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.
Bundesanstalt Statistik Österreich ("STATISTICS AUSTRIA")
1.2. Contact organisation unit
Directorate Social Statistics, Unit Research and Digitalisation
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Guglgasse 13, 1110 Vienna, AUSTRIA
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
10 February 2025
2.2. Metadata last posted
10 February 2025
2.3. Metadata last update
10 February 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 of 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
IKT-Einsatz in Unternehmen 2024 – Erhebung über den Einsatz von Informations- und Kommunikationstechnologien (ICT usage in enterprise 2024 – Survey on the usage of information and communication technologies in enterprises)
All economic activities in the scope of Annex of the Commission Regulation are intended to be included in the general survey, covering enterprises with 10 or more employees and self-employed persons. These activities are:
Section C – “Manufacturing”
Section D, E – “Electricity, gas, steam and air conditioning supply”, “Water supply, sewerage, waste management and remediation activities”
Section F – “Construction”
Section G – “Wholesale and retail trade; repair of motor vehicles and motorcycles”
Section H – “Transportation and storage”
Section I – “Accommodation and food service activities”
Section J – “Information and communication”
Section L – “Real estate activities”
Section M – “Professional, scientific and technical activities”
Section N – "Administrative and support service activities"
Group 95.1 – “Repair of computers and communication equipment”.
For micro-enterprises see the sub-concepts 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?
Micro-enterprises are not included in the survey.
3.4. Statistical concepts and definitions
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access to and use of the Internet;
E-commerce and e-business;
ICT specialists and skills;
ICT security;
Artificial Intelligence.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
3.5. Statistical unit
Enterprise.
3.6. Statistical population
Target Population
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
3.6.1. Coverage of micro-enterprises
No
3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable.
3.7. Reference area
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Compleeness“.
All territories of Austria are included.
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 period of the Model Questionnaire is followed completely.
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:
There is no complementary national legislation.
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
At national level:
The strict confidentiality provisions of the Austrian Federal Statistics Act 2000 regulate the handling of sensitive data relating to individuals and organisations.
7.2. Confidentiality - data treatment
Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.
At national level:
Data is transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. National Statistical Institutes are requested to add flags for confidentiality in case results must not be disclosed.
8.1. Release calendar
Dates of the release of the ICT in enterprises results (press release and website) are preannounced in the release calendar of Statistics Austria which is publicly accessible.
Results are disseminated to all users at the same time via a press release and standardized tables via the website of Statistics Austria for free.
Specific data is provided to everyone with a specific request. Feasibility of the request and payment of possible expenses are checked in advance.
Annual
10.1. Dissemination format - News release
A press release was published on 16 October 2024 ("Enterprisesʼ use of artificial intelligence almost doubled within a year").
A press release was published on 9 December 2024 ("31% of enterprises use e-commerce").
A press release was published on 27 January 2025 ("20% of enterprises employ ICT specialists").
10.2. Dissemination format - Publications
A standard publication was established covering the results on the ICT usage in enterprises 2024, available on the website of Statistics Austria.
10.3. Dissemination format - online database
See detailed section 10.3.1.
10.3.1. Data tables - consultations
Results for selected variables collected in the framework of this survey are available for all participating countries on Digital economy and society of Eurostat website.
At national level:
Not available.
10.4. Dissemination format - microdata access
Due to national regulation Statistics Austria has to provide microdata results in case of a specific request by selected scientific organisations. Therefore, information on the questionnaire, indicators and codes are provided to the public via the website of Statistics Austria. The dissemination of microdata is checked for each data request to ensure that it meets the quality requirements regarding confidentiality and flagging specified in the Regulation (EC) No 223/2009 on European statistics.
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:
A national standard documentation is updated on a yearly basis to cover the latest information of each reference year and is published on the website of Statistics Austria. The detailed standard documentation is published in German only. A short summary is available in English.
The detailed German standard documentation was published on Statistic Austria's IKT-Einsatz in Unternehmen website > Dokumentationen > Standard-Dokumentationen.
The English summary was published on Statistic Austria's ICT usage in enterprises website > Documentation > Standard documentation.
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
A national standard documentation is updated on a yearly basis to cover the latest information of each reference year and is published on the website of Statistics Austria. The detailed standard documentation is published in German only. A short summary is available in English.
The detailed German standard documentation will be published on Statistic Austria's IKT-Einsatz in Unternehmen website > Dokumentationen > Standard-Dokumentationen.
The English summary will be published on Statistic Austria's ICT usage in enterpriseswebsite > Documentation > Standard documentation.
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.
At national level:
Statistics Austria is committed to ensuring the highest quality with respect to the compilation of statistical information. In accordance with the Federal Statistics Act (Article 24), Statistics Austria has to use statistical methods and processes in compliance with internationally recognised scientific principles and standards, conduct ongoing analyses of the statistics with a view to quality improvements and ensure that statistics are as up to-date as possible. This commitment to quality is also specified in Statistics Austria’s mission statement. In adopting the European Statistics Code of Practice, Statistics Austria has committed to adhering to principles and standards for the production and dissemination of high-quality statistics. As part of the European Statistical System (ESS), Statistics Austria recognises the Quality Declaration of the ESS. The Statistics Council has set up a Quality Assurance Committee, a primary focus of which is the ongoing examination of potential quality improvements. The Methodological Manual provides guidelines and standards for the implementation of the surveys in the Member States. It is updated every year according to the latest content of the model questionnaire.
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:
In cooperation with the Statistic Committee’s Quality Assurance Committee, feedback meetings concerning the quality of the different statistical products are held regularly within the framework of Statistics Austria’s quality management programme. In addition, internal quality audits are carried out by the quality management team. The content and objectives concern critical examination of the quality aspects of statistics with particular consideration of the methods and processes used; identification of quality improvement potential; development of recommendations for improvement measures; improvement of the standard documentation relating to the statistics in question, with special attention to the views of users and external experts.
12.1. Relevance - User Needs
At national level, the Federal Ministries (e.g. Bundeskanzleramt (BKA; in English: Federal Chancellery Republic of Austria) are the main users of the data on ICT usage in enterprise. Statistics Austria is closely collaborating with ministries to interpret different results on the survey, to observe the goals in regard to European and national benchmarks and to identify new developments on digitalisation which are shared in task force and working group meetings. Several other national users (e.g. public organisations, universities, private enterprises) regularly request data on ICT usage in enterprises.
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).
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
Horvitz-Thompson estimator for stratified sampling
b) Basic formula
See e.g. Cochran for stratified sampling
c)Main reference in the literature
E.g. Cochran
d)How has the stratification been taken into account?
Fully
e)Which strata have been considered?
NACE x Size x NUTS
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
52 out of 10 512 sampled units were identified, which were classified as "out of scope" during the field phase (mainly due to becoming inactive units during that period). The over-coverage rate was therefore 0.5%.
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 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%
10 512
100%
1. Response (questionnaires returned by the enterprise)
6 738
64.1%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
6 622
63.0%
1.2 Not used for tabulation
116
1.1%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
52
0.5%
1.2.2 Other reasons (e.g. unusable questionnaire)
64
0.6%
2. Non-response (e.g. non returned mail, returned mail by post office)
3 774
35.9%
Comments on unit response, if unit response is below 60%
National calculation of unit response is as follows: 6 622/(10 512-52)=63.3%
13.3.3.1.2. Methods used for minimizing unit non-response
A new designed covering letter was established.
Electronic questionnaire via internet (eQuest-Web)
A new designed information sheet on how to use the electronic questionnaire was sent out and an information sheet about the current privacy policy as well.
A telephone hotline for the respondents was established.
Two written reminders were sent out. The paper questionnaire was enclosed to the reminders as well as a stamped addressed envelope for returning the questionnaire.
Wrong mail addresses were investigated to send the questionnaire once again.
Last year's respondents were addressed (if available) to ensure a direct contact to the responsible person.
Responding enterprises will receive the main results after the survey for free.
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)
X
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
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)
Re-weighting using Horvitz-Thompson estimator and based on the base weights weighting with auxiliary information on turnover and number of employees and self-employed persons inside each stratum.
13.3.3.1.4. Assessment of unit non-response bias
Response rate was higher than 60%.
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.
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 is used where exact value can be derived directly from known information. Nearest-Neighbour imputation based on a distance function is used for imputing missing items (only for e-commerce values).
13.3.3.2.2. Questions or items with item response rates below 90% and other comments
Other comments relating to the item non-response
Additional issues concerning "item non-response" calculation (e.g. method used in national publications).
Not applicable.
Questions and items with low response rates (cut-off value is 90%) and item non-response rate.
Not applicable.
13.3.4. Processing error
No processing errors were detected.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed 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:
A final and validated dataset was delivered to Eurostat on 25 September 2024. Final results were released on 16 October 2024 on the website of Statistics Austria (press release and website).
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 25 September, 2024; 10 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 report.
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.
The statistical unit enterprise was implemented in 2024.
15.3. Coherence - cross domain
Not applicable
15.3.1. Coherence - sub annual and annual statistics
The practices of possible data revisions are followed completely, based on the general data revision policy of Statistics Austria, which corresponds to the Quality Assurance Framework of the European Statistical System. Only final results were published. No data revision was needed.
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:
Sampling was carried out as stratified random sampling. Three dimensions were used as stratification variables (33 x 3 x 9 = 891 strata):
Main economic activity (33 strata)
10–12
13–15
16–18
19
20
21
22–23
24–25
26.1–26.4+26.8
26.5–26.7
27
28
29–30
31–33
35
36–39
41–43
45
46
47
49–53
55
56
58–60
61
62–63
68
69–71
72
73–75
77–78+80–82
79
95.1
Size classes (3 strata)
10–49 employees
50–249 employees
250 or more employees
Region NUTS2 (9 strata)
Burgenland
Kärnten
Niederösterreich
Oberösterreich
Salzburg
Steiermark
Tirol
Vorarlberg
Wien
Other surveys were not considered during the sampling process, but the two previous ICT surveys have an influence. If a unit was in the sample in one of the two previous years, the probability to be in the sample again is decreased compared to the other units in the same strata. This is only valid for non-complete sample strata.
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):
Different snapshots, e.g. the frame for SBS 2023 is drawn in summer 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):
Not applicable.
e) Indication the shortcomings in terms of timeliness (e.g. time lag between last update of the sampling frame and the moment of the actual sampling), geographical coverage, coverage of different subpopulations, data available etc., and any measures taken to correct it, for this survey.
Not applicable.
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
29 February, 2024
22 July, 2024
Micro-enterprises
Not included.
Not included.
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
Not applicable
18.3.4. Survey type
Web questionnaire.
Paper questionnaire.
18.3.5. Survey participation
Voluntary
18.4. Data validation
Plausibility checks are carried out during the field phase in order to detect incorrect or missing information in the filled-in questionnaires (using the web questionnaire with incorporated checks).
As far as possible, phone calls or mails are carried out to clarify open issues with the respondents. After the field phase, the dataset is checked again regarding consistency and plausibility in order to gain a valid dataset.
The grossing-up of indicators is done according to the transmission format by Eurostat.
For validating the final data file, the validation process by Eurostat is used (using the test version of eDamis to receive the validation report). Validation errors detected were corrected by Statistics Austria. In case a correction is not possible, a comment in the notes of the dataset is provided (e.g. due to rounding or non-responses).
18.5. Data compilation
Grossing-up procedures
After the survey was performed, grossing up took place simply by (Nh/nh) where Nh represents the number of enterprises in the sampling frame (Austrian Business Register) in a certain stratum h and nh denotes the number of enterprises which responded in that stratum. The additional weights by employment and turnover were calculated in a similar way, so that total employment (and total turnover, resp.) equals the totals in the sampling frame for each stratum. Altogether, three weighting factors were calculated for each of the strata:
by number of enterprises,
by employment,
by turnover.
18.5.1. Imputation - rate
No imputation was carried out for the vast majority of variables.
Only for e-commerce values imputation was done if the requested value couldn't be provided, even after further inquiry. As only 3 units had to be imputed, the imputation rate is about 0.04%.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt:
None.
19.1. Documents
Questionnaire in national language
X
Questionnaire in English (if available)
X
National reports on methodology (if available)
X
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 of 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
IKT-Einsatz in Unternehmen 2024 – Erhebung über den Einsatz von Informations- und Kommunikationstechnologien (ICT usage in enterprise 2024 – Survey on the usage of information and communication technologies in enterprises)
10 February 2025
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access to and use of the Internet;
E-commerce and e-business;
ICT specialists and skills;
ICT security;
Artificial Intelligence.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
Enterprise.
Target Population
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Compleeness“.
All territories of Austria are included.
The reference period of the Model Questionnaire is followed completely.
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
After the survey was performed, grossing up took place simply by (Nh/nh) where Nh represents the number of enterprises in the sampling frame (Austrian Business Register) in a certain stratum h and nh denotes the number of enterprises which responded in that stratum. The additional weights by employment and turnover were calculated in a similar way, so that total employment (and total turnover, resp.) equals the totals in the sampling frame for each stratum. Altogether, three weighting factors were calculated for each of the strata:
by number of enterprises,
by employment,
by turnover.
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:
Sampling was carried out as stratified random sampling. Three dimensions were used as stratification variables (33 x 3 x 9 = 891 strata):
Main economic activity (33 strata)
10–12
13–15
16–18
19
20
21
22–23
24–25
26.1–26.4+26.8
26.5–26.7
27
28
29–30
31–33
35
36–39
41–43
45
46
47
49–53
55
56
58–60
61
62–63
68
69–71
72
73–75
77–78+80–82
79
95.1
Size classes (3 strata)
10–49 employees
50–249 employees
250 or more employees
Region NUTS2 (9 strata)
Burgenland
Kärnten
Niederösterreich
Oberösterreich
Salzburg
Steiermark
Tirol
Vorarlberg
Wien
Other surveys were not considered during the sampling process, but the two previous ICT surveys have an influence. If a unit was in the sample in one of the two previous years, the probability to be in the sample again is decreased compared to the other units in the same strata. This is only valid for non-complete sample strata.
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:
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.
