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 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.
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
Yes
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?
All economic activities in the scope of Annex I of the Commission Regulation are intended to be included in the general survey, covering enterprises with 2 up to 9 employees. These activities are: NACE Rev. 2 sections C, D, E, F, G, H, I, J, L, M and N, division 95.1.
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 security
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 used is the business 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
Yes
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.
(2-9)
3.7. Reference area
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
The geographic scope of the ICT-survey is the (European) Netherlands, i.e. excluding Caribbean Netherlands (which are also part of the Kingdom of the Netherlands).
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 and million euro (for selected indicators).
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.
For the 2025 ENT survey, the reference period is the current survey period (2025) except for the value or % of sales data of the modules on e-commerce, total cost of the cloud computing services and (some questions of) ICT-security where respondents should report 2024 values.
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:
Statistics Netherlands (CBS) carries out its statistical research using the encrypted version of the data. It goes without saying that CBS also adheres to all the relevant legislative requirements in order to safeguard data privacy. These include:
The General Data Protection Regulation (Algemene Verordening Gegevensbescherming, AVG 679/2016)
The Statistics Netherlands Act (CBS-wet effective from 2 March 2022 on Act of 20 November 2003 enacting a law governing Statistics Netherlands on acquisition, use and provision of data in the context of the supply of statistical information.)
This latter is the cornerstone of the Statistical Business Register (SBR) of the CBS.
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:
At National level, the Dutch Data Protection Authority (DPA) supervises compliance with regulations of the law concerning personal data protection. An important contact person for the Dutch DPA is the CBS Data Protection Officer. Statistics Netherlands has its own Data Protection Officer (DPO). This officer monitors the implementation of and compliance with the GDPR by CBS and keeps a register of all personal data processing.
The measures of Statistics Netherlands (CBS) to safeguard the privacy and confidentiality of the collected data include technical and logistical measures:
All CBS employees are bound by an obligation of confidentiality and have signed a confidentiality agreement.
CBS only uses data for statistical and scientific purposes. CBS is excluded by law from using the data for fiscal, administrative, verification and legal purposes. Furthermore, CBS is not allowed to use data for marketing.
All statistical processes at CBS are certified in terms of personal data protection. This privacy proof audit is carried out by an accredited external party.
The data protection policy concerning a minimum frequency rule has been updated. Recently, it is advised to use 10 units for all NSI publications.
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:
More specific measures of Statistics Netherlands (CBS) to safeguard the privacy and confidentiality of the collected data are:
When respondents complete a survey or submit any data, this information is delivered to CBS in encoded form. The data are received by CBS in a secured environment. Only authorised personnel shall have access to these data.
At the earliest possible stage in the process, all directly identifiable personal data are removed from the files. This means datasets for research will never contain any data such as names, addresses or citizen service numbers.
Additional information about confidentiality policies and measures are available via Statistics Netherlands webpagina and brochures.
8.1. Release calendar
The target is to release the data within the survey year. A public announcement is placed about a month previous the data release. The CBS Publication calendar is weekly updated. Furthermore, an update of the Thema page of the ICT usage in enterprises (in Dutch) is made freely available and publicly accessible online.
Five tables about the results of the ICT usage in enterprises will be published in December 2025. By that time an announcement will be placed in the CBS-Publication calendar and short after a map will be made available via CBS-opendata: ICT usage in enterprises (in Dutch).
In general, news releases on the latest (or most prominent) ICT-statistieken are available online in December of the survey year or in January of the following year.
10.2. Dissemination format - Publications
The National dissemination of results is carried out twice a year:
At the beginning of the data collection. Enterprises are provided the links to the statistical outcomes of the previous year along with the invitation to participate in the survey "ICT usage in enterprises" (in Dutch).
At the publication and release of the outcomes of the current year via Statline and MKB Statline. The latter is an open data site dedicated to statistics on Small and Medium-sized Enterprises (SMEs).
Furthermore, the yearly dissemination of results includes also:
Since 2024, there is a dashboardcontaining a selection of the most relevant figures on the ICT usage in enterprises and in households in The Netherlands. Indicators are presented in an interactive manner and in time series. The dashboard is published inDutch and is available as afree of charge web publication. The release of the "Dashboard Digitalization and Knowledge Economy" with the latest 2025 ICT-figures (in Dutch) is scheduled for the first quarter of 2026.
The publication "Cybersecurity Monitor" (in Dutch) is available as a PDF file and it is also free of charge. A link to the publication series on cybersecurity is available online as well.
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:
Outcome tables are available via de websites Statline and MKB Statline. This later is a dedicated website for Small and Medium Enterprises (SME's). The total number of public accesses is measured along with the number of visits per table and both are quarterly reported.
10.4. Dissemination format - microdata access
Microdata requests are granted under a number of conditions. See Microdata.
10.5. Dissemination format - other
Not requested
10.5.1. Metadata - consultations
Not requested
10.6. Documentation on methodology
The European businesses statistics compilers’ manual for ICT usage and e-commerce in enterprises provides guidelines and clarifications for the implementation of the surveys.
At national level:
Methodological explanation about the ICT survey in enterprises is provided. In 2025, methodological improvements have been made (e.g. improved imputation procedures, improved weighting).
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
Documentation on quality management is recently updated as a part of the Year Plan of Statistics Netherlands (2023 and 2025, in Dutch). See section 4.2 (Kwaliteitsmanagement, in Dutch).
The purpose is to develop a central management of the quality management system. Since 2022 a Chief Quality Officer advises on organization-wide policy frameworks in the field of quality assurance. This task is carried out in cooperation with appointed quality and process coordinators in the various departments and with the internal audit departments.
A main development concerns connecting the management systems for quality, information security and information privacy as well as setting up a Register of Improvements, whereby outstanding points from audits in the areas of quality, information security and information privacy are monitored in a structured manner and demonstrably followed up.
11.1. Quality assurance
The European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises provides guidelines and standards for the implementation of the surveys. It is updated every year according to the changed contents of the model questionnaires.
The general quality management principles in Statistics Netherlands are actively promoted by means of the Statistical Netherlands’ Quality Assurance Framework at Process Level (Quality Guidelines for Process Assurance). These guidelines are continuously revised and operationalized in a template to support National Information Protection. The template includes general information of the statistical (production) process as well as workflows and descriptions at different detail levels (top-down). Moreover, documentation on connected information systems and software are also provided along with self-assessments and GDPR-documentation. Monitoring of compliance and audits are carried out by the department of Methodology of Statistics Netherlands. The updates to these documentation about the process ICT-usage in enterprises are executed yearly.
Moreover, in July 2022, CBS was the subject of a peer review under supervision of the European Statistical System (ESS).
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:
The statistical processing is automatized from reading the survey data to the ready-to-upload data delivery. Evaluations and consistency tests are rule-driven. Process includes also rest-points to check data and metadata quality. Higher-level script is updated yearly based on Model Questionnaire such that handlings are minimal and reproducibility of results is increased. Lower-level scripts (and packages) are brought under a version control and management system. Updates of these scripts follow technical requirements of delivery.
12.1. Relevance - User Needs
European level:
At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DG REGIO, DG JRC) are the principal users of the data on ICT usage and e-commerce in enterprises and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage.
User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies.
At European level, contacts within the Commission, the OECD and other stakeholders give a clear picture about the key users' satisfaction as to the following data quality aspects: accuracy and reliability of results, timeliness, satisfactory accessibility, clarity and comparability over time and between countries, completeness and relevance. Overall users have evaluated positively (good, very good) the data quality on the ICT usage and e-commerce in enterprises.
National level :
The current level of disaggregation of enterprises' size classes reaches the requirements of the main users of the data of the ICT usage and e-commerce in enterprises.
As for the user satisfaction results, these are not available.
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:
Standard errors are estimated using the R package survey. The standard estimation method is an adjusted Horvitz-Thompson estimator for the residuals in the linear regression of the outcome variable against the weighting model. The estimator accounts for unequal inclusion weights and includes a finite population correction. The estimator adjusts for the sample variation in the weights themselves. The size of this adjustment depends on the number of respondents in the publication cell.
Basic formula:
A simplified formula for calculating the standard error (SE) of a weighted estimate for stratum s is as follows:
where: σw (ps): is the weighted standard deviation for stratum s, ns: is the sample size of stratum s, Ns: is the population size of stratum s.
How has the stratification been taken into account? Stratification has been accounted for by including the stratification variables in the survey design (Lumley, Gao & Schneider, 2025). This ensures that the standard errors are calculated correctly based on the stratified sampling method.
Which strata have been considered? All breakdowns for which the data were delivered to Eurostat, but only for the variables that were asked in this section of the QR.
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 concerns two concepts 18.1. Description of frame population of the ICT- usage enquiry and 13.3.3.1.1. Enterprises out of scope (e.g. deaths, misclassified originally in the target population, etc.). See values provided in table 13.3.3.1.1.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No measurement errors were 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
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)
11 219
100%
14 502
100%
1. Response (questionnaires returned by the enterprise)
5 495
49%
11 319
78%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
5 495
49%
10 940
75%
1.2 Not used for tabulation
0
379
3%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
0
11
0%
1.2.2 Other reasons (e.g. unusable questionnaire)
0
368
3%
2. Non-response (e.g. non returned mail, returned mail by post office)
5 724
51%
3 183
22%
Comments on unit response, if unit response is below 60%
The percentage unit response (enterprises with 2-9 employees, E2T9) is 49%. The feedback of the respondents is that complexity of some questions or modules (i.e., Cloud service expenses and Artificial Intelligence) explain the lower response rates.
13.3.3.1.2. Methods used for minimizing unit non-response
After the invitation letters in February, we have 3 reminders in total until June in order to motivate enterprises to fill in the ICT-survey before the summer holiday. If enterprises wish to be addressed as a group (e.g. those with more business units and different locations) and use an enquiry to respond for all business units, this is allowed also to reduce the response burden of respondents.
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)
2.2 Treatment by re-weighting: Re-weighting by identified response homogeneity groups (created using sample-level information)
2.3 Treatment by re-weighting: Re-weighting through calibration/post-stratification (performed using population information) by the groups used for calibration/post-stratification
X
3. Treatment by imputation (done distinctly for each variable/item)
4. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of unit non-response. (e.g. Re-weighting using Horvitz-Thompson estimator, ratio estimator or regression estimator, auxiliary variables)
13.3.3.1.4. Assessment of unit non-response bias
The response rate was over 75% for EGE10 and over 49% for E2T9 (micro-enterprises).
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.
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.
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
We did not have processing errors.
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:
Data are published nationally at StatLine in December 2025, the time lag will be T+1 for indicators referring to 2025 (most of variables), T+12 months for indicators referring to 2024 (e-commerce and cloud services).
14.2. Punctuality
See detailed section in the full metadata view.
14.2.1. Punctuality - delivery and publication
2025 ENT Data were delivered to Eurostat on 3 October 2025 without NUTS; 2 days before the deadline. (NUTS data cannot be delivered in 2025.)
The Quality Report (QR) 2025 was delivered on due time and sent for validation; 3 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:
In the year 2025, no data on regions will be delivered to Eurostat.
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.
A break in series is reported by some specific indicators and NACE breakdowns with regard to last year. These have been flagged using code "B" following the transmission protocol.
15.3. Coherence - cross domain
Not applicable
15.3.1. Coherence - sub annual and annual statistics
A second register data source has been used to improve the current imputation method. It is connected to quarterly statistics based on VAT-data.
15.3.2. Coherence - National Accounts
Not applicable
15.4. Coherence - internal
Not applicable
Restricted from publication
17.1. Data revision - policy
Data have a provisional status from the first time they are published. Target is achieving a definitive status within two periods after.
17.2. Data revision - practice
Not requested.
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:
Enterprises with 100 or more employees are all included in the gross sample. For enterprises with 2-100 employees a random sample is used, stratified by NACE (32) and size class (6). Moreover, sample size is also based on prior experiences and cost considerations. For the optimal distribution of sample units across the strata, the Neymann allocation method is used. Enterprises that are drawn in other business survey samples have a reduced likelihood of being drawn into the sample of this survey.
C) Gross sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
D) 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?
4 February 2025
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
3 February 2025
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):
Not actively coordinated but both have as basis the SBR-stand 1 December 2024
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):
n.a.
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.
The Statistical Business Register (SBR) is daily updated. The sample was drawn at 4 February 2025 based on the population snap-shot of 1 December 2024. Because of the time lag between snap-shot date of sampling frame (4 February 2025) and the start of data collection (21 February 2025) some enterprises were found not active anymore during the data collection. Enterprises of the sample which were not active anymore at 21 February were excluded from the data collection. No measures were taken to correct for this except that the weights of the sample data change.
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
21 February 2025
26 September 2025
Micro-enterprises
21 February 2025
26 September 2025
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
The collection of micro-enterprises was integrated with the general survey
18.3.4. Survey type
This is a fully web survey, meaning that responses are collected online only. The sample of respondents is randomly split in two portions. The first portion is addressed around half February and the second portion is reached at the end of February.
18.3.5. Survey participation
Voluntary
18.4. Data validation
We have used the server-based validation tool provided by Eurostat (both Acceptance and Production environments) to validate the data deliveries plus an in-house developed tool for a year-on-year comparison.
Internal validation is executed by adding the last results to the existing time series. Positive and negative trends are detected structurally using time series plots. The monitoring of the results is based on step-wise filtering of the results using a top-down approach, i.e. the first results to be reviewed are the top NACE code aggregations and thereafter the higher enterprise size classes. In the next step, cross tables between size class versus medium and low NACE code aggregations are performed.
The log files of the processing tool are also reviewed. Those contain data about coverage and imputation rates.
Relating the output datasets of the statistic ICT usage in enterprises with other datasets should be explored yet, given that such a comparisons are cross-domain statistics. Those require often other identification codes and methodological considerations to match those consistently.
18.5. Data compilation
Grossing-up procedures
Depending on the variable that has to be reported, background variables such as “number of persons employed”, "number of enterprises" and "turnover" are needed for grossing up the responses from industry level towards economic sector level. Most variables collected are qualitative ones. A few are quantitative variables, i.e. percentage or real values.
Three variable cases are considered:
Case 1. Variables such as (overall) percentage of persons employed having access remotely to IT-services of their enterprises
Case 2. Variables such as (overall) percentage of enterprises using social media or having a website or
Case 3. Variables such as (overall) percentage of turnover via online platforms.
We use weights to aggregate from industry-level towards economic sector-level. Subgroup weights are based on the number of enterprises that are within the strata (i.e. survey size classes by sector levels) of the target population and the corresponding number of enterprises in the response. These weighting factors (partially) correct biases caused by the unit non-response for target variables of Case 1 and Case 2. The e-commerce turnover-related variables are estimated using weighting factors based on enterprises' turnover (variables of Case 3) and are less robust to unit non-response.
18.5.1. Imputation - rate
This value varies from breakdown to breakdown and from item to item. These values are reported in the logging files and depend strongly on the filters provided in the specifications. We do not report these in a separate table.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt: In 2025, there was an issue while addressing enterprises of the first lot (50% of the sample). Two standard sentences on the compulsory character of the ICT-survey were erroneously added to the invitation letter to participe in the ICT-survey on enterprises. Fortunately, it was quickly corrected and an analysis showed that this issue had no statistical consequencies on the quality of the response when compared with the second lot (standard letter).
19.1. Documents
Questionnaire in national language
ict_survey_2025.pdf
Questionnaire in English (if available)
ict_survey_2025eng.pdf
National reports on methodology (if available)
Analysis of key results, backed up by tables and graphs in English (if available)
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
ICT-gebruik bij bedrijven 2025
18 March 2026
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT security
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 used is the business 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 geographic scope of the ICT-survey is the (European) Netherlands, i.e. excluding Caribbean Netherlands (which are also part of the Kingdom of the Netherlands).
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.
For the 2025 ENT survey, the reference period is the current survey period (2025) except for the value or % of sales data of the modules on e-commerce, total cost of the cloud computing services and (some questions of) ICT-security where respondents should report 2024 values.
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 and million euro (for selected indicators).
Grossing-up procedures
Depending on the variable that has to be reported, background variables such as “number of persons employed”, "number of enterprises" and "turnover" are needed for grossing up the responses from industry level towards economic sector level. Most variables collected are qualitative ones. A few are quantitative variables, i.e. percentage or real values.
Three variable cases are considered:
Case 1. Variables such as (overall) percentage of persons employed having access remotely to IT-services of their enterprises
Case 2. Variables such as (overall) percentage of enterprises using social media or having a website or
Case 3. Variables such as (overall) percentage of turnover via online platforms.
We use weights to aggregate from industry-level towards economic sector-level. Subgroup weights are based on the number of enterprises that are within the strata (i.e. survey size classes by sector levels) of the target population and the corresponding number of enterprises in the response. These weighting factors (partially) correct biases caused by the unit non-response for target variables of Case 1 and Case 2. The e-commerce turnover-related variables are estimated using weighting factors based on enterprises' turnover (variables of Case 3) and are less robust to unit non-response.
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:
Enterprises with 100 or more employees are all included in the gross sample. For enterprises with 2-100 employees a random sample is used, stratified by NACE (32) and size class (6). Moreover, sample size is also based on prior experiences and cost considerations. For the optimal distribution of sample units across the strata, the Neymann allocation method is used. Enterprises that are drawn in other business survey samples have a reduced likelihood of being drawn into the sample of this survey.
C) Gross sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
D) 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:
In the year 2025, no data on regions will be delivered to Eurostat.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
