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.
Knowledge Economy and Special Surveys Statistics Devision
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
29 Gedimino ave., LT - 01500 Vilnius, Lithuania
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
28 October 2025
2.2. Metadata last posted
28 October 2025
2.3. Metadata last update
28 October 2025
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
Annual survey 'Informacinių technologijų naudojimas įmonėse / ICT usage in enterprises'
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.
The statistical unit - enterprise with 10 and more persons employed.
3.6. Statistical population
Target Population
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“.
Enterprises located in the territory of whole country.
Data for a specific 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:
Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics, repealing 10 legal acts in the field of business statistics and Commission and yearly Implementing Regulations laying down the technical specifications of data requirements for the topic ‘ICT usage and ecommerce’ for the reference years.
6.2. Institutional Mandate - data sharing
The exchange of statistical data required for the implementation of the Official Statistics Program is defined in Article 17 of Law on Official Statistics and State Data Governance of the Republic of Lithuania.
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:
In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of Statistics Lithuania.
By national policy on confidentiality the minimum number of enterprises in breakdowns must be 3 enterprises.
7.2. Confidentiality - data treatment
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.
The State Data Governance Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the State Data Governance Information System, approved by Order No DĮ-202 of 27 August 2021 of the Director General of Statistics Lithuania.
8.1. Release calendar
Statistical information is published on the Official Statistics Portal according to the Official Statistics Calendar.
Statistical information is prepared and disseminated under the principle of impartiality and objectivity, i.e. in a systematic, reliable and unbiased manner, following professional and ethical standards (the European Statistics Code of Practice), and the policies and practices followed are transparent to users and survey respondents. All users have equal access to statistical information. All statistical information is published at the same time – at 9 a.m. on the day of publication of statistical information as indicated in the calendar on the Official Statistics Portal. Statistical information is published following the Official Statistics Dissemination Policy Guidelines and Statistical Information Dissemination and Communication Rules of Statistics Lithuania approved by Order No DĮ-176 of 2 July 2021 of the Director General of Statistics Lithuania.
Annual
10.1. Dissemination format - News release
Short sentences about the ICT indicators on the publication day in the Database News.
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:
Statistical indicators are published in the Database of Indicators (Science and technology -> Information and communication technologies -> Use of information and communication technologies in enterprises).
10.4. Dissemination format - microdata access
Not applicable.
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.
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.
In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. The main trends in activity of Statistics Lithuania aimed at quality management and continuous development in the institution are established in the Quality Policy. Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify areas which need improvement and to promptly eliminate shortcomings. More information on assurance of quality of statistical information and its preparation is published in the Quality Management section on the Statistics Lithuania website.
11.2. Quality management - assessment
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:
After survey implementation, the quality of obtained information is assessed. Outliers are identified and analysed. In case of significant discrepancies, data providers are contacted and reasons are determined. If inaccuracies are detected, data are corrected. The results are compared with the results of the previous year. Model errors and relative absolute error of estimate are estimated.
12.1. Relevance - User Needs
The main users of statistical information are State authorities and agencies, international organisations, the media, research and business communities, students, whose needs are satisfied without a breach of the confidentiality principle.
Major share of the statistical information produced is used to set EU and national digital targets for 2030 and to measure their achievement through the Digital Economy and Society Index (DESI), which measures EU countries' progress and the European Digital Agenda.
12.2. Relevance - User Satisfaction
Since 2005, in Lithuania user opinion surveys have been conducted on a regular basis. Official Statistics Portal traffic is monitored, website visitor opinion polls, general opinion poll on the products and services of Statistics Lithuania, target user group opinion polls and other surveys are conducted. In 2007, the compilation of a user satisfaction index was launched. The said surveys are aimed at the assessment of the overall demand for and necessity of statistical information in general and specific statistical indicators in particular.
More information on user opinion surveys and results thereof are published in the User Surveys section on the Statistics Lithuania website.
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: The sampling error in the survey is calculated using the Horvitz and Thomson formula.
Basic formula: The estimate of variance in separate stratum is (1-n/N) p(1-p)/n-1 , where N is stratum size, n is the number of the sample units and p is the estimate proportion.
Main reference in the literature: Särndal, C.E.. Swemsson, B. ,Wretman, J. 1992 Model Assisted Survey Sampling New York,Springer-Verlag
How has the stratification been taken into account? In inverse ratio to sampling rate in the separate stratum.
Which strata have been considered? Enterprises are stratified by NACE group and size class.
13.3. Non-sampling error
See detailed sections below.
13.3.1. Coverage error
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Over-coverage was 0.70 %.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No measurement errors detected.
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)
100%
3003
100%
1. Response (questionnaires returned by the enterprise)
3001
99.93
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
2980
99.23
1.2 Not used for tabulation
21
0.70
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
21
0.70
1.2.2 Other reasons (e.g. unusable questionnaire)
2. Non-response (e.g. non returned mail, returned mail by post office)
2
0.07
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
The survey is mandatory, and respondents are required to report digitally – on survey questionnaire online. Only fully completed questionnaire are accepted. 3 automatic reminders (3 days to deadline, deadline day and 1 day after) were sent via the e-system. After deadline specialists of the Data preparation division calls, sent manually e-reminders to enterprises before enterprises were coded as non-responding.
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
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)
Due to refusals or other reasons, some enterprises do not submit statistical reports. In this case, the weights of the responding enterprises are recalculated. Estimates are calculated using Horvitz - Tompson estimator for stratified sampling.
13.3.3.1.4. Assessment of unit non-response bias
Not available.
13.3.3.2. Item non-response - rate
The survey are mandatory and only fully completed questionnaire are accepted.
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.
Not applicable
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
Additional issues concerning "item non-response" calculation (e.g. method used in national publications): Not applicable
Questions and items with low response rates (cut-off value is 90%) and item non-response rate: Not applicable
13.3.4. Processing error
No processing errors were detected.
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 on 16 October 2025, with time lag T+0 months for indicators referring to the current year, T+10 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 01 October 2025; 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.
Since 2004 for some variables.
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
Cost: Not available.
Burden: Average time needed to fill out questionnaire - 63 min.
The published data may be revised if errors are discovered.
17.2.1. Data revision - average size
Not requested
18.1. Source data
Frame population description and distribution: For more information see concept 18.1.1.
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:
The sample is stratified random sample made by use of register-based data and previous year sample data. The number of persons employed and economy activity were used to stratify the population. The were 32 NACE Rev. 2 groups and 3 enterprise size groups (10-49,50-249,250+). All enterprises from small groups (less than 20 units) by NACE Rev. 2 activities and number of persons employed groups were included into the sample. Within every NACE Rev. 2 groups the strata of enterprises were formed by number of persons employed groups. Then the Neyman optimal allocation (with variable number of persons employed) was used for determination of the sample size for each stratum specified. In each stratum sample random sampling was used. The sample was designed with no reference to other surveys.
Gross sample distribution: Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
Net sample distribution: Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: NET SAMPLE)
18.1.1. Source data - frame population
A) Description of frame population
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
November 2024
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
October 2024
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):
The frame populiation is the same with SBS and other business statistics surveys
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):
Enterprises, which do not match the survey criteria, are removed from the frame used for grossing up
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.
Time lag between the last update of the sampling frame and the moment of actual sampling - 1 month.
B) Frame population distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (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
3 March 2025
15 May 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
Online web questionnaire.
18.3.5. Survey participation
Mandatory
18.4. Data validation
Server based EDIT validation.
18.5. Data compilation
Grossing-up procedures
Strata are defined by crossing the following size classes of persons employed and NACE groupings. To conduct grossing up procedures, the initial sampling weight within each stratum is adjusted using the response rate for that stratum. This adjustment scales up the sample estimates to accurately represent the entire population.
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:
19.1. Documents
Questionnaire in national language
Annex LT questionnaire on ICT usage and e-commerce 2025
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
Annual survey 'Informacinių technologijų naudojimas įmonėse / ICT usage in enterprises'
28 October 2025
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.
The statistical unit - enterprise with 10 and more persons employed.
Target Population
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“.
Enterprises located in the territory of whole country.
Data for a specific 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
Strata are defined by crossing the following size classes of persons employed and NACE groupings. To conduct grossing up procedures, the initial sampling weight within each stratum is adjusted using the response rate for that stratum. This adjustment scales up the sample estimates to accurately represent the entire population.
Frame population description and distribution: For more information see concept 18.1.1.
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:
The sample is stratified random sample made by use of register-based data and previous year sample data. The number of persons employed and economy activity were used to stratify the population. The were 32 NACE Rev. 2 groups and 3 enterprise size groups (10-49,50-249,250+). All enterprises from small groups (less than 20 units) by NACE Rev. 2 activities and number of persons employed groups were included into the sample. Within every NACE Rev. 2 groups the strata of enterprises were formed by number of persons employed groups. Then the Neyman optimal allocation (with variable number of persons employed) was used for determination of the sample size for each stratum specified. In each stratum sample random sampling was used. The sample was designed with no reference to other surveys.
Gross sample distribution: Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
Net sample distribution: Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (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.
