COMMISSION STAFF WORKING DOCUMENT First annual report on key findings from the European Monitor of Industrial Ecosystems (EMI) Accompanying the document Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions “The 2024 Annual Single Market and Competitiveness Report"
Date: 2024-02-14
Institutions: Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs, European Commission
Subjects: competitiveness, digital transformation, economic growth, free movement of capital, green economy, innovation, investment, research and development, single market

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EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 14.2.2024  SWD(2024) 77 final  COMMISSION STAFF WORKING DOCUMENT      First annual report on key findings from the European Monitor of Industrial Ecosystems (EMI) Accompanying the document Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions “The 2024 Annual Single Market and Competitiveness Report" {COM(2024) 77 final} - {SWD(2024) 78 final}  
 
 
 
 
Table of Contents 

Executive Summary ......................................................................................................................... 3 

1. Introduction .................................................................................................................................... 5 

2. Uptake of green and digital technologies ..................................................................................... 5 

2.1. Presence of digital tech startups in the industrial ecosystems................................................ 5 

2.2. Adoption of green and digital technologies by SMEs across industrial ecosystems ............... 7 

2.3. Environmental impact of industrial ecosystems .................................................................... 11 

2.4. Private investments and funding per ecosystem ................................................................... 13 

2.5. Supply and demand of skills to support the twin transition .................................................. 17 

3. Position of EU industry in the global technology race ................................................................ 20 

3.1. The EU’s innovation capacity in green and digital technologies............................................ 20 

3.2. EU capacity to produce technology-based products ............................................................. 22 

3.3. Scaling-up capacity in the EU ................................................................................................. 27 

ANNEX ....................................................................................................................................... 29 

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Executive Summary 

The European Monitor of Industrial Ecosystems (EMI) aims to inform EU policymakers, industry, and Member States 
about the evolution of the twin transition across individual industrial ecosystems1, notably by looking at some of its 
key enablers, and about EU  competitiveness in key technologies for the twin transition, also compared to other 
foreign competitors.  

This annex provides a first annual report on EMI findings, first as regards the progress of the twin transition by 
individual ecosystem, and then as regards the position of EU industry in the global technology race. 

On the progress of the twin transition by individual ecosystem, the initial results show the following: 

•  Uptake of digital and green technologies 

EMI finds that basic digitalisation2 is still taking place across all industrial ecosystems, with only 69% of Small and 
Medium-Sized Enterprises (SMEs) having at least basic level of digital intensity in 2022, below the 2030 EU target 
of 90%3. However, there is evidence of a serious commitment by industry to speeding up: e.g., 49% of SMEs reported 
increasing their investments in digital technologies4. This trend is particularly visible in the aerospace and defence 
and the cultural and creative industries ecosystems. Similarly, 42% of SMEs reported increasing their investments 
in green technologies, with energy-intensive industries, aerospace and defence, and agrifood leading this. 

•  Supply and demand of green and digital skills 

EMI also finds that the availability of digital skills remains limited, especially in some service-based ecosystems like 
tourism. These low levels of supply contrast with the high demand for such skills, and this gap is particularly high 
in cultural and creative industries, construction, and tourism. The availability of green skills also remains limited, 
with no ecosystem having a share of professionals with such skills over 7%. Demand also remains low, with the 
exception of the Energy-Renewables ecosystem, but is increasing with an average annual growth rate reaching 40% 
from 2019 to 2022. 

•  Private equity and venture capital 

European private equity and venture capital investment in green and digital tech firms have consistently increased 
since 2016, with significant increases in 2021 and 2022, followed by a drop  in the first quarters of 2023. The 
ecosystems that attracted the most investment in digital firms in 2021 were electronics, retail, and mobility. The 
latter two were also the ecosystems that captured the most investment in green tech firms, along with agrifood. 
Despite this, EU businesses are still constrained by the limited availability of private financing, with the US having 
a much larger number of scale-ups than the EU across all industrial ecosystems, though this gap is narrowing in 
certain ecosystems, such as mobility, electronics, tourism, and energy-intensive industries. 

On the position of EU industry in the global technology race, EMI shows the following: 

•  Capacity to innovate 

EMI finds that EU innovation is concentrated in climate change technology, but that the EU is giving way in digital 
competitiveness, with the EU retaining a leading position on transnational patent applications in Renewable Energy 

1 The definition of industrial ecosystems can be found in the 2020 EU Industrial Strategy. The methodology used to define each 
industrial ecosystem and the NACE rev.2 that each industrial ecosystem encompasses are outlined in the Annual Single Market 
Report 2021.    
2 The adoption of basic technologies like software services. 
3 Established by the Digital Decade Policy Programme https://ec.europa.eu/commission/presscorner/detail/en/ip_23_4619 
4 These figures are sourced from the results of the business survey that was conducted among SMEs in the context of the EMI 
project. 

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Technologies, but lagging behind China and the US in Artificial Intelligence and Big Data. China has caught up with 
the EU on solar power. On the other hand, the EMI provides further evidence that the EU is still in the lead worldwide 
in terms of transnational patents in Advanced Manufacturing technologies.  

• 

 Capacity to produce technology-based goods  

EMI shows that the EU produces more than it imports in advanced manufacturing and robotics, renewable energy 
technologies, advanced materials and nanotechnology, and biotechnology5. However, the positive balances between 
production and imports which were found in the advanced manufacturing and renewable energy technologies have 
recorded a decrease. Moreover, the analysis shows that the EU produces much less than it imports in Artificial 
Intelligence and Big Data, both of which are key for industrial competitiveness and to deploy Industry 5.0 solutions.  

5 This data is obtained by matching technology domains with production data from Prodcom,  

4 

 
 
 
 
 
 
1.  Introduction 

The European Monitor of Industrial Ecosystems (EMI)6 project was launched in 2022 to support EU policymakers, 
industrial stakeholders, and Member States in assessing the performance of the 14 industrial ecosystems in terms 
of their green and digital transition. To this effect, based on an established monitoring framework, the project will 
deliver 14 industrial ecosystem reports on a yearly basis, starting this year, allowing for an assessment of progress 
over time. This will be complemented annually by 27 Member State reports, several international reports, and one 
EU  report,  to  provide  insights  both  at  country  level  and  vis-à-vis  other  foreign  competitors.  In  this  way,  EMI 
complements other monitoring exercises undertaken by the Commission, such as the Annual Single Market and 
Competitiveness Report (ASMCR) and the multiple observatories developed by industrial ecosystems. It also helps 
the monitoring of the implementation of transition pathways7. 

First, EMI has a strong focus on technology generation and uptake as key drivers of competitiveness and of the twin 
transition. Second, in addition to relying on traditional data sources such as transnational patents and trade, EMI 
uses novel metrics such as private equity and venture capital based on data from Crunchbase, supply and demand 
of skills based on data from LinkedIn and Cedefop8. In doing so, it is able to address gaps in traditional data sources 
and deliver findings on a more regular basis.  

This  is  the  first  annual  report  and  sets  out  results  in  five  areas:  uptake  of  green  and  digital  technologies, 
environmental impact, investments and funding, supply and demand of skills, and position of the EU in the global 
technology race. Although EMI is still in its first year, it presents trends where data has been available for more than 
5 years.  

2.  Uptake of green and digital technologies  
2.1. Presence of digital tech startups in the industrial ecosystems 

KEY MESSAGES: 

- The industrial ecosystems that attract the highest share of digital tech startups are health, mobility, and cultural 
and creative industries. 

- Artificial Intelligence-based tech startups are the most common in health and cultural and creative industries. 

- Internet of Things plays the most important role in electronics, healthcare, mobility, and construction. 

- Robotics plays the most important role in aerospace and defence and mobility. 

-  Augmented  and  virtual  reality  and  blockchain  are  still  considered  as  niche  technologies,  but  both  have  been 
intensifying. 

-  There  is  a  strong  increase  in  digital  tech  used  for  environmental  protection  across  all  ecosystems,  but  most 
importantly in mobility, electronics, and proximity and social economy. 

The uptake of digital technologies can be partially assessed by the presence of digital tech startups in each industrial 
ecosystem,  as  such  companies  can  disrupt  existing  models,  push  the  boundaries  of  industrial  activities  and 
encourage the broader industrial ecosystem to embrace digitalisation. Digital tech firms have become an integral 

6 European Monitor of Industrial Ecosystems (europa.eu) 
7 Transition pathways were announced by the 2021 Industrial Strategy Update. They consist of actionable plans to accelerate 
the transition in each industrial ecosystem, considering seven building blocks: sustainable competitiveness; regulation and public 
governance; infrastructure; investments and funding; research, innovation, techniques, and technological solutions; the social 
dimension; and skills. 
8 A more comprehensive description of the methodology, including a full list of indicators that will be analysed on a yearly 
basis, is attached at the end of this document. 

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part of various industries (providing, e.g., online booking and recommendation platforms in tourism or connected 
vehicles in mobility) and new start-ups are providing a diverse and dynamic nature of solutions shaping industrial 
futures. 

This section identifies which ecosystems have more digital tech startups and which type of technologies (basic or 
advanced) they adopt. The exercise builds upon the analysis of data from Crunchbase and NetZero Insights. 

As found by the analysis of startup data9, in Europe, a high share of tech startups across all industrial ecosystems 
offer basic digital solutions such as online platforms (like online marketplaces) and software services or digital 
applications that are specific to each ecosystem.  

This suggests that the more basic forms of digitalisation such as going online and leveraging digital tools are still 
taking place. Overall, the analysis identified more startups in these fields compared to advanced digital technologies 
such as Artificial Intelligence (AI), Big Data, Internet of Things (IoT), robotics, blockchain or Augmented and Virtual 
Reality (AVR). Figure 1 below provides an overview of the intensity level of technology startups using different digital 
technologies within industrial ecosystems. 

It should be noted that in many cases, more basic forms of digitalisation are more transformative for industrial 
ecosystems than deep tech. Basic software services provide essential functionality to industrial firms and enable 
them  to  manage  their  operations  more  effectively.  For  example,  in  service  ecosystems,  emerging  cloud-based 
solutions bridge the gap between the physical and digital world and help these companies to reach out to customers 
in new ways.  

That said, advanced digital technologies provide more innovative functionalities to industrial firms and 
allow  them  to  be  more  competitive.  As  shown  by  Figure  1  below,  some  industrial  ecosystems  have 
leveraged specific technologies to that end. Such is the case of certain service ecosystems like health 
and cultural and creative industries, where both AI-based and Big Data-based tech startups are found to 
be particularly common. 

9  The  analysis 
https://netzeroinsights.com/ 

relies  on  data 

from  Crunchbase  and  Net  Zero 

Insights:  https://www.crunchbase.com  and 

6 

 
 
 
 
Figure 1: Number of digital tech startups (business creation) per EU industrial ecosystem 

Source: Technopolis Group, Crunchbase and Net Zero Insights, for the European Monitor of Industrial Ecosystems (EMI) project 
2023 

On the other hand, in some manufacturing and device-based ecosystems such as electronics, healthcare, mobility, 
and construction, IoT plays the most important role. Agri-food is following close. Emerging IoT-based products and 
services  include  for  example,  connected  elderly  care  solutions  in  healthcare,  and  smart  farming  and  real  time 
monitoring in agri-food.  

Robotics  have  been  transforming  the  aerospace  and  defence  ecosystem,  particularly  the  application  of  drone 
technologies and unmanned aerial vehicles. Robotics startups are also active in the mobility ecosystem, contributing 
to automating car assembly and other production processes.  

AVR and blockchain are still considered as niche technologies with fewer specialised startups across all industrial 
ecosystems. However, they are becoming more popular, especially AVR, which is naturally the more present among 
start-ups specialised in cultural and creative industries. Blockchain is also gaining ground: for instance, it is used in 
the cultural and creative industries to manage digital rights.  

Digital technologies are increasingly interlinked with clean technologies and environmental solutions, as the growing 
number  of  startups  that  combine  both  fields  demonstrate.  Examples  include  big  data  analytics  and  AI-based 
software that provide solutions for waste management or material optimisation in specific industries.  

7 

 
 
 
 
 
 
 
 
 
2.2. Adoption of green and digital technologies by SMEs across industrial ecosystems 

KEY MESSAGES: 

- On average, 42% of SMEs surveyed reported increasing their investments in the green transition, and 49% claimed 
to have increased their investments in digital technologies;  

- The lowest levels of uptake of digital technologies are in the proximity and social economy ecosystem, whereas 
the highest are in aerospace and defence; 

- On average, 20% of surveyed SMEs reported investing into energy-saving technologies, with agri-food, tourism, 
and textiles accounting for most of the investments; 

- On average, 25% of European SMEs have adopted cloud technologies, predominantly in aerospace and defence 
and in textiles; 

- The adoption rate of AI among European large enterprises was 28%, while for SMEs, it was 9%, with the highest 
rates being recorded in the health and aerospace and defence ecosystems.  

The technological uptake of green and digital solutions by SMEs offers a snapshot of how the European economy 
is transforming at large, beyond big companies that have more resources to dedicate to this process. This section 
details the results of a dedicated survey among SMEs and explores their level of investments and adoption of green 
and digital technologies10. 

Investments and adoption of Green Technologies by SMEs 

According to the business survey conducted under EMI11, 42% of SMEs on average across all industrial ecosystems 
have increased their investments aimed at the green transition and plan to continue investing. In general, service 
ecosystems12 have a more diverse green technology uptake than manufacturing ecosystems. The latter mainly focus 
on energy saving and recycled materials. Technologies related to carbon capture or the use of green hydrogen have 
been taken up the least. 

In terms of the specific green technologies13 that these companies have invested in, on average 20% of SMEs across 
industrial ecosystems invested into energy-saving technologies. Similarly, the use of recycled materials has been 
an emerging practice, with an adoption rate of 21% among SMEs, particularly by manufacturing ecosystems such 
as textiles and agri-food (see Table 1 below). 

However, there is a lower take up - 11% - of circular business models. The most popular business practices and 
business models are the product-as-a-service and leasing models, where customers obtain temporary access to a 
product via leasing or pay-per-use schemes. The ecosystems using this the most are health with 22.3%, aerospace 
and  defence  with  14.3%,  and  construction  with  13.4%.  However,  remanufacturing,  which  increases  a  product’s 
lifetime and allows the revaluation of products, is still very limited, which may be due to the related complexities, 
software restrictions, and high costs.  

10 It should be noted that industrial ecosystems are different in terms of structure and nature – therefore, when making a direct 
comparison of the survey  results, one should put the results into context. The focus of this survey has been SMEs as they 
represent 99,9% of European businesses. 
11 The in-house business survey collected data about the level of change towards the green and digital transition of European 
SMEs  across  twelve  industrial  ecosystems  and  gathered  opinions  about  the  related  investments  and  expected  future 
developments. The survey was based on using Computer Assisted Telephone Interviewing (CATI). The final sample included 8 
987 companies with input from high-level decision-makers. 
12 The following ecosystems are considered services ecosystems: CCI, tourism, proximity and social economy, health, and retail. 
13 The complete list of advanced technologies (green, digital, and key enabling technologies) can be found in the annex.  

8 

 
 
 
 
There is a mixed uptake of clean production technologies, including waste and water reduction technologies. 
Ecosystems such as tourism, health, and agri-food show a high degree of clean production technologies with 23.3%, 
24.3% and 28.6% respectively, whereas electronics and cultural and creative industries show lower levels.  

Figure  2:  Share  of  SMEs  that  have  reported  increasing  their  expenditure  in  green  technologies  per 
industrial ecosystem in the EU27 over the past 5 years 

Source: Technopolis Group and KAPA Research, for the European Monitor of Industrial Ecosystems (EMI) project 2023 

Investments and adoption of Digital Technologies by SMEs 

On average, 49% of surveyed SMEs across all industrial ecosystems have  increased their investments in digital 
technologies. However, the share varies across the ecosystems with higher levels in aerospace and defence (68.8%), 
and cultural and creative industries (65.3%) and mush lower levels in textiles, retail, and electronics. 

Figure 3: Share of SMEs that reported increasing their expenditure in digital technologies per industrial 
ecosystem in the EU27 over the past five years 

Source: Technopolis Group and KAPA Research, for the European Monitor of Industrial Ecosystems (EMI) project 2023 

9 

 
 
 
 
 
 
 
As regards the adoption of advanced digital technologies more specifically, Figure 4 indicates the share of SMEs 
in each industrial ecosystem that have adopted each technology. The results show that cloud technologies have 
overall the most relevance for SMEs, corroborating Eurostat data14. Similarly, the data suggests that adoption is 
increasing, but use is mainly limited to communication systems and data storage. Textiles (32.3%), health (31.0%) 
and aerospace and defences (30.4%) are the ecosystems that are using the most cloud computing technologies. 

Figure 4: Share of SMEs that have adopted advanced digital technologies per industrial ecosystem in the 
EU27  

Source: Technopolis Group and KAPA Research, for the European Monitor of Industrial Ecosystems (EMI) project 2023  

New streams of big data (such as production or customer data) also seem to have high relevance for SMEs, in 
particular those in the aerospace and defence ecosystem and to a lesser extent those in the health and agri-food 
ecosystems.  

AI has been taken up by 9% of SMEs corroborating Eurostat data (and as highlighted in the First SDD Report of the 
European Commission using DESI15.  which also shows that the AI adoption rate among European large enterprises 
was  30%.  Industrial  ecosystems  with  the  highest  uptake  include  aerospace  and  defence  and  health.  The  most 
relevant application of AI concerns the optimisation and automation of production (or other business) processes. 

14https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Cloud_computing_-
_statistics_on_the_use_by_enterprises#:~:text=41%20%25%20of%20EU%20enterprises%20used,mail%20and%20storage%
20of%20files.&text=Compared%20with%202020%2C%20the%20use,the%20retail%20trade%20in%202021.  
15  State  of  the  Digital  Decade  Report  (September  2023),  https://digital-strategy.ec.europa.eu/en/library/2023-report-state-
digital-decade. Source: Enterprises using any AI technology as % enterprises (Eurostat - European Union survey on ICT usage 
and 
2023; 
(indicator 
https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai__custom_9268325/default/table?lang=en – EU DESI 2023). 

[E_AI_TANY], 

e-commerce 

ISOC_EB_AI 

enterprises 

code: 

in 

10 

 
 
 
 
 
 
 
Blockchain technologies16 have the lowest adoption rate across industrial ecosystems with an average uptake of 
3%. They are mostly used in the health and agri-food ecosystems, where they can be leveraged to ensure food 
safety and enhance transparency throughout their supply chains.  

2.3. Environmental impact of industrial ecosystems 

KEY MESSAGES: 

- Total net greenhouse gas emissions have fallen by 0.3% over the period from 2010-2021. 

- Material extraction in most industrial ecosystems has fallen slightly, except for agri-food and energy intensive 
industries, which have seen an increase over the past decade. 

- Industrial ecosystems increased their negative impact to the environmental ecosystem (i.g. loss of biodiversity) 
with a 2.3% compound annual growth rate from 2010 to 2021. 

- Land use and the water consumption have also been steadily growing, each at an estimated compound annual 
growth rate of around 1% in the most industrial ecosystems from 2010 to 2021. 

- Environmental impacts per value added have been decreasing in some industrial ecosystems such as construction.  

This  section  assesses  the  environmental  impact  of  the  14  industrial  ecosystems  by  adapting  the  European 
Environmental  Agency’s  environmental  indicators  typology17  in  six  areas  of  analysis  notably:  GHG  emissions, 
particulate matter emissions (air pollution), levels of material extraction, land use, blue water consumption, and 
damage to the environmental ecosystem.  Such an analysis of industrial ecosystems offers a snapshot of the main 
factors that cause pressure on the environment as a result of industrial development. The assessment of this impact 
is measured by Exiobase data.  

According to Exiobase data18, and as shown by Figure 5, material extraction across industrial ecosystems during 
the last 10 years declined, albeit slightly. This reduction may be due to the reduction in material extraction by the 
construction ecosystem (-0.7%), which is the major cause of material extraction. However, the agri-food and the 
energy intensive industries saw an increase in material extraction over the last decade, (0.5% and 1.4% respectively). 

Similarly, the total net greenhouse gas emissions from the EU industrial ecosystems fell by 0.3%,  over the period 
of 2010-2021 with the exception of the agri-food (0.1%) and energy-intensive industries (1.1%) ecosystems.  

On average, all industrial ecosystems increased their level of damage to the environmental ecosystem (i.e., damage 
to biodiversity) by 2.3% yearly (over the period from 2010-2021). Land use and blue water consumption in most 
industrial ecosystems have also been growing steadily. The estimated compound annual growth rate in land use 
was 1.2%, and 1.1% in blue water consumption over the period from 2010 to 2021.  The ecosystems that require 
more land use and blue water consumption are agri-food and tourism. 

16 Blockchain technologies are a particular type of DLT that employs cryptographic techniques to record and synchronize data 
in 'chains of blocks'. All types of Blockchain are DLTs but not all DLTs are Blockchains. Blockchain entails three technologies, 
the blockchain itself, distributed ledger technologies, and smart contracts. Together they represent a fault-tolerant systems 
synchronising data through consensus mechanisms, able to verify - peer to peer - the correctness of such data through hash 
functions and values without central authorities and executed upon some basic premises and protocols specified in digital form. 
17 Indicators (europa.eu) 
18 Exiobase is a global, detailed Multi-Regional Environmentally Extended Supply-Use Table (MR-SUT) and Input-Output Table 
(MR-IOT). It was developed by harmonizing and detailing supply-use tables for a large number of countries, estimating emissions 
and resource extractions by industry. Exiobase is a legitimate source of information referred by the European Environmental 
Agency, JRC and Eurostat and the European Commission to propose the regulation on carbon border adjustment mechanisms. 

11 

 
 
 
 
 
Figure 5: Environmental impacts of the EU industrial ecosystems in 2021 and over time 

Source: Technopolis Group based on Exiobase, 2023, for the European Monitor of Industrial Ecosystems (EMI) project 2023 

At a more granular level, within each industrial ecosystem, there are certain industries that drive the environmental 
impact.  

The agrifood ecosystem is the one that naturally requires more land use and blue water consumption, which have 
seen (for this ecosystem) a compound annual growth rate of 0.8% and 1% respectively from 2010 to 2021. Most 
environmental impacts of the ecosystem are driven by the manufacturing of food products. As regards blue water 
consumption more specifically, crop and animal production, hunting and related services are the key drivers. 

In energy-intensive industries, the manufacturing of rubber and plastic products were the major contributors to 
material extraction and blue water consumption. Overall, the energy-intensive industries ecosystem increased its 
material usage from 1 225 megatons in 2010 to 1 425 megatons in 2021. These results align with other studies 

12 

 
 
 
 
finding  that  in  2015,  seven  EU  countries  that  manufacture  rubber  and  plastic  were  major  contributors  to 
environmental damage per unit of production value19. On the other hand, the manufacturing of basic metals is the 
key driver of the damage to the environmental ecosystem, whereas the manufacturing of wood and wood products 
and cork is the key driver of land use in this industrial ecosystem.  

2.4. Private investments and funding per ecosystem  

KEY MESSAGES: 

- European private equity and venture capital investment in green tech and digital tech firms 20increased significantly 
in 2021 and 2022, followed by a drop in the first quarters of 2023. 

- In 2021, the ecosystems that attracted the most venture capital investments and private equity for digital tech 
firms were retail, electronics, and mobility, whereas for green tech companies, it was mobility, agrifood, and retail. 

- The industrial ecosystem that attracts the least amount of venture capital is textiles. 

- Since 2018, the EU has had an increasingly negative FDI balance in the renewables ecosystem. 

- The electronics ecosystem is one of the few industrial ecosystems that has maintained a positive net FDI balance 
since 2017. 

Private  funding  plays  a  crucial  role  in  driving  competitiveness  and  transformation  within industrial  ecosystems, 
enabling advancements in technology and infrastructure and helping industries adapt to digital trends and address 
pressing environmental challenges.  

This section looks at how private equity, venture capital, and foreign direct investments are supporting green and 
digital firms. Investment data has been captured from Crunchbase21, NetZero Insights22  and Trendeo23 and considers 
the 4 investment stages (seed, early investments, late investments, and exit). 

European private equity and venture capital investment (VC) for green and digital investments increased significantly 
in 2021 and 2022, followed by a drop in the first quarters of 2023. This can be seen in the venture capital investment 
analysis of industrial ecosystems (see Figure 6) and has been highlighted in several recent reports24 25.  

Private equity and venture capital investments into digital tech firms embedded in different ecosystems have 
been continuously increasing. The ecosystems that attracted the most investment in digital transformation in 2021 
include retail (42 billion euros), electronics (25 billion euros), and mobility (16 billion euros). 

19 The seven EU countries included Austria, Belgium, Germany, Denmark, France, Netherlands, and United Kingdom. See Brink, 
C., Drissen, E., Vollebergh, H., & Wilting, H. (2020). Accounting for Environmental Damage by Material Production and Use: A 
Comparison of Seven Western European Countries. (PBL Publication; Vol. 3512). Planbureau voor de Leefomgeving. 
20 Digital or green/environmentally sustainable companies have been defined as those that specifically serve or are part of the 
industrial ecosystem in focus and at the same time develop or deploy any of the green or digital technologies defined under 
the EMI project.  
21 https://news.crunchbase.com/venture/europe-vc-funding-drops-q1-2023/ 
22 The Net0 Platform enables users to filter organisations based on Technology, EU Taxonomy, Value Chain, Business model, 
funding data, stage, investors, etc. The data provided by Net) platform allow to get insights on climate tech investments. 
23 Trendeo: https://trendeo.net  
24 
at  Work 
https//www.investeurope.eu/research/private-equity-at-work/  
25 European VC funding drops 66% as seed takes a hit, US investors pull back: http://news.crunchbase.com/venture/europe-vc-
funding-drops-q1-2023/  

employment 

creation 

Private 

Europe 

Europe: 

across 

Equity 

Invest 

and 

job 

- 

| 

13 

 
 
 
 
 
Figure 6: Private equity and venture capital funding raised in digital transition-related technologies per 
industrial ecosystem 

Source: Technopolis Group based on Crunchbase and Net Zero Insights, for the European Monitor of Industrial Ecosystems (EMI) 
project 2023 

As regards green tech companies, private equity and venture capital investment shows a similar pattern with 
investments  increasing  since  2016.  Ecosystems  with  the  highest  private  equity  and  VC  funding  into  green 
technology-related firms include mobility, given the link to electric vehicles and shared mobility services. Agri-food 
follows suit, with investments into precision agriculture and other sustainability startups. Retail has also attracted 
investments, captured especially for second-hand retail and sharing economy26. 

26 The sharing economy is an economic model defined as a peer-to-peer(P2P) based activity of acquiring, providing, or sharing 
access to goods and services that is often facilitated by a community-based online platform. 

14 

 
 
 
 
Figure 7: Private equity and venture capital funding raised in green transition related technologies per 
industrial ecosystem 

Source: Technopolis Group based on Crunchbase and Net Zero Insights, for the European Monitor of Industrial Ecosystems (EMI) 
project 2023 

Generally speaking, foreign direct investments (FDI) are often regarded as a channel to foster technology and 
knowledge diffusion, as well as global value chain integration. Within the EU more specifically, intra-EU FDI also has 
an extremely relevant role, as it enables the creation of new value chains and industrial capacities. Nonetheless, it 
should be noted that FDI can also mean creation of dependencies in industrial value chains.  

With this in mind, trends in FDI have been analysed with data from foreign direct investments intelligence27 that 
tracks cross-border greenfield investment both intra EU, extra EU and globally, covering each industrial ecosystem.  

Figure  8  displays  the  industrial  ecosystems  that  witnessed  the  largest  FDI  flows,  including  renewable  energy, 
electronics, and mobility, transport and automotive. 

27 FDI Intelligence tracks cross-border greenfield investment covering all sectors and countries worldwide, it provides real-time 
monitoring  of  investment  projects,  capital  investment  and  job  creation  with  powerful  tools  to  track  and  profile  companies 
investing overseas. FDI Intelligence only track real projects that will create new jobs, therefore they do not cover merges and 
acquisitions.  

15 

 
 
 
 
 
 
 
 
 
 
 
 
Figure 8: Foreign direct investments per industrial ecosystem 

Source:  Technopolis  Group  calculations  based  on  foreign  direct  investments  insights  Intelligence  for  the  European  Monitor  of 
Industrial Ecosystems (EMI) project 2023 

In the field of renewable energy/energy, the EU’s net FDI balance has been increasingly negative, despite the 
increasing  number  of  greenfield  investments  since  2012.  This  is  due  to  a  rise  in  FDI  outflows  from  European 
countries to non-EU destinations since 2018, which amounted to a total of EUR 92 billion in 2022, compared to EUR 
53 billion of FDI inflows into the EU. The primary recipients of EU27 FDI outflows during the period of 2018-2022 
were the UK and the US, which received EUR 33 billion (33%) and EUR 88 billion (13%) respectively. On the other 
hand, intra-EU investments for the renewable energy sector have been increasing for the considered period, reaching 
a total of €EUR 38 billion in 2022, which represents a compound annual growth rate of 18.7% from 2015 to 2022. 

The  electronics  ecosystem  has  maintained  a  positive  net FDI  balance  since 2017,  with both  intra-EU  FDI  and 
inward investments increasing in recent years. Non-EU FDI inflows into the EU account for the largest volume of 
investments, reaching a peak of EUR 27.8 bn and experiencing an average growth rate of 83% since  2016. The 
United States was the top investor during this period, having invested EUR 44 bn (62% of total FDI), followed by 
China (22%). Looking at the European recipients, Germany ranks first, having received EUR 27.6 bn during the period 
2016-2022, followed by Ireland (EUR 17.6 bn), Hungary (EUR 12 bn), and Italy (EUR 6.4 bn). 

In the mobility, transport and automotive ecosystem, the net FDI balance has been negative between 2010 
and 2022. However, after 2018, FDI outflows from the EU in the ecosystem sharply decreased, resulting in a 50% 

16 

 
 
 
 
 
 
decrease in this deficit in 2022 compared to 2010. Germany is the largest European investor, both outside and 
intra-EU,  having  invested  a  total  of  EUR  84  bn  between  2015  and  2022.  Out  of  this  amount,  24.4%  of  the 
investments were directed to China. 

In the energy-intensive industries ecosystem, the EU also has a negative net FDI balance, amounting to EUR 
2.9 billion in 2022. However, this negative net FDI has decreased in volume due to a decrease in the outflows of 
investments by 53% in 2022 compared to 2010 data. Moreover, intra-EU27 investment and FDI flows into the EU27 
increased by 32% and by 63% respectively since 2015. 

On the other hand, the EU’s net FDI balance in agri-food has been increasingly negative since 2018. This can be 
attributed to an increasing outward investment flow from the EU, accompanied by a declining FDI inflow since 2017. 
The top recipients of EU FDI during the period between 2015 and 2022 were the United States, United Kingdom, 
Russia,  and  China.  Among  the  EU,  the  Netherlands  is  the  largest  investor  outside  the  EU  (followed  closely  by 
Germany), having invested a total of EUR 11.84 billion between 2015 and 2022. 

The top foreign investors into the EU economy during the considered period over the period from 2015 to 2022 
were  the  United  States  and  United  Kingdom,  which  invested  a  total  of  EUR  29.5  billion  and  EUR  15  billion 
respectively. The largest recipients in the EU during the same period were Poland, Spain, and France, accounting for 
27%, 15%, and 14% of the total FDI flowing into the EU.  

2.5. Supply and demand of skills to support the twin transition 

KEY MESSAGES: 

- The highest share of professionals indicating at least one green transition related skill28 are in construction, energy-
intensive industries and aerospace and defence. 

- Demand for green skills has been growing from 2019 to 2022, particularly in energy-renewables, which has seen 
an average annual growth rate of 40%.  

- The supply of moderate digital skills remains particularly limited in healthcare, agrifood, tourism, and textiles. 

- Cultural and creative industries, aerospace and defence, electronics, and construction are the ecosystems with the 
highest levels of supply of moderate digital skills. 

- The industrial ecosystems that recorded the highest demand of moderate to advanced digital skills were cultural 
and creative industries, construction, and energy 

Upskilling and reskilling is one cornerstone of the EU industrial policy. This section showcases the supply and demand 
of  green  and  digital skills  in each  industrial ecosystem by using  LinkedIn  and CEDEFOP  data.  The  use  of  these 
sources is a way of overcoming the lack of data sources where skills can be monitored. LinkedIn data is particularly 
informative, as it allows for the consideration of not only formal skills recognised by certifications or diplomas but 
also skills acquired on the job29. 

28 EMPLOYMENT AND SOCIAL AFFAIRS (EXTERNAL COM) - New taxonomy of skills for the green transition (europa.eu). Examples 
of green transition skills are: sustainable design or passive house building skills in construction,. agronomy in agri-food. 
29  It  is  important  to  highlight  the  information  provided  by  the  LinkeIn  users  in  their  profiles  is  based  on  their  self-
assessment/self-evaluation. 

17 

 
 
 
 
 
 
Supply and demand of green skills 

LinkedIn  data  show that  construction,  energy-intensive industries  and  aerospace  and defence  are the industrial 
ecosystems with the highest share of professionals indicating at least one green transition related skill30 on their 
LinkedIn profile.  

Nevertheless,  these  differences  should  be  treated  with  caution.  First,  some  industrial  ecosystems  have  strong 
environmental standards, so it is natural to find more professionals with the related skills. Second, although there 
is a need to hire environmental specialists, this green expertise is often outsourced to consulting companies. Third, 
some traditional functions have become greener without this change having been made explicit.  

In terms of demand for green skills, there is a growing interest for the integration of more sustainable processes, 
confirmed by the data on green job advertisements extracted from Cedefop which shows that in the period 2019 – 
202231, the demand for green skills in job advertisements grew consistently throughout most industrial ecosystems. 
More specifically, the share of job advertisements requiring green skills grew at an average annual growth ranging 
from 2% (textiles) to 40% (energy-renewables).  

Nevertheless, the analysis shows that the shares of job advertisements with the explicit requirement of a green 
transition-related skill are still low (below 3%) across most industrial ecosystems, except for the energy ecosystem. 

Figure 9: Share of online job advertisements requiring green skills

Source: Technopolis Group based on Cedefop Skillovate data, for the European Monitor of Industrial Ecosystems (EMI) project 2023 

Supply and demand of digital skills 

Increasing digital skills in the population is one of the biggest challenges of the EU, cutting across all objectives and 
targets32.  LinkedIn data shows that the industrial ecosystems with the highest supply of moderate digital skills 

30 EMPLOYMENT AND SOCIAL AFFAIRS (EXTERNAL COM) - New taxonomy of skills for the green transition (europa.eu) 
31 Outcome of assimilation of information through learning. Knowledge is the body of facts, principles, theories, and practices 
related to a field of study or work (Cedefop Glossary, 2023) 
32 2023 Report on the state of the Digital Decade | Shaping Europe’s digital future (europa.eu), P.25 

18 

 
 
 
 
 
 
(about 30%) are those that use advanced software and programming: cultural and creative industries and aerospace 
and defence. In industrial ecosystems that are ‘digital by definition’, such as the digital and the electronic industries, 
there is also a considerable share of professionals with digital skills (e.g., in electronics, it is 27%).  

Nevertheless, overall, the supply of digital skills remains limited, in particular in services-related ecosystems. For 
example,  in  the  tourism  industry,  only  5%  of  the  workforce  have  advanced  digital  skills  such  as  computer 
programming and database management. However, the data on the demand of digital skills in the next section 
indicates that the tourism industry is eager to attract more digital talents as 17% of the advertisements require 
digital skills.  

In the health ecosystem, the uptake of digital skills in the workforce seems slower than in other ecosystems. LinkedIn 
data indicates that only 13.7% of health professionals highlighted moderate digital skills on their profiles.  

As regards advanced digital skills (e.g. AI, robotics or IoT), these are found mostly in aerospace and defence and 
electronics. The lowest share of professionals with advanced digital skills were found in tourism, textiles and agri-
food.  

In  terms  of  demand  for  digital  skills,  Cedefop  data  indicates  that  there  are  large  variations  among  industrial 
ecosystems. Cultural and creative industries (CCI) are embracing the digital transition, as more than half of job 
advertisements (58%) require at least moderate digital skills. However, in the retail industry, digital skills are not in 
high demand, as only 4% of job advertisements required them. According to the Retail Pact for Skills, digital skills 
are however highly needed in the retail sector33, especially advanced IT skills for e-commerce and knowledge of 
data analytics.  

Figure 10: Share of online job advertisements requiring moderate and advanced digital skills in the EU27 

Source: Technopolis Group analysis based on Cedefop Skillovate data, for the European Monitor of Industrial Ecosystems (EMI) 
project 2023 

33 Pact for Skills – Skills Partnership for the Retail Ecosystem 

19 

 
 
 
 
 
 
At a more granular level, the skills which are driving the demand are business ICT systems, computer programming, 
databases, and performing data analysis. These skills are among the top 10 skills required in job advertisements 
for most industrial ecosystems. 

Many of these skills are connected with online marketing techniques, for which there is a clear demand, especially 
among service-based ecosystems34.  These skills include proficiency in digital marketing strategies, social media 
marketing, advanced web techniques such as web analytics and programming, as well as online analytics processing. 
The industrial ecosystems where this is especially relevant are tourism, textiles, retail, health, creative and cultural 
industries, proximity and social economy, and agri-food.  

That said, AI is also gaining importance in terms of skills demand – as highlighted by the job titles ‘AI Engineer’ and 
‘Head of AI’ ranking as the fastest growing digital titles. These findings indicate that there an increasing interest for 
integrating AI into industrial processes, especially in the digital and the aerospace and defence ecosystems. However, 
despite this strong growth, there is still a reported lack of supply of AI specialists35. 

3. Position of EU industry in the global technology race 
3.1. The EU’s innovation capacity in green and digital technologies 

KEY MESSAGES: 

- Levels of innovation for the EU and the US have remained stable in absolute terms, but both have lost some 
ground in relative terms to China. 

- Although the EU is still ahead in terms of green technologies, its innovation capacity in digital technologies is 
relatively limited compared to the China and the US, especially in AI and Big Data. 

-The EU displays a relatively strong position globally in terms of patent data in aerospace & defence, agri-food, 
construction, renewable energies, mobility, transport and automotive and textiles. 

In  this  section,  we  examine  data  provided  by  the  EPO’s  Worldwide  Patent  Statistical  Database36  pertaining  to 
transnational patents per individual technology and per industrial ecosystem, comparing the EU to the US and China. 

Comparing the EU, China, and the US on transnational patents indicate that the EU’s world share of transnational 
patents has been similar to that of the US, and in absolute terms, the level of innovation in the EU has remained 
stable. However, China's increase in global patent applications has led to a fall in the world share of transnational 
patents filed by the EU and the US respectively – in the EU’s case, from approximately 32% in 2010 to 23% in 
2020. By 2020, China had begun to catch up with both the 27 and the US, reaching a global share of transnational 
patents of 23% (up from a mere 7% in 2010).  

On green transition-related global patent applications, Figure 11 shows that the EU has maintained its leadership 
in terms of technology generation. However, its global share of transnational patents has fallen from above 30% in 
2010 to 24% in 2020, a similar trend to that of the US. In parallel, China's contribution has increased from about 

34 Pact for Skills – Skills Partnership for the Retail Ecosystem 
35 https://data.jrc.ec.europa.eu/collection/id-0130  
36 As a disclaimer, it should be noted that the use of patent data has some drawbacks. First, some companies may decide to 
pursue other strategies to market their inventions beyond patenting them. Second, the volume of transnational patents filed by 
each country does not  speak necessarily to  the quality of  those  same  patents.  Nevertheless,  patent data  is a widely used 
measure for tracking technological development activities, and by focusing on transnational patents (which are more expensive 
to file and maintain), we ensure that these patents are valid in more than one national market and that they are worth the 
investment needed to protect it. 

20 

 
 
 
 
 
4%  in  2010  to more  than  15%  in  2020.  The  EU’s  leadership  can  be  largely  attributed  to  its  strong  innovation 
capacity in Renewable Energy Technologies, especially wind power, where it has a world share of patents of 62%. 
However, the EU is now head-to-head with China as regards solar power (with both having shares of approximately 
27%).  It  should  also  be  noted  that  the  US  has  a  much  more  competitive  position  in  terms  of  energy-saving 
technologies, with a share of global patents of 41.3%. 

Figure  11:  World  share  in  patent  applications  of  the  EU,  US  and  China  in  green  transition  related 
technologies 

Source: Fraunhofer ISI based on Patstat for the European Monitor of Industrial Ecosystems (EMI) project 2023 

In the digital domain, Figure 12 shows that, in aggregate terms, the EU’s share has neither fallen faster than that 
of the US over the last fifteen years, nor has the absolute level of technology generation fallen. This is partially due 
to the fact that it has maintained its edge in Advanced Manufacturing technologies and IoT. However, the EU has 
lost ground in the field of Robotics, where China now leads with a global share of 30%. 

Additionally, the EU is visibly behind both China and the US in AI and Big Data (China is in the lead in AI with a share 
of 31%, whereas the US is in the lead in Big Data with a share of 28%). This is particularly relevant given the role 
of these technologies in operations or approaches that are key to making industry more competitive, such as data 
management  and  analysis,  predictive  maintenance,  human-machine  collaboration,  and  error  and  resource 
minimisation. 

The  EU  is  also  less  competitive  innovation-wise  in  the  domains  of  Micro-  and  Nanoelectronics,  Photonics,  and 
Advanced Materials, where Japan is in the lead. Japan is especially competitive in Advanced Materials, where it 
boasts a share of 37%, but in Micro- and Nanoelectronics, it is head-to-head with China. As regards Biotechnology, 
US leads with 44% of transnational patents. 

21 

 
 
 
 
 
 
Figure 12: World share in patent applications of the EU, USA and China in digital technologies 

Source: Fraunhofer ISI based on Patstat for the European Monitor of Industrial Ecosystems (EMI) project 2023 

When looking at patent data per industrial ecosystem, the EU displays a relatively strong technological position 
globally  in  various  industrial  ecosystems,  notably  in  aerospace  and  defence,  agri-food,  construction,  renewable 
energies, mobility, and textiles. However, it trails behind the US and China in the digital ecosystem. 

Figure  13: World  share  of  the  EU,  the US  and  China  in  transnational  patent  applications  in  industrial 
ecosystems related technologies and relevant for the digital and green transition (2018-20) 

Source: Fraunhofer ISI, based on EPO PATSTAT, for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

3.2. EU capacity to produce technology-based products 

KEY MESSAGES: 

- The EU is relatively self-sufficient in most industrial ecosystems, but it has dependencies in Digital 
and Electronics and in individual technologies 

- The EU maintains its ability to produce more than it imports as regards advanced manufacturing, 
robotics, energy-saving technologies, and renewable energy technologies. 

22 

 
 
 
 
 
- The EU produces considerably less than it imports in AI and Big Data.  

- The production of technology-based products and products that integrate advanced technologies 
has remained relatively stable over time. 

-  The  EU  has  been  able  to  translate  its  innovation  capacity  in  advanced  manufacturing  and 
renewable energy technologies into marketable results. 

Beyond innovation, actual production capacity matters to secure the EU’s competitiveness and strategic autonomy. 
In  this  section,  we  provide  data  from  Prodcom37  as  regards  the  self-sufficiency  of  the  EU  across  the  different 
industrial  ecosystems  and  across  different  advanced  technologies.  For  this,  we  analyse  data  on  EU  imports 
compared to EU-based production, as well as trade data from UNCOMTRADE. We complement these results with 
data on the weight of technology-based products and products that incorporate advanced technologies38 in the 
overall production of the EU. This allows us to assess the EU’s capacity to translate research into products.  

Figure 14 shows that the EU remains comparatively self-sufficient in most industrial ecosystems. In six out of ten 
production-oriented ecosystems, the relation of imports to local production does not exceed 50%, even if it is in 
most cases increasing. The exceptions to this are Aerospace and Defence and Textiles, where the relation of imports 
to  local  production  has  exceeded  60%  since  the  mid-2010s,  and  Digital  and  Electronics,  where  imports  have 
exceeded local production since the early 2010s.  

Figure 14: Ratio of EU imports to local EU production per industrial ecosystem from 2008 to 2020 (ratios 
above the -100% line indicate that the EU produced more than it imported in the technology at hand) 

0%

-50%

-100%

-150%

-200%

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Source: Fraunhofer ISI, based on UNCOMTRADE, for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

While  most  industrial  ecosystems  are  relatively  self-sufficient,  this  is  less  the  case  for  individual  advanced 
technologies. 

37 Prodcom is the title of the EU production statistics for Mining, Quarrying and Manufacturing, i.e., Sections B and C of the 
Statistical Classification of Economic Activities in the European Community (NACE Rev. 2). The headings of the Prodcom list are 
derived from the Harmonized System (HS) or the Combined Nomenclature (CN), which enables comparisons between production 
and trade statistics. The data only covers manufacturing goods, not services. 
38 Technology-based products are associated in whole or in a dominant part with the respective technology, i.e., they have these 
technologies as crucial components, unlike products that simply incorporate advanced technologies 

23 

 
 
 
 
 
 
 
Figure 15 shows the ratio of net imports in each technology in relation to local production of this same technology 
for each year from 2008 to 2020. Europe produces more than it imports in advanced materials and nanotechnology, 
biotechnology,  advanced  manufacturing  and  robotics,  and  renewable  energy  technologies.  However,  as  regards 
products  directly  based  on  digital  technologies  such  as  AI  or  big  data,  net  imports  are  high  in  relation  to  local 
production. Moreover, in the two main areas related to the green transition (renewable energies and energy saving 
technologies),  ratios  of  net  imports  to  local  production  have  also  increased,  as  have  those  in  Advanced 
Manufacturing, indicating an increasing dependence on imports. On the other hand, as regards Microelectronics and 
Digital Technologies for Mobility, ratios of net imports to local production have decreased somewhat, suggesting an 
increase in self-sufficiency. 

Figure 15: Ratio of EU imports of advanced technologies to EU production of those technologies from 
2008 to 2020 (ratios above the -100% line indicate that the EU produced more than it imported in the 
technology at hand) 

0%

-50%

-100%

-150%

-200%

-250%

-300%

-350%

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Source: Fraunhofer ISI, based on UNCOMTRADE, for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

These findings are complemented by the analysis of trade data sourced from UNCOMTRADE39, which shows that 
the EU is exporting more than both China and the US as regards advanced manufacturing and robotics. The EU is a 
net exporter in two other technology areas, i.e., renewable energy technologies and energy-saving technologies (in 
which, however, China has overtaken the EU). China, on its part, registered significant trade surpluses and is ahead 
of both the US and the EU on a wide array all technologies, particularly in Biotechnology, Advanced materials and 
Nanotechnology,  IoT,  and  AI.  However,  it  has  significant  trade  deficits  in  Digital  Security and  Micro-  and  Nano-
engineering both of which are considerably higher than the trade deficits recorded by both the US and the EU, and 
in advanced manufacturing and robotics. 

39 It is not possible to show the the ratio of US or Chinese imports of technology-based products to US or Chinese production 
of the latter, because Prodcom data (related to production) only covers the EU. Therefore, we use UNCOMTRADE data to measure 
US and Chinese capacity to produce technology-based goods vis-à-vis the EU. 

24 

 
 
 
 
 
Figure 16: Trade balance in relation to overall trade volume – comparison between EU27, China and USA 

Source: Fraunhofer ISI, based on UNCOMTRADE, for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

As regards the EU’s capacity to translate research into products, Figure 17 below shows that technology-based 
goods represented 6.32% of overall EU production of manufacturing goods in 2021.. Of this share, in 2021, key 
technologies included advanced manufacturing and robotics (1.5%), advanced materials and nanotechnology (1.4%), 
micro- and nanoelectronics and photonics (1.3%), and renewable energy technologies (1.2%).  Between 2010 and 
2021, the share of products directly based on advanced technologies increased 0.76%, with advanced materials 
and nanotechnology, and renewable energy technologies showing a particularly strong increase over the period of 
2020 to 2021. 

Products that integrate advanced technologies represented 19.3% of total EU production of manufacturing goods 
in 2021. Figure 18 below shows the importance of advanced manufacturing and robotics, advanced materials and 
nanotechnology, and biotechnology compared to other technologies. Over time, the relative importance of products 
that indirectly incorporate these technologies in the EU’s overall production fell slightly. Values remain quite stable 
for most technologies, with the exception of biotechnology, which shows a strong decrease over the period of 2020 
to 2021, and of renewable energy technologies, which shows a slight increase in recent years. 

25 

 
 
 
 
 
 
Figure 17: Technology-based goods as a percentage of total EU production over the period 2010-2021 

Source: IDEA Consult based on Eurostat [prom], for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

Figure  18:  Production  of  goods  incorporating  advanced  technologies  as  a  percentage  of  total  EU 
production over the period 2010-2021 

Source: IDEA Consult based on Eurostat [prom], for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

26 

 
 
 
 
 
 
 
 
 
 
3.3. Scaling-up capacity in the EU 

KEY MESSAGES: 

- The US has considerably higher number of scale-ups than the EU. 

- A deeper analysis reveals that the EU-US gap is narrowing, particularly in Mobility, Transport and Automotive, 
Electronics, Tourism, and Energy-intensive Industries. 

Scale-ups are key drivers of innovation in any industrial ecosystem, as they push other industrial firms to adopt 
their production and operation models. This section reviews the number of active scaleups per industrial ecosystem 
in the EU, the US, and China40, based on Crunchbase data41. 

Figure 17 below shows the number of scale-ups for the EU, the US, and China in absolute terms across the different 
industrial ecosystems. The US has a much larger number of scale-ups than the EU across all industrial ecosystems. 
However, the gap is smaller in some ecosystems than in others. The gap is particularly large in the healthcare 
ecosystem (where the number of EU scale-ups is 22% of the number of US scale-ups) and smallest in mobility 
(where it is 56% of the number of US scale-ups). 

Figure 19: Number of scale-ups related to twin transition technologies per industrial ecosystem in the 
EU, US and China and ratio of EU scaleups to US scaleups per industrial ecosystem 

Source: Technopolis Group, Crunchbase, 2023, for the European Monitor of Industrial Ecosystems (EMI) project (2023) 

However, an analysis of Crunchbase suggests that the gap is narrowing with the US both in start-ups and scale-
ups. This trend is particularly relevant for Mobility, Transport and Automotive, Electronics, Tourism, and Energy-
intensive Industries. At the start of 2023, and according to data collected by the Commission’s First SDD Report, 

40 A disclaimer must be made regarding the data presented for China: the data shown refers to scale-ups that are registered 
on the Crunchbase database, on which Chinese companies are not properly represented 
41 Crunchbase is a platform that provides business information on private and public companies, especialy in the tech industry. 

27 

 
 
 
 
 
 
only 249 unicorns42 were based in the EU as compared to 1,444 in the US and 330 in China.43 The largest EU 
unicorns include companies from the energy, retail, ICT, and mobility industries. Further information provided by the 
SDD Report acknowledges that the EU seems to have progressed well recently with respect to the Digital Decade 
target of 500 unicorns to reach by 2030, with analysts pointing also to a strong growth in the number of EU-based 
unicorns in the past decade. The report mentioned that should this trend continue,44 the EU is likely to meet the 
Digital Decade target on the number of unicorns in two years. Despite this, the report recommends further effort 
for the EU to achieve a leadership position on the global stage, facilitating the growth of the Union’s innovative 
scale-ups and improving their access to finance.45 

42 EU unicorn numbers stated are for EU-founded companies that continue to have their HQ in the EU. 
43 2023 Report on the state of the Digital Decade | Shaping Europe’s digital future (europa.eu), P.20. Source: Dealroom. 
44 See C(2023) 7500 ‘Communication from the Commission establishing the Union-level projected trajectories for the digital targets’ on the 
volatility of the trend over the past few years. 
45 2023 Report on the state of the Digital Decade | Shaping Europe’s digital future (europa.eu), P.20 

28 

 
 
 
 
 
ANNEX 

Introduction of the measurements and NACE 2 codes used to monitor industrial ecosystems towards 
green and digital transition 

The methodology builds on the definition of industrial ecosystems outlined in the 2021 and 2022 Annual Single 
Market Reports (ASMR), taking into account the key performance indicators and the methodology presented for 
constructing the data used for the analysis of industrial ecosystems.  

The industrial ecosystems methodology aims at analysing the EU economy. It extends and complement the 
mostly linear approach typical of value chain analysis to highlight the network of complex interlinkages between 
economic  actors  across  sectors  and  regions.  The  identified  industrial  ecosystems  have  a marked  pan-European 
nature, but their composition is very heterogeneous in terms of sectoral composition, size and scope. Industrial 
activities  represent  a  significant  share  of  course,  but  services  play  a  fundamental  role.  SMEs  represent  a  very 
significant share of these ecosystems, up to 99% in the case of tourism. The ecosystems do not cover the whole 
economy. Notably, the financial sector and most of the public sector are not included. 

Ecosystems  are  linked  to  each  other.  For  instance,  the Retail ecosystem  provides  (downstream) services to 
virtually all other ecosystems. Similarly, the Energy Intensive Industry ecosystem supplies inputs to many other 
ecosystems. Moreover, ecosystems overlap with each other, as some activities are relevant for more than one; 

The  statistical  definitions  of  the  industrial  ecosystems  as  laid  down  in  the  ASMRs  have  the  following 
characteristics: 

• 

They are based on 2-digits NACE classification. While a list of 4-digits sectors was initially used, data is 
not available for all sectors at such level of disaggregation.  

•  Whenever a 2-digits sector is considered too large or heterogeneous, a share was calculated using these 

possible approaches: 
−  Whenever possible, we identified the appropriate 4-digit sectors and calculated their share into the 
corresponding 2-digit sector. For that operation, we used data from the Structural Business Statistics. 
Weights were calculated for both Value Added and Employment. 

−  Use of specialised knowledge (specific studies or contacts with industry).  

As noted in Annual Single Market Report (ASMR) 202246, the data used to compile indicators on the ecosystems are 
derived from official statistics, including national accounts, Structural Business Statistics, and short-term business 
statistics. These statistical sources use the NACE rev.2 classification to identify enterprises according to their main 
activity. 

It is important to note that this level of granularity is not optimal to identify all the elements of the ecosystems, but 
most of the data sources used to calculate indicators are only available at the 2-digits level and therefore this 
affects the precision of the indicators.  

The  indicator  framework  used  by  EMI  for  the  monitoring  of  twin  transition  includes  the  same  NACE  rev.2 
classification as in ASMR 2021 by using a set of traditional and novel data sources that allow shedding new light 
on ongoing transformation patterns. However, the novelty of the analysis lies in the exploratory and innovative data 
sources such as Crunchbase, Exiobase and Linkedin, used across the different pillars of the analysis. These new 
sources of data allow to explore new areas of measurement for the green and digital transition that has not been 

46 DocsRoom - European Commission (europa.eu) 

29 

 
 
 
 
 
analysed  yet  by  any  other  Commission  initiative  or  observatory.  In  addition,  the  data  provided  is  industrial 
ecosystems specific which also brings a new perspective to monitor twin transition over time.  

Lastly,  the  analysis  covers  a  list  of  technologies  that  support  twin  transition.  These  lists  of  technologies  were 
selected among others as being the most strategic technologies for the competitiveness of the EU Internal Market. 
The  list  is  defined  as  advanced  technologies,  and  it  is  divided  in  two  groups;  technologies  that  support  digital 
transformation and technologies that support green transformation.  

Digital transformation 

1 

Advanced Manufacturing and Robotics 

   Advanced Manufacturing (ICA and Mechanical Engineering) 

   Robotics 

Artificial Intelligence 

Augmented and Virtual Reality  

Big Data  

Blockchain  

Cloud technologies 

Digital Security & Networks/ Cybersecurity 

Internet of Things  

Micro- and Nanoelectronics & Photonics 

2 

3 

4 

5 

6  

7 

8 

9 

10 

Online platforms 

Green transformation 

Green 
technologies 

Circular 
business 
models 

11 

12 

13 

14 

15 

16 

Advanced Materials and Nanotechnology 

Biotechnology  

Energy Saving Technologies 

Renewable Energy Technologies 

   Solar Power 

   Wind Power 

   Other (geothermal, hydropower, biomass) 

Clean Production Technologies 

Recycling Technologies  

Circular business models including: 

   Remanufacturing 
   Renting, leasing and related service models  
   Repair and maintenance services 
   Resell, reuse  
   Circular design (products that can be disassembled and recycled) 
   Design for durability (products that can last longer) 

30 

 
 
 
 
 
 
 
 
 
 
 
List of indicators used in this report 

Indicator 

Production global competitiveness: AT country share in global 
production of manufacturing goods 

Production country significance: Share of production in AT over a 
country’s total production of manufacturing goods 

Source 

Prodcom 

Time series 

2015-2020 

Prodcom 

2015-2020 

Trade 

Global emissions 

Material consumption 

Share of renewable energy 

Environmental management: Number of organisations with registered 
environmental management system ISO 14001, EMAS and other 

Use of circular technologies and business models 

Inventive activity global competitiveness: twin technology share in 
global patenting 

Inventive activity global competitiveness: AT country share in global 
patenting in Advanced Materials, Photonics, Biotechnology related to Green 
transition 

UNCOMTRADE 

Exiobase 

Exiobase 

Exiobase 

ISO 

Survey 

Patstat 

Patstat 

2015-2020 

2015-2021 

2015-2021 

2010-2019 

2010-2021 

2023 

2015-2020 

2015-2020 

Technology startups: Number of technology startups generating 
technologies; share in total start-ups 

Crunchbase 

2010-2022 

Technology startups: Number of technology startups generating 
technologies; share in total start-ups 

NetZero 

2010-2022 

Technology adoption: Share of companies adopting advanced (and basic) 
technologies  

Survey 

2023 

SMEs and Large company Private equity and Venture Capital (VC): 
Value of private equity and VC funding raised in technologies supporting 
the digital transition  

SMEs and Large company Private equity and Venture Capital (VC): 
Value of private equity and VC funding raised in technologies supporting 
the digital transition  

Private investment in transition 

Crunchbase 

2015-2022 

NetZero 

2015-2022 

FDI insights, 
Trendeo 

2016-2022 

Number of twin transition public procurement notices 

TED (+ National) 

2022-2023 

Supply of professionals - share of professionals with twin transition 
skills within total economy 

LinkedIn 

2019-2022 

Share of professionals with twin transition skills within IE total 

LinkedIn 

2019-2022 

Demand for professionals (basic to advanced digital transition expertise)   Cedefop 

2022 

31