Presentation from the online workshop: Statistical Needs for Research in Social Sciences, 29.03.2021

1. Nathalie Greenan, Silvia Napolitano
Expert Workshop on 29th of March 2021
How to measure technological
transformation with EU-wide statistical
surveys?

2. Introduction
Existing statistical surveys struggle in providing timely, comparable and
representative information on technological transformation.
• The literature does not provide a unique comprehensive definition of
technological transformation (Warhurst et al., 2019)
• The unit of analysis may differ

3. Key concepts:
the technological transformation
Innovation: complex phenomenon which
changes the existing production system
(Schumpeter, 1939)  not only big bang events
but also incremental innovations (Freeman and
Soete, 1997; Lundvall, 1992; Nelson, 1995).
Clusters of innovations  a dominant
technology establishes in the market (Perez,
2010).
Technological revolution : changes to the
technological system are sufficiently radical and
stimulate a whole industry, but also modify the
economic system, the institutional context and,
eventually, the cultural context (Perez, 2010)

4. Key concepts:
the current digital and industrial transformation
• Fifth technological revolution (from the ‘70s)  ICTs
• Recent new acceleration phase  increased network connectivity  big data,
cloud computing, artificial intelligence and the integration of digital and
analogue or operational technologies in manufacturing (Industry 4.0)
• Sluggish growth  incompleteness of the economic and social
transformation

5. Technological change as socially determined
Organisational change is more gradual than technological change
 Organisational change simultaneously concern management tools, organisational
structures, work practices and skills sets (Greenan, 2003)
 productive complementarities captures the idea that tangible and non-tangible
investments reinforce the performance of one another in the change process
(Milgrom and Roberts 1990)  call for a radical changes
 BUT the inertia of routines and trade-off which make the transition difficult
(Brynjolfsson and Milgrom 2013) slow down the organisational transformation
New business process model across global value chains has to deal with a knowledge
management issue (Bodrožić and Adler, 2018)
 favour enabling rather than coercive uses of new technologies, management
tools and organisational practices
 enhance the learning capacity of the organisation by engaging employees and
business partners to create and share new ideas, expertise and knowledge in
networks

6. Conceptual and measurement framework
Networks
Public
policies
and
institutional
arrangements
Outputs
New or
improved
products,
processes,
organisational
marketing
practices
Inputs
R&D,
digital and
industrial
technologies,
learning
capacity
Outcomes
Inequalities in
skills
utilisation,
employment,
occupational
risks, quality of
working life
The measurement framework on
technological transformation
and organisational practices

7. Measuring the technological transformation
with statistical surveys: measures’ types
Three types of measures:
1. measures of innovation activities, on the input side (e.g. R&D)
and on the output side;
2. measures of technology adoption and use;
3. measures of learning capacity in networks, related with
organisational structures and practices, management models
and tools.

8. Measuring the technological transformation with
statistical surveys: the identified datasets
1 measures of innovation activities
and innovation outputs
• Community Innovation Survey (CIS, Eurostat)  data about various aspects of the
implementation of innovation activities in firms + innovation outputs
2 measures of technology adoption
and use
2 yearly survey on the use of ICTs at the EU level:
• the Community survey on ICT usage and e-commerce in enterprises (Eurostat)
• the Community Survey on ICT usage in households and by individuals (Eurostat)
 no distinction between uses at home, at work or any other place.
3 measures of learning capacity • the European Company Survey (ECS, Eurofound): two different sources of
information (management and employee representative ) BUT instable
questionnaire
• the European Working Condition Survey (EWCS, Eurofound): stable questionnaire,
but only one source of information, the employees. It provides information about
work organisation and working practices.

9. Measuring the technological transformation with
statistical surveys: the identified datasets
1 measures of innovation activities
and innovation outputs
• Community Innovation Survey (CIS, Eurostat)  data about various aspects of the
implementation of innovation activities in firms + innovation outputs
2 measures of technology adoption
and use
2 yearly survey on the use of ICTs at the EU level:
• the Community survey on ICT usage and e-commerce in enterprises (Eurostat)
• the Community Survey on ICT usage in households and by individuals (Eurostat)
 no distinction between uses at home, at work or any other place.
3 measures of related new
managerial practices
• the European Company Survey (ECS, Eurofound): two different sources of
information (management and employee representative ) BUT instable
questionnaire
• the European Working Condition Survey (EWCS, Eurofound): stable questionnaire,
but only one source of information, the employees. It provides information about
work organisation and working practices.

10. Measuring the technological transformation
with statistical surveys: challenges
Measures of innovation :
• Direct measures about the introduction of a new or significantly
improved product, process, organisational or marketing method
by an enterprise (Oslo Manual)
• Black box:
• does not allow to capture the type of technology, how much it is advanced, nor how it
is used and embedded in the production process
• limited information on the direction of change and on the extent of the innovation
• no information on whether the company is technologically advanced

11. Measuring the technological transformation
with statistical surveys: challenges
Measures of technology adoption and use:
• allow for more fine grained analysis, but poor availability at micro level
• dynamic concept that, in the case of the current digital and industrial transformation,
seems particularly rapid in its pace
• No systematic method to update surveys according to technological evolutions

12. Measuring the technological transformation
with statistical surveys: challenges
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Label
E_CUSE Use computers
E_IACC Access to the Internet
E_DSL 79 DSL, ADSL connection
E_BROAD 90 Fixed broadband access
E_FIXBB 92 use of DSL or any other type of fixed broadband
E_MOBBB 69 Mobile broadband
E_BROAD2 96 Enterprises with broadband access (fixed or mobile)
E_WEB Website or Home Page,
E_AEBUY 45 Enterprises purchasing online
E_AESELL E_commerce sale (web sales)
E_AXSELL 5 Enterprises with EDI-type sales
E_EMPMD1_GT0 66 Provide to the persons employed port. devices that allow a mobile con. to the int. for bus. use
E_SM1_SNET 33 Use social networks (e.g. Facebook, LinkedIn, Xing, Viadeo, Yammer, etc.)
E_ERP1 Enterprises who have ERP software package to share information between different functional areas
E_SISC Sharing electronically business processes with their suppliers and/or customers
E_CRM Enterprises using software solutions like Customer Relationship Management (CRM)
E_RFID 4 Enterprises using Radio Frequency identification (RFID) technologies (as of 2014)
E_CC_HI 9 Buy high CC services (accounting software applications, CRM software, computing power)
E_CC_LO 7 Buy only low CC services (e-mail, office software, storage of files)
E_CC_ME 9 Buy only medium CC services (e-mail, office software, storage of files, hosting of the enterprise's database)
E_P3D 4 Use 3D printing
E_RBT 7 Use industrial or service robots
E_RBTI 5 Use industrial robots
E_RBTS 2 Use service robots

13. Measuring the technological transformation
with statistical surveys: challenges
Measures of the learning capacity of the organisation in networks
• From the managerial strategies to the employees level  sources of information
• Complementarities and bundling of management tools and organisational practices
intention and direction of change
• Dynamic concept, but less rapid than technological change
• Emergence of digitally operated networks
• Important data gap on this central issue, e.g. digital platforms
• at the employer level, not “standards” firms + no info on the use of digital platforms
by companies to deliver or purchase goods or services
• at the workers’ level, platform work shifts the employment relationship to grey areas,
blind spot

14. Data coverage in the identified datasets
TARGET TIME COUNTRIES NACE Rev. 2 LIMITATIONS
CIS Firms with
10 or more
employees
• 2010
• 2012
• 2014
+ 2016
(aggregated
level)
Micro-level: 15 countries
Macro-level: EU 27 Member
States, plus UK, Norway,
Serbia, Turkey, Iceland,
Switzerland, Macedonia and,
from 2016, Montenegro
A to N (2-digit level BUT
only NACE B to E +
wholesale trade (NACE
G46); + some services
sectors (NACE H, J, K and
M71 to M73) are
mandatory
Aggregated data
• aggregation
level may not be
chosen
• interaction and
complementarit
ies between
different
variables cannot
be explored,
except for those
combinations
that have been
anticipated.
ICT usage
and e-
commerce
in
enterprises
Firms with
10 or more
employees
• 2009-
2019
EU-Member States, plus
Iceland and Norway, United
Kingdom, Serbia, Turkey and
Macedonia
C to N + S (1-digit level +
some sub-aggregated for
some sections)
D-E aggregated
K excluded from 2014

15. Data coverage in the identified datasets
TARGET TIME COUNTRIES NACE Rev. 2 LIMITATIONS
CIS Firms with
10 or more
employees
• 2010
• 2012
• 2014
+ 2016
(aggregated
level)
Micro-level: 15 countries
Macro-level: EU 27 Member
States, plus UK, Norway,
Serbia, Turkey, Iceland,
Switzerland, Macedonia and,
from 2016, Montenegro
A to N (2-digit level BUT
only NACE B to E +
wholesale trade (NACE
G46); + some services
sectors (NACE H, J, K and
M71 to M73) are
mandatory
Aggregated data
• aggregation
level may not be
chosen
• interaction and
complementarit
ies between
different
variables,
except for those
combinations
that have been
anticipated.
ICT usage
and e-
commerce
in
enterprises
Firms with
10 or more
employees
• 2009-
2019
EU-Member States, plus
Iceland and Norway, United
Kingdom, Serbia, Turkey and
Macedonia
C to N + S (1-digit level +
some sub-aggregated for
some sections)
D-E aggregated
K excluded from 2014
EWCS Employed or
self-
employed at
the time of
the survey
• 2010
• 2015
EU28, Albania, North
Macedonia, Montenegro,
Serbia, Turkey, as well as
Norway and Switzerland
All sectors, 2-digit level Small sample size

16. Key messages
• Data gaps in the measurement of the digital and industrial transformation
with EU-wide statistical surveys:
1. Lack of unique dataset that collects information both at employer and
worker level  ECS, but non time depth
2. Available datasets are poorly accessible at micro level  limitations to
explore complementarities and interconnections among different
measures and to explore different levels of aggregations
3. Data coverage should be more extensive, considering that technological
transformation pervades all sectors
4. A lack of systematic method to nimbly adapt surveys to contextual changes
by introducing new questions and dropping obsolete ones
5. Together with the uses of digital and industrial technologies review the
uses of accompanying tools and organisational practices at the employer
level in particular those that equip relationships within networks in
global value chains