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Intangible capital has long been investigated as one of the key sources of growth. While it is often superficially assumed that intensive, knowledge driven growth is in particular important for developed economies, the catch-up process in countries such as Slovenia is also heavily dependent on intangible investments. The purpose of this chapter is to examine the importance of intangible investments for productivity growth and present the comparative position of Slovenia compared to Finland, Denmark and Norway using the innovative GLOBALINTO methodology and micro-based estimates of intangible capital.
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Hannu Piekkola, Carter Walter Bloch, Tjaša Redek, Marina Rybalka
Intangible capital has long been investigated as one of the key sources of
growth. This work stretches from Veblen’s (1908) definition stressing that “In-
tangible assets” are immaterial items of wealth, immaterial facts owned, valued,
and capitalized on an appraisement of the gain to be derived from their posses-
sion” to a more systematic analysis of the intensity of the investments as well
as their contribution to productivity growth beginning in the 1970s, and further
to the work from 2005 onwards of Corrado et al. (Corrado et al., 2005, 2006)
and their definition of intangible capital comprising computerised information,
innovative capital, and economic competencies. Intangible investments have
been acknowledged as an important source of productivity growth. For example,
Van Ark et al. (2009) showed that intangible investments can contribute a sig-
nificant proportion to total productivity growth.3 In the US, intangible capital
deepening contributed 0.83 p.p. out of 2.96 percent annual labour productivity
growth between 1995 and 2006 (van Ark et al., 2009). Following the spike in
productivity growth with the emerging new economy in the 1990s, productivity
growth stagnated and on average declined after the 2008 economic downturn
in developed countries (OECD, 2021). Interest in “new” growth determinants
thereby increased, and in addition to the focus on technology and innovation,
1 This work is p art of the GLOBALINTO p roject. The GLO BALINTO projec t has received fun ding from the Eur opean Union’s Horizo n 2020 pro-
gramme. The m echanisms to promote sm art, sustainabl e and inclusive growt h under grant agreeme nt No 822259. The data analysis is
based on lin ked employer-emp loyee data. For D enmark, the dat a was prepare d based on regis ter data made ava ilable by Statist ics Denmark ,
data for Fin land was prepar ed based on reg ister data mad e available by Stati stics Finlan d, data for Nor way was prepare d based on regi ster
data collec ted by Statistic s Norway. For Sloveni a, the data was prepar ed using the protec ted micro data sets with of the Sta tistical Of fice
of the Repub lic of Slovenia and the supp ort of the User relat ions section of t he Data publicatio n and communication d ivision (Statistic al
Off ice of the Republic of S lovenia, 2020).
2 Acknowledgement: The Slovenian data pre paration was also supp orted by Aleš Gorišek and Daša Farčnik. We would like to thank also
Matjaž Koman and Polona Domadenik Muren for their contributions.
3 But taking in to consideration th at also the estimate o f value added change s if intangible inve stment componen ts are no longer trea ted
as expend iture but rather a s investments (pl ease, see Corrado e t al., 2006, for detai ls).
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global value chains, intangible investments are seen as crucial in increasing
productivity growth as well as pushing the technological frontier outwards
(Hintzmann et al., 2021; Piekkola, 2011).
While it is often superficially assumed that intensive, knowledge driven
growth is in particular important for developed economies, the catch-up process
in countries such as Slovenia is also heavily dependent on intangible invest-
ments. But Slovenia on average lags behind the developed economies, focus-
ing more on tangible investments. For example, the 2020 European Investment
Survey showed that in Slovenia, 59 percent of all investments were investments
into machinery and equipment and only 20 percent into all intangible capital
components combined, compared to an average of 33 percent in European
economies. German companies, for example, reported investing 13 percent of
all spending into only software, data, IT networks, and further eight percent into
training, seven into R&D, and three percent into organizational improvements
(European Investnment Bank, 2020). These survey data results are also sup-
ported by micro-based estimates, developed within the H2020 GLOBALINTO
project (Piekkola et al., 2021b), which using extensive population data show that
Slovenia lags behind Finland, Denmark and Norway in intangible assets. On
the other hand, results show that intangible capital importantly contributes to
value added in all studied economies.
The purpose of this chapter is to examine the importance of intangible
investments for productivity growth and present the comparative position of
Slovenia using the innovative GLOBALINTO methodology and micro-based
estimates of intangible capital.
1 Intangible capital and productivity: theoretical background
and empirical evidence
A more in-depth empirical analysis of the growth process began in the 1940s,
1950s and 1960s with the papers of Tinbergen (1942), Solow (1957) and Kend-
rick (1961), and their analyses of the process of economic growth that showed
that the majority of growth was unexplained by either accumulation of capital
or labour. Later, Kendrick (1972), who studied the capital stock and tangible
and intangible investments between 1929 and 1966, showed that the share of
total investments in the US GDP rose, also because of the “increase () in the
intangible component comprising R&D, education and training, health, and
mobility”. Despite the evidence that economic growth must be related to in-
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tangible capital, capturing the value of intangibles was the main challenge in
the empirical analysis and consequently for a long period, the analysis of the
impact of “intangibles” was partial, usually limited to either R&D or human
resources (education) impact on economic growth (Cameron et al., 2005; Hall,
2011; Hall & Mairesse, 2006; Ibrahim et al., 2014; Lawrence & Murray, 2017;
McMahon, 1984; Romer, 1990). This measurement problem of intangible assets
and intangible investments came to the forefront of the analysis in the late 1990s
and the early 2000s (Lev, 2001; Nakamura, 1999). In 2005 and 2006, a system-
atic analysis of the intangibles began, based on the definition set by Corrado
et al. (2005, 2006), who defined intangible capital using a three-dimensional
approach. Intangible capital comprises: (1) computerised information (computer
software, computerised databases); (2) innovative capital (which mainly incor-
porates R&D, but also other innovative expenditure, such as design, mineral
exploration, etc.); and (3) economic competencies (brand equity, firm-specific
human capital, and organisational structure).
Overall, estimates of intangible investments show that some countries invest
a similar proportion in intangibles as in tangibles (e.g. the USA); otherwise, the
share of intangible investments is around 5 to 13 percent of GDP, depending on
the country and year (CoInvest Project, 2012; Corrado et al., 2009b; Fukao et
al., 2009; Innodrive, 2008; van Ark et al., 2009). For example, between 2000
and 2013 the level of intangible investments was on average 9.2 percent in the
EU-14 (Jona-Lasinio & Meliciani, 2018). Piekkola (2011) summarised key re-
sults on the impact of intangibles on European performance from the EU FP7
Innodrive project. First, if intangibles are considered as an investment and not
as costs, GDP increases by 5.5 percent. The differences between European coun-
tries (studied between 1995 and 2006/2008) are substantial, but convergence is
observed. Primarily high-income countries with a comparatively smaller share
of intangible capital have been investing more, which the authors see as a move
towards the knowledge economy and convergence. More recent GLOBALINTO
industry-level estimates show that intangible investments represent roughly
between 4.5 (Greece) and 17 percent (Sweden) of gross value added, which in-
dicates significant differences among EU economies in size (and structure) of
intangible investments. The overall contribution of intangibles to growth has
been significant, also when considering the interaction with countries’ inclusion
in global value chains (Roth, 2020; Tsakanikas et al., 2020).
Many other studies also confirm that intangible capital is very important
for economic growth in developed economies (that are most represented in the
literature). The contributions in other countries were also significant, ranging
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from around one quarter to around one third of total labour productivity growth
(Corrado et al., 2009a; Fukao et al., 2009; van Ark et al., 2009). Further, Roth
and Thum (2013b) find a positive and robust relationship between intangible
investments and labour productivity growth, in addition stressing that intan-
gibles explain a large share of the unexplained variance in labour productivity
growth. This relationship is found to be stronger between 1995 and 2000 than
between 2000 and 2005. Corrado et al. (2018) investigate the period between
2000 and 2013. They find that during the crisis, intangible investments were
relatively resilient, while tangible investments fell. Intangible investments also
bounced back relatively fast. This is consistent with the results of Roth (2020).
Jona-Lasinio and Meliciani (2018) also show that between 2000 and 2013 the
contribution of intangibles to total factor productivity growth was between 14
percent (Denmark) to even 30 percent or more (the Netherlands, Spain, Finland,
and the UK (even 33 percent). According to the authors, the overall decline in
labour productivity growth is mostly the result of the TFP slowdown, and not
tangible and intangible capital. Piekkola (2020) indeed shows that since the
2009 financial crisis the innovation-labour biased technical change in Finland
has not been decreasing, meaning that low growth is related to a decrease in
markups, which plays the dominant role in the TFP slowdown (TFP measured
as a residual also accounts for pure profit). However, it should be stressed that
while the components of intangible capital are on average positively related to
productivity growth, the size of the contribution (similarly as the size of invest-
ments in a certain component) depends also on the economy’s industrial struc-
ture and development (Griffith et al., 2004; Hall & Mairesse, 1995; Miyagawa,
2010; Roth & Thum, 2013a; van Ark et al., 2009; Wakelin, 2001).
2 Productivity gap and intangible investments in Slovenia:
macro and micro perspectives
Overall productivity growth has been slower after the 2008 crisis than ever
before (Redek et al., 2021). And although in emerging EU economies produc-
tivity was growing faster than in old EU members, Slovenia made significant
progress in GDP per hour worked (2015 prices in PPP) between 2000 and 2008
(Figure 1). By 2008 it reached 40.8 US$ per hour worked that corresponded to
83.6 percent of the average amount in the EU27. By 2020 productivity basically
remained the same in comparative terms, with Slovenian GDP per hour worked
increasing to only 83.9 percent of the EU27 average.
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Slovenia, which was once the most developed transition economy, is losing
its growth momentum and relative development position. In 2020, Slovakia
was ahead of Slovenia in hourly output produced, and more importantly, in
contrast to Slovenia, it increased its hourly GDP from 54 to 83 percent of the
EU27 average between 2000 and 2020, while Slovenia only increased it from
70.8 to 83.9 percent. Similarly, Czechia in the same time period increased its
hourly relative output from 58 to 77 percent of the EU average. Although eco-
Index (EU27=100)
GDP per hour worked
EU27Slovenia (EU=100) Slovenia
Figure 1. GDP per hour worked in Slovenia and the EU27 between
2000 and 2020, in US$ (left axis, 2015 constant US$ in PPP)
and index (right axis, EU27=100)
Source: OECD (2021).
Czech R.
Slovak R.
OECD - Total*
United Kingdom
Euro area
United States
75.4 74.4 74.3 72.0 70.7 70.2 68.0 67.0 66.3 61.1 60.2 59.5 54.7 54.5 52.3 52.2
45.8 45.7 44.2 42.3 42.1 41.0 40.3 38.6 38.5 35.5
Figure 2. GDP per hour worked in 2020*, 2015 constant US$ in PPP
*The asterisk next to a country implies that the data is for 2019.
Source: OECD (2021).
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nomic theory stresses that countries at the technological frontier grow slower,
Denmark for example increased its relative productivity from 131 to 138 percent
of the EU average between 2008 and 2020 – in the same period when Slovenia
stagnated. With 45.7 US$ per hour worked, Slovenia is well below the EU27
average and even further behind the developed economies it is trying to catch
up with (Figure 2, OECD, 2021).
There are numerous factors that affect the trajectories of national growth,
from global factors to domestic macroeconomic, institutional, financial and
other environmental factors, as well as firm-level determinants of growth. Af-
ter all, macroeconomic developments reflect firm-level dynamics. Firm-level
determinants include investments into tangible and intangible capital compo-
nents, as well as employment changes, sectoral specifics and other factors, such
as technological factors.
In this chapter, we are interested primarily in intangible investments. The
most recent widely available data from the European Investment Bank (survey
data, 2020) shows that Slovenia invests significantly less in intangible capital
than developed EU countries and focuses primarily on tangible investments
(Figure 1). This is, following the recent findings in the literature about key
contributions of intangibles to growth, myopic and strategically not the best
decision for a firm, which also hampers efficient productivity increase and
technological restructuring.
Land, business buildings and infrastructure Machinery and equipment Research and Development
Software, data, IT networks and website activities Training of employees Organisation and business
process improvements
Figure 3. Intangible and tangible investment structure in EU countries,
2020, as percentage of all investments
Source: European Investment Bank (2020).
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The analysis in continuing focuses on a selection of key sectors and firms with
at least five employees. Slovenia has a significantly different sectoral structure than
the three developed economies (Denmark, Finland and Norway). In particular, what
stands out are the significantly higher shares of medium-low tech manufacturing,
significantly lower shares of medium-high tech manufacturing (albeit low in all
countries), and lower shares of knowledge-intense services. Denmark, Slovenia and
Finland stand out in their share of high-tech firms. Slovenia was also strong in the
medium-high tech sector. However, the share of medium-low tech companies is in
Slovenia significantly higher than in other investigated countries, while also having
significantly less knowledge-intense services. Norway is a bit specific due to its
industrial focus and role of resources, nonetheless, higher-tech sectors are also more
pronounced. The sectoral structure on the one hand relates to the comparatively
poorer performance of Slovenian companies in terms of value added created (e.g.,
GDP per hours). On the other hand, low intangible investments will be problematic
if the country wants to restructure towards higher value added industries, especially
(as shown in our further analysis) when intangible investments are more important
in terms of value added in comparison to tangible investments.
3. Firm-level intangible investments in Denmark, Finland,
Norway and Slovenia and their contribution to value added
The Globalinto approach is based on assessing investments into intangible
capital components based on the occupational structure of employees. To cap-
ture the investments, which are divided into different components of intangible
LKIS servicesMGMT servicesRD servicesICT servicesKISlow-techmed-lowmed-highhigh-tech
Finland Norway Denmark Slovenia
Figure 4. Structure of Slovenian, Danish, Finnish, and Norwegian economies
by tech and knowledge intensity
Source: Piekkola et al., (2021a).
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assets (R&D, ICT and organizational capital), we apply the number of employees
in specific occupations according to the International Standard Classification
of Occupations (ISCO) (Table A1 in the Appendix). Furthermore, based on the
spending for their wages, the share of time spent on “intangibles” work and
the use of non-labour inputs, we calculate the total intangible investments. For
example, to measure the amount of ICT investments, the number of employees
with occupations such as “Information and Communications Technology Ser-
vices Managers”, “Information and Communications Technology Profession-
als”, “Information and Communications Technicians” are selected.4 A similar
approach is used for the other two categories of intangible capital.
Figure 5 presents the shares of intangible workers among all employees in
2017. Overall, Norway had the highest share of intangible workers among all em-
ployees in the private sector. In 2017, the organizational, ICT and R&D workers
in total represented more than 25 percent of all employees. Denmark followed
closely with just under a quarter of all employees being classified in one of the
intangibles categories. In Slovenia, intangible workers represented 16.4 percent of
all employees. The share of organizational capital workers was 4.3 percent, R&D
workers 9.5 percent and ICT workers 2.6 percent. Slovenia lagged significantly
behind Norway and Denmark, in particular when considering the total intangible
workers’ share. The lag was also significant in the share of ICT workers, which
was by far the lowest, being less than half of the share in Denmark.
4 Details avail able in Piekkola et al. (2021b).
OC worker R&D worker ICT worker
Figure 5. Share of intangible workers as percent of all employees
in the private sector, 2017*
*Danish data for 2016.
Source: Piekkola et al. (2021a).
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Nevertheless, lagging behind the Nordic countries, Slovenian companies have
been increasing the share of intangible employees. Their cumulative share (all
types combined) increased from 13.2 percent in 2007 to 16.4 percent in 2017 (Fig-
ure 6). The increase was most pronounced in the share of organizational workers.
All shares were increasing until 2013 and then the change slowed down or even
declined a bit (ICT and organizational). This change could be explained by the
general labour market trends and the lay-offs caused by the 2009 crisis and the
austerity crisis that followed. Companies in particular were more prone to lay-
ing off workers who were not their core employees, which often meant it was the
production workers who were let go (Prašnikar et al., 2017; Prašnikar, 2010, 2012).
However, when growth returned in 2014-2015, the shares either continued to grow
(R&D) or declined only a bit, which in view of overall increasing employment
means that the number of intangible employees was increasing.
Despite the increasing shares, Slovenia continues to lag behind the other
three economies, where the shares of intangible workers also increased in the
same period. For example, in Norway the share of all intangible workers com-
bined increased between 2008 and 2017 from 19.7 to 25.1 percent, in Denmark
from 17.4 percent in 2007 to 24.6 percent in 2016, while in Finland it remained
stable at about 18 percent given the downsizing of Nokia in 2009-2011.
The comparatively lower shares of intangible workers in Slovenia are rel-
evant also in view of the contribution of intangible assets to productivity growth
(estimation methodology explained in Piekkola et al., 2021b). The estimation
Organizational workers R&D workers ICT workers
Figure 6. Share of intangible workers as percent of all employees
in the private sector in Slovenia
Source: Piekkola et al. (2021a).
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method considered the elasticity of value added to tangible capital, employment
(non-intangible workers), average years of education, intangible capital compo-
nents with relevant controls. The estimation was carried out on the population
of companies with 20 or more employees for the period of ten years or more,
depending on country samples (details in Piekkola, 2021).
Comparing the role of intangibles in the creation of value added using the
elasticities of value added to intangible and tangible capital components shows
that intangible capital in Slovenia is on average as high or higher than in other in-
vestigated countries (Figure 3). Overall, the combined elasticity of value added to
intangible capital is 0.059 in Slovenia, in comparison to 0.056 in Denmark, 0.058
Finland, and 0.065 in Norway. Norway had the most pronounced role of tangible
capital among the economies, due to the characteristics of larger companies in
Norway. Importantly, the elasticity of value added to intangible capital in Slove-
nia (all components combined) is just as high as the elasticity of value added to
tangible capital. Overall (see Piekkola et al., 2021), the elasticity of output is still
highest with regards to employment (around 0.6-0.8), however, the contribution
of intangible capital is also high, especially if compared to tangible capital.
In view of sectoral differences and the Slovenian economic structure by sec-
tor, R&D intangibles were most important in R&D services, where the elastic-
ity of output was between 0.06 and 0.095 in the investigated economies. R&D
assets were also very important in the high to middle-high tech sectors, where
the elasticity of value added to R&D assets was even 0.08 in Norway and 0.04 in
Slovenia. In all Slovenian sectors, the contribution of R&D assets was positive
and highly significant. OC assets had the most pronounced effect in knowledge-
intense services, where the elasticity of value added to OC assets was between
0.02 and 0.03 in Finland and Norway, respectively. In Denmark, the impact of
OC was highest in R&D services, while in Slovenia, it had a relatively balanced
effect across the investigated sectors, between 0.011 and 0.016, but the effect
was insignificant in R&D services. In the R&D sector in Slovenia, interestingly,
the elasticity of value added to “tangible assets” was higher than the average
of the economy with 0.086. The elasticity of value added to tangible capital in
Slovenia was highest in high and middle-high tech sectors (0.092), followed
by the R&D sector and low to middle-high tech sectors (0.081). In Finland and
Norway, the elasticity of output in high and middle-high tech sectors was lower
than the average of the economy, while in Denmark it was higher. In Slovenia,
the elasticity of value added to tangible capital in high and middle-high tech
industries was significantly higher than on average in the economy (0.092 and
0.081 in comparison to 0.059), which highlights the importance of Slovenian
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high and middle-high tech industry companies to increase also their tangible
investment. Intangible investments in total had a comparatively higher impact
than tangible in low-tech manufacturing and knowledge-intense services. In the
case of low-tech manufacturing, this result could also highlight that the com-
paratively higher returns stem from the catch up process, which is driven not so
much by tangible, but rather intangible investments, also implies restructuring
towards higher value added sectors. Only in Denmark the impact of intangibles
was lower and partially insignificant. ICT assets have the highest impact in KIS
market services and ICT services, where the elasticity in Slovenia is around
0.033 (which is comparable to Norway (0.036), but lower than in Finland and
Denmark, where it is 0.04 or higher). On average (Figure 7), the elasticity of
value added to ICT assets is around 0.022 in Slovenia.
Policy implications
Productivity growth in Europe and in developed countries in general has
slowed down significantly from the pre-crisis levels. In the level of productivity,
Slovenia significantly lags behind developed economies, with its productivity
growth remaining low, comparable to the EU average after the 2008 crisis.
Productivity growth depends on a number of factors, including intangible capi-
tal, which is according to the literature one of the key sources of productivity
growth, both in less and more knowledge and technology intensive sectors.
0.020 0.023
0.022 0.023
Finland Norway Denmark Slovenia
Figure 7. Estimated elasticity of value added to intangible
asset types (all sectors, companies with at least 20 employees,
random effects estimation)*
*For detailed regression results and an estimation procedure explanation see Piekkola (2021).
Source: Piekkola, (2021).
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Being significantly behind the EU average also in intangible assets and in-
tangible investments, Slovenia has a number of challenges to face while catch-
ing up with the more developed countries. These issues are highly relevant to
policymakers as well as managers.
Intangibles have a direct impact on a firm’s productivity, which in the in-
vestigated economies is higher than the contribution of tangible capital, with
primarily R&D and organizational capital being the most important (Piekkola
et al., 2021b). In addition, firms’ mark-ups strongly depend on intangible assets
as well (Piekkola et al., 2021b). Given the strong and positive effects of intan-
gible assets, which by nature are more firm-specific, it can also be expected
that within-firm growth, a systematic and strategic approach to generating
intangible assets and managing them efficiently could become one of the key
sources of growth in the future. In Slovenia, managerial awareness of the role
of intangibles should be promoted. The earlier research for Slovenia showed that
only the best firms had a systematic approach to managing their intangibles,
while the majority, despite in fact acknowledging their lag, did not (Prašnikar
et al., 2017).
In the future, due to increasingly more service-oriented economies in Eu-
rope, the role of knowledge-intensive services will increase as well. Firstly,
their role will increase directly, as their share in GDP continues to grow and
their productivity depends largely on human capital (intangibles). On the other
hand, knowledge-intensive services can (depending on a country’s structure)
also strongly cooperate with other sectors, particularly manufacturing, and
therefore their increased productivity will also contribute to increased produc-
tivity in other sectors, creating a positive growth spiral.
The firm-specific (private) intangibles are one segment of intangible capital
covered in the literature. However, public intangibles, as well as “intangible”
commons, which may be present within clusters of companies, industries and
regions, will additionally spur growth. Such “intangible commons” have been
identified to be important in Slovenia also within global value chains (Prašnikar
et al., 2017). The state may further promote intangible investments by strength-
ening public intangibles (Corrado et al., 2017), which includes increasing digi-
talization, human capital investments and other.
Small and medium-sized companies (SMEs) have long been seen as one of
the key sources of growth in Schumpeterian creative destruction. In Slovenia,
the majority of firms are small and medium-sized with only a handful of large
— 13 —
companies. SMEs rely on their growth through the increased productivity of
intangibles workers and are especially dependent on knowledge spill-overs in
their industry. The state should promote their development by also considering
policies that would increase their interest in intangible investments and their
international orientation.
Tangible investments, of course, continue to be important, however, the ag-
gregate picture, revealing high interest of companies in Slovenia to invest in
buildings and machinery, may on the other hand be hiding underinvestments
in other sectors or sectoral misallocation. In particular, if Slovenia would like
to make a shift from low-medium tech industry to strengthen the high and
medium-high tech sectors and knowledge-intensive services, both national de-
velopment policymakers as well as managers should consider the longer-term
perspective and the rationality of the investment structure. This is especially
important also in view of global competition.
To conclude, it can be said that Slovenia is at the moment lagging behind the
developed countries and its growth has been more sluggish in the past decade
than before. To increase the pace of growth, a smart national policy approach
as well as a firm’s strategic focus will be required.
— 14 —
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Appendix 1: Intangible capital estimation –
selection of relevant occupations
Table A1: List of relevant occupations, used in intangible asset classification
and evaluation
1 Managers
112 OC Managing Directors and Chief Executives
12 OC Administrative and Commercial Managers
121 OC Business Services and Administration
122 Sales, Marketing and Development Managers
1221 OC Sales and Marketing Managers
1222 OC Advertising and Public Relations Managers
1223 R&D Research and Development Managers
13 Production and Specialized Services Managers
131 OC Production Managers in Agriculture,
Forestry and Fisheries
132 OC Manufacturing, Mining, Construction
and Distribution Managers
133 ICT Information and Communications
Technology Services Managers
134 OC Professional Services Managers
14 Hospitality, Retail and Other Services Managers
2 Professionals
21 Science and Engineering Professionals
211 R&D Physical and Earth Science Professionals
212 R&D Mathematicians, Actuaries and Statisticians
213 R&D Life Science Professionals
214 R&D Engineering Professionals
(excluding Electrotechnology)
215 R&D Electrotechnology Engineers
2151 Electrical Engineers
2152 R&D Electronics Engineers R&D
2153 ICT Telecommunications Engineers
216 R&D Architects, Planners, Surveyors
and Designers
22 Health Professionals
221 R&D Medical Doctors
222 R&D Nursing and Midwifery Professionals
223 Trad. and Complementary Medicine Professionals
224 Paramedical Practitioners
226 R&D Other Health Professionals
23 Teaching Professionals
24 Business and Administration Professionals
241 OC Finance Professionals
242 OC Administration Professionals
243 Sales, Marketing and Public Relations
25 ICT Information and Communications
Technology Professionals
26 Legal, Social and Cultural Professionals
3 Technicians and Associate Professionals
31 Science and Engineering Associate Professionals
311 R&D Physical and Engineering
Science Technicians
312 Mining, Manufacturing and Construction
313 Process Control Technicians
314 R&D Life Science Technicians and Related
Associate Professionals
315 Ship and Aircraft Controllers and Technicians
32 Health Associate Professionals
321 R&D Medical and Pharmaceutical Technicians
33 Business and Adm. Associate Professionals;
34 Legal, Social, Cultural Associate Professionals;
35 ICT Information and Communications
Source: Piekkola et al., 2021.
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ResearchGate has not been able to resolve any citations for this publication.
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