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.
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 2024 is Commission Implementing Regulation (EU) 2023/1507 of 20 July 2023 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2024. Large part of the data collected is used to measure the progress in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age.
Furthermore, ICT data facilitate the 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, big data (data analytics) and the digital intensity index for businesses (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
ICT usage survey Chestionar statistic privind utilizarea produselor TIC in intreprinderi
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 below.
3.3.1. Coverage-sector economic activity for micro-enterprises - All NACE Rev. 2 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 to and use of the Internet
E-commerce and e-business
ICT specialists and skills
ICT security
Artificial Intelligence.
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.
3.5. Statistical unit
Enterprise
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“.
The country area.
3.8. Coverage - Time
Years 2023 and 2024.
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).
In line with the EU model of the questionnaire; Current situation and year 2023 for certain variables.
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 legal acts consists of the National Statistical Law and National Annual Statistical Programme.
6.2. Institutional Mandate - data sharing
Not applicable
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:According to national legislation are considered as confidential data all aggregates with less than 4 units or one/two units dominate the aggregate.
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.
At national level: Data are treated to insure statistical confidentiality and prevent unauthorised disclosure. Access to data is provided to the authorised staff (survey managers).
8.1. Release calendar
The calendar of publications is publicly available.
The users can access the publications' calendar. On the NIS website a section is dedicated to dissemination of statistical data providing information about the access to data. The dissemination of statistical data is done identical for all users at the same time.
Annual
10.1. Dissemination format - News release
For this statistical domain we do not have news release.
10.2. Dissemination format - Publications
Regular annual publication Societatea Informationala on the INSSE website.
10.3. Dissemination format - online database
See detailed section 10.3.1.
10.3.1. Data tables - consultations
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
Micro-data are not disseminated. There is allowed the access for research purposes to the anonymised micro-data.
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.
At national level:
At national level the methodology is based on the compliers’ manual for ICT usage and e-commerce in enterprises
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:
At national level we used the Methodological Manual as basis for drafting the methodological explanations and definitions that are included in the statistical questionnaire. The MoQ and the European business statistics compilers manual for ICT usage ans e-commerce in enterprises are also used in all phases of the survey.
12.1. Relevance - User Needs
Internally the main users are the National accounts department. The National Agency for Digitisation is the main user outside the NIS.
12.2. Relevance - User Satisfaction
No user satisfaction survey is carried out specifically for the domain but the contacts with the users provide valuable input to asses the relevance of the ICT statistics
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).
More 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 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. Eurostat will make basic assumptions to compute these measures for all indicators produced (e.g. stratified random sampling assuming as strata the crossing of the variables “Number of employees and self-employed persons” and “Economic Activity” as it was defined in the 3 tables of section 18.1).
More detailed information is available in“ Annex III. Sample and standard error tables 2024 “ – 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.
a) Name and brief description of the applied estimation approach
The total error of an estimate relative to the unknown population value is expressed as a root mean square error. RMSE is defined as the square root of the sum of variance and the square of the bias. Relating to the accuracy, RMSE is rarely estimated. Sampling errors should be reported for all estimates resulting from a statistical process where sampling is involved. The standard error is the square root of the variance of an estimator.
The coefficient of variation (CV) is defined as the standard error divided by the expected value of the estimator. CV represents the standard error in relative (percentage) terms and it is more suitable in order to quantify the sampling error for economic statistics.
b) Basic formula
We calculate the CV at cell level, using SAS procedure PROC SURVEYMEANS
c)Main reference in the literature
not aplicable
d)How has the stratification been taken into account?
CV at cell level, using SAS procedure PROC SURVEYMEANS
e)Which strata have been considered?
The strata are based on the enterprise economic activity code (NACE code) and the size level (employment)
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
the over-coverage rate is 5%, which is due mainly to change of size class comparated to the target population initial size class.
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 sub-concepts 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%
11487
100%
1. Response (questionnaires returned by the enterprise)
10376
90.3
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
9807
85.3
1.2 Not used for tabulation
569
5.0
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
1.2.2 Other reasons (e.g. unusable questionnaire)
2. Non-response (e.g. non returned mail, returned mail by post office)
1111
9.7
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
Enterprises are contacted by phone call and reminders
13.3.3.1.3. Methods used for unit non-response treatment
1. No treatment for unit non-response
2. Treatment by re-weighting
2.1 Re-weighting by the sampling design strata considering that non-response is ignorable inside each stratum (the naïve model)
2.2 Re-weighting by identified response homogeneity groups (created using sample-level information)
2.3 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)
X
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)
13.3.3.1.4. Assessment of unit non-response bias
Not available.
13.3.3.2. Item non-response - rate
Not available
13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response
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
X
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.
X
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
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 available
Questions and items with low response rates (cut-off value is 90%) and item non-response rate.
Not available
13.3.4. Processing error
No processing errors were detected.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed section in the Full metadata report.
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: Data will be published in January 2025.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on October 4th ; one day 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:
There was no deviation from the model questionnaire or the concepts described in the Methodological manual
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 report.
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.
The ICT usage model of the questionnaire is used and the lenght of compable time series depends on the module and the variable.
15.3. Coherence - cross domain
Not applicable
15.3.1. Coherence - sub annual and annual statistics
National revision policy is appled when it is the case.
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:
The method used is stratified random sampling. Variables used for stratification are NACE code activity (according both to national and European aggregates) and size class in terms of employment.
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. Sampling design & Procedure frame
A) Description of frame population
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
March 2024
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
January-February 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):
Sample is coordonated with one used for SBS
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):
Not the case
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.
Not the case
B) 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
April
July
Micro-enterprises
Not included
Not included
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
18.3.5. Survey participation
Mandatory
18.4. Data validation
Inhouse developed validation IT tool and the server-based validation provided by Eurostat are used to validate the data.
18.5. Data compilation
Grossing-up procedures
The computation of the final weights was performed according to the following steps:
Calculation of a selection weight (πih) for each unit. The selection weight is a Horvitz-Thompson weight and is computed as the inverse of the selection probability.
pih=Nh/nh
where:
pih = the selection probability of unit i for stratum h
Nh=the number of units in the sampling frame, in the stratum h
nh= the number of units in the sample, in the stratum h
Calculation of a non-response weight (cih). The non-response weight is computed at each stratum level, as the inverse of the response probability. The purpose of this coefficient is to compensate the non-respondent units, under the assumption that these non-respondent units have the same training patterns compared with the respondent units in the same stratum. Another considered premise is the fact that answering and non-answering is a random variable.
nh/mh
where:
nh= the number of units in the sample, in the stratum h
mh = the number of respondent units selected in the sample,
in the stratum h
Calculation of the final weight ( )
The estimator used for computing the estimated data and the estimated variance is Horvitz-Thomson estimator, as the fraction between the number of units in the sampling frame in the stratum h and the number of respondent units in the sample in the same stratum (Nh/mh).
The estimation is based on the next assumptions:
The response is stochastic and there is a response distribution.
All units within a stratum respond with the same probability.
18.5.1. Imputation - rate
Not available.
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
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 2024 is Commission Implementing Regulation (EU) 2023/1507 of 20 July 2023 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2024. Large part of the data collected is used to measure the progress in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age.
Furthermore, ICT data facilitate the 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, big data (data analytics) and the digital intensity index for businesses (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
ICT usage survey Chestionar statistic privind utilizarea produselor TIC in intreprinderi
25 March 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 to and use of the Internet
E-commerce and e-business
ICT specialists and skills
ICT security
Artificial Intelligence.
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.
Enterprise
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“.
The country area.
In line with the EU model of the questionnaire; Current situation and year 2023 for certain variables.
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).
More 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
The computation of the final weights was performed according to the following steps:
Calculation of a selection weight (πih) for each unit. The selection weight is a Horvitz-Thompson weight and is computed as the inverse of the selection probability.
pih=Nh/nh
where:
pih = the selection probability of unit i for stratum h
Nh=the number of units in the sampling frame, in the stratum h
nh= the number of units in the sample, in the stratum h
Calculation of a non-response weight (cih). The non-response weight is computed at each stratum level, as the inverse of the response probability. The purpose of this coefficient is to compensate the non-respondent units, under the assumption that these non-respondent units have the same training patterns compared with the respondent units in the same stratum. Another considered premise is the fact that answering and non-answering is a random variable.
nh/mh
where:
nh= the number of units in the sample, in the stratum h
mh = the number of respondent units selected in the sample,
in the stratum h
Calculation of the final weight ( )
The estimator used for computing the estimated data and the estimated variance is Horvitz-Thomson estimator, as the fraction between the number of units in the sampling frame in the stratum h and the number of respondent units in the sample in the same stratum (Nh/mh).
The estimation is based on the next assumptions:
The response is stochastic and there is a response distribution.
All units within a stratum respond with the same probability.
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:
The method used is stratified random sampling. Variables used for stratification are NACE code activity (according both to national and European aggregates) and size class in terms of employment.
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 section in the Full metadata report.
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:
There was no deviation from the model questionnaire or the concepts described in the Methodological manual
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
