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.
INSEE (for the French Public Statistical System - SSP)
1.2. Contact organisation unit
Division Enquêtes thématiques et études transversales - Timbre E430
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
88 avenue Verdier CS 70058 92541 Montrouge Cedex
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
28 March 2025
2.2. Metadata last posted
28 March 2025
2.3. Metadata last update
28 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.
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“.
France (all territory, including overseas regions).
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 in the national survey.
6.1. Institutional Mandate - legal acts and other agreements
Complementary national legislation constituting the legal basis for the survey on the use of ICT in enterprises:
The survey is mandatory at national level. Non-respondent units can be fined by the litigation committee after the data collection period.
6.2. Institutional Mandate - data sharing
Data are shared on demand within the national statistical system.
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:
No cell of the table may concern less than three units.
No cell of the table may contain data for which a company represents more than 85 % of the total.
No cell of the table can be calculated from other cells.
None of those cells can be deducted from others.
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:
The tool Tau-Argus is used to identify values to flag as confidential.
8.1. Release calendar
Some indicators calculated from microdata are planned to be disseminated in December 2024.
A publication analysing results of the survey is planned to be released in April 2025.
There is a short-time release calendar on Insee website.
Data tables of indicators and a thematic analyse (analyse on 2022 data added in URL as example, analyse on 2023 data is late and planned to be published in december) are publicly disseminated on our website Insee.fr. Information on publication releases is given by Insee twitter account. Users can also subscribe to the newsletter on Insee.fr.
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:
Every survey year leads to a database publication, there is no fixed location on the Insee website for a unique database.
2023 data tables : 413 viewers during the first quarter since the publication.
2022 data analysis : 5065 viewers during the first quarter since the publication.
10.4. Dissemination format - microdata access
Microdata are disseminated via the Secure Data Access Centre (CASD). Any access has to be justified and granted (for example a study of a PHD student) by the Insee comité du secret. Some restrictions (for example relating to confidentiality) are indicated to users.
The main purpose of CASD (a public interest group) is to organize and implement secure access services for confidential data for non-profit research, study, evaluation or innovation purposes. Its mission is also to promote the technology developed to secure data access in the public and private sectors.
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: "L’enquête sur les technologies de l’information et de la communication, auprès des entreprises", Sources et méthodes, 27 April 2012 (Methodologique_TIC_Entreprises_2012).
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
At the end of the survey, a methodological documentation of every part of the survey process is published with microdata (with restricted access, see 10.4).
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 Methodological Manual provides guidelines and standards for the implementation of the surveys in the Member States. It is updated every year according to the changed contents of the model questionnaires.
The quality informations are filled in the SIMS format.
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:
Model questionnaire is translated to produce the national questionnaire. Methodological Manual guidelines are also used.
12.1. Relevance - User Needs
Once available, the model questionnaire is translated into French and discussed with national stakeholders (from administrations and civil society) and users (e.g. researchers). The discussion includes fine-tuning the translations, choosing the proper examples, deciding on the optional questions considering the overall response burden/length of the questionnaire and sometimes adding national questions.
12.2. Relevance - User Satisfaction
A satisfaction survey is punctually conducted (last from March until June 2020, results have been detailed in the 2020 quality report) on data users (users displaying ICT survey aggregated data and publications on the NSI website or being granted an access to ICT survey microdata through CASD.eu).
During the annual meeting concerning the national questionnaire, users provide feedback on the survey.
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
The SAS macro “Everest” developed at Insee is used. The standard error is calculated as sqrt(variance)*100. Variance due to sampling, to unit non-response, to calibration and winsorization is taken into account, but not variance due to item non-response. Our variance estimations are therefore under-estimated.
b) Basic formula
see annex 'std_error_basic_formula_FR'
c)Main reference in the literature
Philippe Brion / Emmanuel Gros
d)How has the stratification been taken into account?
See above
e)Which strata have been considered?
The strata considered have been the sampling strata, and the response homogeneity groups (non response has been considered as a second phase sampling).
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Over-coverage is treated during collection: -during data collection, if a unit states that it is out of scope, mostly because they stopped existing or their number of persons employed dropped under 5* persons, it is properly flagged and excluded from the data processing; -an estimate of the share of over-coverage due to ceased units (not existing anymore) is calculated and used during calibration step. Over-coverage concerns about 2% of units in the sample (excluded from final data). *threshold of 5 persons instead of 10 is used to compensate for the units that were not included in the frame because they were registered below 10 in the business register, though they would have 10 or more persons employed at the time of the survey
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
None.
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%
10200
100%
1. Response (questionnaires returned by the enterprise)
6926
68%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
6673
65%
1.2 Not used for tabulation
253
2%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
253
2%
1.2.2 Other reasons (e.g. unusable questionnaire)
0
0%
2. Non-response (e.g. non returned mail, returned mail by post office)
3274
32%
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
Monitoring the survey included the following phases: - First reminder by mail one month after having sent the first letter; - Second reminder by mail 20 days after (giving notice to answer); - No response statements 30 days after; - Fine for main non-responding units (not this first year on enterprises); A systematic phone call reminder was organised at the same time for the most important units. Reminders are sent to respondents who have logged in the response website but have not finalized and send 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)
2.3 Re-weighting through calibration/post-stratification (performed using population information) by the groups used for calibration/post-stratification
x
3. Treatment by imputation (done distinctly for each variable/item)
x
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)
First step of re-weighting is based on the GRH method (response homogeneity groups). Several characteristics were found (by logistic regression models) to explain most of the bias due to nonresponse behaviour, mainly economic activity, geographic localisation, legal situation, staff bracket, accounting information. Second step of re-weighting is calibration on known margins, using population information.
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
Not available.
13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response
2. Deductive imputation An exact value can be derived as a known function of other characteristics.
x
3. Deterministic imputation (e.g. mean/median, mean/median by class, ratio-based, regression-based, single donor nearest-neighbour) Deterministic imputation leads to estimators with no random component, that is, if the imputation were to be re-conducted, the outcome would be the same.
4. Random imputation (e.g. hot-deck, cold-deck) Random imputation leads to estimators with a random component, that is, if the imputation were re-conducted, it would have led to a different result.
x
5. Re-weighting
6. Multiple imputation In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets.
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
A two-step method is used:
First, series of deductive rules are defined and used when possible (taking into account the global consistency of the questionnaire).
Secondly, when this is not possible, groupings of units having the same response behaviour regarding a specific question (or a class of questions linked) are defined. A hot-deck procedure is implemented within the grouping taking into account the distribution of answers within this group.
For background questions, other sources may be used (turnover and number of persons employed).
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 available
Questions and items with low response rates (cut-off value is 90%) and item non-response rate.
No response rate under 90% (minimum for B8 (92,3%))
13.3.4. Processing error
There is no imputation for unit non-response (treated with reweighing).
The imputation rates for item non-response are attached (file Imputation_rates_2024.ods).
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:
December of the reference year. T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 25th September; 10 days before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data on NUTS 2 regional level were not delivered.
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.
No significant change that could impact the comparability with previous year.
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
No planned revisions to the survey data.
17.2. Data revision - practice
Should a considerable mistake be noticed after the timely data transmission, a corrected table would be produced and sent, even years after (as was done in 2018 to fix mistakes in number of person employed in 2016 data).
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:
This section includes a 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 categories related to the "possible calculation of European aggregates", and the final number of strata.
The sample is stratified by sector (divisions or groupings of divisions), reported employment and turnover (about 200 non-empty strata each year). Random sampling is used for most strata. A full enumeration is used for strata meeting one of the following criteria (take-all strata): • 500 persons employed and more • High level of turnover (“high” depends on the employment range (e.g. >=100 M€ for 10-19 persons employed strata, turnover>=110 M€ for 20-49 persons employed strata, etc.)) • Retail sale via mail order houses or via Internet (NACE 47.91A and 47.91B) (to gain precision in the measure of the e-sales amounts) Local accuracy constraints are added to improve the quality of the results for small strata. The goal is that in every breakdown, the estimated standard error shall be less than 5 percentage points. Last, the response rate per strata from the previous year is used to adjust the number of units in each stratum (increasing the size of strata with lesser response rates). Coordination with the sampling of 2022 ICT survey (only for single legal units this year due to statistical unit transition from legal unit to enterprise) is done in order to keep in 2023 half of the sample of the 2022 survey (besides the take-all strata). That way, we steady the year-to-year comparisons, especially for e-sales amounts. Negative coordination with most of the other surveys led in 2022 by Insee is done to make sure the response burden is equally shared within the enterprises (other than the enterprises belonging to a take-all strata).
C) Gross sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: NET SAMPLE)
18.1.1. Sampling design & Procedure frame
A) Description of frame population
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
November 2023
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
September 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):
Yes
d) Description if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up):
No
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.
None
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
2024 January 16th
2024 June 28th
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
Web survey (using phone, mails and emails for reminders and further information). If the enterprise doesn't want to answer using the website, self-administered mail survey (less than 1% of the respondents, either paper or email PDF).
18.3.5. Survey participation
Mandatory
18.4. Data validation
The server based validation tool by Eurostat is used. We also check for consistency during various stages of the data collection and processing.
18.5. Data compilation
Grossing-up procedures
As for the majority of surveys at INSEE, the procedure used is calibration on margins using CALMAR (SAS macro “calage sur marges”). Margins are the number of enterprises by group of economic activity, staff size and turnover in the frame population.
18.5.1. Imputation - rate
There is no imputation for unit non-response (treated with reweighing). The imputation rates for item non-response are attached (file Imputation_rates_2023.ods in 13.3.4).
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt.
19.1. Documents
Questionnaire in national language
x
Questionnaire in English (if available)
x
National reports on methodology (if available)
x
Analysis of key results, backed up by tables and graphs in English (if available)
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2024 is Commission Implementing Regulation (EU) 2023/1507 of 20 July 2023 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2024. Large part of the data collected is used to measure the progress 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
TIC 2024
28 March 2025
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access to and use of the Internet
E-commerce and e-business
ICT specialists and skills
ICT security
Artificial Intelligence.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
Enterprise.
Target Population
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
France (all territory, including overseas regions).
Reference periods defined in the model questionnaire were followed in the national survey.
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
As for the majority of surveys at INSEE, the procedure used is calibration on margins using CALMAR (SAS macro “calage sur marges”). Margins are the number of enterprises by group of economic activity, staff size and turnover in the frame population.
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:
This section includes a 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 categories related to the "possible calculation of European aggregates", and the final number of strata.
The sample is stratified by sector (divisions or groupings of divisions), reported employment and turnover (about 200 non-empty strata each year). Random sampling is used for most strata. A full enumeration is used for strata meeting one of the following criteria (take-all strata): • 500 persons employed and more • High level of turnover (“high” depends on the employment range (e.g. >=100 M€ for 10-19 persons employed strata, turnover>=110 M€ for 20-49 persons employed strata, etc.)) • Retail sale via mail order houses or via Internet (NACE 47.91A and 47.91B) (to gain precision in the measure of the e-sales amounts) Local accuracy constraints are added to improve the quality of the results for small strata. The goal is that in every breakdown, the estimated standard error shall be less than 5 percentage points. Last, the response rate per strata from the previous year is used to adjust the number of units in each stratum (increasing the size of strata with lesser response rates). Coordination with the sampling of 2022 ICT survey (only for single legal units this year due to statistical unit transition from legal unit to enterprise) is done in order to keep in 2023 half of the sample of the 2022 survey (besides the take-all strata). That way, we steady the year-to-year comparisons, especially for e-sales amounts. Negative coordination with most of the other surveys led in 2022 by Insee is done to make sure the response burden is equally shared within the enterprises (other than the enterprises belonging to a take-all strata).
C) Gross sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: NET SAMPLE)
Annual
See detailed section in the Full metadata report.
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data on NUTS 2 regional level were not delivered.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
