1.1. Contact organisation
Statistical Office of the Republic of Slovenia (SURS)
1.2. Contact organisation unit
Department for Transport, Tourism and Information Society Statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Litostrojska cesta 54, 1000 Ljubljana, Slovenija
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
27 February 2025
2.2. Metadata last posted
27 February 2025
2.3. Metadata last update
27 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 in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age.
Furthermore, ICT data facilitate the monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme. Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, big data (data analytics) and the digital intensity index for businesses (DII) - a composite indicator reflecting the digital transformation of business. The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
| Name of data collection |
|---|
| Uporaba informacijsko-komunikacijske tehnologije in e-trgovanje v podjetjih, 2024 Usage of Information-Communication Technologies and e-commerce in enterprises, 2024 |
3.2. Classification system
NACE Rev.2 2008 - Statistical classification of economic activities
3.3. Coverage - sector
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
No3.3.2. 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
Statistical unit used is enterprise. In majority of cases, enterprise equals legal unit. 14 enterprises were comprised of more than one legal unit.
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
No3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable.
3.7. Reference area
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
The whole territory of the country was 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 was current usage in 2024 and the whole year 2023.
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:
- Annual Programme of Statistical Surveys (LPSR) (only in Slovene)
- National Statistics Act (OJ RS, No. 45/95 and 9/01)
6.2. Institutional Mandate - data sharing
SURS is transmitting and sharing aggregated data of the survey with Eurostat in accordance with the EU Regulation (Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics, repealing 10 legal acts in the field of business statistics).
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 National Statistics Act (hereinafter the ZDSta) stipulates within fundamental principles of national statistics in Article 2 that “national statistics shall be implemented on the principles of … confidentiality …”. The principle is concretised in further provisions of the ZDSta, while for explanation one can turn to some international documents. The United Nations Resolution on Fundamental Principles of Official Statistics (adopted by the UN Statistical Commission in 1994 and confirmed by the UN General Assembly on 29 January 2014) determines in Principle 6 that “individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes”.
7.2. Confidentiality - data treatment
Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.
At national level:
Data are 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.
All SURS employees are obliged to protect the content of personal and individual data and data on reporting units which they learn during their work as official secrecy. All employees sign a statement of data protection and thus confirm that they are informed about the issue. The obligation to protect the official secrecy continues after the termination of employment.
In line with the National Statistics Act (ZDSta) the statistical purpose is providing and disseminating aggregate data on mass phenomena. The ZDSta also stipulates that the data can be used exclusively for statistical purposes, i.e. for disseminating aggregate data, unless otherwise provided by law. On the basis of an application written by a user, individual data can be transmitted, but only in the form and way which does not enable the identification of the unit to which the data refer. The data that enable the identification of the unit to which they refer can only be transmitted to those units to which the data refer or if these units sent the data.
SURS can publish the data only in aggregate form, so that it is not possible to identify the unit to which the data refer. The data must be available in the same way (at the same time and under the same conditions) to all users. Only exceptionally can SURS publish individual data: upon written consent of the reporting unit to which the data refer that they agree with the publication of data in such a way or if the data are collected from public (generally accessible) data collections (records, registers, databases, etc.). Click for more info on our websites Statistical confidentiality and General information on personal data protection.
8.1. Release calendar
A release calendar for the statistical outputs is available and publicly accessible.
8.2. Release calendar access
The release calendar is available here.
8.3. Release policy - user access
SURS provides access to official statistical data to all users. The latest statistical data are published in press releases every workday at 10:30 on the date announced in advance in the Release Calendar. The calendar also includes releases of authorised producers of national statistics, i.e. the National Institute of Public Health and the Bank of Slovenia. The dates of first releases are announced a year in advance, usually in November for the coming year. During the year, SURS prepares and publishes – depending on current events – special and experimental releases, which are also announced in the Release Calendar. Users can subscribe to receiving a weekly calendar on their e-mails every Monday at 9:00.
Press releases are published in Slovenian and English language. SURS makes sure that results of statistical surveys are presented in an unbiased, objective, clear and understandable way. It is important that the published data are of high quality, timely, and internationally comparable.
ICT statistics follows the described practices. Regular press releases are published in the Release Calendar one year in advance (3 press releases). SURS also publishes special releases on the topic of ICT – on World Telecommunication and Information Society Day and Safer Internet Day.
Annual
10.1. Dissemination format - News release
National dissemination of results:
- First Release (Development and Technology, Information Society): »Digital Entrepreneurship, Slovenia, 2024«.
- Electronic Release (Development and Technology, Information Society): »Web sales, Slovenia, 2023«.
- Electronic Release (Development and Technology, Information Society): »Digital Entrepreneurship, detailed data, Slovenia, 2024«.
10.2. Dissemination format - Publications
Non-applicable. Data are published in online database.
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:
Results for selected variables collected in the framework of this survey are available at national level in Sistat database.
10.4. Dissemination format - microdata access
Access to the micro data can be provided according to the established rules and procedures to researches. Information is available on this website for researchers.
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:
SURS prepares and publishes on the website the following documentation on methodology:
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
Quality report is published on the website - Theme: Development and Technology; Sub-theme: Digital Society.
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:
The Statistical Office of the Republic of Slovenia operates on the basis of the National Statistics Act and Regulation (EC) No. 223/2009 on European statistics; in performing its tasks it follows the general principles of quality management, the European Statistics Code of Practice and the Fundamental Principles of Official Statistics. In line with the stated, SURS declares that it takes into account the following principles: professional independence, process orientation, quality of products and services, planning of improvements, stimulating working environment for employees, data providers-friendly official statistics, user-oriented official statistics. The principles are more in detail presented in the Quality Statement of the Statistical Office of the Republic of Slovenia.
Work at SURS is process-oriented. This means that different departments (which have appropriate skills and experiences) take care of different parts of the process and every process has a special monitoring system. The project manager additionally oversees all the phases of conducting the survey.
- Preparation of the survey (translation and preparation of the model questionnaire, etc.) The task is performed by the project manager, the methodologist for questionnaire design and the IT expert.
- Sampling design The task is performed by the methodologist for sample design.
- Fieldwork The task is performed by the department for data reception and by the department for enterprise cooperation (contact center) in cooperation with the project manager (provides instructions regarding timetable for sending information letters, reminders, availability of electronic questionnaire, content of the survey, etc.).
- Data review, data entry, data processing, editing and grossing-up Data validation is carried out by or under the instruction of the project manager and grossing-up by the appropriate methodologist.
- Aggregation/tabulation of data The tasks is carried out by the project manager (preparing tabulation rules) in cooperation with the IT expert.
- Publication of the data and preparation of the data for detailed data publication. The task is performed by the project manager.
- Preparation of reports The task will be performed by the project manager and the methodologist for sample and grossing-up.
SURS follows the methodology proposed by Eurostat to meet the general and specific objective of the action as defined in the implementing regulation. The sample is of sufficient size to ensure obtaining accurate, reliable and representative results (keeping in mind the required accuracy level).
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 quality of statistical data used to be dealt with mostly in connection with data accuracy in the narrow sense (as coherence between statistical data and exact values). Quality is dealt with in terms of quality dimensions: relevance, accuracy of estimates, timeliness and punctuality of publication, accessibility and clarity of information, comparability of statistics and coherence of results. SURS regularly publishes reports on the quality of statistical surveys, which contain detailed descriptions of individual statistical surveys regarding all quality dimensions. Quality reports also contain the values of quality indicators, i.e. numerical values of achieved quality levels for individual quality components.
The survey has a satisfactory quality. The biggest challenge is the formulation of questions. Due to technological advances and the content of the survey, these are often technical and difficult to understand by respondents – employees and self employed who have different digital skills. Due to this reason, we cognitively test the new questions.
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.
National level:
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.
National users were consulted before the 2024 questionnaire was finalised. They expressed needs for more data on the level of the digitalisation in enterprises and the usage of AI.
12.2. Relevance - User Satisfaction
European level:
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:
Direct communication with users takes place at the meetings of the Working Group on Information Society Statistics at Eurostat and the OECD and at the meetings of the statistical advisory committees group - the Statistical advisory committee for Digital Society Statistics. The members are representatives of key data users: from the public sector (Ministry of public administration), scientific sphere (University of Maribor) and they meet every 18 months. The last meeting of the panel was on 18 April 2024. More information on the content of committee is available at: Stat National Statistics.
12.3. Completeness
Detailed information is available in “ Annex I. Completeness “ - related to questionnaire, coverage, additional questions, regional data.
12.3.1. Data completeness - rate
Not requested
13.1. Accuracy - overall
Comments on reliability and representativeness of results and completeness of dataset
These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
More detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
13.2. Sampling error
For calculation of the standard error see 13.2.1.1.
13.2.1. Sampling error - indicators
Standard error (for selected indicators and breakdowns)
Precision measures related to variability due to sampling, unit non-response (the size of the subset of respondents is smaller than the size of the original sample) and other (imputation for item non-response, calibration etc.) are not (yet) required from the Member states for all indicators. Eurostat will make basic assumptions to compute these measures for all indicators produced (e.g. stratified random sampling assuming as strata the crossing of the variables “Number of employees and self-employed persons” and “Economic Activity” as it was defined in the 3 tables of section 18.1).
More detailed information is available in“ Annex III. Sample and standard error tables 2024 “ – worksheets starting with “Standard error".
13.2.1.1. Sampling error indicator calculation
Calculation of the standard error
Various methods can be used for the calculation of the standard error for an estimated proportion. The aim is to incorporate into the standard error the sampling variability but also variability due to unit non-response, item non-response (imputation), calibration etc. In case of census / take-all strata, the aim is to calculate the standard errors comprising the variability due to unit non-response and item non-response.
| a) Name and brief description of the applied estimation approach |
| See Annex'estimation approach Slovenia' |
| b) Basic formula |
| Formulas incorporated into sas surveymeans procedure. |
| c) Main reference in the literature |
| The reference in the literature can be findat this website. |
| d) How has the stratification been taken into account? |
| Stratification has been taken into account in the surveymeans procedure (statement strata). |
| e) Which strata have been considered? |
| Activity group and size class. |
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 was 0.2%.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No measurement errors.
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% | 1,794 | 100% | |
| 1. Response (questionnaires returned by the enterprise) | 1.582 |
88.2 | ||
| 1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D) | 1.582 | 88.2 |
||
| 1.2 Not used for tabulation | 3 | 0.2 | ||
| 1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.) | 3 | 0.2 | ||
| 1.2.2 Other reasons (e.g. unusable questionnaire) | ||||
| 2. Non-response (e.g. non returned mail, returned mail by post office) | 208 | 11.6 | ||
| Comments on unit response, if unit response is below 60% |
| Not applicable. |
13.3.3.1.2. Methods used for minimizing unit non-response
Enterprises were requested to fill out a web version of the questionnaire via eSTAT application. The web questionnaire included some basic controls which alerted respondents in case of inconsistent or illogical answers. The intention of the controls was to increase the quality of provided data. The selected sample included: enterprises that were already registered in the eSTAT application, which is a condition for filling out the web questionnaire and enterprises that had to register prior to completing the questionnaire. Enterprises already registered - received information/invitation via post that they were selected into the survey and that the web questionnaire is prepared and can be filled out. An e-mail was also sent to the person who was designated by the enterprise as contact person for e-reporting providing. Enterprises not yet registered received via conventional post two separate deliveries: user name with information that they were selected into the survey and instructions how to register in eSTAT and in separate delivery the password for registration. After the deadline we sent a reminder (via e-mail or regular post, if no e-mail address was available) to enterprises. To comply with the enterprise’s needs questionnaires in pdf format was prepared and published on our website. We called enterprises that did not fill out the web questionnaire and requested them to fill out the web questionnaire.
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) | |
| We used the correction factor in the weighting procedure. The correction factor was calculated by assuming two stage sampling design. | |
13.3.3.1.4. Assessment of unit non-response bias
Not applicable.
13.3.3.2. Item non-response - rate
Not applicable.
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. |
|
| 5. Re-weighting | |
| 6. Multiple imputation In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets. |
|
| 7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response. | |
| Deductive imputation was conducted only in a few cases. If we found out (during the editing process) on the websites of the enterprise that enterprise is selling via a website (is receiving reservations via other websites) ‘yes’ answer was imputed and the enterprise was contacted. The enterprise was then requested to provide the missing data. | |
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. |
|---|
| No questions with item response rate below 90%. |
13.3.4. Processing error
There were no processing errors.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed section in the Full metadata report.
14.1.1. Time lag - first result
Not applicable
14.1.2. Time lag - final result
Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce).
At national level:
Data were released on the 9th October 2024.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 4 October 2024; 1. day before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data are comparable across regions. When comparing, it is necessary to take into account geographical characteristics (e.g. the coastal area, which conditions the operation of companies in certain activities), economic centres, etc.
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.
Data from 2024 are comparable with data from 2021 (if variables were collected).
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
Users are informed about data revisions. Annually, usually in January, SURS prepares the list of statistical surveys subject to planned revision of statistical data (Slovene only). Users are also informed when the data are released.
Each data release contains information about the status of published data: they can be final or provisional data or experimental statistics. The exception is national and regional accounts data. In publishing these data, the status is marked as “no status”. After publishing provisional data, final data are always published.
As regards the SiStat Database, the status of data is stated in table titles if the data are provisional or if this is experimental statistics. If the status in not stated, the data are final. In the SiStat Database, the latest version of revised data always replaces the older.
Stat - Revision of Statistical Data.
17.2. Data revision - practice
No data were revised in 2024.
17.2.1. Data revision - average size
Not requested
18.1. Source data
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
The sampling unit was the statistical unit enterprise. Sampling design was stratified sampling (SRS within each stratum). Coordinated sampling was used. Activity group and size class was used as stratification variables.
All large enterprises and a quarter of enterprises with the highest turnover in the strata were defined as Key Units (a third of sample) and were included in the survey. Specific enterprises that were identified as key enterprises in a specific activity (e.g. enterprises with specific business model or with dominant role in e-commerce) were also included in the survey. These enterprises will have a weight of 1 and will represent only themselves in the grossed-up population.
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? | The sample was drawn in February (12 February 2024). |
|---|---|
| b) Last update of the Business register that was used for drawing the sample of enterprises for the survey: | Business Register was updated in the last week of the month of December 2023 – status on the 31 December 2023. |
| 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): | In Slovenia the data necessary for SBS statistics obtained by a 'census'. Data for SBS variables are derived from annual accounts of companies, co-operative societies, funds, sole proprietors, legal entities of private law and legal entities of public law, which are gathered by the Agency of the Republic of Slovenia for Public Legal Records and Related Services - AJPES) for the statistical purposes and prepayment of income taxes for the income realised upon the pursuit of activities and their enclosures Profit and Loss Accounts and Balance Sheet (the source of both mentioned additional data is the Tax Administration of the Republic of Slovenia). Three additional sources are also taken into account: Quarterly Questionnaire on Value Added and Gross Investment for Companies (NR-PODJ/ČL) and VAT data (the source of the latter is the Tax Administration). The scope of the SBS survey – 'census' is thus much broader in regard of number of persons employed and activities included in the SBS and ICT survey. |
| d) Description if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up): | The sampling frame that was used for drawing the sample was also used for grossing up. However, summing up the weights of units that participate in the survey does not coincide with the frame size due to the fact that the ratio estimator was used (calibration on the number of employees) and due to the fact that there were some non-eligible units in the sample (frame). |
| 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 time lag between the last update of the sampling frame and of the sampling was around one month. |
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 | 31 July 2024 |
| Micro-enterprises | Not applicable | Not applicable |
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey18.3.3. Survey vehicle – micro-enterprises
Not applicable18.3.4. Survey type
The survey was a web survey. Enterprises were asked to fill out electronic version of the questionnaire in the eSTAT application.
18.3.5. Survey participation
Mandatory18.4. Data validation
Data are validated during the transmission process according to Eurostat's standards. Data were edited with individual corrections – enterprises were contacted and requested to confirm the validity of provided data or to provide corrected or missing data.
18.5. Data compilation
Grossing-up procedures
18.5.1. Imputation - rate
Imputation was not used.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt:
Not all questions are understood by the majority of respondents. They are often not ICT specialist or do not have an overview of the ICT usage.
19.1. Documents
| Questionnaire in national language | X |
| Questionnaire in English (if available) | |
| National reports on methodology (if available) | X |
| Analysis of key results, backed up by tables and graphs in English (if available) | |
| Other Annexes |
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2024 is Commission Implementing Regulation (EU) 2023/1507 of 20 July 2023 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2024. Large part of the data collected is used to measure the progress in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age.
Furthermore, ICT data facilitate the monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme. Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, big data (data analytics) and the digital intensity index for businesses (DII) - a composite indicator reflecting the digital transformation of business. The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
| Name of data collection |
|---|
| Uporaba informacijsko-komunikacijske tehnologije in e-trgovanje v podjetjih, 2024 Usage of Information-Communication Technologies and e-commerce in enterprises, 2024 |
27 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.
Statistical unit used is enterprise. In majority of cases, enterprise equals legal unit. 14 enterprises were comprised of more than one legal unit.
Target Population
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
The whole territory of the country was included.
The reference period was current usage in 2024 and the whole year 2023.
Comments on reliability and representativeness of results and completeness of dataset
These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
More detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Grossing-up procedures
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
The sampling unit was the statistical unit enterprise. Sampling design was stratified sampling (SRS within each stratum). Coordinated sampling was used. Activity group and size class was used as stratification variables.
All large enterprises and a quarter of enterprises with the highest turnover in the strata were defined as Key Units (a third of sample) and were included in the survey. Specific enterprises that were identified as key enterprises in a specific activity (e.g. enterprises with specific business model or with dominant role in e-commerce) were also included in the survey. These enterprises will have a weight of 1 and will represent only themselves in the grossed-up population.
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 are comparable across regions. When comparing, it is necessary to take into account geographical characteristics (e.g. the coastal area, which conditions the operation of companies in certain activities), economic centres, etc.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
See detailed section in the Full metadata report.
