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.
Innovation, Business sector production and Research
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Statistics Sweden ESA/NUP/INF Solna Strandväg 86 SE-171 54 Solna
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
16 March 2026
2.2. Metadata last posted
16 March 2026
2.3. Metadata last update
16 March 2026
3.1. Data description
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
ICT usage and e-commerce in enterprises 2025 (Swedish: "It-användning i företag 2025")
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?
Not applicable since all activities 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 and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
The statistical unit is 'enterprise,' which may consist of one or more legal units. In situations where an enterprise consists of several legal units, a representative legal unit is selected and assessed following "the representative approach." This means that if an enterprise consists of more than one legal unit, one legal unit within the enterprise is selected to represent the entire enterprise to which it belongs. The selection of the representative is based on a set of predetermined criteria:
1. Industry classification (NACE) 2. Number of employees 3. Total turnover
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]
Yes
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable since no different size delimitation was used.
3.7. Reference area
The reference area consisted of all geographical regions of Sweden at NUTS2 level.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
3.8. Coverage - Time
Years 2024 and 2025.
3.9. Base period
Not applicable, no indexing was done.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data or where specified.
6.1. Institutional Mandate - legal acts and other agreements
Complementary national legislation constituting the legal basis for the survey on the use of ICT in enterprises:
The obligation to provide information applies according to the Act (2001:99) on the official statistics. The statistics are also regulated by the Ordinance (2001:100) on the official statistics and Statistics Sweden's regulations (SCB-FS 2024:27).
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:
The national policy employs the p-percent rule. According to this rule, a cell is deemed sensitive if the largest contributor to the cell can be estimated with an error margin within P% of the true value.
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:
For the Quality report, the national policy involves suppressing cells classified as sensitive according to the p-percent rule. The software TauArgus is used for confidentiality control and cell suppression, including secondary suppression when necessary.
8.1. Release calendar
There is a release calendar for the statistical outputs. This calendar is publicly accessible (see 8.2.).
The results are published according to a predetermined release schedule and made available to all users at the same time. Information about upcoming releases is announced in advance on Statistic's Swedens website.
Annual
10.1. Dissemination format - News release
The national results were published on Statistics Sweden’s website on November 6, 2025, as a press release. The release was accompanied by an online tool for extracting time series data from the national statistical database and is available in both English and Swedish.
An article on the use of AI in enterprises is scheduled for publication in December 2025 and will be available on the ICT usage in enterprises website.
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:
Results are published in the national statistical database on Statistics Sweden’s website.
10.4. Dissemination format - microdata access
Statistics Sweden’s enterprise microdata is confidential. However, you can access anonymized microdata following a confidentiality assessment, provided Statistics Sweden deems that you have valid grounds to process the data. For more information, see: Ordering 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:
Documentation on the production of statistics on ICT usage and e-commerce in enterprises 2025 was published on Statistics Sweden’s website (only available in Swedish) alongside the national release on November 6, 2025. This documentation includes the survey design and the implementation of the statistical production.
A quality declaration was published on Statistics Sweden’s website (only available in Swedish) alongside the national release on November 6, 2025. This document includes quality, production, and a detailed description of the content of the statistical production.
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 survey refers to Sweden's official statistics (SOS). Therefore special rules apply for quality and accessibility, see the Act (2001:99) and the Ordinance (2001:100) on official statistics and Statistics Sweden's regulations (SCB-FS 2024:27) on quality for official statistics.
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:
We follow the framework established by the Eurostat model questionnaire, which undergoes national-level testing before being translated accordingly. Additionally, we strive to adhere as closely as possible to the guidelines outlined in the Methodological Manual. Estimations are conducted by methodological statisticians, while the data is reviewed by domain expert statisticians. The data collection process ensures that the response rate is sufficiently, ensuring quality and reliable results.
12.1. Relevance - User Needs
The Ministry of Finance and other relevant authorities are consulted when determining the optional and national questions to be included in the national questionnaire. Additionally, Statistics Sweden seeks their input if they believe an issue falls within the ministry's purview.
12.2. Relevance - User Satisfaction
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: A precision for the estimated proportion, in terms of a standard error, is specified for each economic activity strata. The Horwitz-Thompson estimator is used. Unit non-response is compensated by means of adjusting the weights to reflect the actual number of respondents. Item non-response are imputed when answers can be derived from other questions (known as “logical corrections”). Due to survey errors, a few units did not receive all the questions they were supposed to, and these item non-responses were also imputed.
Basic formula: Estimator for Totals (t_d)
The following estimator is used to calculate totals for a domain d:
t_d = Σ (h = 1 to H) [ (N_dh / n_dh) × Σ (y(k) for k in s_dh) ]
Where:
y(k) is the value of the variable y for unit k
s_dh is the sample in stratum (d,h)
N_dh is the number of units in the population in stratum (d,h)
n_dh is the sample size in stratum (d,h)
In case of nonresponse, n_dh is replaced with the actual number of respondents in the stratum.
For variables estimating the number of enterprises, y(k) is set to 1 for enterprises responding "yes" and 0 for all others.
Estimator for Turnover Variables
For turnover-related variables, the following estimator is used:
t_d = Σ (h = 1 to H) [ (Turnover_pop_dh / Turnover_resp_dh) × Σ (y(k) for k in s_dh) ]
Where:
Turnover_pop_dh is the total turnover for the population in stratum (d,h)
Turnover_resp_dh is the total turnover for the respondents in stratum (d,h)
Estimator for Number of Employees
For variables related to the number of employees, the estimator is:
t_d = Σ (h = 1 to H) [ (Empl_pop_dh / Empl_resp_dh) × Σ (y(k) for k in s_dh) ]
Where:
Empl_pop_dh is the total number of employees in the population in stratum (d,h)
Empl_resp_dh is the total number of employees among respondents in stratum (d,h)
Main reference in the literature: Särndal, C.-E., Swensson, B. och Wretman J. (1992). Model Assisted Survey Sampling. New York: Springer-Verlag
How has the stratification been taken into account? The sampling frame is stratified along three dimensions:
Economic activity, based on NACE Rev. 2
Enterprise size, measured by number of employees
Region, based on the NUTS1 classification
Stratification by economic activity is designed to closely align with the study’s target domains, representing distinct subpopulations. Within each economic activity stratum, enterprises are further divided into ten size classes based on employee count, including three strata specifically for micro enterprises.
Enterprises with 200 or more employees are included in a full census. For enterprises with 0–199 employees, stratification is applied using both economic activity and size.
Sweden is divided into three regional subgroups: SE1, SE2, and SE3. For sampling purposes, SE1 and SE2 are combined into a single stratum, while SE3 is treated separately to enhance precision in that region.
Which strata have been considered?
Strata are defined by NACE classes according to NACE Rev. 2 (NACE 2007), further subdivided by enterprise size and region (NUTS1: SE1+SE2, SE3).
Size classes for enterprises with 10 or more employees:
Size class 1: 10–19 employees
Size class 2: 20–49 employees
Size class 3: 50–99 employees
Size class 4: 100–199 employees
Size class 5: 200–249 employees
Size class 6: 250–499 employees
Size class 7: 500 or more employees
Size classes for enterprises with 0–9 employees:
Size class 8: 0–1 employee;
Size class 9: 2–9 employees;
Size class 10: 0–9 employees (used for specific purposes where a broader grouping is needed).
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
One enterprise in total of the sample of 4,800 enterprises with 10 or more employees were identified as over-covered, corresponding to an over-coverage rate of 0.02%. No over-coverage was identified among enterprises with 0–9 employees. This is assumed to reflect the over-coverage rate in the sampling frame.
Overall, the coverage is considered good, and the impact of coverage error on the total estimation uncertainty is therefore assessed to be minimal.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
Measurement errors primarily arise from unclear questions, incomplete answer options, or choices that are not mutually exclusive. These errors are challenging to quantify, and their impact on overall uncertainty remains difficult to assess.
To minimize such errors, considerable effort is devoted to designing questions that are clear, simple, and easy to interpret. Feedback from respondents and follow-up contacts suggest that measurement errors most commonly affect quantitative variables related to e-commerce. In addition, some respondents may have difficulty interpreting certain qualitative variables. For instance, if an enterprise uses a technology referenced in the questionnaire but not explicitly listed among the examples, they may mistakenly report that they do not use the technology.
13.3.3. Non response error
See detailed sections below.
13.3.3.1. Unit non-response - rate
See detailed sections below.
13.3.3.1.1. Unit response
The following table contains the number of units (i.e. enterprises), by type of response to the survey and by the percentage of these values in relation to the gross sample size.
Type of response
Enterprises
0-9 (or 2-9) employees and self-employed persons
10 or more employees and self-employed persons
Number
%
Number
%
Gross sample size (as in section 3.1 C)
3092
100%
4800
100%
1. Response (questionnaires returned by the enterprise)
2277
73,64%
3865
80,52%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
2242
72,51%
3852
80,25%
1.2 Not used for tabulation
35
1,13%
13
0,27%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
0,00%
1
0,02%
1.2.2 Other reasons (e.g. unusable questionnaire)
35
1,13%
12
0,25%
2. Non-response (e.g. non returned mail, returned mail by post office)
815
26,36%
935
19,48%
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
Language Support: The questionnaire is available in both Swedish and English to accommodate respondents who do not speak Swedish. This facilitates participation from enterprises with international staff or operations outside Sweden.
Targeted Follow-ups: After the second written reminder, email follow-ups are sent to prioritized enterprises—specifically medium-sized and large companies, as well as those with significant e-commerce turnover—that have not yet responded.
Fillable PDF Option: The questionnaire is also provided as a fillable PDF, which supports internal coordination and preparation within enterprises.
Respondent Support Service: SCB offers assistance via phone and email to answer questions and provide guidance throughout the data collection process.
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
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)
Unit non-response is addressed through reweighting. This means that the number of enterprises in the sample (n_dh) is replaced by the actual number of respondents (m_dh), and the full sample (S_d) is replaced by the group of respondents (r_d). This adjustment ensures that estimates are based only on enterprises that have submitted responses.
13.3.3.1.4. Assessment of unit non-response bias
Response rate was higher then 60%.
13.3.3.2. Item non-response - rate
In 2025, a technical error in a filter caused a small number of enterprises to miss certain questions they should have received. The issue was corrected through imputation. Despite this, the impact on the reliability of the results is considered minimal.
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.
Nearest neighbour was used when we had filter errors in the survey.
4. Random imputation (e.g. hot-deck, cold-deck) Random imputation leads to estimators with a random component, that is, if the imputation were re-conducted, it would have led to a different result.
5. Re-weighting
6. Multiple imputation In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets.
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
13.3.3.2.2. Questions or items with item response rates below 90% and other comments
Other comments relating to the item non-response
A) Additional issues concerning "item non-response" calculation (e.g. method used in national publications):
Not applicable
B) Questions and items with low response rates (cut-off value is 90%) and item non-response rate:
Not applicable
13.3.4. Processing error
In 2025, a technical error was identified in a filter, causing a small number of enterprises to miss certain questions they should have received. The issue was resolved through imputation. Despite this, the impact of the processing error on the overall reliability is considered minor.
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 collection start in February and end in August. National results are released by in the beginning of November, resulting in a time lag of 9 months.
14.2. Punctuality
See detailed section in the full metadata view.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on October 1st; four days before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
See detailed section in the full metadata view.
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.
In the 2025 data collection, the wording of question E_ERP1 (Use of Enterprise Resource Planning (ERP) software) was adjusted. A break in the time series was introduced to reflect this change 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
Not available
17.2. Data revision - practice
There are no revisions to report regarding the 2025 data collection.
17.2.1. Data revision - average size
Not requested
18.1. Source data
A) Frame population description and distribution
The sampling frame for the survey on ICT usage and e-commerce in enterprises 2024 consists of all active enterprises in the Swedish Business Register (BR) classified into the economic activities (based on NACE Rev 2) 10-82 and 95.1 (excluding 64-67, 76) and institutional sector codes (INSEKT 2014) 111000, 112000, 113000. A version of the BR established in November year 2024 is used. Micro enterprises (0-9 employees) and enterprises with 10 or more employees are included
For more information see concept 18.1.1.
B) Sampling design - Sampling method
The statistical unit is enterprise, which may comprise one or more legal units. A stratified simple random sampling method is applied, using Neyman (optimal) allocation. In cases where an enterprise includes multiple legal units, one representative unit is selected to represent the entire enterprise. This "representative approach" is based on the following criteria:
Industry classification (NACE)
Number of employees
Total turnover
This method is necessary due to the large number of multi-unit enterprises in the Business Register (BR). Swedish legislation prohibits disclosure of which legal units belong to a given enterprise, making it impossible to request that one unit respond on behalf of others. Additionally, collecting data from every legal unit would impose excessive response burden and cost. To balance feasibility and data quality, only legal units with 10 or more employees are included in the data collection of enterprise units with 10 or more employees.
Sampling Framework:
Enterprises with 200 or more employees are fully enumerated (censused).
Enterprises with 0–199 employees are sampled using stratified simple random sampling.
Stratification is based on:
Economic activity (NACE Rev. 2)
Number of employees
Region (NUTS1)
The NACE categories follow the European aggregates outlined in the Eurostat Model Questionnaire for the 2025 Community Survey on ICT Usage and E-commerce in Enterprises. Employee size categories are defined according to the classification in section 13.2.1.1 e) of the methodology. Stratification on region are SE1 + SE2 and SE3, and is only used in the stratification of enterprises with 10 or more employees.
The final stratification includes:
241 strata for enterprises with 10 or more employees
81 strata for enterprises with 0–9 employees
Allocation Procedure:
Neyman allocation is used to determine sample sizes within each stratum, except for those with 200 or more employees. The allocation is based on three variables:
Number of enterprises
Number of employees
Total turnover
For each variable, stratum-level variance is calculated at the population level. Sample sizes are then computed to achieve a specified level of precision, expressed as a relative standard error. Neyman allocation is performed separately for each variable, and the largest resulting sample size is selected for each stratum.
Calculation Overview:
The sample size for each stratum is calculated using the following formula:
n= (N^2 (∑(h = 1 to H) W_h x S_h )^2)/(∝^2 x t^2+N∑(h = 1 to H)S_h^2 )
Where:
n_h: sample size in stratum h
n: total sample size for the survey
α: selected precision
t: total of the allocation variable
S_h: standard deviation in stratum h
H: number of strata
N: population size
W_h: proportion of the population in stratum h
A minimum of three enterprises is sampled per stratum. Note that the allocation only applies to domains that align with strata or their aggregates; domains that span across strata are excluded. The method does not account for potential nonresponse.
To enhance comparability over time, the sample is coordinated with other surveys, including the Enterprises' IT Expenditure Survey and the Community Innovation 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?
December 2024
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
November 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):
No coordination with the SBS, different snapshots from the SBR are used
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):
No difference
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 sampling frame has some undercoverage of start-up and “growing” enterprises, while overcoverage includes discontinued and merged enterprises. These coverage issues arise due to delays in reporting to the registry. Overall, the coverage is considered good, and the contribution of coverage errors to the overall uncertainty in estimates is deemed to have a minimal impact.
B) Frame population distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: FRAME POPULATION)
18.2. Frequency of data collection
Annual
18.3. Data collection
See detailed sections below.
18.3.1. Survey period
Survey / Collection
Date of sending out questionnaires
Date of reception of the last questionnaire treated
General survey
3 February 2025
31 August 2025
Micro-enterprises
3 February 2025
31 August 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
Self-administrated web survey. The enterprises are invited to fill in a web questionnaire in Swedish or in English. If needed, in rare cases, a PDF version will be sent to the respondent and answers will be collected through e-mail.
18.3.5. Survey participation
Mandatory
18.4. Data validation
Data were validated during the transmission process in line with Eurostat's standards. In few cases of suspected misreporting, enterprises were contacted directly to verify the accuracy of the submitted data and made necessary corrections accordingly.
18.5. Data compilation
Grossing-up procedures
The result is weighted by numbers of enterprises, numbers of employees and self-employed persons and turnover in the net sample depending on the variable. See section 13.2.1.1. B) Basic formula. Unit non-response is compensated by changing the denominator from the sample units to the responding units or the respondents’ turnover or number of employees depending on the variable. Post-stratification is not applied.
18.5.1. Imputation - rate
Item non-response are imputed when answers can be derived from other questions (known as “logical corrections”). Due to survey errors, a few units did not receive all the questions they were supposed to, and these item non-responses were also imputed.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
19.1. Documents
Questionnaire in national language
It-användning i företag 2025
Questionnaire in English (if available)
ICT usage in enterprises 2025
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 usage and e-commerce in enterprises 2025 (Swedish: "It-användning i företag 2025")
16 March 2026
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
The statistical unit is 'enterprise,' which may consist of one or more legal units. In situations where an enterprise consists of several legal units, a representative legal unit is selected and assessed following "the representative approach." This means that if an enterprise consists of more than one legal unit, one legal unit within the enterprise is selected to represent the entire enterprise to which it belongs. The selection of the representative is based on a set of predetermined criteria:
1. Industry classification (NACE) 2. Number of employees 3. Total turnover
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.
The reference area consisted of all geographical regions of Sweden at NUTS2 level.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data or where specified.
Comments on reliability and representativeness of results and completeness of dataset
These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
Detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Grossing-up procedures
The result is weighted by numbers of enterprises, numbers of employees and self-employed persons and turnover in the net sample depending on the variable. See section 13.2.1.1. B) Basic formula. Unit non-response is compensated by changing the denominator from the sample units to the responding units or the respondents’ turnover or number of employees depending on the variable. Post-stratification is not applied.
A) Frame population description and distribution
The sampling frame for the survey on ICT usage and e-commerce in enterprises 2024 consists of all active enterprises in the Swedish Business Register (BR) classified into the economic activities (based on NACE Rev 2) 10-82 and 95.1 (excluding 64-67, 76) and institutional sector codes (INSEKT 2014) 111000, 112000, 113000. A version of the BR established in November year 2024 is used. Micro enterprises (0-9 employees) and enterprises with 10 or more employees are included
For more information see concept 18.1.1.
B) Sampling design - Sampling method
The statistical unit is enterprise, which may comprise one or more legal units. A stratified simple random sampling method is applied, using Neyman (optimal) allocation. In cases where an enterprise includes multiple legal units, one representative unit is selected to represent the entire enterprise. This "representative approach" is based on the following criteria:
Industry classification (NACE)
Number of employees
Total turnover
This method is necessary due to the large number of multi-unit enterprises in the Business Register (BR). Swedish legislation prohibits disclosure of which legal units belong to a given enterprise, making it impossible to request that one unit respond on behalf of others. Additionally, collecting data from every legal unit would impose excessive response burden and cost. To balance feasibility and data quality, only legal units with 10 or more employees are included in the data collection of enterprise units with 10 or more employees.
Sampling Framework:
Enterprises with 200 or more employees are fully enumerated (censused).
Enterprises with 0–199 employees are sampled using stratified simple random sampling.
Stratification is based on:
Economic activity (NACE Rev. 2)
Number of employees
Region (NUTS1)
The NACE categories follow the European aggregates outlined in the Eurostat Model Questionnaire for the 2025 Community Survey on ICT Usage and E-commerce in Enterprises. Employee size categories are defined according to the classification in section 13.2.1.1 e) of the methodology. Stratification on region are SE1 + SE2 and SE3, and is only used in the stratification of enterprises with 10 or more employees.
The final stratification includes:
241 strata for enterprises with 10 or more employees
81 strata for enterprises with 0–9 employees
Allocation Procedure:
Neyman allocation is used to determine sample sizes within each stratum, except for those with 200 or more employees. The allocation is based on three variables:
Number of enterprises
Number of employees
Total turnover
For each variable, stratum-level variance is calculated at the population level. Sample sizes are then computed to achieve a specified level of precision, expressed as a relative standard error. Neyman allocation is performed separately for each variable, and the largest resulting sample size is selected for each stratum.
Calculation Overview:
The sample size for each stratum is calculated using the following formula:
n= (N^2 (∑(h = 1 to H) W_h x S_h )^2)/(∝^2 x t^2+N∑(h = 1 to H)S_h^2 )
Where:
n_h: sample size in stratum h
n: total sample size for the survey
α: selected precision
t: total of the allocation variable
S_h: standard deviation in stratum h
H: number of strata
N: population size
W_h: proportion of the population in stratum h
A minimum of three enterprises is sampled per stratum. Note that the allocation only applies to domains that align with strata or their aggregates; domains that span across strata are excluded. The method does not account for potential nonresponse.
To enhance comparability over time, the sample is coordinated with other surveys, including the Enterprises' IT Expenditure Survey and the Community Innovation 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:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
