Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Department of education, culture and information society
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Branimirova 19, 10000 Zagreb, Croatia
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
11 March 2026
2.2. Metadata last posted
11 March 2026
2.3. Metadata last update
11 March 2026
3.1. Data description
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
Primjena informacijskih i komunikacijskih tehnologija u poduzećima
All economic activities in the scope of Annex of the Commission Regulation are intended to be included in the general survey, covering enterprises with 10 or more employees and self-employed persons. These activities are:
Section C - “Manufacturing”
Section D, E - “Electricity, gas, steam and air conditioning supply”, “Water supply, sewerage, waste management and remediation activities”
Section F - “Construction”
Section G - “Wholesale and retail trade; repair of motor vehicles and motorcycles”
Section H - “Transportation and storage”
Section I - “Accommodation and food service activities”
Section J - “Information and communication”
Section L - “Real estate activities”
Section M - “Professional, scientific and technical activities”
Section N - "Administrative and support service activities"
Group 95.1 - “Repair of computers and communication equipment”.
For micro-enterprises see the sub-concepts in the full metadata view.
3.3.1. Coverage-sector economic activity for micro-enterprises - All NACE categories are covered
Micro-enterprises are not included in the survey
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?
Not applicable.
3.4. Statistical concepts and definitions
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
3.6.1. Coverage of micro-enterprises
No
3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable.
3.7. Reference area
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
Whole territory of the country is covered. Data for aspecific set of variables will be delivered on NUTS 2 regional level.
3.8. Coverage - Time
Years 2024 and 2025.
3.9. Base period
Not applicable
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data and where specified.
6.1. Institutional Mandate - legal acts and other agreements
Complementary national legislation constituting the legal basis for the survey on the use of ICT in enterprises:
National law on Statistics, 2020
Program of statistical activities of the Republic of Croatia 2021-2027
Data sharing procedure is established with International Telecommunication Union.
7.1. Confidentiality - policy
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.
At national level:
Confidentiality protocol is the one used in SBS survey. If there are less than 3 enterprises within particular aggregate, data is considered confidential.
General notes on the NSI Confidentiality policy can be found at the link below.
Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.
At national level:
If there are less than 3 enterprises within particular aggregate, data is considered confidential.
8.1. Release calendar
There is a release calendar and is publicly available at CBS website.
8.2. Release calendar access
Release calendar can be accessed at CBS website (link included in Annex).
Results for selected variables collected in the framework of this survey are available for all participating countries on Digital economy and society of Eurostat website.
At national level:
Not available.
10.4. Dissemination format - microdata access
Not available.
10.5. Dissemination format - other
Not requested
10.5.1. Metadata - consultations
Not requested
10.6. Documentation on methodology
The European businesses statistics compilers’ manual for ICT usage and e-commerce in enterprises provides guidelines and clarifications for the implementation of the surveys.
At national level:
Not available.
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
Not available.
11.1. Quality assurance
The European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises provides guidelines and standards for the implementation of the surveys. It is updated every year according to the changed contents of the model questionnaires.
At national level:
The Methodological Manual provides guidelines and standards for the implementation of the surveys in the Member States. It is updated every year according to the changed contents of the model questionnaires. The methodological manual is provided to CBS staff before survey conduct. Quality assurance procedures described in manual are strictly followed through training courses and use of best practices. General notes on the NSI Quality policy can be found at the link below.
At European level, the recommended use of the annual Eurostat model questionnaire aims at improving comparability of the results among the countries that conduct the survey on ICT usage and e-commerce in enterprises. Moreover, the European businesses statistics compilers’ manual for ICT usage and e-commerce in enterprises provides guidelines and clarifications for the implementation of the surveys.
At national level:
Quality management is currently work in progress. There are several ongoing projects through which quality management system is being developed. Pilot programme is completed resulting in development of quality indicators database for different statistical domains within NSI. Goal is to link several different sources of data to create unified data source for quality indicators and metadata information.
12.1. Relevance - User Needs
European level : At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DGREGIO, DG JRC) are the principal users of the data on ICT usage and e-commerce in enterprises and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaire at a very early stage. User needs are considered throughout the whole discussion process of the model questionnaire aiming at providing relevant statistical data for monitoring and benchmarking of European policies.
National level : Central agency for Development of Digital Society Ministry of Regional Development and EU funds Researchers
12.2. Relevance - User Satisfaction
At present moment, there are no tools to measure user satisfaction.
12.3. Completeness
Detailed information is available in “ Annex I. Completeness “ - related to questionnaire, coverage, additional questions, regional data.
12.3.1. Data completeness - rate
Not requested
13.1. Accuracy - overall
Comments on reliability and representativeness of results and completeness of dataset
These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
Detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
13.2. Sampling error
For calculation of the standard error see concept 13.2.1.1.
13.2.1. Sampling error - indicators
Standard error (for selected indicators and breakdowns)
Precision measures related to variability due to sampling, unit non-response (the size of the subset of respondents is smaller than the size of the original sample) and other (imputation for item non-response, calibration etc.) are not (yet) required from the Member States for all indicators.
Detailed information is available in“ Annex III. Sample and standard error tables 2025 “ – worksheets starting with “Standard error".
13.2.1.1. Sampling error indicator calculation
Calculation of the standard error
Various methods can be used for the calculation of the standard error for an estimated proportion. The aim is to incorporate into the standard error the sampling variability but also variability due to unit non-response, item non-response (imputation), calibration etc. In case of census / take-all strata, the aim is to calculate the standard errors comprising the variability due to unit non-response and item non-response.
Name and brief description of the applied estimation approach: Taylor linearisation approach was used, incorporated in SAS surveymeans procedure.
Basic formula: See statistical computation section of SURVEYMEANS procedure in SAS user's guide, available at URL provided in annex.
Main reference in the literature: Cochran, W. G. (1977), Sampling Techniques, Third Edition, John Wiley & Sons.
How has the stratification been taken into account? Stratification was taken into account by listing the strata in the SURVEYMEANS procedure (STRATA statement).
Which strata have been considered? Enterprise size and NACE activity groups.
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Over-coverage rate is 1,0%.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No errors were found.
13.3.3. Non response error
See detailed sections below.
13.3.3.1. Unit non-response - rate
See detailed sections below.
13.3.3.1.1. Unit response
The following table contains the number of units (i.e. enterprises), by type of response to the survey and by the percentage of these values in relation to the gross sample size.
Type of response
Enterprises
0-9 (or 2-9) employees and self-employed persons
10 or more employees and self-employed persons
Number
%
Number
%
Gross sample size (as in section 3.1 C)
4500
100%
1. Response (questionnaires returned by the enterprise)
3177
70,6%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
3052
67,8%
1.2 Not used for tabulation
125
2,8%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
44
1,0%
1.2.2 Other reasons (e.g. unusable questionnaire)
81
1,8%
2. Non-response (e.g. non returned mail, returned mail by post office)
1323
29,4%
Comments on unit response, if unit response is below 60%
Not applicable.
13.3.3.1.2. Methods used for minimizing unit non-response
Advance notifications were sent to all enterprises by e-mail and by postal service before the start of the data collection. Reminders were sent by e-mail to enterprises which did not complete the questionnaire. Reminders were sent 4 times. Non-responders were also tried to be contacted by telephone.
13.3.3.1.3. Methods used for unit non-response treatment
1. No treatment for unit non-response
2.1 Treatment by re-weighting: Re-weighting by the sampling design strata considering that non-response is ignorable inside each stratum (the naïve model)
X
2.2 Treatment by re-weighting: Re-weighting by identified response homogeneity groups (created using sample-level information)
2.3 Treatment by re-weighting: Re-weighting through calibration/post-stratification (performed using population information) by the groups used for calibration/post-stratification
X
3. Treatment by imputation (done distinctly for each variable/item)
4. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of unit non-response. (e.g. Re-weighting using Horvitz-Thompson estimator, ratio estimator or regression estimator, auxiliary variables)
Re-weighting was performed in two steps. In the first step the re-weighting inside the stratum was carried out, assuming MAR mechanism (2.1). In the second step re-weighted weights were calibrated according to the following two auxiliary variables from the Business register: turnover and number of employees. Calibration for number of employees was performed on the level of NACE activity group and size class, while the calibration for turnover was performed only on the level of size class. Calmar software was used to implement the calibration procedure.
13.3.3.1.4. Assessment of unit non-response bias
Response rate was higher then 60%.
13.3.3.2. Item non-response - rate
Item non-response rate was 0,3%.
13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response
X
2. Deductive imputation An exact value can be derived as a known function of other characteristics.
3. Deterministic imputation (e.g. mean/median, mean/median by class, ratio-based, regression-based, single donor nearest-neighbour) Deterministic imputation leads to estimators with no random component, that is, if the imputation were to be re-conducted, the outcome would be the same.
4. Random imputation (e.g. hot-deck, cold-deck) Random imputation leads to estimators with a random component, that is, if the imputation were re-conducted, it would have led to a different result.
5. Re-weighting
6. Multiple imputation In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets.
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
Item non-response was very small. In rare cases when enterprises did not respond to some question, missing variables were deducted by known variables, if possible. If deduction was not possible enterprises were contacted to provide the missing data. Cases included in this treatment cover submission of incomplete web questionnaires and in very rare instances paper questionnaires.
13.3.3.2.2. Questions or items with item response rates below 90% and other comments
Other comments relating to the item non-response
A) Additional issues concerning "item non-response" calculation (e.g. method used in national publications):
Not available.
B) Questions and items with low response rates (cut-off value is 90%) and item non-response rate:
No items were found to have response rates below 0,90.
13.3.4. Processing error
No errors were found.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed sections below.
14.1.1. Time lag - first result
Not applicable
14.1.2. Time lag - final result
Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce).
At national level:
Results were released at national level in December 2025, with time lag T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year.
14.2. Punctuality
See detailed section in the full metadata view.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 1st October; 4 days before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
See detailed section in the full metadata view.
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.
No changes in the national survey from the previous year(s).
15.3. Coherence - cross domain
Not applicable
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
Not applicable
15.4. Coherence - internal
Not applicable
Restricted from publication
17.1. Data revision - policy
Although the CBS employees make maximum efforts to reduce errors prior to the data release,some might occur occasionally. It is important to preserve the confidence in the official statistics, aswell as in the CBS as the institution whose highest goal is dissemination of official statistics. For that reason, it is crucial that the CBS acknowledges and documents the error, and that a candid and professional explanation is given. Given that there is a high risk of users retrieving and using the data before errors have been detected and corrected,the errors must be published in the shortest period possible, and users must be enabled to see clearly what has been corrected.
Having all of this in mind, corrections of material errors in the CBS statistics shall always be indicated with a note pointing out the amendmentsand that the incorrect data released must not in any case be replaced with the revised version without providing prior access to both versions. This note must never be removed. If errors occur in larger publications (this includes all except First Releases), the CBS is obliged to issue a list of all required corrections (corrigenda) which clearly indicates which publication has an error and where exactly the amends have been made: on which pages of the original publication and in which tables. The corrigenda are published in an electronic format together with the publication. If they are available on the CBS website, they will be accompanied by a notice stressing it being a case of a revised version, and the release date of the corrections. Printed corrigenda are inserted into the printed publications available for sale, and to all copies of publications available for use in the CBS library.
17.2. Data revision - practice
Procedures for handling errors of the released data are adapted to the gravity of error. Excluding proofing/printing errors, the basic procedure following detection of an error is as follows:
1. a correction of a detected error, and reissuing the data/publications or corrigenda only in case of a larger publication on the CBS website in shortest period of time possible
2. a notice stating the case of anamendment next to the link with the revised data or a notice stating availability of the corrigenda in cases of larger publications together with the release data of amended data
3. an e-mail to the subscribers of the data/publications in which an error has been detected containing electronic version or the revised data or corrigenda in cases of larger publications, together with an apology letter and explanation as to why the error/errors occurred
4. sending printed version of the revised data to the subscribers, regardless of whether it was the case of data processing, purchase of publications, or just the corrigenda, if it is a larger publication together with an apology letter and explanation of the error
In the case of a serious error that requires a period longer than one working day to correct, the incorrect data/publication shall be removed from the CBS website, and a message stating when the corrected version or corrigenda will be posted on the homepage. With the release of the amended version of the data/publication or corrigenda, the first released version is released simultaneously, in which the amendment is displayed clearly. In otherwords, released data containing an error shall never be replaced by the correct version, without being clearly displayed.
If an error is detected and corrected on the day of the release, the correction notice must state precise release time of the correction. Corrections of proofing/printing errors shall be made without issuing a correction notice. The errors that are discovered in released publications must be conveyed to the relevant statistics department without any delay, to correct the error in the shortest period possible. Apart from the statistics department in charge of the statistics, the Information Servicesand Publications Directorate must be involved aswell in all stages of preparation and issuing of the amendment or corrigenda. The employees of the specialist department in charge of the statistical area in which the error was detected, must, first of all, focus on correcting the detected error, while the ISPD employees are in charge of giving a notice to internal and external users and informing the Director General of the CBS.
17.2.1. Data revision - average size
Not requested
18.1. Source data
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
Stratified random sampling was used for small enterprises (with 10-49 employees), NACE Rev. 2 economic activity was used as stratification variable (25 strata in total). In each particular stratum we used random sample selection of units. If allocated number of units is lower than 8, 8 units are allocated to the sample. Census approach was used for medium and large enterprises (50 and more employees). None of the procedures for the coordination or non-overlapping with samples of other surveys were applied. Sample rate by number of enterprises is 37%, sample rate by turnover value is 86%, while sample rate by number of persons employed is 84%.
C) Gross sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: NET SAMPLE)
18.1.1. Source data - frame population
Description of frame population
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
10 February 2025
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
31 December 2023
c) Indication if the frame population is the same as, or is in some way coordinated with, the one used for the Structural Business Statistics (different snapshots):
Frame population is included in SBS data since it is drawn from the same source, Statistical business register.
d) Description if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up):
Sampling frame is different than the one used for grossing up, since the updated frame for grossing up is completed after the data collection and the updated data from Business register. Recalibration is performed to reflect discrepancies between two frames, sampling frame is adjusted for non-response.
e) Indication the shortcomings in terms of timeliness (e.g. time lag between last update of the sampling frame and the moment of the actual sampling), geographical coverage, coverage of different subpopulations, data available etc., and any measures taken to correct it, for this survey.
There is a time lag of 12-15 months between last update of sampling frame and the moment when sampling takes place.
Frame population distribution: More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: FRAME POPULATION)
18.2. Frequency of data collection
Annual
18.3. Data collection
See detailed sections below.
18.3.1. Survey period
Survey / Collection
Date of sending out questionnaires
Date of reception of the last questionnaire treated
General survey
14 April 2025
30 June 2025
Micro-enterprises
Not applicable.
Not applicable.
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
Not applicable
18.3.4. Survey type
Web survey - introduction letters were send by e-mail to enterprises (enterprise managers) with available email contact, all participants were contacted by mail with guidelines for completion of web survey. In extreme situations (e.g. no internet connection available) respondents were allowed to complete the survey on printed questionnaire or via CATI interview.
18.3.5. Survey participation
Mandatory
18.4. Data validation
Before sending data was verified on the Acceptance platform of eDAMIS.
18.5. Data compilation
Grossing-up procedures
Grossing-up weights are calculated by performing the three-step approach, usually used in business surveys:
Calculation of the design weight as the reverse value of the inclusion probabilities
Adjustment for the non-response. The non-response adjustment factors were calculated by assuming missing at random mechanism, meaning that the factors were uniform inside the strata
Weights calibration. Weights were calibrated according to the following two auxiliary variables from the Business register: turnover and number of employees. Calibration for number of employeeswas performed on the level of NACE activity group and size class, while the calibration for turnover was performed only on the level of size class.
Calmar software was used to implement thecalibration procedure.
18.5.1. Imputation - rate
Imputation was not used.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt: No additional comments.
19.1. Documents
Questionnaire in national language
X
Questionnaire in English (if available)
National reports on methodology (if available)
Analysis of key results, backed up by tables and graphs in English (if available)
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
Primjena informacijskih i komunikacijskih tehnologija u poduzećima
ICT usage and E-commerce in enterprises
11 March 2026
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
Whole territory of the country is covered. Data for aspecific set of variables will be delivered on NUTS 2 regional level.
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data and where specified.
Comments on reliability and representativeness of results and completeness of dataset
These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
Detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Grossing-up procedures
Grossing-up weights are calculated by performing the three-step approach, usually used in business surveys:
Calculation of the design weight as the reverse value of the inclusion probabilities
Adjustment for the non-response. The non-response adjustment factors were calculated by assuming missing at random mechanism, meaning that the factors were uniform inside the strata
Weights calibration. Weights were calibrated according to the following two auxiliary variables from the Business register: turnover and number of employees. Calibration for number of employeeswas performed on the level of NACE activity group and size class, while the calibration for turnover was performed only on the level of size class.
Calmar software was used to implement thecalibration procedure.
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
Stratified random sampling was used for small enterprises (with 10-49 employees), NACE Rev. 2 economic activity was used as stratification variable (25 strata in total). In each particular stratum we used random sample selection of units. If allocated number of units is lower than 8, 8 units are allocated to the sample. Census approach was used for medium and large enterprises (50 and more employees). None of the procedures for the coordination or non-overlapping with samples of other surveys were applied. Sample rate by number of enterprises is 37%, sample rate by turnover value is 86%, while sample rate by number of persons employed is 84%.
C) Gross sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: NET SAMPLE)
Annual
See detailed sections below.
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
