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.
Research, Development and Information Society Statistics Section
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Czech Statistical Office
Na padesátém 81
Prague 10
10082
The Czech Republic
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
13 February 2025
2.2. Metadata last posted
13 February 2025
2.3. Metadata last update
13 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
Šetření o využívání informačních a komunikačních technologií a elektronickém obchodování v podnikatelském sektoru
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?
Not applicable.
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: Enterprise
The statistical unit enterprise has been implemented to the national business register and consequently to all relevant business statistics including SBS since 2001. The implementation, in conformity with Council Regulation No. 696/93, is based on an assumption that legal units represent a good approximation of enterprise. In addition, we continuously evaluate all methodological aspects related to the definition of the statistical unit "enterprise" and, if necessary, we are ready to take all necessary steps to maintain a consistently high relevance of statistical outputs.
3.6. Statistical population
Target Population
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
3.6.1. Coverage of micro-enterprises
No
3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable.
3.7. Reference area
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
All territories of the country were covered.
3.8. Coverage - Time
Years 2023 and 2024.
3.9. Base period
Not applicable
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Reference periods defined in the model questionnaire were followed. Where not specified respondents should consider as reference their current situation in 2024 when they are filling the questionnaire (e.g. February 2024). Year 2023 for the value or % of sales data and 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:
Statistical surveys in the Czech Republic are in compliance with Act No. 89/1995 Coll., on the State Statistical Service, as amended, conducted by the Czech Statistical Office. An overview of statistical surveys is published every year in the form of a Decree on the Programme of Statistical Surveys.
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:
Minimum number of enterprises for breakdowns: unreliable outcomes of the survey are when we have answers from too few enterprises for particular combination of variable and breakdown. That means the number of enterprises in a given group is null or smaller than 5.
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:
We use "u" flag (unreliable) when we have answers from too few enterprises for particular combination of variable and breakdown. That means the number of enterprises in a given group is null or smaller than 5.
Rules for confidentiality treatment of both aggregate and microdata (for scientific purposes) are defined in special internal guidelines.
Moreover, special general guideline by the CZSO is available for other national authorities (ONAs) as a part of methodological guidelines for coordination of the Czech statistical system within scope of official statistics.
Standard frequency and dominance rules are used for aggregate outputs. The combination and rules varies among different statical domains (business statistics, households surveys, demographic statistics).
For business statistics, a combination of frequency and dominance rule is applied. The values of parameters are not publicly available to make quess the range for suppressed cells.
The primary confidential aggregate can be publish, if the CZSO gets written approval of all units in the aggregate.
The secondary confidentiality treatment is done by SW Tau-Argus and the outputs can be further manually modified by the subject matter statisticians
Secondary confidentiality treatment is almost solely by suppression, in some rare cases by cell aggregation.
For micro-level outputs:
Describe the procedures that are used in protecting confidentiality.
The approach for microdata files both in business statistics is as follows:
+ no direct identifiers (ID, address, name)
+ very sensitive variables are excluded from the microdata file,
+ descriptive variables (like nace, size groups) can be grouped,
+ perturbation of variables is not done.
In general, if the Eurostat provides the methodology, we apply it, only if necessary. The CZSO policy is to provide microdata as least modified, as possible.
We are not aware of any divergences from the best practises within the European Statistical System or OECD.
No checking for residual disclosure is carried out.
8.1. Release calendar
The publication of the ICT ENT survey is scheduled to be released on 21st January 2025. This date is published in the product catalogue of the Czech Statistical Office.
The publication can be found in the Catalogue of Products of the CZSO and has the code 062005-24. It will be published only in Czech at 21st January 2025.
8.3. Release policy - user access
Statistical data are issued in various forms. The CZSO has for example:
the Catalogue of products – a comprehensive list of all outputs of the CZSO. Besides publications, you can find there all time series, revisions, analyses, News Releases, and data sets;
All products issued by the CZSO are published on dates determined in advance, usually at 9 a.m.
ICT ENT survey website part (also in english): ICT in enterprises | Statistics(the website is going to be updated on 30 October 2024, a press release is goisng to be published (in Czech only) and data (tables, figures, product catalogue) from the last survey in 2024 is going to be updated)
Annual
10.1. Dissemination format - News release
At the end of October 2024 a press release was issued (in Czech only). Issued were also tables with basic indicators + time series of the main indicators from the ICT ENT survey (survey data 2024)
Along with the publication, we also publish tables with international comparisons of the main indicators - the source is Eurostat's comprehensive database. We also publish cartograms with selected key indicators. This is again a summary of the main indicators in international comparison (EU27 countries): The above mentioned tables in xlsx format can be found at this link (only in Czech): CSU website in the section "data a časové řady" under the displayed table.
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.
Data up to survey year 2024 are currently available in the public CZSO database. Indicators from survey year 2024 were released together with the publication on 21st January 2025: tables in xlsx format can be found at CSU website in the section "data a časové řady" under the displayed table. Tables available in Czech only.
Number of accesses to on-line database is not available.
10.4. Dissemination format - microdata access
Micro-data from ICT ENT surveys are not disseminated, not publicly available.
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.
Detailed methodological information is available (but only in Czech language) in the "Metodika" section of the website in a PDF file entitled "Podrobné metodické informace k šetření v roce 2024" (CSU website).
Quality Indicators are compiled in accordance with current version of ESS Handbook for Quality Reports.
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:
CZSO use Eurostat's European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises with provided guidelines and standards for the implementation of the ICT survey. The ICT survey is carried out and prepared in line with standards used in CZSO for enterprise surveys and in line with ICT surveys in previous years.
General quality assurance framework of the Czech Statistical Office can be found at the following link (in english): Quality and innovation | Statistics
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:
Eurostat model questionnaire and European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises were used.
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.
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
The sampling design, sample size in both strata and total sample sizes were set to guarantee the required precision by the Eurostat. The calculations were carried using approximate standard errors for the GREG estimates. The sample is updated yearly to reflect changes in the strata size between years and fluctuations of standard errors in the previous year.
b) Basic formula
see annex "Basic formula"
c)Main reference in the literature
Carl-Erik Sarndal, Model Assisted Survey Sampling
d)How has the stratification been taken into account?
Stratification is made according to the regulation of the Eurostat
e)Which strata have been considered?
Stratified random sampling for enterprises with 10-249 and a census for 250 or more persons employed with respect to Business Register. A census has been also applied for enterprises with large share of e-commerce or with high turnover according to its size.
For stratification have been used:
1/CZ NACE groups (classification system NACE rev.2 2008),
2/number of persons employed according to the Business Register,
Alternatively 3/ value of turnover according to administrative data.
The sample has been designed with no reference to any other survey.
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Over-coverage units were identified during data collection and appropriately coded. They were eliminated from the central set of data and the weights were corrected. Inappropriate units are included in the list although they do not belong there according to their activities. During the survey, the level of inappropriateness also takes account of the units that were appropriate when the selection for the survey was made, but then changed their activity or stopped operating during the year. Over-coverage rate was computed as the proportion of units from the sample which do not belong to the target population to the overall sample size.
Over-coverage rate for year 2023 is 0,07 % (unweighted data) and 0,12 % (weighted data).
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
A special training is organized for staff that process the questionnaires and transfer data from printed questionnaires to databases (data entry). When the respondent fills inconsistencies into the online questionnaire (e.g. failure to comply with the filter question, year-to-year inconsistency in answers), he is alerted to this error(s) by interactive controls (checks).
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%
8126
100%
1. Response (questionnaires returned by the enterprise)
7403
91,10 %
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
7391
90,95 %
1.2 Not used for tabulation
10
0,12 %
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
9
0,11 %
1.2.2 Other reasons (e.g. unusable questionnaire)
1
0,01 %
2. Non-response (e.g. non returned mail, returned mail by post office)
723
8,90 %
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
In order to reduce unit non-response two reminders with attached questionnaire were sent by e-mail (data box) to any enterprise that didn’t return filled questionnaire by the asked date. Later a telephone reminder was carried out in order to ensure responses from enterprises of particular importance for the quality of the results of the survey (generally for enterprises within NACE /size groups in which the number of responses was found to be too low).
We sent to all respondents together with the questionnaire also enclosure with the main results from previous year’s survey and answers on frequently asked questions. We considered this is the way to motivate the respondents to fill in the 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)
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
Item non-response is not an issue (no imputations made for item non-response) except of imputation of some variables (persons employed, turnover) not be available in SBS database.
13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response
x
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.
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
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
Processing error is reduced by many measures.
For each statistical form, set of logical check and consistency rules are defined.
They are applied for online questionnaires, so respondents can see message errors (inconsistencies) before submitting the questionnaire.
The more detailed sets of these rules are applied to data by coresponsible for data capturing. If there are some serious errors, respondents are contacted by phone or e-mail. Key variables are also evaluated in time series for individual respondents.
For each questionnaire, the global quality score (EQA) is computed automatically. If the score is below 4, the questionnaire is treated as unit non-response. In these cases, further contacts of respondent are carried out to improve the quality to satisfactory level.
No quantitative measures are computed.
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:
The publication of the ICT ENT survey is scheduled to be released on 21st January 2025. This date is published in the product catalogue of the Czech Statistical Office.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 27 September 2024; 5 working 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 on NUTS 2 regional level were not delivered from the 2024 survey.
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 changes we made in the national questionnaire are based only on the annual changes in the model questionnaire.
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
In general the data revisions are treated in the CZSO publicly available key document CZSO Data Revision Policy - As of April 2020 (see Quality management strategies and policies | Statistics). There are no ordinary revisions planned for the ICT ENT survey (see Chapter 2.19 of the CZSO Data Revision Policy - As of April 2020): Politika revizí_ČSÚ_2020_en.indd
"Final data from the ICT 5-01 survey are published usually in January of the following year. Data as at these dates are considered final and are not revised by ordinary revisions; nevertheless, an occasional revision may be performed." The user would be informed on an occasional revision in advance with explanation of its reason in the Catalogues of Products and on the CZSO website.
17.2. Data revision - practice
Online questionnaires (computer assisted) includes all necessary consistency checks (controls). We set approximately 200 of consistency checks (controls) in the questionnaire every survey year. Inconsistencies in controls notify junior statisticians of necessity to check answers. Phone calls are used for validation of the data (corrections) and quality improvement if necessary. Reminders are sent out during May and June/July to obtain higher response in general (but especially in low response strata and important enterprises with annual large share of e-commerce or with great turnover according to its size). Reminders are sent via data mailboxes and some of them are made by phone.
Validated data are saved into database. Time series of different shares and percentages on microdata level are analysed. Abrupt changes of individual data are verified and respondents are contacted.
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:
Stratified random sampling for enterprises with 10 - 249 and census for 250 and more employees with respect to Business Register. An intent sampling was used for enterprises with large share of e-commerce or with huge turnover according to its size.
Number of enterprises and number of employees was used for stratification. The sample was designed with no reference to any other survey. Sample size was designed to enable accurate, reliable and representative results.
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)
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
31 December 2023
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
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):
The frame population is the same as the one for the Structural Business Survey (SBS). Different latest snapshots on the frame population are used during the statistical process.
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):
--
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 all background information is available for all enterprises in the sample; in this case imputation was used for missing data. The number of employees in Business Register (BR) is filled up from administrative sources on the number of the insured.
B) Frame population distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: FRAME POPULATION)
Date of reception of the last questionnaire treated
General survey
09 January 2024
26 September 2024
Micro-enterprises
Not applicable
Not applicable
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
Not applicable
18.3.4. Survey type
The survey is a combination of computer assisted filling (web questionnaires or PDF questionnaires) in and paper questionnaires. There is a possibility for enterprises to fill in PDF format of questionnaire or web (online) questionnaire available to fill in the special application especially developed for the purpose of this survey. Respondents receive instructions (via a message in their data box) describing how to get the online questionnaire (computer assisted) or have an opportunity to download the online questionnaire from the CZSO website. We send paper questionnaires to enterprises that do not own data boxes (approximately 500 enterprises a year), paper questionnaires are sent and returned by post.
18.3.5. Survey participation
Mandatory
18.4. Data validation
Before data are transmitted we saved them into the database. Time series of different shares and percentages on microdata level are analysed. Abrupt changes of individual data are verified and respondents are contacted.
We used the validation tool provided by Eurostat - we used the EDAMIS "Acceptance" validation environment, which provided feedback reports, and after we removed the errors, we sent the data in the required SDMX format to the EDAMIS "Production" environment.
18.5. Data compilation
Grossing-up procedures
According to results from previous years we expect to collect approx. 7000 questionnaires for enterprises with 10 or more persons employed (=Net sample).
Results are then reweighted on whole population of enterprises with 10 or more persons employed. The estimates are made by re-weighting method. Generalized Regression Estimators (GREG) using model with three auxiliary variables and without intercept is applied.
Initial weight IWi for each sample unit i from hth stratum
IWi =IWh= Nh/nh ,
where Nh = number of unit of hth stratum BR
nh = number of unit of hth stratum sample.
Let mh = number of responding units in hth stratum sample.
Because of non-response, IWi is recalculated on RWi:
for each sample response unit i from hth stratum
RWi=IWi * nh/mh = (Nh/nh)nh/mh,
It holds RWi=0 for each sample non-response unit i.
Finally, we use auxiliary information from BR about number of social security policyholders, number of persons employed and turnover according to administrative data and number of enterprises to recalculated RWi by calibration method (GREG – Generalized Regression Estimators). Calibration is applied in three stages to weight in strata given by combination of CZ NACE and size class. Weights from one stage are further recalculated in another stages. Moreover, in each stage constraints on the weight change is imposed to guarantee that resulting weight is not to be smaller than 1. In the first stage starting weights are calibrated to preserve number of enterprises and number of social policyholders in strata. In the second stage starting weights are calibrated to preserve number of enterprises and number of persons employed in strata. In the third (final) stage starting weights are calibrated to preserve number of enterprises and sum of turnover in strata.
Note1: The mentioned treatment doesn’t ensure equality of all weight in a given frame stratum.
Note2: All kind of recalculation are pursued with respect to h, that are defined according to NACE and SIZE of BR (not surveyed one).
Note3: We have in our file including enterprises with real number of employees < 5. These units weren’t excluded from treatment because ones represent possible overcoverage of our frame opposite the BR. The number of persons employed in BR is updated by number of person paying social insurance that is always higher than real number persons employed. For this reason we include very small units in fact because these are higher in BR.
18.5.1. Imputation - rate
Imputation was not used.
This issue is not relevant, no imputation procedures are applied, only complete questionnaires are used for estimation of aggregates.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt:
FYI: The gross sample table has been updated for the Quality report.
19.1. Documents
Questionnaire in national language
x
Questionnaire in English (if available)
x
National reports on methodology (if available)
Analysis of key results, backed up by tables and graphs in English (if available)
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2024 is Commission Implementing Regulation (EU) 2023/1507 of 20 July 2023 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2024. Large part of the data collected is used to measure the progress in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age.
Furthermore, ICT data facilitate the monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme. Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, big data (data analytics) and the digital intensity index for businesses (DII) - a composite indicator reflecting the digital transformation of business. The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
Šetření o využívání informačních a komunikačních technologií a elektronickém obchodování v podnikatelském sektoru
13 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: Enterprise
The statistical unit enterprise has been implemented to the national business register and consequently to all relevant business statistics including SBS since 2001. The implementation, in conformity with Council Regulation No. 696/93, is based on an assumption that legal units represent a good approximation of enterprise. In addition, we continuously evaluate all methodological aspects related to the definition of the statistical unit "enterprise" and, if necessary, we are ready to take all necessary steps to maintain a consistently high relevance of statistical outputs.
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“.
All territories of the country were covered.
Reference periods defined in the model questionnaire were followed. Where not specified respondents should consider as reference their current situation in 2024 when they are filling the questionnaire (e.g. February 2024). Year 2023 for the value or % of sales data and 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).
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
According to results from previous years we expect to collect approx. 7000 questionnaires for enterprises with 10 or more persons employed (=Net sample).
Results are then reweighted on whole population of enterprises with 10 or more persons employed. The estimates are made by re-weighting method. Generalized Regression Estimators (GREG) using model with three auxiliary variables and without intercept is applied.
Initial weight IWi for each sample unit i from hth stratum
IWi =IWh= Nh/nh ,
where Nh = number of unit of hth stratum BR
nh = number of unit of hth stratum sample.
Let mh = number of responding units in hth stratum sample.
Because of non-response, IWi is recalculated on RWi:
for each sample response unit i from hth stratum
RWi=IWi * nh/mh = (Nh/nh)nh/mh,
It holds RWi=0 for each sample non-response unit i.
Finally, we use auxiliary information from BR about number of social security policyholders, number of persons employed and turnover according to administrative data and number of enterprises to recalculated RWi by calibration method (GREG – Generalized Regression Estimators). Calibration is applied in three stages to weight in strata given by combination of CZ NACE and size class. Weights from one stage are further recalculated in another stages. Moreover, in each stage constraints on the weight change is imposed to guarantee that resulting weight is not to be smaller than 1. In the first stage starting weights are calibrated to preserve number of enterprises and number of social policyholders in strata. In the second stage starting weights are calibrated to preserve number of enterprises and number of persons employed in strata. In the third (final) stage starting weights are calibrated to preserve number of enterprises and sum of turnover in strata.
Note1: The mentioned treatment doesn’t ensure equality of all weight in a given frame stratum.
Note2: All kind of recalculation are pursued with respect to h, that are defined according to NACE and SIZE of BR (not surveyed one).
Note3: We have in our file including enterprises with real number of employees < 5. These units weren’t excluded from treatment because ones represent possible overcoverage of our frame opposite the BR. The number of persons employed in BR is updated by number of person paying social insurance that is always higher than real number persons employed. For this reason we include very small units in fact because these are higher in BR.
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:
Stratified random sampling for enterprises with 10 - 249 and census for 250 and more employees with respect to Business Register. An intent sampling was used for enterprises with large share of e-commerce or with huge turnover according to its size.
Number of enterprises and number of employees was used for stratification. The sample was designed with no reference to any other survey. Sample size was designed to enable accurate, reliable and representative results.
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)
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 on NUTS 2 regional level were not delivered from the 2024 survey.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
