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.
Institut national de la statistique et des études économiques (STATEC)
1.2. Contact organisation unit
ENT3 - Structural Business Statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
STATEC B.P. 10 L-4401 Belvaux
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 March 2025
2.2. Metadata last posted
28 March 2025
2.3. Metadata last update
28 March 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 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
Enquête relative à l’usage des technologies de l’information et de la communication dans les entreprises – 2024
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?
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
The enterprise unit was used.
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 whole economic territory was covered.
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).
The reference periods defined in the model questionnaire were followed in the national survey :
Where not otherwise specified, the reference period is the current situation (year 2024).
The reference period for the percentages of sales/orders data is financial year 2023.
6.1. Institutional Mandate - legal acts and other agreements
Starting with reference year 2021 two new regulations currently form the legal basis for the survey on the use of ICT in enterprises:
Regulation (EU) 2019/2152 repealing 10 legal acts in the field of business statistics (EBS Regulation), and
Complementary national legislation constituting the legal basis for the mandatory nature of the survey on the use of ICT in enterprises, as well as governing the general production process:
Law of 10 July 2011 organising the Institut national de la statistique et des études économiques (STATEC).
6.2. Institutional Mandate - data sharing
Not applicable for this survey.
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:
Loi du 10 juillet 2011 portant organisation de l’Institut national de la statistique et des études économiques on statistical confidentiality as it applies to the Luxembourgian Statistical System.
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 :
Quantitative variables
Primary rules
We apply the (n,k)-dominance rule, i.e. a cell is suppressed if n units separately or jointly dominate the total value of a cell by at least k%. The (n, k) parameters for Luxembourg are confidential. For any cells that are left after applying the sensitivity rule, a minimum frequency is applied. A cell is suppressed if there are less than n units in a given cell. The n parameter for Luxembourg is confidential.
The primary rules' underlying parameters are kept confidential because their disclosure could compromise the safety of the primary suppressed cells.
Secondary confidentiality rules
The secondary suppression is calculated by tau-Argus using the ‘Modular’ algorithm. Manual suppressions or cost adjustments are performed to adjust the secondary confidentiality pattern calculated by the software.
a) Secondary suppression within a table
A cell is suppressed for secondary confidentiality if n units jointly or separately dominate the confidential subtotal by at least k%;
special attention is paid to the impact of singletons, a risk which is in most cases directly addressed by the tau-Argus Modular algorithm;
tau-Argus is set to minimise the cost when determining the secondary suppressed cells.
However, we also want to provide the user with relevant data, whether it is in terms of interpretation and/or availability of time series. Consequently, the cost minimisation can be overridden for economic and/or historical reasons.
b) Secondary suppression due to linked-table disclosure risks
A link is defined to exist between a cell sharing the same cell coordinates in two tables if an estimate for that cell based on the source table can be produced within p% range of the primary confidential cell's value of the target table. Most often, estimates based on the rule of three and linear interpolation, both of which are common user scenarios, are tested. Please note that p% only refers to the relationship between the dominance and p% thresholds and not to the p% sensitivity rule.
The following linked-table risks are addressed:
historical disclosure (time dimension): no primary historically confidential cell should be compromised by disclosing the same cell for the current reference year. As long as there is a significant link with a prior year primary confidential data, a cell may not be disclosed for the current reference year.
links to any other table sharing at least one dimension, including SBS tables by activity, e.g. turnover for the ICT survey is compared to the SBS preliminary series of the same reference year (e.g. T-1 for the survey carried out in year T).
Other SDC policy considerations
The statistical confidentiality analyses are performed on the basis of turnover (shadow variable approach). The same pattern is therefore applied to all quantitative variables.
As a general principle, the NACE section level data, if not broken down by any other dimension than NACE and if unfiltered, are not considered confidential, except if the section has a trivial breakdown. There can be other case-by-case exceptions to this general principle.
Qualitative variables For qualitative variables a minimum frequency is applied to cells broken down exclusively by variables which are available for every unit in the target population. Beyond this general rule, variable-specific rules are applied, based on the evaluation of the following risk potentials:
disclosure risk (none/low/high): the potential of identification of the variable ;
sensitivity (none/low/high): the potential damage dealt by the information in case of the disclosure ;
group sensitivity (none/low/high): the potential damage dealt by the information in case of group disclosure.
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.
Any national micro-data access is governed by article 16 of the Law of 10 July 2011 on the organisation of the National Institute for Statistics and Economic Studies.
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:
The application of the European Statistics Code of Practice is monitored by the national quality delegate. Further documentation can be found here: Qualité - Statistiques - Luxembourg (public.lu)
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:
Not available.
12.1. Relevance - User Needs
STATEC's research unit is routinely asked to provide feedback on new modules in the model questionnaire, as well as to indicate any variables used in research projects that might be missing from the model questionnaire.
12.2. Relevance - User Satisfaction
No user satisfaction survey conducted in this statistical area.
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
Estimations of the variables of interest were performed with the calibrated weights.
For a sufficiently large sample size, the calibration estimator is equivalent to the linear regression estimator and its bias tends to be minor. Consequently, the variance of the estimation is based on the residuals resulting from the relationship between the variable of interest and the ancillary variables which have been used for the calibration.
The standard error for a given survey stratum (which is normally also the stratum used for grossing-up) is calculated based on these properties. If necessary, these standard errors are then aggregated to the breakdowns requested by Eurostat.
b) Basic formula
See Annex 'basic formula Luxembourg'
c)Main reference in the literature
“Techniques de sondage” by Pascal Ardilly (ISBN 10: 2-7108-0847-1)
d)How has the stratification been taken into account?
See Annex 'stratification Luxembourg'
e)Which strata have been considered?
The strata used were the ones used for grossing-up. In cases where several strata had to be combined to allow calibration, these regroupings were also taken into account for the calculation of standard errors.
Generally, strata were defined by crossing the following size classes and NACE groupings (exceptions in parenthesis):
Size classes:
S - 10-49 employees
M - 50-249 employees
L - 250 employees
NACE groupings:
C10_18
C19_23
C24_25
C26_33
D35_39 (S+M combined)
F41_43
G45_46
G47
H49_53
I55 (M + L combined)
I56
J58_63
L68 (S+M combined)
M69_75 (M + L combined)
N77_82
S951
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
1%
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
No specific errors were detected in the implementation, coding and routing of the 2024 questionnaire.
In order to minimise measurement errors by respondents, the online questionnaire includes mandatory filters as well as validations on key variables. For some variables, no specific checks are performed during the data entry, in order not to force answers from respondents, preferring instead to treat any measurement errors arising from erroneous data entry by the respondent during the data validation or during imputation.
Responses are tested to be in the correct format and in the correct range (e.g. 0-100 for percentages, below a certain maximum for monetary and employment variables). Since most of the responses are received by electronic questionnaire, the number of exceptions is very low.
Micro-data validation also includes data consistency checks, both with other variables for the same reference year, as well as with the same variable for previous reference years. If possible, deductive imputation is performed, otherwise respondents are contacted to validate the response.
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%
2535
100%
1. Response (questionnaires returned by the enterprise)
2150
85%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
2127
84%
1.2 Not used for tabulation
23
1%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
23
1%
1.2.2 Other reasons (e.g. unusable questionnaire)
2. Non-response (e.g. non returned mail, returned mail by post office)
385
15%
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
In order to reduce the non-response, 3 reminders are sent (with a registered letter to high-impact enterprises, on the 3rd reminder).
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)
To treat non-response, the initial sampling weight is first adjusted using the response rate for each stratum. Strata are defined by crossing the size classes and NACE groupings listed in point 13.2.1.1.
In order to obtain reliable results for quantitative variables (that are in line with SBS totals), the corrected weights are calibrated to the number of units, using the total turnover and the total employment per stratum as auxiliary information. Calibration is carried out in R, using the “calib” method of the “sampling” package with a “logit” distance function.
13.3.3.1.4. Assessment of unit non-response bias
Not available
13.3.3.2. Item non-response - rate
There are no questions with response rates lower than 90%.
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.
X
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.
X
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.
X
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.
Deductive imputation was used in cases when filters were not respected.
Cold-deck imputation, based on 2023 data, was used for variables that were present in last year's survey and which do not change much over time.
Hot-deck imputation based on random sampling without replacement was performed by predefined strata for other variables.
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:
Not available.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Restricted from publication
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:
Not applicable
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.
No methodological changes occurred compared to the 2023 survey.
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
Currently, no revision of the ICT data is foreseen.
17.2. Data revision - practice
ICT data are currently not revised.
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 for sampling was a stratified random sample, with varying sampling rates depending on size class:
For the two size classes 50-249 and 250+, the sampling rate was 100% (i.e. a census); For the size class 10-49, the sampling rate was generally fixed at 60%, the only exceptions being F41_43, G45-46, G47, and I56 with a sampling rate of 35%. For small strata where the sample would have consisted of 3 units or less, a minimum of 3 units were sampled.
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?
February 2024
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
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):
The frame population used for the sample differs from the one used in SBS. It is based on the most recent SBS preliminary data available at that moment, but is adjusted using business register data in order to take into account the most recent figures for turnover and employment.
However, the frame population for the final data production uses the same snapshot as the SBS preliminary results for the same reference year.
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):
The frame population used for sampling is in part based on an early version of the business register, where not all information on turnover or employment is complete. Therefore, this frame will be updated in September for the grossing up procedure.
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.
Given that the sampling frame only contains 9 months’ worth of employment data for the reference year, we use the average employment over the 12 previous months as a criteria for the size classes used in sampling. These size classes are recalculated when the final frame population is drawn for grossing up and production of final results.
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
05 March 2024
09 Ocotber 2024
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
Possibility for respondents to choose between an online questionnaire or printing out and filling in a PDF version of the questionnaire.
18.3.5. Survey participation
Mandatory
18.4. Data validation
Micro-data
Quantitative variables
Quantitative data (e.g. turnover from websales, number of employees using the Internet) are tested to be in the correct format and in the correct range (e.g. 0-100 for percentages, below a certain maximum for monetary and employment variables). Since most of the responses are received by electronic questionnaire, the number of exceptions is very low.
Data are also compared, at the enterprise level, to values from previous surveys (if available). Additionally, some checks also compare the responses to administrative data (total turnover, number of employees). Respondents are contacted for further information if necessary.
Qualitative variables
Some qualitative data are compared, at the enterprise level, to values from previous surveys (if available). If respondents are contacted for further information relating to quantitative variables, they are also asked to confirm any fluctuations detected for qualitative variables.
Micro-data coding is tested to be in line with Eurostat's transmission format.
Aggregate data
Data is validated using the server-based validation provided by Eurostat (acceptance/pre-validation flow).
For certain key variables (related to e-commerce, module filters, etc) significant variations at the aggregated NACE section level are analysed and traced back to micro-data. If necessary, respondents are contacted.
18.5. Data compilation
Grossing-up procedures
Please refer to section 13.2.1.1 e) for the strata used.
Please refer to section 13.3.3.1.3 4) for a description of how weights are calculated.
Please note that due to the small number of observations leading to co-linearity problems, some strata cannot be calibrated over all size classes. For these strata, several size classes were combined.
18.5.1. Imputation - rate
The imputation rate ranges from 0,47% to 4% depending on the question.
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
FR/DE
Questionnaire in English (if available)
Yes
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
Enquête relative à l’usage des technologies de l’information et de la communication dans les entreprises – 2024
28 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.
The enterprise unit was used.
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 whole economic territory was covered.
The reference periods defined in the model questionnaire were followed in the national survey :
Where not otherwise specified, the reference period is the current situation (year 2024).
The reference period for the percentages of sales/orders data is financial year 2023.
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
Please refer to section 13.2.1.1 e) for the strata used.
Please refer to section 13.3.3.1.3 4) for a description of how weights are calculated.
Please note that due to the small number of observations leading to co-linearity problems, some strata cannot be calibrated over all size classes. For these strata, several size classes were combined.
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 for sampling was a stratified random sample, with varying sampling rates depending on size class:
For the two size classes 50-249 and 250+, the sampling rate was 100% (i.e. a census); For the size class 10-49, the sampling rate was generally fixed at 60%, the only exceptions being F41_43, G45-46, G47, and I56 with a sampling rate of 35%. For small strata where the sample would have consisted of 3 units or less, a minimum of 3 units were sampled.
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:
Not applicable
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
