ICT usage in enterprises (isoc_e)

National Reference Metadata in SIMS structure for INFOSOC Enterprises

Compiling agency: National Institute of Statistica


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)



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1. Contact Top
1.1. Contact organisation

National Institute of Statistica
1.2. Contact organisation unit

Directorate of Structural Business Statistics
1.5. Contact mail address

bulevardul Libertatii nr.16, Bucuresti, Romania


2. Metadata update Top
2.1. Metadata last certified 20/03/2024
2.2. Metadata last posted 20/03/2024
2.3. Metadata last update 20/03/2024


3. Statistical presentation Top
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.

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. Part of this is the "European strategy for data", envisioning a single market for data to ensure the EU's global competitiveness and data sovereignty, in which context a comprehensive set of new rules for all digital services was proposed: the Digital Services Act and the Digital Markets Act, which are centrepieces of the EU digital strategy. Furthermore, the Commission and the High Representative of the Union for Foreign Affairs and Security Policy presented a new “EU cybersecurity strategy”, which is intended to bolster the EU's collective resilience against cyber threats, safeguard a global and open internet and protect EU values and the fundamental rights of its people. Furthermore, data will allow monitoring the progress towards  A Europe fit for the digital age, one of the six priorities for the period 2019-2024 of the von der Leyen European Commission.

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
Chestionar statistic privind utilizarea produselor TIC in intreprinderi
3.2. Classification system

 NACE Rev.2 2008
3.3. Coverage - sector

All economic activities in the scope of Annex I 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: NACE Rev. 2 sections C, D, E, F, G, H, I, J, L, M and N, division 95.1.

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
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?

Micro-enterprises are not 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 areas:

-          Access to and use of the Internet

-          E-commerce and e-business

-          Use of cloud computing services

-          Artificial Intelligence

-          Other topics: Data utilisation, sharing, analytics and trading, Invoicing.

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 shall be 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

The country area
3.8. Coverage - Time

Years 2022 and 2023.
3.9. Base period

Not applicable


4. Unit of measure Top

Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons.


5. Reference Period Top

Similar to EU model of the questionnaire; Current situation and year 2022 for certain variables


6. Institutional Mandate Top
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:

National legal acts consists of the National Statistical Law (https://legislatie.just.ro/Public/DetaliiDocument/106793) and National Annual Statistical Programme (https://legislatie.just.ro/Public/DetaliiDocument/265412)
6.2. Institutional Mandate - data sharing

Not applicable


7. Confidentiality Top
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 : 

According to national legislation are considered confidential data for all aggregates with less than 4 units or one/two units dominate the aggregate.

 
7.2. Confidentiality - data treatment

Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.

At national level :

Data are treated to ensure statistical confidentiality and prevent unauthorised disclosure. Access to data is provided to the authorised staff (survey managers).


8. Release policy Top
8.1. Release calendar

The publication calendar is publicly accessible.
8.2. Release calendar access

The publications calendar is available on NIS website https://insse.ro/cms/files/catalog/calendar-comunicate-de-presa-2023.pdf
8.3. Release policy - user access

The users are informed that the data are being released based on the dissemination calendar; the dissemination of statistical data is for all users at the same time.


9. Frequency of dissemination Top

Annual


10. Accessibility and clarity Top
10.1. Dissemination format - News release

No news release
10.2. Dissemination format - Publications

Regular annual publication Societatea Informationala https://insse.ro/cms/sites/default/files/field/publicatii/seria_statistica_de_intreprinderi_societatea_informationala_11.pdf
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 :

Not available
10.4. Dissemination format - microdata access

Micro-data are not disseminated
10.5. Dissemination format - other

Not requested
10.5.1. Metadata - consultations

Not requested
10.6. Documentation on methodology

Methodological guideline and statistical metadata http://statistici.insse.ro:8077/tempo-online/#/pages/tables/insse-table and http://statistici.insse.ro:8077/tempo-online/#/pages/tables/insse-table
10.6.1. Metadata completeness - rate

Not requested
10.7. Quality management - documentation

Quality guideline https://insse.ro/cms/files/eurostat/Ghid%20de%20calitate%20al%20statisticii%20oficiale.pdf


11. Quality management Top
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 :

At national level the methodology is based on the compliers’ manual for ICT usage and e-commerce in enterprises
11.2. Quality management - assessment

European level :

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 Methodological Manual provides guidelines and clarifications for the implementation of the surveys.

National level :

At national level we used the Methodological Manual as basis for drafting the methodological explanations and definitions that are included in the statistical questionnaire. The MoQ and the methodological manual requirements are also used in all phases of the survey.

 


12. Relevance Top
12.1. Relevance - User Needs

European level : 

At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DG REGIO, DG JRC) are the principal users of the data on ICT usage and e-commerce in enterprises and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage.

User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies.

National level :

Internally the main users are the National accounts department. The National Agency for Digitisation is the main user outside the NIS
12.2. Relevance - User Satisfaction

European level : 

At European level, contacts within the Commission, the OECD and other stakeholders give a clear picture about the key users' satisfaction as to the following data quality aspects: accuracy and reliability of results, timeliness, satisfactory accessibility, clarity and comparability over time and between countries, completeness and relevance. Overall users have evaluated positively (good, very good) the data quality on the ICT usage and e-commerce in enterprises.

National level :

No user satisfaction survey is carried out specifically for the domain but the contacts with the users provide valuable input to asses the relevance of the ICT statistics
12.3. Completeness

Detailed information is available in “ Annex I _ Completeness “ excel file - related to questionnaire, coverage, additional questions.
12.3.1. Data completeness - rate

Not requested. 


13. Accuracy Top
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 “ excel file - 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“ Sample and standard error tables 2023 “ excel file – 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 total error of an estimate relative to the unknown population value is expressed as a root mean square error. RMSE is defined as the square root of the sum of variance and the square of the bias. Relating to the accuracy, RMSE is rarely estimated. Sampling errors should be reported for all estimates resulting from a statistical process where sampling is involved. The standard error is the square root of the variance of an estimator.

The coefficient of variation (CV) is defined as the standard error divided by the expected value of the estimator. CV represents the standard error in relative (percentage) terms and it is more suitable in order to quantify the sampling error for economic statistics.
b) Basic formula
 We calculate the CV at cell level, using SAS procedure PROC SURVEYMEANS

 

c) Main reference in the literature
 not applicable

 

d) How has the stratification been taken into account? 
 CV at cell level, using SAS procedure PROC SURVEYMEANS

 

e) Which strata have been considered? 
  The strata are based on the enterprise economic activity code (NACE code) and the size level (employment)
13.3. Non-sampling error

See detailed sections below.
13.3.1. Coverage error

See concept 18.1.1. A) Description of  frame population.
13.3.1.1. Over-coverage - rate

4.6%
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 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%  11347 100%
1. Response (questionnaires returned by the enterprise)     10326 91.0 %
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)      9807 86.4%
1.2 Not used for tabulation     519  4.6%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)     519  4.6%
1.2.2 Other reasons (e.g. unusable questionnaire)        
2. Non-response (e.g. non returned mail, returned mail by post office)      1021  9.0%

 

Comments on unit response, if unit response is below 60%
 
13.3.3.1.2. Methods used for minimizing unit non-response

Enterprises are contacted by phone call and reminders
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 )
 
13.3.3.1.4. Assessment of unit non-response bias

Not available
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.		  
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  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.		  X
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
 
13.3.3.2.2. Questions or items with item response rates below 90% and other comments

Other comments relating to the item non-response

Additional issues concerning "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 available
13.3.4. Processing error

No processing errors were detected

13.3.5. Model assumption error

Not requested


14. Timeliness and punctuality Top
14.1. Timeliness

See detailed section below.
14.1.1. Time lag - first result

Not applicable
14.1.2. Time lag - final result

European level : 

Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce).

At national level : 

Data will be published in January 2024

14.2. Punctuality

 See detailed section below.
14.2.1. Punctuality - delivery and publication

Data were delivered on October 5; no delay


15. Coherence and comparability Top
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 “ excel file - related to questionnaire, coverage, additional questions.
15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable
15.2. Comparability - over time

See section below.
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.

 
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


16. Cost and Burden Top
Restricted from publication


17. Data revision Top
17.1. Data revision - policy

National revision policy https://insse.ro/cms/files/sistemul%20statistic%20national/Politica%20de%20revizuire%20final%20v1.pdf
17.2. Data revision - practice

According to the national policy when is the case
17.2.1. Data revision - average size

 Not requested


18. Statistical processing Top
18.1. Source data

A) Frame population description and distribution

For more information see concept 18.1.1.

 

B) Sampling design - Sampling method

Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata: 

The method used is stratified random sampling. Variables used for stratification are NACE code activity (according both to national and European aggregates) and size class in terms of employment.

 

C) Gross sample distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (Worksheet: GROSS SAMPLE)

 

D) Net sample distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (Worksheet: NET SAMPLE)



Annexes:
RO questionnaire
Sampling frame and sample
18.1.1. Population frame

A) Description of frame population

a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?   March 2023                          
b) When was the last update of the Business register that was used for drawing the sample of enterprises for the survey?  January 2023
c) Please indicate 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)  coordinated with SBS
d) Please describe if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up):  
e) Please indicate shortcomings in terms of timeliness (e.g. time lag between last update of the sampling frame and the moment of the actual sampling), geographical coverage, coverage of different subpopulations, data available etc., and any measures taken to correct it, for this survey.  not the case

 

 B) Frame population distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (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  April  End July
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
The collection of micro-enterprises was integrated with the general survey
18.3.4. Survey type

Web survey
18.3.5. Survey participation
Mandatory
18.4. Data validation

National validation tools and Server based EDIT validation
18.5. Data compilation

Grossing-up procedures

 

The computation of the final weights was performed according to the following steps:

 

  • Calculation of a selection weight (πih) for each unit. The selection weight is a Horvitz-Thompson weight and is computed as the inverse of the selection probability.

 

 

 

 

where:

pih = the selection probability of unit i for stratum h

Nh=the number of units in the sampling frame, in the stratum h

nh= the number of units in the sample, in the stratum h

 

 

  • Calculation of a non-response weight (cih). The non-response weight is computed at each stratum level, as the inverse of the response probability. The purpose of this coefficient is to compensate the non-respondent units, under the assumption that these non-respondent units have the same training patterns compared with the respondent units in the same stratum. Another considered premise is the fact that answering and non-answering is a random variable.

 

 

where:

nh= the number of units in the sample, in the stratum h

mh = the number of respondent units selected in the sample,

in the stratum h

 

Calculation of the final weight ( )

 

 

 

The estimator used for computing the estimated data and the estimated variance is Horvitz-Thomson estimator, as the fraction between the number of units in the sampling frame in the stratum h and the number of respondent units in the sample in the same stratum (Nh/mh).

 

 

 

The estimation is based on the next assumptions:

 

  • The response is stochastic and there is a response distribution.
  • All units within a stratum respond with the same probability.

.
18.5.1. Imputation - rate

Not available
18.6. Adjustment

Not applicable
18.6.1. Seasonal adjustment

Not applicable


19. Comment Top

Problems encountered and lessons to be learnt: 
19.1. Documents
Questionnaire in national language  
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)  
Other Annexes  


Annexes:
Romanian questionnaire


Related metadata Top


Annexes Top
annex 1
Annex II Accuracy
Sample and standard error tables 2023