|---|---|
| See in below text | See in below text |
| See in below text | See in below text |
Methodological deviations from the CIS Harmonised Data Collection (HDC) and Questions not included in national questionnaire compared to HDC
The EU-harmonised core version of the questionnaire was used in full, with no deviations. All compulsory questions were included.
Non-mandatory HDC question(s) (voluntary questions) that Cyprus drop in the CIS 2022 national questionnaire are:
From Section 2 : Strategies and Knowledge Flows, the following questions and parameters:
Questions 2.1 (COND)
From Section 3: Innovation, the following questions and parameters:
Question 3.8 (the last 3 non-mandatory parameters EXP_INNO_INN_XRND_OWN_PER and EXP_INNO_INN_XRND_SMSP and EXP_INNO_INN_XRND_CGO)
From Section 5: Specific factors and actions (All questions)
Questions 5.1 to 5.4
From Section 7: Basic information on your enterprise, the following questions and parameters:
Question 7.2 [EMPUD]
Question 7.4 [TUR]
All questions from 7.6 to 7.9
| Changes in the filtering compared to HDC | Comment |
|---|---|
| Not applicable. | The EU-harmonised core version of the questionnaire was used in full, with no deviations. |
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 |
|---|---|
| Yes | Extra questions concerning the COVID19 and how much it affected the enterprices, to serve national needs were added to the EU-harmonised core version of 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 | 100.2 | 99.7 | 106.7 |
| Core industry (B_C_D_E - excluding construction) | Total | 100.3 | 99.5 | 101.5 |
| Core Services (46-H-J-K-71-72-73) | Total | 99.0 | 99.7 | 113.6 |
* Numbers are to be provided for the last year of the reference period (t)
Comment
- NACE divisions 64-66 were excluded from the calculations of relative difference between SBS and CIS 2022 data, since they are not fully covered in the national SBS survey.
- Part of the differences may be explained by the different definition of the “enterprise” between SBS and CIS.
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)
The official, up-to-date, statistical business register was used.
18.1.2. Sampling design
The Eurostat guidelines and recommendations regarding sample design were followed. A census of enterprises with 20 or more employees was taken for all NACE activities while for the size class 10-19 a sample was drawn. The sample was drawn on the basis of the economic activity (at the NACE Rev. 2 three-digit level) and the enterprise size (according to the number of employees). The selection of the sample within each stratum was done by simple random sampling without replacement, with known selection probabilities.
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
| Target population (A) (*) | 2257 |
| Sample (B = C+D) | 1673 |
| In case of combination sample/census: | |
| Sampled units (C) | 664 |
| Enumerated units/census (D) | 1009 |
| Overall sample rate (E = 100*B/A) | 74.12% (1673/2257) |
(*) 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 Employment 2022 | Short Business Statistics (SBS) survey | 2022 |
| Total Turnover 2022 | Short Business Statistics (SBS) survey | 2022 |
| Variables/Indicators | Source | Reference year |
|---|---|---|
| Age of the enterprice (Year of the enterprice established) |
The national 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 | The national statistical business register was used. |
| Variables used for weighting | The number of employees and economic activity (at the NACE Rev. 2 three-digit level). |
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
The survey was mandatory, in accordance with the provisions of the national Statistics Law, No. 25(I) of 2021.
18.3.2. Survey type
A combination of a census and a sample survey was used.
18.3.3. Combination of sample survey and census data
For all NACE Rev. 2 activities, complete enumeration (census) of enterprises with 20 or more employees was taken. Enterprises in the size class 10-19 employees were selected by sampling.
18.3.4. Census criteria
The only criterion used to distinguish whether a census or a sample would be conducted was size class: a census was conducted in enterprises with 20 or more employees for all NACE activities.
18.3.5. Data collection method
Data collection method
| Survey method | Yes/No | Comment |
|---|---|---|
| Face-to-face interview | Yes | For the vast majority of cases (about 85% of cases) |
| Telephone interview | Yes | Less than 5% of cases |
| Postal questionnaire | Yes | Less than 5% of cases |
| Electronic questionnaire (format Word or PDF to send back by email) | Yes | About 35% of cases. Any mistakes in questionnaires were corrected using other methods of communication (such as telephone, Skype, Viber). Less than 10% as a pure method of collection. |
| Web survey (online survey available on the platform via URL) | No | |
| Other | Yes | In addition of carrying out face to face interviews at the enterprises premises, all other auxiliary methods and tools for face to face interviews such as Skype and Viber were used. See comment below the table |
Comment: Data collection was carried out by face-to-face interviewing at the enterprises’ premises; this is the usual practice with all business surveys in Cyprus. In addition of carrying out face to face interviews at the enterprises premises, all other auxiliary methods and tools for face to face interviews such as Skype and Viber were used. The interview was computer assisted. Persons interviewed normally comprised high level executives of the enterprise, such as the director-general, production and/or quality manager, R&D manager, finance director, etc.
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 | 0% | 0% | 0% | 0% | 0% | 0% |
| Core industry (B_C_D_E - excluding construction) | Total | 0% | 0% | 0% | 0% | 0% | 0% |
| Core Services (46-H-J-K-71-72-73) | Total | 0% | 0% | 0% | 0% | 0% | 0% |
(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 Eurostat guidelines and recommendations regarding the calculation of weights were followed. The inverse of the sampling fraction (using the number of employees) was used to adjust for different probabilities of selection in the sampling process. Only one set of weights was used. |
| Non-respondent adjustments | ||
| Other |
18.6. Adjustment
No non-response analysis was deemed necessary, as the survey had resulted in extremely high response rates. There was no need for adjustment/calibration of the weights.
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).
30 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.
It is the business enterprise.
Sampling was carried out at the level of the Statistical Unit Enterprise. The observation unit was the Statistical Unit Enterprise. For complex enterprises, the reporting unit was determined by contacting the decision making legal unit.
For quantitative variables, Structural Business Statistics (SBS) data were used. The SBS uses consolidated accounts to consolidate the accounts of the legal units in complex enterprises.
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).
All statistical surveys in Cyprus cover all economic activities in the Government controlled area only.
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.
This part focuses on reporting the deviations from the harmonised CIS questionnaire (see below).
Cypus followed the same international standards, concepts and definitions (Oslo manual and Eurostat guidelines) at the whole territory and there is not discrepancy at national level and in comparison to remaining EU countries.
Cyprus is one area in all NUTS levels.
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.
