Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the ... (32024R1883)
EU - Rechtsakte: 13 Industrial policy and internal market
2024/1883
10.7.2024

COMMISSION IMPLEMENTING REGULATION (EU) 2024/1883

of 9 July 2024

laying down the technical specifications of data requirements and the deadlines for submission of metadata and quality reports for the topic ‘Information and Communication Technologies usage and e-commerce’ for the reference year 2025, pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council

(Text with EEA relevance)

THE EUROPEAN COMMISSION,
Having regard to the Treaty on the Functioning of the European Union,
Having regard to Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics, repealing 10 legal acts in the field of business statistics (1), and in particular Article 7(1) and Article 17(6) thereof,
Whereas:
(1) The topic ‘Information and Communication Technologies (“ICT”) usage and e-commerce’ provides data required by the Digital Decade Policy Programme to monitor the Union’s digital targets for 2030, such as the Digital Intensity Indicator for the digital transformation of businesses or the take-up of cloud computing services, big data (data analytics) or artificial intelligence. It also provides information for various other Union policies related to digital performance among which ‘A Europe fit for the digital age’ policy.
(2) In order to allow to assess the quality of the data and to ensure that data on ICT usage and e-commerce are comparable and harmonised, metadata and quality reports are required to be provided before the data are released.
(3) The measures provided for in this Regulation are in accordance with the opinion of the European Statistical System Committee,
HAS ADOPTED THIS REGULATION:

Article 1

For the topic ‘ICT usage and e-commerce’, as referred to in Annex I to Regulation (EU) 2019/2152, Member States shall transmit to the Commission (Eurostat) the data for the reference year 2025 in accordance with the Annex to this Regulation.

Article 2

1.   The annual metadata report for the topic ‘ICT usage and e-commerce’ for the reference year 2025 shall be transmitted to the Commission (Eurostat) by 31 May 2025.
2.   The annual quality report for the topic ‘ICT usage and e-commerce’ for the reference year 2025 shall be transmitted to the Commission (Eurostat) by 5 November 2025.

Article 3

This Regulation shall enter into force on the twentieth day following that of its publication in the
Official Journal of the European Union
.
This Regulation shall be binding in its entirety and directly applicable in all Member States.
Done at Brussels, 9 July 2024.
For the Commission
The President
Ursula VON DER LEYEN
(1)  
OJ L 327, 17.12.2019, p. 1
.

ANNEX

Technical specifications of data requirements for the topic ‘Information and Communications Technologies usage and e-commerce’

Mandatory/optional

Scope (filter)

Variable

Mandatory variables

(i)

for all enterprises:

(1)

main economic activity of the enterprise, in the previous calendar year

(2)

average number of employees and self-employed persons, in the previous calendar year

(3)

total value of turnover (in monetary terms, excluding VAT), in the previous calendar year

(4)

number of employees and self-employed persons or percentage of the total number of employees and self-employed persons who have access to the internet for business purposes

(5)

use of ICT systems and solutions to reduce the energy consumption of the enterprise

(6)

use of ICT systems and solutions to reduce the material used (including consumables) or to enhance the use of recycled material

(ii)

for enterprises with employees and self-employed persons who have access to the internet for business purposes:

(7)

use of any type of fixed connection to the internet

(8)

having a website

(9)

use of social media (i.e. having a user profile or an account)

(10)

having web sales of goods or services via the enterprise’s websites or apps (including extranets), in the previous calendar year

(11)

having web sales of goods or services via e-commerce marketplace websites or apps used by several enterprises for trading goods or services, in the previous calendar year

(12)

having Electronic Data Interchange (EDI)-type sales of goods or services, in the previous calendar year

(13)

use of Enterprise Resource Planning (ERP) software to manage resources by sharing information among different functional areas such as accounting, planning, production, marketing

(14)

use of Customer Relationship Management (CRM) software for managing information about customers such as relations or transactions

(15)

use of Business Intelligence (BI) software for accessing and analysing data, presenting analytical findings to provide detailed insights for decision-making and strategic planning

(16)

performing data analytics (from internal and external data sources) by own employees

(17)

having data analytics performed by an external enterprise or organisation for the enterprise (including data analytics based on data from internal and external sources)

(18)

using paid cloud computing services

(19)

use of Artificial Intelligence technologies performing analysis of written language (such as text mining)

(20)

use of Artificial Intelligence technologies converting spoken language into machine-readable format (speech recognition)

(21)

use of Artificial Intelligence technologies generating written, spoken language or programming codes (natural language generation, speech synthesis)

(22)

use of Artificial Intelligence technologies generating pictures, videos, sound/audio

(23)

use of Artificial Intelligence technologies identifying objects or persons based on images or videos (image recognition, image processing)

(24)

use of machine learning (such as deep learning) for data analysis

(25)

use of Artificial Intelligence technologies automating different workflows or assisting in decision-making (such as Artificial Intelligence based software robotic process automation)

(26)

use of Artificial Intelligence technologies enabling physical movement of machines via autonomous decisions based on observation of surroundings (autonomous robots, self-driving vehicles, autonomous drones)

(iii)

for enterprises using any type of fixed internet connection:

(27)

maximum contracted download speed of the fastest fixed internet connection in the ranges: [0 Mbit/s, < 30 Mbit/s], [30 Mbit/s, < 100 Mbit/s], [100 Mbit/s, < 500 Mbit/s], [500 Mbit/s, < 1 Gbit/s], [≥ 1 Gbit/s]

(iv)

for enterprises having a website:

(28)

enterprise’s website has a description of goods or services or price information

(29)

enterprise’s website has online ordering or reservation or booking (such as shopping cart)

(30)

enterprise’s website has a possibility for visitors to customise or design online goods or services

(31)

enterprise’s website has tracking or status of orders placed

(32)

enterprise’s website has personalised content on the website for regular/recurrent visitors

(33)

enterprise’s website has a chat service for customer support (a chatbot, virtual agent or a person replying to customers in real-time)

(34)

enterprise’s website has advertisement of open job positions or online job application

(35)

enterprise’s website has content available in at least in two languages

(v)

for enterprises which had web sales of goods and services via the enterprise’s websites or apps and/or via e-commerce marketplace websites or apps used by several enterprises for trading goods or services, in the previous calendar year:

(36)

value of web sales of goods or services, or percentage of total turnover generated by web sales of goods and services, in the previous calendar year

(37)

percentage of value of web sales generated by web sales to private consumers (Business to Consumers: B2C), in the previous calendar year

(38)

percentage of value of web sales generated by web sales to other enterprises (Business to Business: B2B) and to public sector (Business to Government: B2G), in the previous calendar year

(vi)

for enterprises which had web sales of goods and services via the enterprise’s websites or apps and via e-commerce marketplace websites or apps used by several enterprises for trading goods or services, in the previous calendar year:

(39)

percentage of value of web sales of goods or services generated by sales via the enterprise’s websites or apps (including extranets), in the previous calendar year

(40)

percentage of value of web sales of goods or services generated by sales via e-commerce marketplace websites or apps used by several enterprises for trading goods or services, in the previous calendar year

(vii)

for enterprises which had EDI-type sales of goods and services, in the previous calendar year:

(41)

value of EDI-type sales of goods or services or percentage of the total turnover generated by EDI-type sales of goods or services, in the previous calendar year

(viii)

for enterprises performing data analytics (from internal and external data sources) by own employees:

(42)

performing data analytics on data from transaction records such as sale details, payments records (for example from ERP, enterprise’s webshop)

(43)

performing data analytics on data about customers such as customer purchasing information, location, preferences, customer reviews, searches (for example from CRM system or enterprise’s website)

(44)

performing data analytics on data from social media, including from enterprise’s own social media profiles (such as personal information, comments, video, audio, images)

(45)

performing data analytics on web data (such as search engine trends, web scraping data)

(46)

performing data analytics on location data from the use of portable devices or vehicles (such as portable devices using mobile telephone networks, wireless connections or GPS)

(47)

performing data analytics on data from smart devices or sensors (such as Machine to Machine (M2M) communications, sensors installed in machinery, manufacturing sensors, smart meters, Radio frequency identification (RFID) tags)

(48)

performing data analytics on government authorities’ open data (such as enterprise public records, weather conditions, topographic conditions, transport data, housing data, buildings data)

(49)

performing data analytics on satellite data (such as satellite imagery, navigation signals, position signals), including data acquired from enterprise’s own infrastructure or from externally provided service (for example AWS Ground Station) and excluding location data from the use of portable devices or vehicles using GPS)

(ix)

for enterprises using paid cloud computing services:

(50)

using e-mail as a paid cloud computing service

(51)

using office software (such as word processors or spreadsheets) as a paid cloud computing service

(52)

using finance or accounting software applications as a paid cloud computing service

(53)

using Enterprise Resource Planning (ERP) software applications as paid cloud computing service

(54)

using Customer Relationship Management (CRM) software applications as a paid cloud computing service

(55)

using security software applications (such as antivirus program, network access control) as paid cloud computing service

(56)

using hosting the enterprise’s database(s) as a paid cloud computing service

(57)

using storage of files as a paid cloud computing service

(58)

using computing power to run the enterprise’s own software as a paid cloud computing service

(59)

using computing platform providing a hosted environment for application development, testing or deployment (such as reusable software modules, application programming interfaces (APIs)) as a paid cloud computing service

(x)

for enterprises using Artificial Intelligence technologies, referring specifically to mandatory variables (19) to (26):

(60)

use of Artificial Intelligence software or systems for marketing or sales (such as customer profiling, price optimisation, personalised marketing offers, market analysis based on machine learning, chatbots based on natural language processing for customer support, autonomous robots for orders processing)

(61)

use of Artificial Intelligence software or systems for production or service processes (such as predictive maintenance or process optimization based on machine learning, tools to classify products or find defects in products based on computer vision, autonomous drones for production surveillance, security or inspection tasks, assembly works performed by autonomous robots)

(62)

use of Artificial Intelligence software or systems for organisation of business administration processes or management (such as business virtual assistants based on machine learning and/or natural language processing (for example for document drafting), data analysis or strategic decision making based on machine learning (for example risk assessment), planning or business forecasting based on machine learning, human resources management based on machine learning or natural language processing (for example candidates pre-selection screening, employee profiling or performance analysis)

(63)

use of Artificial Intelligence software or systems for logistics (such as autonomous robots for pick-and-pack solutions in warehouses for parcel shipping, tracing, distribution or sorting, route optimization based on machine learning)

(64)

use of Artificial Intelligence software or systems for ICT security (such as face recognition based on computer vision for authentication of ICT users, detection and prevention of cyber-attacks based on machine learning)

(65)

use of Artificial Intelligence software or systems for accounting, controlling or finance management (such as machine learning to analyse data that helps to make financial decisions, invoice processing based on machine learning, machine learning or natural language processing used for bookkeeping tasks)

(66)

use of Artificial Intelligence software or systems for research and development (R&D) or innovation activity, excluding research on Artificial Intelligence (such as analysis of data for conducting research, solving research problems, developing a new or significantly improved product/service based on machine learning)

Optional variables

(i)

for all enterprises:

(1)

disposal of ICT equipment (such as computers, monitors, mobile phones) in electronic waste collection/recycling (including leaving it to the retailer to dispose of) when it is no longer used

(2)

keeping of ICT equipment (such as computers, monitors, mobile phones) in the enterprise when it is no longer used (for example to be used as spare parts, fear of sensitive information being disclosed)

(3)

selling, returning to a leasing enterprise or donating ICT equipment (such as computers, monitors, mobile phones) when it is no longer used

(ii)

for enterprises which had web sales of goods and services via the enterprise’s websites or apps and/or via e-commerce marketplace websites or apps used by several enterprises for trading goods or services, in the previous calendar year, type of product:

(4)

percentage of value of web sales generated by web sales of physical goods, in the previous calendar year

(5)

percentage of value of web sales generated by web sales of digital goods or services (digitally delivered) (such as software or other digital content as downloads or as a streaming service (e.g. software licences, e-books, e-newspapers, apps, online course/webinars)), in the previous calendar year

(6)

percentage of value of web sales generated by web sales of services not digitally delivered, in the previous calendar year

(7)

web sales to customers located in the enterprise’s own country, in the previous calendar year

(8)

web sales to customers located in other Member States, in the previous calendar year

(9)

web sales to customers located in the rest of the world, in the previous calendar year

(iii)

for enterprises which had web sales to customers located in at least two of the following geographic areas: own country, other Member States or rest of the world, in the previous calendar year:

(10)

percentage of value of web sales generated by web sales to customers located in enterprise’s own country, in the previous calendar year

(11)

percentage of value of web sales generated by web sales to customers located in other Member States, in the previous calendar year

(12)

percentage of value of web sales generated by web sales to customers located in the rest of the world, in the previous calendar year

(iv)

for enterprises which had web sales to other Member States, in the previous calendar year:

(13)

difficulties experienced when selling to other Member States: high costs of delivering or returning products, in the previous calendar year

(14)

difficulties experienced when selling to other Member States: difficulties related to resolving complaints and disputes, in the previous calendar year

(15)

difficulties experienced when selling to other Member States: adapting product labelling for sales to other Member States, in the previous calendar year

(16)

difficulties experienced when selling to other Member States: lack of knowledge of foreign languages for communicating with customers in other Member States, in the previous calendar year

(17)

difficulties experienced when selling to other Member States: restrictions from enterprise's business partners to sell to certain Member States, in the previous calendar year

(18)

difficulties experienced when selling to other Member States: difficulties related to the VAT system in other Member States (such as uncertainty regarding VAT treatment in different countries), in the previous calendar year

(v)

for enterprises using paid cloud computing services:

(19)

total cost of the cloud computing services purchased by the enterprise, in the previous calendar year

(vi)

for enterprises using Artificial Intelligence technologies, referring specifically to mandatory variables (19) to (26):

(20)

Artificial Intelligence software and systems were developed by own employees (including those employed in parent or affiliate enterprise)

(21)

commercial Artificial Intelligence software or systems were modified by own employees (including those employed in parent or affiliate enterprise)

(22)

open-source Artificial Intelligence software or systems were modified by own employees (including those employed in parent or affiliate enterprise)

(23)

commercial Artificial Intelligence software or systems ready to use were purchased (including examples where they were already incorporated in a purchased item or system)

(24)

external providers were contracted to develop or modify Artificial Intelligence software and systems

(vii)

for enterprises which did not use any Artificial Intelligence technologies, referring specifically to mandatory variables (19) to (26):

(25)

consideration of using any of Artificial Intelligence technologies, referring specifically to mandatory variables (19) to (26)

(viii)

for enterprises which did not use but considered to use Artificial Intelligence technologies, referring specifically to mandatory variables (19) to (26):

(26)

Artificial Intelligence technologies not used because the costs seem too high

(27)

Artificial Intelligence technologies not used because there is a lack of relevant expertise in the enterprise

(28)

Artificial Intelligence technologies not used because of incompatibility with existing equipment, software or systems

(29)

Artificial Intelligence technologies not used because of difficulties with availability or quality of the necessary data

(30)

Artificial Intelligence technologies not used because of concerns regarding violation of data protection and privacy

(31)

Artificial Intelligence technologies not used because of lack of clarity about the legal consequences (such as liability in case of damage caused by the use of Artificial Intelligence)

(32)

Artificial Intelligence technologies not used because of ethical considerations

(33)

Artificial Intelligence technologies not used because they are not useful for the enterprise

 

(ix)

for enterprises which used ICT systems or solutions with the purpose to reduce the energy consumption or to reduce material used (including consumable) or to enhance the use of recycled material:

(34)

monitoring and quantifying the impact of using ICT systems or solutions on energy and/or material consumption

Measurement unit

Absolute figures, except for characteristics related to turnover in national currency (thousands) or percentage of (total) turnover

Statistical population

Activity coverage:

NACE Rev. 2 Sections C to J, L to N and group 95.1

Size class coverage:

Enterprises with 10 or more employees and self-employed persons. Enterprises with less than 10 employees and self-employed persons may be covered optionally.

Breakdowns

Activity breakdown

for calculation of national aggregates:

aggregates of NACE Rev. 2 sections and group: C + D + E + F + G + H + I + J + L + M + N + 95.1, D + E

NACE Rev. 2 sections: C, F, G, H, I, J, L, M, N

NACE Rev. 2 divisions: 47, 55

aggregates of NACE Rev. 2 divisions: 10 + 11 + 12 + 13 + 14 + 15 + 16 + 17 + 18, 19 + 20 + 21 + 22 + 23, 24 + 25, 26 + 27 + 28 + 29 + 30 + 31 + 32 + 33

aggregate of the NACE Rev. 2 divisions and groups: 26.1 + 26.2 + 26.3 + 26.4 + 26.8 + 46.5 + 58.2 + 61 + 62 + 63.1 + 95.1

for contribution to the European totals only

NACE Rev. 2 sections: D, E

NACE Rev. 2 divisions: 19, 20, 21, 26, 27, 28, 45, 46, 61, 72, 79

NACE Rev. 2 group: 95.1

aggregates of NACE Rev. 2 divisions: 10 + 11 + 12, 13 + 14 + 15, 16 + 17 + 18, 22 + 23, 29 + 30, 31 + 32 + 33, 58 + 59 + 60, 62 + 63, 69 + 70 + 71, 73 + 74 + 75, 77 + 78 + 80 + 81 + 82

Size class of number of employees and self-employed persons: 10+, 10-49, 50-249, 250+; optional: 0-9, 0-1, 2-9

Data transmission deadline

5 October 2025

ELI: http://data.europa.eu/eli/reg_impl/2024/1883/oj
ISSN 1977-0677 (electronic edition)
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