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.
Lāčplēša Street 1, Riga, LV-1301, Republic of Latvia
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
11 March 2025
2.2. Metadata last posted
11 March 2025
2.3. Metadata last update
11 March 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
"2024. gada pārskats par informācijas un komunikācijas tehnoloģiju izmantošanu uzņēmumos"- "ICT usage and e-commerce in enterprises 2024"
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
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. Completeness“.
All the territory of Latvia is considered by the survey.
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).
Year 2023 for the data in the modules B, some data in C and D, and year 2024 for all other data.
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:
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:
Confidentiality of the information provided by respondents is protected by the Statistics Law stipulating rights and obligations of the Central Statistical Bureau (CSB) and other state authorities producing official statistics.
From January 2016 the new Statistics Law entered into force. which is adopted by Saeima on 4 June 2015.
The policy of data protection and dissemination has been described in Section 5 of „Quality Guidelines of the CSB”.
Data are published only at a level of activity at which it is not confidential. Confidential data is not given to users.
Data are confidential if (primary criteria for determining confidentiality):
A summary score derived from one two or three statistical units (enterprises);
Share of the one statistical unit (enterprise) is 80% or more;
Share of the summary from two statistical units (enterprise) is 90% or more.
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.
Data are confidential if (primary criteria for determining confidentiality):
A summary score derived from one two or three statistical units (enterprises);
Share of the one statistical unit (enterprise) is 80% or more;
Share of the summary from two statistical units (enterprise) is 90% or more.
8.1. Release calendar
Press release was published on the CSB website on 01 November 2024
All data users are introduced to the data at the same time. The press release and data are published on the CSB website on 01 November 2024. There is calendar, were data users could see when data will be published.
Annual
10.1. Dissemination format - News release
Press release was published on the CSB website on 01 November 2024.
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:
Before 1st November 2024 the CSB prepared the main results of the ICT survey in enterprises of the year 2024 for the public CSB database.
The article of publication you will find in the web site of the CSB of Latvia.
10.4. Dissemination format - microdata access
Not applicable.
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:
The main results and methodological information about survey are available on-line in Latvian and in English languages.
Quality guidelines of the CSB is an informative document describing the CSB and the main aspects of its activity: stages, methods and organizational principles of producing the national statistics, policy of data protection and dissemination. The objective of these Guidelines is to promote the implementation of the CSB’s operational strategy by involving in this process every employee of the CSB, developing the communication with society and extending the knowledge of every interested person – respondent, data user and all society – about the activity of CSB.
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 National Statistical System of Latvia (hereinafter – NSS of Latvia) is established by statistical institutions and the Statistical Council. The managing institution of the NSS of Latvia is the Central Statistical Bureau of Latvia (hereinafter – the CSB), which implements functional subordination over other statistical institutions in the field of production of official statistics, providing methodological guidelines, by supervising the conformity of production of official statistics with the laws and regulations, and also by issuing orders that are required to produce official statistics.
To ensure that NSS of Latvia has common principles and requirements, CSB has developed the Quality Policy of the National Statistical System of Latvia and imposed total quality requirements for statistical institutions which are based on European Statistics Code of Practice.
For implementation of Quality Policy of the NSS of Latvia, the CSB has developed a Memorandum of Understanding, by which the statistical institutions confirm their commitment to implementing and promoting quality standards in their statistical institutions.
Guidelines for Implementation of European Statistics Code of Practice were developed to facilitate common perception and understanding of the requirements imposed by the Code of Practice. Based on the situation in Latvia, the Guidelines explain principles of the Code, as well as indicators and statistical terms used, moreover, requirements are supplemented with binding national legislation, explanatory information, and examples of good practice.
The Quality Policy of CSB consists of the CSB's vision, mission, core values and commitment to meet the requirements, follow good practice and ensure continuous improvement. The quality policy is designed and implemented in accordance with the CSB strategy (3-year period) and the action plan.
Statistical dissemination policy defines general principles of statistical data dissemination, availability of CSB`s products and services for data users, communication with data users, cooperation with the media, availability of individual data for scientific and educational purposes.
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:
When creating a data entry program, we write validations, that we check before the survey starts. In the questionnaire we have placed a request to be filled out by an IT specialist or at least consult with an IT specialist , if it is possible.
We compare data at the enterprise level with previous periods when necessary.
Instructions for data collectors are included in the annexes.
The Latvian Information and Communications Technology Association, Ministry of Economy, Ministry of Transport, Ministry of Environmental Protection and Regional Development. Main users are consulted regularly for their needs and are involved in the process of the development of the model questionnaires (optional questions, terminology of specific ICT variables etc.)
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.
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".
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
R software is used for calculation of standard errors with Taylor linearization method.
b) Basic formula
Please see the attachment "Basic formula".
c)Main reference in the literature
Särndal C. E., Swensson B., Wretman J. (1992). Model Assisted Survey Sampling
Guillaume Osier and Emilio Di Meglio. The linearisation approach implemented by Eurostat for the first wave of EU_SILC: what could be done from the second wave onwards? 2012.
d)How has the stratification been taken into account?
The standard error is calculated according to the sampling design.
e)Which strata have been considered?
The population is divided into two segments: one for a full survey, covering enterprises with large employee numbers, significant e-commerce activity, or consolidated companies, and the other for remaining enterprises, which are used for sampling. Further stratification is applied by NACE group and 3 enterprise size groups by number of employees.
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Over-coverage rate 1.3%
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No measurement errors 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%
3115
100%
1. Response (questionnaires returned by the enterprise)
2938
94.3%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
2898
93.0%
1.2 Not used for tabulation
40
1.3%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
40
1.3%
1.2.2 Other reasons (e.g. unusable questionnaire)
0
2. Non-response (e.g. non returned mail, returned mail by post office)
177
5.7%
Comments on unit response, if unit response is below 60%
No comments
13.3.3.1.2. Methods used for minimizing unit non-response
To minimize the unit of non-response, the following methods were used:
after the deadline of submission several e-mails, telephone calls as reminders where used;
respondents had a possibility to submit the questionnaires using our on-line submission system via Internet (in the CSB web-site) or in electronic form by e-mail;
Descriptions and definitions of the variables were included 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)
2.2 Re-weighting by identified response homogeneity groups (created using sample-level information)
x
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)
Horvitz – Tompson estimators are used.
The design weights were calculated according to the sample design, with all enterprises within the same stratum having equal design weights.
The design weights were adjusted using the data of response level in each stratum.
13.3.3.1.4. Assessment of unit non-response bias
No comments.
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
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.
No comments
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).
Validation rules of data entering programme were built to exclude of item non-response. In cases of necessities separate telephone calls were used to clarify inconsistencies.
Questions and items with low response rates (cut-off value is 90%) and item non-response rate.
Not available
13.3.4. Processing error
No processing errors were detected.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed section below.
14.1.1. Time lag - first result
See detailed section in the Full metadata report.
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:
We publish data in accordance with CSB work plan and data publication calendar, T+11.
Data were delivered to Eurostat on September 30; 5 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:
Not requested
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 sample size practically did not change, so there should be no impact on comparability over time and standard error estimates.
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
Planned revisions of statistical data are understood as:
further updates of previously published data of higher aggregation level, by adding more detailed information on the aggregation level;
revision of published data by applying seasonal adjustment method or changing the definition of reference period;
revision of published data pursuant to the changes in the methodology or classifications.
In general, statistical data is revised pursuant to the planned revision cycle and timetable: information is stored on the errors in the data sources or calculations after data publishing till the next planned data publishing date, thus following the planned revision cycle and timetable, as well as avoiding to carry out data revision too frequently.
Unplanned revisions of statistical data are such revisions, which cannot be impartially connected to the previously defined revision cycle. Necessity to carry out unplanned revisions can emerge when identifying significant errors in data sources or calculations, as well in cases if methodology or data sources are changed without being planned to. Unplanned data revisions are carried out in exceptional cases when the amount of revision according to the assessment of the CSB’s experts has a significant impact on the quality of remaining statistical data.
Revised and/or further to be revised statistical data, when adding them to publicly available databases or statistical publications, are particularly stipulated or marked. It is carried out as:
reference to the revision policy or a link to the CSB web site;
report on the amount of carried out revisions and assessment of their impact.
As the result of significant methodological changes, the revised data is published only after the introduction of the most important data users with reasons for the expected revision, methodology used in recalculations, possible impact of data revision and other related information. Informing the data users can be carried out through a press release of respective content timely placed on the CSB Web site or having discussions with data users
17.2. Data revision - practice
No data revisions over past year.
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 simple random sampling is used as sampling design. Enterprises are stratified by population segment (for full survey or for sampling), NACE groups and number of groups of employed persons (10-49, 50-249, 250+). Optimal sample size was calculated for ICT use survey. In each NACE group sample allocation is computed using iterative procedure for Neyman optimal allocation, taking into account the proportion 0.5 for each enterprise and maximum of allowed standard error 4%. Based on previous three years QR information in several NACE groups allowed standard error was 3%. Large enterprises with number of employees 250 and higher, enterprises with significant e-commerce activity and consolidated companies are sampled with sampling fraction 100%. The procedures for the coordination are applied.
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?
November 2023
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
November 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 used for the SBS. The sampling frame is made from the Statistical Business Register. The CSB has business samples co-ordination system, where all samples are negatively co-ordinated with each other.
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 was 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.
Data available: there is no full information in sampling frame about number employees in enterprises from September till December of 2023 in the time of the sampling. The average number of employees are predicted for all 2023 year (actually based on known information)
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
11 January 2024
29 Mars 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
The enterprises were able to submit the filled web-questionnaires electronically using our on-line submission system via Internet in the CSB website (94.6% of net sample) or by telephone/mail (5.4% of net sample).
18.3.5. Survey participation
Mandatory
18.4. Data validation
The CSB has validation rules in ISDAVS programme - primary data checking, primary validation of output tables, analysis of results.
18.5. Data compilation
Grossing-up procedures
Grossing-up procedures
The design weights were computed as the inverse of the inclusion probabilities.
The design weights were adjusted within strata for non-response correction.
18.5.1. Imputation - rate
No need for imputation.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt: No comments.
19.1. Documents
Questionnaire in national language
yes
Questionnaire in English (if available)
-
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
"2024. gada pārskats par informācijas un komunikācijas tehnoloģiju izmantošanu uzņēmumos"- "ICT usage and e-commerce in enterprises 2024"
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. Completeness“.
All the territory of Latvia is considered by the survey.
Year 2023 for the data in the modules B, some data in C and D, and year 2024 for all other data.
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
Grossing-up procedures
The design weights were computed as the inverse of the inclusion probabilities.
The design weights were adjusted within strata for non-response correction.
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 simple random sampling is used as sampling design. Enterprises are stratified by population segment (for full survey or for sampling), NACE groups and number of groups of employed persons (10-49, 50-249, 250+). Optimal sample size was calculated for ICT use survey. In each NACE group sample allocation is computed using iterative procedure for Neyman optimal allocation, taking into account the proportion 0.5 for each enterprise and maximum of allowed standard error 4%. Based on previous three years QR information in several NACE groups allowed standard error was 3%. Large enterprises with number of employees 250 and higher, enterprises with significant e-commerce activity and consolidated companies are sampled with sampling fraction 100%. The procedures for the coordination are applied.
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 below.
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Not requested
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
