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.
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
Encuesta sobre el uso de TIC y comercio electrónico en las empresas 2022-2023 (Survey on ICT usage and e-commerce in enterprises 2023, Spain)
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
Yes
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?
All activities were covered.
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
The statistical unit is enterprise but the sampling and respondent unit is legal unit.
We consolidate data from legal units to enterprise using Eurostat rules.
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
Yes
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.
[0-2][3-9]
3.7. Reference area
All national territory was considered.
Data for a specific set of variables were delivered on NUTS 2 regional level.
3.8. Coverage - Time
Years 2023 and 2024.
3.9. Base period
Not applicable
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
The reference period is:
2023 for the % of sales data and where specified
Where not specified respondents should consider as reference their current situation (first quarter of 2024)
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 Law No. 12/1989 "Public Statistical Function" of May 9, 1989, (BOE website) and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2021-2024, approved by Royal Decree 1110/2020, of 15 December, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2021-2024 (BOE website).
6.2. Institutional Mandate - data sharing
At national level:
The exchanges of information needed to elaborate statistics between the INE and the rest of the State statistical offices (Ministerial Departments, independent bodies and administrative bodies depending on the State General Administration), or between these offices and the Autonomic statistical offices, are regulated in the LFEP (Law of the Public Statistic Function). This law also regulates the mechanisms of statistical coordination, and concludes cooperation agreements between the different offices when necessary.
There are two types of agreement for the data distribution:
A. Framework Agreements between the INE and the statistics institutions of the Autonomous Communities.
Via said agreements, it is established that the INE will send the non-anonymised microdata file for their territorial area to those Autonomous Communities with which it has an agreement. Currently, this is sent to all of the Autonomous Communities, except Castilla y León, Ceuta, Melilla and País Vasco.
B. Agreements between the INE and other public institutions.
The agreement currently in force is the Ministry for Digital Transformation and Public Administration, through of ONTSI.
At european level:
Implementation Act:
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, pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council.
7.1. Confidentiality - policy
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
At national level:
The Statistical Law No. 12/1989 specifies that the INE cannot publish, or make otherwise available, individual data or statistics that would enable the identification of data for any individual person or entity. Regulation (EC) No 223/2009 on European statistics 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
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:
INE provides information on the protection of confidentiality at all stages of the statistical process: INE questionnaires for the operations in the national statistical plan include a legal clause protecting data under statistical confidentiality. Notices prior to data collection announcing a statistical operation notify respondents that data are subject to statistical confidentiality at all stages. For data processing, INE employees have available the INE data protection handbook, which specifies the steps that should be taken at each stage of processing to ensure reporting units' individual data are protected. The microdata files provided to users are anonymised.
This statistical operation follows all of the guidelines referring to meeting and safeguarding statistical secrecy.
8.1. Release calendar
The INE Advance Release Calendar shows the precise release dates for the coming year is disseminated in the last quarter of each year.
This publication was released 21 October 2024
8.2. Release calendar access
The calendar is disseminated on the INEs Internet website (Publications Calendar) INE website calendario.
8.3. Release policy - user access
The data are released simultaneously according to the advance release calendar to all interested parties by issuing the press release. At the same time, the data are posted on the INE's Internet website (INE website) almost immediately after the press release is issued. Also some predefined tailor-made requests are sent to registered users. Some users could receive partial information under embargo as it is publicly described in the European Statistics Code of Practice
Annual
10.1. Dissemination format - News release
National dissemination of results:
INE publishes a press release at 11:00 AM the day the figures are published (21 Ocotber 2024) INE website.
10.2. Dissemination format - Publications
The results of this statistical operation are disseminated in a press release published on the INE website. Press release and the detailed results may be viewed at the following INE website Estadistica.
Some results are also included in general publications, such as the Statistical Yearbook, INE Figures, etc.
10.3. Dissemination format - online database
See detailed section 10.3.1.
10.3.1. Data tables - consultations
Results for selected variables collected in the framework of this survey are available for all participating countries on Digital economy and society of Eurostat website.
At national level:
The data from this statistical operation may be viewed in INEbase, within the "INEbase /Science and Technology / New information and communication technologies" section in INE website. More specifically, it may be viewed at the following INE website. The website with the database may be accessed. The structure of said database is as follows:
1. National results.
Enterprises with 10 or more employees: E-commerce in 2023 for group of economic activity (except CNAE 56, 64-66 and 95.1) and size of the enterprise;
Enterprises with 10 or more employees: ICT usage in (first quarter 2024) for group of economic activity (except CNAE 56, 64-66 and 95.1) and size of the enterprise;
Enterprises with less than 10 employees: E-commerce in 2023;
Enterprises with less than 10 employees: ICT usage in the enterprises (first quarter of 2024).
2. Results by Autonomous City or Community.
ICT usage in the enterprises with 10 or more employees (first quarter of 2024) by group of economic activity (except CNAE 56, 64-66 and 95.1) and size of the enterprise;
ICT usage in the enterprises with less than 10 employees (first quarter of 2024).
3. Sampling errors.
10.4. Dissemination format - microdata access
Any researcher who wants access to the microdata must sign an agreement with the National Statistics institute, for access for statistical purposes, by the research personnel, to the confidential data from the INE. The agreement describes the project, and the need to access said microdata, specifies the period during which the research time would work in the INE, provides the name of the research team and establishes the agreement clauses, including the statistical confidentiality clause.
This access is made through the so-called Secure Places, which consist of computers where said databases are available, and which verify a series of physical and technological provisions to protect the security and integrity of the statistical databases, which in practice implies that strict protocols are applied to those external users who wish to access the microdata for research purposes.
Also Statistics Institutes of the Autonomous Communities and Red.es have microdata access. These mailings microdata files are regulated via Framework Agreements with the INE. These are provided the information from the statistics units with headquarters in any of the provinces comprising them.
There are current agreements with all of the Autonomous Communities, except Castilla y León, Ceuta, Melilla and País Vasco.
The microdata files are not sent to the remaining private institutions. Nevertheless, tailor-made requests may be made of specific tabulations from said microdata file. Said tabulations are performed by the responsible department, and sent to the user, once the quote is accepted, in the case of there not being a partnership agreement between the INE and the requesting entity.
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 methodological manual describing the features of this statistical operation may be viewed at the following INE website.
The questionnaires from the previous editions of this statistical operation may also be viewed at this INE website.
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
INE publishes a Methodological Report at the same time that the publication is released in the following INE website.
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:
Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 16 principles, gathered in three areas: Institutional Environment, Statistical Processes and Statistical Output. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, Self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation.
The compilation process of this statistical operation has established controls in the information collection process to detect and correct errors, for the purpose of guaranteeing their quality. Said controls are implemented in the computer application that enables respondents to fill in the questionnaire online. This means guarantees that the information arrives, at an individual level, without response coherence errors or magnitude aggregation errors. In addition, once the information is received in the unit responsible for this statistical operation, the data from the specific respondent units is compared with the item of data from the stratum to which they belong.
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:
Main strengths:
. Timing: the survey is collected in the first quarter of the reference year and published in October of that same year, being one of the fastest structural surveys of the INE in this regard.
. Response rate: since the survey is collected through the Iria web portal, the response rate is usually very high. This allows us to have very low sampling errors in general, which affects the accuracy of the data.
. Flexibility: This survey changes a lot from year to year as technologies change. This survey is designed to collect all the technologies that are contemplated by Eurostat, as well as the technologies that are suggested to us by other national agents.
Qualitative improvements:
. The strong point about flexibility creates a problem: the questionnaire can be too long if you try to cover too many technologies in the questionnaire. It is difficult to balance the number of questions to ask, therefore every year it is necessary to decide on which technologies to include and discard in the questionnaire, in consensus with all the agents involved (Eurostat, national agents, INE's own needs ...)
. Complicated terms: many terms in the questionnaire are very complicated for informants in general, so it is always tried to include clarifications, definitions, annexes ... within the questionnaire to clarify these terms.
12.1. Relevance - User Needs
National level :
Main users are Regional Statistical Institute of Galicia and ONTSI. They include questions in the national questionnaire to get specific indicators. On the other hand, this statistical operation provides relevant information on the Information Society for public/private entities according to requests as they are made.
12.2. Relevance - User Satisfaction
National level:
The INE has carried out general user satisfaction surveys in 2007, 2010, 2013, 2016 and 2019 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...
On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date. (INE website)
The specific needs of users are borne in mind, so long as methodological revisions of the survey are carried out. In this way, and based on the regulation governing it, the content thereof is adapted as much as possible to the specific requirements of its users, increasing their satisfaction levels.
In the User Satisfaction Surveys conducted to date, it is possible to view the evaluation of the sector Science and Technology in which this statistical operation is centred, which can help direct us with regard to user opinions of it.
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 standard errors have been calculated for the statistical unit enterprise (enterprise as defined in European Regulation 696/93) with the Raulin expression for calculate the standard error in a domain.
b) Basic formula
See document 13.2.1.1 Raulin ES.doc
c)Main reference in the literature
Criteria for the Quality Measurement in Statistical Business. Statistics-explanatory document - E. Raulin (eurostat-D2-31/03/99)
d)How has the stratification been taken into account?
Sum of the variance estimator for each stratum
e)Which strata have been considered?
Strata have been built by activity, region and size class
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
A2 (enterprises with less than 10 persons employed)=5.1%
A2 (enterprises with 10 or more persons employed)= 1.5%
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)
9,781
100%
15,219
100%
1. Response (questionnaires returned by the enterprise)
7,695
78.7%
14,498
95.3%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
6,787
69.4%
13,477
88.6%
1.2 Not used for tabulation
908
9.3%
1,021
6.7%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
503
5.1%
231
1.5%
1.2.2 Other reasons (e.g. unusable questionnaire)
405
4.1%
790
5.2%
2. Non-response (e.g. non returned mail, returned mail by post office)
2,086
21.3%
721
4.7%
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
If all Legal Units of the sample belonging to a SUE are missing, the LeU and SUE are represented by weight factors.
If a SUE has any LeU in the sample and at least one LeU has responded, the other LeUs of the SUE are imputed.
Procedure for imputation:
There are two cases:
Legal Unit is in the sample: we impute it with closets neighbour techniques
Legal Unit is not in the sample:
We make a cluster with LeUs with the same NUTS2, size main activity and type (non-market producer7 market producer) of LeU.
We take a random LeU in the same cluster the LeU to impute: qualitative variables are imputed with their values and quantitative variables are imputed with the value of the median or mean value if there is any rule between values (e.g.: B2C+B2B+B2G=100%).
If there is not LeU in the cluster we need, we delete type of LeU condition; if there ie not LeU, discard NUTS2; if ther is not LeU, we eliminate size condition.
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)
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)
Once the data collection phase ends, several enterprises might have changed any of their stratification characteristics. Strata modifications and unit non-response treatment make necessary to recalculate the weighting factors, following the method described in the document Grossing up procedure ES
For each questionnaire used in the tabulation, each non-response item is imputed, so A5=A7
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.
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.
x
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
x
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.
Item-non response:
Qualitative variable. Steps:
Contact with the response unit;
Seek consistency in questionnaire;
Value of previous year for legal unit;
Most used value in stratum.
Quantitative variable. Steps:
Contact with the response unit;
Value of previous year for legal unit;
Seek other sources like Tax Agency, websites,...
Median or average of stratum.
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.
Not applicable
13.3.4. Processing error
No processing errors detected
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed section in the Full metadata report.
14.1.1. Time lag - first result
Not applicable
14.1.2. Time lag - final result
Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce).
At national level:
The results of this statistical operation are published at the end of the third quarter of the year in which the information is collected.
According to the above, the punctuality indicator value of the statistical operations that measures the period of time between the end of the reference period (31 March) and the publication date of the final results is 6,7 months. There are no preview results in this statistical operation, and therefore, the publication of said results is always finals.
14.2. Punctuality
See detailed section below.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 01 Ocotber 2024; 4 days before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
See detailed section in the Full metadata report.
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.
Length of the comparable time series under the Statistical Unit Enterprise approach: CC2=3, because it is the third year we publish under the Statistical Unit Enterprise approach
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
The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (website).
This general policy sets the criteria that the different type of revisions should follow: routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.
Advanced results are not published in this statistical operation. The results published are final, and not subject to any revision.
17.2. Data revision - practice
Advanced results are not published in this statistical operation. The results published are final, and not subject to any revision.
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:
According to the frame population (extracted from the DIRCE), the legal units are stratified by crossing the following variables: size, economic activity and location.
In every stratum, a systematic selection randomly started is executed, sorting out the legal units by size and location.
The categories of the variables used to stratify are: size:
[0 to 2] and [3 to 9] employees and self-employed persons
[10 to 19], [20 to 49], [50 to 99], [100 to 199],[200 to 499] and 500 or more (for legal units with 10 or more employees and self-employed persons
Main activity:
For legal units with less than 10 employees and self-employed persons the aggregations of NACE classification is as followed:
10 -39
41 -43
45
46
47
49 -53
55
56
58 -63
68 + 69 -75+ 77+78+80-82
79+95.1
For legal units with 10 or more employees and self-employed persons the aggregations of NACE classification as followed:
10 - 18
19 - 23
24 - 25
26 - 33
35 - 39
41 - 43
45
46
47
49 -53
55
56
58 -63
68
69 -75
77-82
26.1 - 26.4, 26.8, 46.5, 58.2, 61, 62, 63.1, 95.1
Region: All Spanish regions (19) are covered.
The total number of initial strata for the general questionnaire is 1.938 (17*6*19), including empty strata for legal units with 10 or more employees and self-employed persons and 418 (11*2*19) for legal units with less than 10 employees and self-employed persons (following NACE rev.2).
The survey is carried out alone.
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?
October 2023
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
October 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 of ICT survey is the same than INE uses in SBS; DIRCE (Central Businesses Directory). This directory collects all Spanish enterprises and their information such as identity data, location, main activity, number of employees, etc.
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):
DIRCE is the frame population used in all stages of the statistical process. But we adjust the population with active non-response, deaths and strata jumping when we calculate the weights.
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.
In October 2023, DIRCE has the 2022 final population. It is updated every year and covers all regions at national level and all business activities (NACE 2008 rev.2). Regions, business activities and size are included in the sampling frame.
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
January 2024
March 2024
Micro-enterprises
January 2024
March 2024
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
The collection of micro-enterprises was integrated with the general survey
18.3.4. Survey type
We use a web questionnaire to collect the data. If there are mistakes or a large difference between the time series in the final questionnaire, an agent contacts with the respondents by telephone to request the right information. Moreover, enterprises can call to a free-charge telephone line to get clarification of the questions and to be helped with the filling out of the questionnaire. In all cases there is a system of reminders, including letters and phone calls. The survey is mandatory and enterprises can be penalized in case of no response.
18.3.5. Survey participation
Mandatory
18.4. Data validation
The information collected through the questionnaire filled in online guarantees that there are no consistency errors in said information. This is because it automatically notifies the respondent of the existence of a possible order that must be corrected prior to closing the application and sending the questionnaire.
Once the data is received in the collection units, it is supervised in order to detect possible magnitude errors. Once detected, the interviewer notifies the respondent unit in order to verify, or if necessary, to correct the figure provided.
Subsequently, the unit responsible for the statistical operation also carries out a final validation process, which consists of comparing information aggregate with that of previous years.
18.5. Data compilation
Grossing-up procedures
For the elaboration of the ICT SURVEY under the 'Statistical enterprise' approach, a method has been developed that is based on the following steps, each of which is described in more detail in the ICT SURVEY Methodology document available on the INE website together to the statistical results of the operation.
Delineation of the Statistical enterprises that operate in business groups through the so-called Profiling methodology and classification of the Legal Units that compose them (see details in section 3.3 of the ICT SURVEY Methodology )
Adequacy of the sample design and the information collection phase (see details in sections 5 and 6 of the ICT SURVEY Methodology ).
Aggregation of the Legal Units that make up each Sample Statistical enterprise and study of the combinations of typologies of said Legal Units (see details in section 7.2.1 of the ICT SURVEY Methodology ).
Consolidation for sample Statistical enterprises formed by more than one Legal Unit and containing relationships between them. For these enterprises, the flows between their Legal Units are identified to proceed with the cancellation of intra-enterprise transactions (see details in section 7.2.2 of the ICT Survey Methodology ).
Construction of the complete statistics, based on Statistical enterprises, whether they are independent Legal Units or enterprises of business groups (see details in section 7.2.3 of the ICT SURVEY Methodology ).
The essential idea is that if the Legal Units of a Statistical enterprise serve, exclusively or mainly, other Legal Units of the same enterprise (for example, because they sell products under a vertical integration of the production process or provide services as an auxiliary relationship) , said servile Legal Units must be combined with the others to which they support to form the authentic statistical unit "enterprise", therefore having to combine and consolidate the corresponding variables.
18.5.1. Imputation - rate
A7 (% of e-commerce sales)=0.28%.
A7 (% of the total number of persons employed who have access to the Internet for business purposes)=0%.
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)
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
Encuesta sobre el uso de TIC y comercio electrónico en las empresas 2022-2023 (Survey on ICT usage and e-commerce in enterprises 2023, Spain)
26 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.
The statistical unit is enterprise but the sampling and respondent unit is legal unit.
We consolidate data from legal units to enterprise using Eurostat rules.
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.
All national territory was considered.
Data for a specific set of variables were delivered on NUTS 2 regional level.
The reference period is:
2023 for the % of sales data and where specified
Where not specified respondents should consider as reference their current situation (first quarter of 2024)
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
For the elaboration of the ICT SURVEY under the 'Statistical enterprise' approach, a method has been developed that is based on the following steps, each of which is described in more detail in the ICT SURVEY Methodology document available on the INE website together to the statistical results of the operation.
Delineation of the Statistical enterprises that operate in business groups through the so-called Profiling methodology and classification of the Legal Units that compose them (see details in section 3.3 of the ICT SURVEY Methodology )
Adequacy of the sample design and the information collection phase (see details in sections 5 and 6 of the ICT SURVEY Methodology ).
Aggregation of the Legal Units that make up each Sample Statistical enterprise and study of the combinations of typologies of said Legal Units (see details in section 7.2.1 of the ICT SURVEY Methodology ).
Consolidation for sample Statistical enterprises formed by more than one Legal Unit and containing relationships between them. For these enterprises, the flows between their Legal Units are identified to proceed with the cancellation of intra-enterprise transactions (see details in section 7.2.2 of the ICT Survey Methodology ).
Construction of the complete statistics, based on Statistical enterprises, whether they are independent Legal Units or enterprises of business groups (see details in section 7.2.3 of the ICT SURVEY Methodology ).
The essential idea is that if the Legal Units of a Statistical enterprise serve, exclusively or mainly, other Legal Units of the same enterprise (for example, because they sell products under a vertical integration of the production process or provide services as an auxiliary relationship) , said servile Legal Units must be combined with the others to which they support to form the authentic statistical unit "enterprise", therefore having to combine and consolidate the corresponding variables.
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:
According to the frame population (extracted from the DIRCE), the legal units are stratified by crossing the following variables: size, economic activity and location.
In every stratum, a systematic selection randomly started is executed, sorting out the legal units by size and location.
The categories of the variables used to stratify are: size:
[0 to 2] and [3 to 9] employees and self-employed persons
[10 to 19], [20 to 49], [50 to 99], [100 to 199],[200 to 499] and 500 or more (for legal units with 10 or more employees and self-employed persons
Main activity:
For legal units with less than 10 employees and self-employed persons the aggregations of NACE classification is as followed:
10 -39
41 -43
45
46
47
49 -53
55
56
58 -63
68 + 69 -75+ 77+78+80-82
79+95.1
For legal units with 10 or more employees and self-employed persons the aggregations of NACE classification as followed:
10 - 18
19 - 23
24 - 25
26 - 33
35 - 39
41 - 43
45
46
47
49 -53
55
56
58 -63
68
69 -75
77-82
26.1 - 26.4, 26.8, 46.5, 58.2, 61, 62, 63.1, 95.1
Region: All Spanish regions (19) are covered.
The total number of initial strata for the general questionnaire is 1.938 (17*6*19), including empty strata for legal units with 10 or more employees and self-employed persons and 418 (11*2*19) for legal units with less than 10 employees and self-employed persons (following NACE rev.2).
The survey is carried out alone.
C) Gross sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
More detailed information is available in “ Annex III. Sample and standard error tables 2024 “ (Worksheet: NET SAMPLE)
Annual
See detailed section in the Full metadata report.
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
