Low tech Manufactures in a globalized world

[Low Technology Lock-in]
[Explanatory factors to low technology sustainability in Danish manufacturing.]
Kenney Vesteraa Christiansen
MSc in Innovation, Knowledge and Economic Dynamics
MIKE-E - Cand Oecon
August 5, 2009
[Aalborg University]
Master Thesis
MSc in Innovation, Knowledge and Economic Dynamics (MIKE-E)
10 Semester.
Study number:
Low Technology Lock-In - Explanatory factors to low technology sustainability in Danish manufacturing
Birgitte Gregersen
Date for submission:
August 5, 2009
Name of author:
Kenney Vesteraa Christiansen
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Prefatory note
The thesis’ main objective is to provide insight into the economic performance and sustainability of
the Danish manufacturing industry. Using the most recent published data provided by the OECD, a
comparative calculation of the Danish manufacturing industry’s economic structure is executed, and
presents the recent shift in the manufacturing industry. The driver to analyze this subject is found in
the interest of industrial performance and the curiosity to find the underlying factors enabling advanced economies to compete internationally, when encompassing a large low technology manufacturing industry.
I wish to express my sincere thanks to professors Birgitte Gregersen and Bent Dalum for their guidance, insights, and assistance throughout the stages of this thesis. Additionally, thanks to the OECD
Directorate for Science, Technology and Industry for providing me with the latest available data
and the support and insight into their calculation methods.
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Table of Contents
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9.4.1 APPENDIX 4.1
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As international competition increases and emerging markets gain solid economic ground, fuzzy
words as research intensive, technology intensive and high technology have been regarded as the
revelation in managing global competition, relying on low waged labour and evolutionary processes. OECD, IMF, and EU scoreboards have emphasized the necessity to stature high technology
businesses, i.e. creating high tech funds and policies to provide grounding for “the future production”. However, significant shares of the manufacturing industry in small advanced economies1 rely
on low technology production, and have succeeded to compete through what could be basic learning and solid economic framework conditions.
Questioning the terminology of technology determination, from the OECD methods, provides understanding of the difficulties of analyzing advanced economies low technology industries in such a
context. Danish firms are innovative, however the innovation activity is incremental and fostered
from practical experience, thus the interaction between skilled labour and its ability to build up
competencies. A broader analytical tool to understand the Danish ability to compete on low technology, can be exploited from the context of National Systems of Innovation (NSI) and it explanatory factors of building up good framework conditions. The learning capabilities from NSI do not
only apply in product innovation. Process innovation, where firms are competing through operation
systems can also be traced back to NSI parameters as human capital, networking systems and public
support. Vertical specialization therefore partly reveals how Danish companies utilize these learning
capabilities, thus provide insight into how Danish manufactures can compete though they are low
tech specialized.
The thesis will analyze the robustness in Danish low technology in order to find out if political attention can be withdrawn from this area in the dimensions seen so far. In addition the thesis will
from a comparative study include other small countries to analyze the pattern within low technology
and examine whether a “low tech lock-in” in manufacturing production, can endanger future economic performance.
Definition interpreted from IMF’s advanced economy list, including GDP capita, human development index etc.
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Chapter 1 – Research area
1.1 The general picture of manufacturing
Over the last three decades, technology endorsement in manufacturing industries has been regarded
as the point of orientation in policymaking, when wanting to enhance growth and competiveness in
businesses (Hatzichronoglou.OECD:1997). Scholars, policymakers and public and private authorities and companies have in general a tendency to subscribe high technology enterprises, a predominant part of attention when analyzing economic performance and affluence (Hirsch-Kreinsen et
al:2008). Not surprising, knowing that this sector boost growth acceleration, win new markets, use
available resources to increase productivity and offer, in comparison to low tech, higher remuneration to the workforce they employ (Hatzichronoglou.OECD:1997)
Especially in recent years (2000-2007) the worlds competitive structure has shifted and a higher
degree of complexity and cutting edge technologies are now regarded as a buffer to low wage manufactures (Dicken:2007). Producing standard products in advanced nations has simply been regarded as an omission to exploit the ‘knowledge economy’ and lack in utilizing of the human capital
advantage, thus likely to jeopardize the competiveness and ease the process for rivals to catch up
(Furman, Porter & Stern:2002).
Glancing at the recent statistical surveys, the European Lisbon Scorecard VIII (2008) emphasize
that Europe cannot compete globally when relying on low technology, furthermore the scorecard
emphasizes that rapid changes are needed if Japan, the United States and emerging economies are to
be prevented in dominating the high technology sectors (Lisbon scorecard:2008). It must although
be taken into account that the heterogenic European economic structure cannot explain the European economies as an entity.
1.2 The Danish paradox
Considering the Danish manufacturing structure, a fundamental share of economic activity is concentrated around low and medium low technology production. In Denmark the low tech manufacturing plays a notable role in value added, employment, and international trade and have over the
years had a positive development supported by R&D activity, thus ensured competitiveness also in
comparison with other small economies (Christensen et al;2005).
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In addition Danish export specialization is predominant within low tech, and encompass twice the
share of low tech exports compared with the OECD average (Dalum:2006). A considerable part of
this export belongs to manufacturing within furniture, textile, and metal products and especially up
market products are represented, contributing with 44% of the total Danish export (FI:2008) (Ministry of economic and business affairs:2007).
Denmark’s high tech structure is however differentiating in comparison to other small countries
(Sweden, Finland, Ireland and the Netherlands), where these countries are holding one or more major transnational companies (TNC). Sweden, Finland, Ireland and the Netherlands high tech industries have benefitted from the advantage of having few dominant players creating positive sectorial
spillovers, such as Ericsson (Sweden), Nokia (Finland) Phillips (Netherlands) and the several of
multinationals companies in Ireland (Intel, IBM, DELL etc) 2 (Christensen et al:2008).
Although Denmark is export specialized in low technology, authors have criticized the deficiency in
high tech production stating, that low tech specialization is plausible to generate lower growth with
regard to employment and production (Christensen et al;2005). The predominant Danish low tech
sector has been considered as a national issue for almost two decades. In 1997 the Danish ministry
of research wrote in their annual research report that low tech businesses was accounting for 2/3 of
the Danish production and that “this is something we cannot live on and live with” (Ministry of
science, technology and development:1997&1990).
On one side the Danish low tech manufacturing industry seems to generate quite positive economic
results and on the other side allegations stating that low tech competiveness is untenable, gives an
equivocal picture of how low tech should be regarded in advanced economies, and whether the
Danish business structure stands in an indefensible situation, where changes must be made (innovationsraadet:2007).
The Danish situation has provoked the question, whether there exist a Danish paradox? A paradox
consisting of Denmark having a high volume of value added share and employment within low and
medium low tech, and simultaneous manage to present the fourth highest GDP per capita in the
world (Dalum:2006) (World Bank Development indicators:2007).
The reason to Irelands high tech share originates from the frame conditions given to US manufactures using the
country as an assembling platform for computer technologies.
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The question comes down to how low tech, Danish manufacturing really is? Explanations have
been that the Danish industry encompasses an underlying tacit knowledge, letting the interplay and
intuition in production enhance a key explanation (Dalum:2006) (Laestadius:2004). This explanation raises the question whether a non-measurable indicator, as tacit knowledge, is the best parameter to explain this phenomenon?
A more visible, approach could cover National Systems of Innovation (NSI), including a range of
indicator generating ideal national framework conditions spurring economic competiveness. NSI
explain the level of national, “education system, industrial relations, technical and scientific institutions, government policies, cultural traditions and many other national institutions”, and thus provide grounding for innovation activity, without using high expenditures on R&D3 (Freeman:1995).
The case that favorable framework conditions benefit Danish manufacturing, could be a more visible explanation to how knowledge and economic performance are generated from a broader approach. Furman, Porter and Stern (2001) are among a range of authors who, from an econometric
approach, illustrate how similarities in economic growth and national innovation converge (Furman,
Porter and Stern:2001) (European Innovation Scoreboard:2008) (Lisbon Scorecard Vlll:2008).
The NSI concept may furthermore provide groundwork to explain abilities within vertical specialization i.e.“imported intermediate goods in the production of goods to be exported” (Lüthje:2006).
The favorable low tech economic results could spring from importing basic intermediates, and use
the NSI abilities to manufacture high quality of low tech products, outcompeting low wage countries on quality. Dicken (2007) support this approach by emphasizing the importance of global value and supply chains, letting advanced nations produce low tech product, by solely using fast value
chain management.
As will be seen in chapter two, R&D is the solely parameter to determine technology classification.
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1.3 Problem statement
Today approximately 60% of the Danish value added and employment shares in manufacturing are
maintained by the low and medium low technology manufacturing industry. This has however not
prevented Denmark in obtaining the worlds fourth largest GDP per capita. Although manufacturing
does not encompass all economic activity, it is the instigator to the economic activity in other sectors, and the consequences of continuing low tech production, has therefore been stated to lead to
poor economic performance. Whether this scenario is likely will be analyzed from the following
research question:
What explanatory factors determine the sustainability in Danish low technology manufacturing?
To identify the explanatory factors for low tech sustainability, the thesis will work with two sub
1. How low tech is Danish manufacturing, using the variables value added growth, employment and export specialization as indicators?
2. Can Vertical specialization and National innovation systems reveal the understanding of
Denmark’s degree of low technology level?
The relevance of the research question must be seen in a light of policy making. Promoting high
technology when historical and present competitive advantages could be within low and medium
low technology would endanger future economic performance.
The motivation to study the low technology area is therefore to be found, in the question whether
low tech is a ‘good’ or a ‘bad’ for economic activity, and the explanatory factors to why and how it
still entails a dominant role in the Danish economy. In addition a transition from low to high technology sectors seems to have taken place in recent years, which allows the project to examine this
evolution further. Although many economic policy reports, handling Danish economy, is yearly
published, these analysis’ mostly concentrate on Danish economy in the broad picture rather than
manufacturing performance divided in technology categorizes. (Ministry of economic and business
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Studies regarding the questions of low and high technology classification and performance have
been vast analyzed and provides good insight into how EU and OECD manage low technology production (Robertson and Smith:2008) (Laestadius:2004). The aggregation in this literature although
provides little explanation to how Danish and small countries with some of the worlds highest GDP
shares manage low technology sustainability.
It could be argued that the analytical tools of the project are prejudiced, when choosing National
Systems of Innovation and vertical specialization in advance. The support in choosing this approach
must be found in existing studies questioning of Danish low tech. (Christensen et al:2008) (VejrupHansen et al:2006). The analytical tools are likely to explain whether there exist a Danish low tech
paradox, how Denmark compete on low tech manufacturing, why Danish production of high tech
products is so weak and the influence on Danish high tech when not encompassing one “mega
transnational company”.
Paradox and weaknesses in technology production areas however depends on the interpretation of
technology. Existing studies, analyzing the low technology field, still tumble when determining
what the technology definition is, and give an equivocal definition i.e. (Hirsch-Kreinsen et al:2008).
A determination of technology is necessary to justify further analysis, which will be done from the
common technology determination made in collaboration between OECD and Eurostat.
To understand low tech sustainability and the degree of the technology level in the Danish economy, the technology definition must be questioned. The Danish manufacturing structure consist of a
predominant part of Small Medium Enterprises (SME), where a majority are manufacturing products with low R&D intensity (Danish research analysis:2005). However these businesses are using
inter-firm collaboration, high skilled labour interaction, and external sources such as easy access to
finance, when innovating (FI:2008) (Christensen et al:2005). National Systems of Innovation (NSI)
therefore seem likely to determine a broader explanation to the competitiveness of low tech firm.
To support the question of low technology degree in the Danish manufacturing, and explain how
advanced economies can produce low technology goods, a likely and fair reasoning must be that an
increased utilization of supply and value chain management are present Cf. Dicken (2007). By exploiting these chains Danish businesses are likely to import labour abundant intermediate goods,
and embody these in export, thus creating an export specialization without producing the labour
abundant parts.
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The fact that Danish export specialization lies within low technology may provide another meaning
if it originates from foreign value added embodied in Danish low technology export.
1.4 Structure
The project will start discussing the concept of technology content and the controversies in connection with using the OECD approach (chapter two). Understanding and having a definition of technology allows moving on to chapter three analysing the Danish manufacturing’s importance to
overall economic growth, and examining the Danish manufacturing sector, divided according to
technology content. By doing so, the economic significance of low and medium low technology, is
revealed both within value added and employment share, and thus the influence on the Danish
economy in comparison with other small countries.
In addition the growth rate in recent years will be analyzed to see how Danish low technology contribute to economic growth. The data applied to estimate value added and employment shares will
be modelled from the OECD STAN database with the newest available figures from 2006. Although 2008 and to some extend 2009 figures are available in the Danish statistical database (Statistikbanken), benchmark figures are needed to make a comparative analysis to other small and bigger
Having calculated and analyzed the domestic framework, the Danish ability to compete internationally on manufacturing products will be examined in chapter four. The fact that international specialization spur to economic growth highlights the importance in Danish low technology competitiveness. Vertical specialization will in a later chapter (6) support how Danish low tech can manage to
be export specialized. Again comparable figures are applied, where these benchmarks are calculated
from the OECD STAN database.
Analyzing the explanatory factors of how Danish low technology manage to compete, chapter five
will start providing a historical explanation of low tech production and analyze the underlying tacit
knowledge in Danish manufacturing. This explanation will also uncover the interconnection between low tech support of high tech products, and overlap to the broader understanding of competitive framework conditions created by NSI. The main objective of presenting NSI is to emphasize
that the narrow OECD approach of technology determination may place Danish low tech in the
wrong category, and that broader determination would be appropriate to apply.
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Where NSI justifies the interpretation of technology understanding, chapter six and vertical specialization will provide an understanding to how low tech can compete internationally, competing with
low wage countries. Utilizing Hummels (2001) vertical specialization equation presented in chapter
six and the OECD STAN Input-Output tables, foreign value added embodied in Danish export will
be calculated.
Summing up: Low technology has been heavily neglected in the political debate and has been regarded as a negative parameter to economic growth (Hirsch-Kreinsen et al:2008). However, understanding the low technology determination in a broader sense, the political view to support an essential area in Danish economic could be found.
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Chapter 2 – Technology the right parameter?
High, medium and low technology, knowledge intensive, research intensive and technical intensive4
have been preached by economist and politicians ‘intensively’ in the last three decades. (HirschKreinsen et al:2008). Promoting special sectors by catchy words have shown itself as a good weapon in political matters, due to an increasingly social belief in scientific truths (Hirsch-Kreinsen et
al:2008). Words like: advanced, core, generic, strategic, revolutionary, high, progressive etc. have
been referred to as “moral economy”, defining a situation where technology content has been promoted to a ‘size’ that not necessarily indicate relative economic strength (Hirsch-Kreinsen et
al:2008). Although technology content has promoted some manufacturing sectors activity, higher
than others, it must still be regarded as fundamental to understand the implications and significance
of the measurements used in the classification. This chapter will try to reveal some of these implications.
2.1 The OECD definition of technology?
Why is it at all important to classify manufacturing sectors into technology degree? The OECDs
idea behind the separation of manufacturing industries was to provide a more ‘appropriate” tool
when analyzing international trade (Hatzichronoglou.OECD:1997). By doing so, especially politicians would have the opportunity to identify the ‘favourable’ sectors in industrial politics, thus having the best terms to allocate resources to the sectors with the plausible highest return. Since
OECD’s first revision in 1984, the classification has rested solely on the R&D parameter. OECD
present the following explanation to this:
“The Secretariat experimented with various criteria to identify the technology content of an industry, but quantification was hampered by the absence of data. As a result, R&D intensity became the
sole criterion” (Hatzichronoglou.OECD:1997).
The appearance and interest towards R&D estimations in industrial production was first applied in
1939 by Bernal, calculating the British R&D expenditure compared with the US and USSR’s
(Hirsch-Kreinsen et al:2008).
Where research intensive, technology intensive and high tech all are characterized by R&D to sales/turnover value
added – discussed later (Hirsch-Kreinsen et al:2008)
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The case that increasing British R&D expenditure was underestimated, which in comparison could
mean lower economic growth resulted in increased focus and awareness of the potential of the indicator. Hoffmeyer (1958) years later showed an international competitive advantage for US researchintensive industries, and thus supported the use of R&D as a competitive parameter. During the
1980’s, scorecards and scoreboards from the OECD, IMF and EU, increased the attention on R&D
in relation to economic performance.
So what is R&D? The OECD Research and Development parameter can be divided into two main
areas 1. Intramural expenditure covering “expenditures for R&D performed within a statistical unit
or sector of the economy” and a extramural expenditures, which are “payments for R&D performed
outside the statistical unit or sector of the economy” (Stats.OECD.org:2009). Both measures cover
three cost areas applied in the development of new product and processes 1. Capital Expenditure:
Land, buildings, instrument and equipment etc. 2. Other Current Costs: books, water, gas, materials
for laboratories and equipment to support R&D etc. 3. Labour Costs: Salary to R&D and non-R&D
personnel including bonuses, benefits etc. Both Capital Expenditure and Labour costs are calculated using annual costs. All calculations of R&D intensity are exclusive VAT, where R&D intensity
is defined by expenditure as a percentage of gross output and value added, calculated from converting the size of R&D expenditure into GDP Purchasing Power Parity (PPP) (OECD STI Scoreboard:2005). Furthermore depreciation of buildings, cars etc. are excluded (OECD handbook for
internationally comparative education statistics:2004).
Some of the difficulties of the OECD estimations of technology classifications were whether a high
tech industry is an industry producing or using highly advanced technology. This issue was clarified
by assuming that when productions use a high proportion of their turnover on R&D, it would automatically lead to the use of highly advanced technologies, and thus a high tech industry is one who
produces high tech goods.
Technology determinations are important to identify because of its influence and ability to increase
productivity and thus growth. In the OECD International Standard Industrial Classification ISIC
Rev. 3 (NACE rev. 1 in Europe)5 technology intensity is measured from two main indicators 1.
See appendix 3 for an overview of the listed technology industries by OECD’s definition.
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R&D divided by production and 2. R&D divided by value added. The size of both parameters are
converted into GDP Purchasing Power Parity (PPP), (OECD STI Scoreboard:2005).
To create the categories high, medium high, medium low and low technology OECD have used the
time period 1991-1999 estimating the expenditure for 12 OECD countries6 (OECD STI Scoreboard:2005) (Hatzichronoglou.OECD:1997). In appendix 4 and 4.1 the calculations done by the
OECD to determine technology division is made. This is done from the following method:
“Industries classified to higher categories have a higher average intensity for both indicators than industries in lower
categories. Also considered were: i) temporal stability: for adjacent years, industries classified to higher categories have
a higher average intensity than those in lower categories (see appendix 4 and 4.1); and ii) country median stability:
industries classified to the higher categories have a higher median intensity than those in lower categories.” (OECD
STI Scoreboard:2005)7
To transform these parameters into a more tangible measure the mean intensity for total manufacturing, marked with bold in appendix 4.1, can and have been used as a guideline to technology categorization. However the guideline Hirsch-Kreinsen et al (2005) have made and which have and is
used by various of authors only entail selected years of the analyzed time period 1991-1999 and
have a somewhat misleading construction. Table 1 below show the author’s construction of the
technology span estimated from the years 1991, 1995 and 1999.
High tech industries
Medium-high-tech industries
Medium-low-tech industries
Low-tech industries
R&D/Turnover > 5%
5% > R&D/Turnover > 3%
3% > R&D/Turnover > 0.9%
0.9% > R&D/Turnover > 0%
Table 1- R&D determination of Technology level (Hirsch-Kreinsen et al:2005)
The estimation Hirsch-Kreinsen et al (2005) have made is delivered with an R&D to turnover ratio,
which from the OECD definition accounted for above, is incorrect. As the OECD quote above
show, other indicators are in play when categorizing the industries. In addition the spans used in
table 1 to measure technology overlap and have little common sense also when only using the years
1991,1995 and 1999. An example could be that no R&D ratio, from the OECD estimations, in the
Medium high tech sector goes up to 5% and again that every category overlaps in start and end percentage value.
United States, Canada, Japan, Denmark, Finland, France, Germany, Ireland, Italy, Spain, Sweden and United Kingdom.
A normally third measure was included in ISIC rev 2 “R&D expenditure plus technology embodied in intermediate
and investment goods divided by production”, this is not included in the ISIC rev 3 due to lack in Input-output tables.
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Appling the lowest and highest mean intensity (bold figures in appendix 4.1) over the estimated
period 1991-1999, framework guidance would look like table 2 below.
High tech industries
Medium-high-tech industries
Medium-low-tech industries
Low-tech industries
R&D ratio ≥ 3.2%
3,1% ≥ R&D ratio ≥ 1%
0,9% ≥ R&D ratio ≥ 0,5%
0,4% ≥ R&D ratio ≥ 0%
Table 2- R&D determination of Technology level – stat from OECD Science Technology Scoreboard (2005)
This is although still a simplification of the determination of technology, nevertheless these ratios
are the average spans the technology industries would lie within when using the OECD estimation.
The OECD classification of manufacturing industries has been stable since it started. The large time
span and the stabilization median criterion have eliminated large fluctuation in sectors jumping
back and forth in the technology categories. Wong (1990) criticize the OECD estimation by adding:
“Since the R&D ratio captures only the relative effort of industries in acquiring new technological
knowledge, it says nothing about the current technological level of an industry” (Wong:1990).
Nevertheless the OECD definition also applied by Eurostat is the ‘common’ definition of technology and the ISIC 3 rev will be used throughout the project.
2.2 Questioning the Technology Determinants
Since Bernal’s (1939) and Hoffmeyer’s (1958) findings on R&D effectiveness on economic performance, the area has been vast analyzed and several conclusions to R&D’s influence has been
given, without clear-cut conclusions (Hirsch-Kreinsen et al:2008) (Wong:1990). Empirical research
has though identified, that industrial productions engaged with raw materials spend a smaller fraction of their sales on R&D compared with business with ‘highly manufactured character’ (HirschKreinsen et al:2008) .
Distributing R&D expenditure on the world map, the US and Asia spend larger fraction on R&D
than Europe. The diversification can be found in the US and Asian production of radical innovations, and highly innovative start up firms pressuring the established businesses. In Europe traditional industries, within low and medium low tech dominate overall production, which triggers lower R&D expenditure.
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However in a globalized world these expenditures are easier to track distributed on a company basis. This figurate from the EU Industrial R&D Investment Scoreboard (2007) which estimates the
R&D intensity for the 1000 largest EU and 1000 non-EU companies8 investing in R&D. The surveys top ten R&D intensive industries accounted for 86 % of all R&D spending, amounting 315€
million (JRC-IPTS:2007) (Hirsch-Kreinsen et al:2008).
Classification of R&D intensive industries therefore presents a rather blurry picture, with respect to
magnitude of a country’s high tech sector, when one or few big multinationals dominate the overall
R&D expenditure. Controversies have emerged on this behalf, when countries as Finland encompass a major R&D investor as Nokia. The controversies are fostered in the sense that major investors produce an inaccurate picture of sector division and make statistically figures very sensitive to
changes e.g. if big multinational choose to outsource production.
As an example, Finland’s overall high tech manufacturing sector accounted for 22.1% of all value
added share in manufacturing in 2006. Breaking the overall high tech figure into sector level as seen
in appendix 1, it clearly emerges that Radio, television and communication equipment is the overall
factor to the high tech success. Aggregated statistics allocate this contribution to the whole sector
rather than just Nokia. When analyzing the Radio, television and communication equipment sector
it becomes clear that Nokia’s name figurate heavily on the overall R&D. (OECD Science, Technology and Industry Outlook: 2008) Breaking Finland’s national R&D activity down from sectors into
companies, Nokia holds 47 %. of the national R&D investments.
A high tech classification can therefore from the OECD measurements be reduced to few sectors,
and thus representing a very scarce picture of the overall economy (OECD Science, Technology
and Industry Outlook:2008). Furthermore when only using one parameter, it cannot be totally rejected that other variables could influence the R&D ratio. Whether R&D investments will create a
solid high tech manufacturing sector, will from a Danish perspective be self-evident in the two following chapters.
”The term EU company concerns companies whose ultimate parent has its registered office in a Member State of the EU. Likewise, non-EU company
apply when the ultimate parent company is located outside the EU” (EU industrial R&D investment scoreboard:2007)
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Nevertheless, authors as Hirsch-Kreinsen et al (2008) define the fuzz of technology determination
and thus R&D investments in public matter as “OECD storytelling”, persuading governments to
overemphasize the value of science and technology investments. Hirsch-Kreinsen et al (2008) justify this argument by setting up nine points determining high tech subconscious understanding:
Premise: science and technology are for you and the society
Something new is happening in the economy
This something is different from the past
Lets call it NEW NAME (high technology)
This new phenomenon or event will bring big rewards, as well as the possibility of leadership to
those in the front line
It is therefore necessary to know more about it
Lets collect STATISTICS
It is also essential that policies be developed
Lets imagine a CONCEPTUAL FRAMEWORK to this end
Although these arguments are worth considering, countries and businesses still invest heavily in
R&D. Relating the R&D expenditure to economic growth theory, Grossman and Helpman (1991a,
1991b) and Aghion and Howitt (1992) state that “ endogenous growth literature all share the characteristic that a continued increase in the level of resources spent on the creation of new technologies leads to a continued increase in economic growth” (De Loo et al:1999).
Jones (1995) argues for a productivity paradox, where findings show little correlation between
productivity and technological spending9. De Loo et al (1999) have tried to find support in this
statement and listed the productivity paradox in three bullets below, highlighting that evolution in
economics has shifted the transparency in the R&D parameter. All bullets could apply for the Danish case, where close interaction among public and private enterprises and institutions has eliminated some of the magnitude in bullet number one, exploiting organizational management in bullet
two, and creating low technology niche products with respect to bullet number three. Whether this
can find support will be examined in proceeding chapters.
Jones (1995) analyze covers the US only, where De loo et al (1999) prove same pattern for European countries
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1. R&D statistics (particularly in small firms) seem to capture only a part, and sometimes even less than half
of the total efforts attributed to technical progress, which does not show up in official statistics (OECD 1992)
2. The nature of new technologies has changed in such a way that nowadays both complementary technologies have to be developed and radical organizational changes have to be made in order to gain a technology's
full potential (David 1990)
3. R&D efforts may have become more and more devoted to product differentiation than to (product or) process innovation, thus hardly affecting economic growth but more so total consumers' welfare (Soete 1996 and
Young 1998).
Relating R&D to economic activity and growth can from the three bullets generate some implications, especially when R&D is the only parameters in the analysis to determine the technology sectors allocation. To base politics on the R&D measure and stating that high tech is decisive for future
production can, from the OECD classification, still find support due to the sectors in this high tech
class manage high economic growth10 (OECD STI Scoreboard:2007).
However is cannot be concluded with certainty that these sectors are the most technological intensive, when the measure has serious deficiencies (Hirsch-Kreinsen et al:2008) (Wong:1990). Although R&D intensity has gained support to define high tech sectors by OECD definitions, it must
be stated that no single fixed consensus towards the definition of high tech industries exist
(Wong;1990) (cpu.gov:2007). The OECD definition may be regarded as the best available (Mackenzie:1996).
Lundvall et al (2008) find classes, besides high tech, that can obtain a strong innovation activity, if
hiring a person with a graduate degree. Especially small low tech firms can obtain significant positive impact when engaging graduate engineers in production. That patents should be able to measure technological intensity has been shown by Furman, Porter and Stern (2001), calculating the correlation effect between growth and patents granted.
Sector growth see OECD STI Scoreboard 2007 p. 213
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However using knowledge workers and patents tracking sectors technology intensity, also lead to
bias. Patents will usually only measure the granted ones, high tech sectors will often patent more
than low tech, and patents often focus solely on ‘new-to-the-world’ innovations, rather than incremental innovations. Furthermore criticism can be put forward for technology workers, engineers,
scientist etc. The human resource input also rely on praticians and pratical problemsolvers, which
not necessary are technology workers and the learning economy and tacit knowledge strength will
therefore be neglected. This issue will be further analyzed in chapter five.
In relation to the discussion of high technology, the term knowledge intensive is hard to avoid. The
two terms are often used interchangeably, however they are not. A company can have no R&D intensity, but many employed with a higher educational degree, which would make the business
knowledge intensive but not high tech. Knowledge intensive industries are therefore often determined from the knowledge input employed in the business (Hirsch-Kreinsen et al:2008). One could
argue that regardless of the definition of knowledge intensive, finding a none-knowledge-intensivebusiness in an advanced economy would be quite difficult, when these most likely have been outcompeted by the knowledge intensive businesses, or would possess some kind of knowledge input
making them knowledge intensive.
Keeping the critique in mind, the project will proceed with the OECD definition of technology intensity. The following chapter will analyze the domestic strength and determine whether Danish
low tech manufacturing can find support.
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Chapter 3 –Danish manufacturing production
As illustrated in the previous chapter, estimation of technology intensity can be widely debated. The
fact that the OECD high technology sectors indicate higher growth rates through history, must although be regarded as a fair reason to induce such sector. This chapter will, examine the magnitude
of Danish low technology manufacturing and vice versa high technology in order to provide on
overview of the Danish manufacturing production patterns, allowing to partly estimate the economic sustainability. In addition this chapter will partly answer the first sub question, “how low tech is
Danish manufacturing”, analyzing this question from a comparative study to other small economies
with similar economic structure and framework conditions as Denmark.
3.1 Manufacturing’s economic impact
Manufacturing is a generic term used to define materiel production, excluding agriculture and raw
materials (Andersen et al:2008). Manufacturing is embedded in human history of productions, from
basic tolls in the Stone and Iron Age to more efficiently machinery and power under the industrial
revolution in nineteen century. Manufacturing often requires skills and learning capabilities as the
industry adopts highly advanced technologies in the search towards efficient production methods.
As a result, these technologies often generates highly concentrated innovation activities not only on
the “floor” but also in organizational terms, which results in R&D investments or learning by doing
To illustrate manufacturing’s economic influence Dicken (2007) utilize the Kondratiev Waves originated from the work of Freeman and Perez (1988). The waves draw a cycle of innovation series, all
generated within manufacturing, thus describing the changes in the techno-economic paradigm and
economic evolution (Freeman and Perez:1988). Figure 1 sketch how the manufacturing industry
excels economic development through sequences of new innovations - mechanization, steam power,
electrical and heavy engineering, fordism and information and communication.
All waves contribute to the overall economy from manufacturing activity in either mechanical or
organizational matter. Although, Kondratiev waves normally are used in the description of innovations growth effect, these also provide a good indication to which role manufacturing has played
though history in economic growth.
Master Thesis
Figure 1 – Kondratiev Long-waves (Dicken:2007)
Schrader (2000) underline manufacturing’s importance with three main statements 1. History has
documented the fact that few nations have prospered without a strong manufacturing and agriculture sector 2. The economic health of a country is based on the level of manufacturing activity 3.
…manufacturing sector unlike other less technology sectors, invests heavily in R&D.
Manufacturing’s importance has on this behalf gained ground in the overall economy, and increased
the interest in classifying industries into technology level, in order to analyze economic influence.
In 1986 the OECD switched from the term knowledge intensity, and began to use ‘technology’,
which can be used interchangeably with: R&D intensive and technology intensive (Hirsch-Kreinsen
et al:2008). Scholars, policymakers and public and private companies commonly use the definition
‘knowledge intensive’ when handling discussions around the competition parameters. Examining
the Danish manufacturing structure and transition process from a technology perspective may provide a better understanding of the terminology and ease the main focus assigned to higher technology sectors.
3.2 Danish manufacturing – low tech strength?
From the above examination, the importance of manufacturing could apply to ‘the more the better’
principle and be regarded as a buffer to increasing globalization and to the balance of payment deficits (Andersen et al:2006). Besides the view that Danish manufacturing has been relying on low
tech production, the discussion whether it is too small in terms of value added and employment
shares, has been debated in several decades (innovationsrådet:2007) (Andersen et al:2006).
Master Thesis
In Denmark the manufacturing share of value added and employment amounted in 2006 for 14.2%
and 13.8% equal to 385.135 persons (OECD STAN database).11 Since 1840 manufacturing has been
a dominant part of Danish industrial production and has with few exceptions increased up until the
latest accurate OECD statistical figures in 200612. The movement in Danish manufacturing with
respect to value added and employment is sketched in figure 2.
Figure 2 – Movements in Danish value added and employment within manufacturing (Andersen et al:2008)
By historical means the declining employment combined with the overall increase in value added
indicate gain in efficiency in production i.e. figure 2. In 1986 manufacturing employment peaked
with 540.000 persons, since an annual average decline up to 2006 on -1.43% has been present. In
recent years (2000-2006) the decline in manufacturing employment has rapidly advanced, thus resulted in a decrease on 57922 persons equalling -3.8% in relative terms to the total economy.
(OECD STAN database)
From table 3 below, manufacturing is outlined in terms of branches. The figures reflect a declining
tendency at first glance in total manufacturing. The total manufacturing is although a relative measure, indicating that the rest of the Danish economy has or could have performed better in relative
terms, and thus the manufacturing industry has declined. As calculated in table 3, low tech still
holds the overall shares both within employment and value added. The decline in low tech in both
categorizes, illustrates a reallocation within manufacturing, in the current case to the high tech sector.
The figures are directly applied to manufacturing and it must be considered that manufacturing indirectly generate
growth and employment to the primary, tertiary and quaternary industry as well.
By accurate is meant in comparative connection. Figures from Denmark and Ireland are still insignificant in the
OECD database
Master Thesis
Benchmarking Danish performance with a small country average to achieve similarity in comparison, it appears that both Danish manufacturing employment and value added on average from low
technology to medium high tech is close to similar in shares. Only high tech is below the small
country average, which especially is due to the categorizes Radio, television and communication
equipment in the benchmark numbers (see appendix 1 and 2). Looking at the Danish high tech particularly pharmaceuticals gain ground, where companies as Novo Nordisk, H. Lundbeck and
Nomeco holds significant shares. If studying other dominate Danish industries, machinery and
equipment n.e.c. (medium high tech) and basic metals and fabricated metal products (medium low
tech), entail companies as Vestas, Danfoss and Grundfoss. The low tech industries with primary
food and beverage as the overall driver, entail Danish Crown, Arla, and Carlsberg. In relative terms
all these manufactures are not the biggest in the world within their industry measured on turnover
and employees. However companies as Danish Crown encompass 48.663 employees benchmarked
against the worlds number one Phillip Morris with 385.402. This ratio pattern is quite similar in the
other sectors as well. (Andersen et al:2008)
Table 3 – Percentage shares of manufacturing, Danish manufacturing development benchmarked to Small country average of Sweden, Finland,
Ireland, the Netherlands and Denmark. Own calculations based on OECD STAN database see also appendix 1&2
Master Thesis
The Danish high tech products have increased in share since 1996, rising with +5.6% in value added, where low tech decline with -4.6%. Comparing the Danish manufacturing structure with other
small countries, Sweden, Finland, the Netherlands and Ireland, a similar increasing trend for value
added and decreasing trend for employment is present. (see appendix 1 and 2). Finland holds the
biggest change in low tech with a decrease in value added on -10.2% and -5.8% in employment.
Denmark, Ireland, Finland, Sweden and the Netherlands in general all demonstrate a movement
from low technology to middle high or high technology for both value added and employment.
Digging deeper into the calculated figures in appendix 1 and 2 an aggregation of Danish low and
medium low tech accounts for 57.1% of the total manufacturing value added share and approximately 63.2% of the employment. Balanced against the total Danish industry, these shares respectively yield in 2006, 5.1% and 8.9% (OECD STAN:2009).
The Netherland is from appendix 1 and 2 the only small country that deviates from this pattern and
has a declining share in the high tech, hence pulling the average in table 3 down. The drivers behind
the high tech share average lies within other small countries as Finland, with a high tech value added share of 7.8% in 1996 of total manufacturing within Radio, television and communication
equipment. This number had in 2006 risen to 18%, illustrating how players like Nokia can affect the
overall result. The same pattern holds for Denmark and Sweden where especially pharmaceuticals
are a dominant player.
Evaluating the overall manufacturing structure, Denmark follow a similar shifting pattern within
technology structure in comparison t other small countries, where the small countries are a little
above Denmark in the high tech shares presented in table 3, mainly due to the telecommunication
sectors. Questioning the size of Danish manufacturing sector, Sweden, Finland and partly Ireland
have greater total size ratio to industry. Whether this is a relatively weakness can from an economic
historical approach not be concluded. From an overall perspective Denmark’s manufacturing structure is quite similar to the other small countries. That a small manufacturing sector through history
should have affected economic results can also not be confirmed, when World Bank Indicators estimating Denmark’s GDP per capita, higher than other small countries (World Bank:2007). Furthermore no theories conclude that a certain “optimal size” achieves greater economic yield. Andersen et al (2006) conclude in this connection that “in a market economy the important test of value
added is made in the market in the form of a willingness to pay” (Andersen et al:2006).
Master Thesis
It must although be added that the indirect activity the manufacturing industry generate, cannot be
disregarded. The manufacturing industry requires financial services, transport, R&D, organizations
etc. which activities generates both value added and employment. Manufacturing may therefore
consequently be regarded as a main driver in overall economic activity (Schrader:2000). Figures
from the service industry presents a good reason to believe that Danish manufacturing industry
positively affect the service sectors in value added growth and visa versa.
Looking at recent published figures the Danish service sector provides a larger value added share in
comparison to the other countries listed in appendix 1 and 2, with exception of the Netherlands
(OECD:2008)13. Especially the Transport sector with big Danish companies as Maersk and DSV,
but also finance and research and development sectors are supporting Danish manufacturing. (Ministry of economic and business affairs:2007) Including service measures when analyzing manufacturing size would therefore be appropriate in order to generate indirect employment and value added
measures. This will although not be further treated.
From this part, it has been shown that the Danish manufacturing pattern has experiencing no big
fluctuation in comparison to other small counties. The high shares of low and medium low technology although pop the question if low tech is equal to low growth. (innovationsraadet:2007).
3.3 Danish economy - Does a growth issue exist?
When examining Danish manufacturing and whether low tech specialisation occurs, the recent critique of Danish deficiency in growth is hard to avoid. Manufacturing shares provides a good indication to the strength in Danish manufacturing and indirect national economic influence though
employment. Another question is however manufacturing’s ability to generate economic growth
and affluence. Since the 1980s experts have believed in de-industrialization or hollowing out of
western industries, in connection to the discussion of outsourcing and off shoring. With respect to
technology importance in both theory and practise, manufacturing’s benefit to overall economic
growth becomes interesting.
Total economy, both private and public sector included (2008)
Master Thesis
Denmark has since 1992 had a real growth average below OECDs, thus encountered criticism from
the Danish innovation council in 2007 and the European innovation scoreboard 2008 in “economic
effects”. The innovation council’s report is created as a screenplay to emphasize the Danish weaknesses in an increasing globalised world. The report state that Denmark faces real growth crises,
having had lower growth rates than the OECD average from 1992-2005 (innovationsraadet:2007).
Figure 3 illustrates how Danish real GDP growth is placed below the OECD average. Denmark has
from a three year average had an average growth rate at 2.4%, meaning that the Danish growth has
been one of the lowest in comparison to other western countries (OECD average: 2.7%) (innovation
council:2007) (OECD factbook:2009).
Especially new eastern European countries have with the EU membership managed to produce
higher growth rates, and thus increased OECD average significantly (OECD factbook:2009). The
thought could strike that, countries like Slovakia and the Czech Republic had increased growth, as a
result of low tech production moved to these countries from advanced European economies. This is
not the case. Low tech growth has in fact declined with approximately 5% to 7% in the period
2000-2007 for both countries, and the medium high and high tech sectors has therefore been the
driver (OECD factbook:2009).
Figure 3: OECD factbook 2009 – Real GDP growth
The Danish innovation council characterizes the Danish situation as a “growth in crisis”. Denmark
is ranked in top at the international ranking reports: Global Competitiveness Report, IMF’s World
Competitiveness Yearbook and European Innovation Scoreboard (innovation council:2007).
Master Thesis
Furthermore, Denmark has been announced as the world’s foremost e- ready country. Taking the
issue to the focal point, the innovation council state that political plans should be induced, exploiting these good results, however no specific ideas are given in the report. As seen in figure 3, comparative small countries as Finland, Ireland and Sweden have all managed higher growth rates than
Denmark. Whether the comparison is fair, due to big growth machines as Nokia, Ericsson and the
Irish multinational miracle can be discussed. However the countries still possess these major industries, although authors continue deducting them to get a more refined economic picture. (OECD
technology and industry outlook;2008)
3.4 Danish manufacturing – does a growth issue exist?
Christensen et al (2008) who analyses the Danish national innovation system, pose the question
“Why is Danish industrial production so weak in high tech products?” (Christensen et al:2008).
Whether low or high tech productions are the instigators behind the poor growth results can be partly
concluded from table 4. From table 4, a calculation
of the growth contribution within employment and
value added growth is estimated from an average
annual growth over a five-year period is made,
 K  K t 1 
100 . The bold
simply algebraic put as  t
 K t 1 
numbers are total growth in manufacturing contribution to employment and value added. Especially the
Danish medium high and medium low tech sector,
stands as the main driver. As mentioned, a shifting
pattern from low to high technology has existed in
recent years, and the low tech sector, besides its
overall economic shares in employment and value
added, has not been the main driver to increase
Table 4: Yearly percentage growth from a five year average
(end year 2006) Ireland value added end year 2005. SWE
and DK end year of employment 2005 (OECD STAN:2009)
growth. Medium high and medium low tech productions have on the other hand, increased on average relatively more than the overall economy
growth, reaching 3,6% and 3% in value added growth over an five year average.
Master Thesis
From the two parameters used in table 4, the two sectors are contributing positively to the overall
Danish economy and are in relative terms holding a stabile position, in comparison to other small
countries (OECD STAN:2009). The comparative framework shows a rather surprisingly low
growth in recent Irish high tech activity. On the other hand Irelands low tech, especially rubber and
plastic products have increased with over 17% over the five-year average. Sweden, though, represents the expected value of high tech growth, with significant growth in Radio and telecommunication and medical equipment.
Both Sweden and Finland have decreasing growth in their low tech sectors, complemented with
large growth rates in the other sectors, where Sweden manage to boom in high tech production. The
same pattern is valid for Finland, where the Netherlands mainly increases growth within the medium tech categories hereunder petroleum products and chemicals products.
From table 4 a productivity measure is also illustrated in the sense that value added holds a higher
growth rate than employment (Andersen et al:2008). A decreasing employment combined with increased value added, highlights the labour unit productivity. Using labour as measurement has some
implications, when other parameters often stimulate the productivity as well. A high degree of capital could distort the picture of labour productivity. On the other hand if labour productivity increases, it could be tracked back to the ability the use the capital more efficiently, hence having the best
productive worker.14
3.5 Summing up
From the OECD STAN Database Denmark has experienced a decreasing low tech share and transition from low tech to higher technology sector appears. The currently increase from medium high
and medium low technology sectors, seems to manage globalization with other small economies,
without holding a big multinational company. From the above figures it cannot be rejected or confirmed that Denmark holds a ‘wrong size’ based on employment and value added. Denmark has
historically gained efficiency in manufacturing production, and in recent years the shift from low to
higher technology manufacturing must be regarded as a sound development.
Models as the EU KLEMS (capital, Labour, Energy, Material, Service inputs) has been made to measure the multifactor’s productivity.
Master Thesis
In analyzing technology strength, international specialization plays an important role. International
specialization would be able to reveal Danish low tech goods competitive strength in international
comparison, when low waged countries as well could produce these goods.
According to theorists as A. Smith and N. Kaldor, international specialization is likely to lead to
increased specialization and growth, the importance in Danish competitive advantage is therefore
worth to question when entering the market with low tech manufacturing (Laursen:2000). In order
to analyze these statements and the robustness of Danish low tech on international affairs, the next
chapter will proceed within international specialization.
Master Thesis
Chapter 4 – International specialization
The question on whether specialisation is necessary to competitive strength has been controversial
for decades, and several factors have proven it worth believing that international factors can benefit
domestic growth (Laursen:2000). As referred to above, Kaldor has stressed that economic growth
performance is highly correlated with a country’s performance in trade. Krugmann and Obstfeld
(2006) support the argument showing that the interaction not only creates mutual economic gains,
but also mutual specialization patterns. The goal of this chapter is to analyze whether Danish low
tech holds comparative advantages in comparison to other OECD countries, or if low tech can
weaken Danish trade, and thus domestic growth and affluence.
From the OECD STI Scoreboard (2007) Danish low tech and high tech can be concluded to hold a
revealed comparative advantage, calculated on the performance to the total manufacturing industry.
Although the trade balance contribute positively from these two sectors, OECD trade within manufacturing technology areas are rather dispersed with exception of low technology. From figure 4
below the fact that Denmark holds a revealed competitive advantage in low tech is deviating from
the overall OECD picture. The important and interesting question is however, how strong is Danish
low tech in comparison to other countries?
Figure 4 – Growth in OECD manufacturing trade by industry and technological intensity (Average 1996-2005) (OECD STI Scoreboard:2007)
Master Thesis
In order to answer these questions, export specialization is analyzed to find the relative strength.
Strength and weaknesses must although be analyzed in a broader perspective, and the role of imports would provide a good indication of whether low tech relies on intermediate goods (components), thus revealing an understanding of Danish low tech specialisation, and answer how low tech
this structure really is (OECD STI Scoreboard:2007). Import will therefore be included in chapter
five, vertical specialization.
4.1 Theoretical reasoning to international specialization
To underline the mutual gain from trade and identify specializations pattern from a theoretical angle, the Heckscher-Ohlin-Samuelon model (HOS) gives a good interpretation to this section. In
comparison to Ricardo’s principles of political economy and taxation (1817), which entailed labour
productivity as parameter, the HOS model explain trade relations by difference in national endowments. In relation to the low tech paradox Ricardos comparative analyzes was determined from the
comparative productivity, thus technology. Trying to draw a comparison to the paradox, technology
is difficult to use as only parameter to explain national growth. HOS enclosed besides labour, other
production factors as, capital, land and natural resources in their model and examined the comparative advantage in those sectors, which holds an advantage within the country’s production factors.
As will be seen in chapter five, this assumption in not completely wrong, as historical resourcestrong-industries, play an overall role in present production. Whether a country’s production factors
play a dominant role today, will figurate from chapter six, where advanced economies production
factors and competitive advantage are likely to be within services and knowledge.
From figure 5 the HOS model is drawn. Using inspiration from Møller Nielsen et al (1997) and
Christiansen (2007) the model assumes 2x2x2 form: two countries or regions each possess an endowment (two goods) characterized by each country’s productions factors (two factors). Furthermore preferences and technology are assumed as identical. Approaching the model from a low and
high tech perspective, it will be assumed that EU produce pharmaceuticals and Africa produce sugar.
The concave line in figure 5 sketch the production opportunities given to the two parties, where
labour and capital settle in fixed proportions. Along the concave line the parties can move down
substituting one good from another.
Master Thesis
Assuming that EU substitutes some pharmaceutical for sugar production, some of the fixed production factors would not directly could be allocated to engage in sugar production, i.e. a reallocation
of production would increase opportunity costs, thus the EU would submit more of product Y in
order to produce one unit X.
This could be interpreted as the EU would solely produce pharmaceuticals when holding an absolute advantage, but as in the Ricardian trade model the mindset of relative advantage plays a role.
To find the optimal set of endowments produced, the isovaluelines from microeconomic profit maximisation function can be used to write the value of the production. By writing the isoprofit line:
  PEUm M  PAfricasS  C , where π determines the profit, (P) price, (m) pharmaceuticals and (C) is
production cost. Rearranging the equation gives the isovalueline, M 
value on Y axis is
 C
with a slope.
 C
where the
 MRT  Opportunity  Cost Form microeconom-
ics the marginal rate of transformations allows identifying the substitution effect and reaching the
optimal production
Figure 5 – Specialized advantages by international trade (Møller Nielsen et al:1997)
Assuming that both economies are closed the optimal bundle to produce in figure 5 would be at the
dotted line in (a) in the point where Z EU touches the concave production curve (M). However when
analyzing an open economy the demand structure changes, resulting in a change in relative prices
creating a specialization in relative strength.
Master Thesis
The line Z EU Africa illustrates a movement from M to M’. The utilization of inter-state trade allow
both parties to move to M’’ and N’’, thus gaining additionally from engaging in trade.
The essential of the HOS model can be summarized to, that a country will export the goods which
dominates the country’s more abundant factor of production. As in every economic model, the assumptions give implication when exporting the model to practice. Although resources are exported
from countries, which are endowed within a particular field, seems to hold some truth in practice.
As it will be analyzed in chapter five, Denmark has from commodities there have been ‘bound’ to
natural resources in history, gained competitive advantages within pharmaceutical products. Nevertheless the model has hard explaining trade patterns in general. Paul Krugmann put a criticism of
the model quite clear by stating:
While nobody would deny that there must be some relationship between a country’s resources and
the resource content of its trade pattern, the effort to explain trade solely on the basis of such resources – in other words without making allowances for differences in national production function
– is generally seen as having, at long last, failed (1996b, p 345) ( Laursen:2000).
Among other explanations to strong specialization is the “home market effect”, where domestic
linkage to input and output activities, foster new products before bringing them into exports markets. Linder (1961) argued that increased learning capabilities would spring when developing products in a “known market”. As will be discussed in chapter five, the IKE group later examined this
area, and encouraged to the National innovation system approach, explaining economic activity,
growth and specialization as a changing mechanism, thus a learning market (Gregersen & Johnson:2005).
4.2 Export specialization
Export specialization provides linkage to both the Ricardian and the HOS trade theory. When countries specialize in trade a mutual advantage does not only appear by theoretical means, but also in
practice. It is commonly that countries will, when engaging in international trade, experience converge to few special manufacturing sectors. These sectors often rely on the countries comparative
advantage and the subject to economic of scale (Krugmann & Obstfeld:2006).
Master Thesis
From microeconomics liberalization elimination of monopolistic markets creates increasing competition, and forces i.e. manufacturing industries to produce, by theoretical terms to the marginal
product. Increased competition leads indirectly to efficient production and companies would have a
tendency to gather activities, often leading to regional specialization (Krugmann & Obstfeld:2006).
Specialization within few industries has showed its ability to trigger the outset of new industries,
having directly or indirectly (Tidd, Bessant and Pavitt:2005).
Trade specialization is therefore highly relevant to economic performance, due to the adaption of
processes. Furthermore patterns reveal similarities in technology and resources, allowing drawing
comparative conclusions (Krugmann & Obstfeld:2006). To map international trade specialization
Balassa (1965) Revealed Comparative Advantage (RCA) index is utilized.
RCAij 
X ij /  X ij
 X / X
The RCA index measure the numerator as a given sectors export in relation to national export. In
other words the nominator represents the percentage share the sector comprise of total national export. Making the term relative to something, the denominator calculates the percentage share of a
given sector in relation to OECD exports. The parameters in the RCA index is therefore determined
as X ij export from sector i in country j .
It is important to notice that the RCA index calculates the relative export structure, meaning that
table 5 below is calculated from the OECD countries and thus the ratio size in the representative
sectors in country X, depend on the relative size in the other OECD countries sectors. This interpretation is also reflected in the results of the RCA index. When the Index equals 1, the exports share
of that given sector equals the OECD average. A higher share than 1 will therefore equal higher
export share in relation to the OECD average and the country is said to be export specialized, thus
having a revealed comparative advantage. An average below 1 is vice versa, the result of being less
specialised in a given sector compared with the average OECD.
Master Thesis
Table 5 below show the RCA calculations for selected OECD countries, from the latest comparative
data in the OECD STAN Database. Danish revealed competitive advantage is, from an overall
score, significantly strong within low technology, with an average well above the required value of
1. Denmark’s relative strength has especially been within food and beverage, wood and products of
woods (furniture), textile and recycling. The specialization is in comparison to other small economies significantly higher with an increase from 1990-2006. Examining the other small economies
an overall decreasing tendency has happened in low technology exports. Economies as US, Germany and Japan in general holds a smaller fraction of low technology exports, where these countries
instead are specialized in almost every subsector in the medium high tech category.
Table 5 – Export specialization calculated from the OECD STAN - bilateral and multilateral trade 2008 database15
When examining the subcategorized in Danish low and medium low tech manufacturing, an almost
consistent specialization occurs, that can be found in no other of the small economies represented.
ICT is not in the low tech category and dose not count when summarizing the numbers to 1 for each sector. ICT is
included to show this as a new parameter considered by the OECD. Summarizing the
Master Thesis
As was the case with the parameters value added and employment in chapter three, big multinationals in the small countries is affecting the outcome. The Netherland and Ireland are both specialized
in high tech in 2006, where especially radio, television and communication equipment and accounting and computing machinery and pharmaceuticals are dominant for the two countries. Although
Finland (Nokia) had a high value added share, the figures has to be remembered as relative to other
OECD countries, thus Nokia has not pulled Finland up as high tech specialised in the overall category, although Finland is specialized in the radio television and communication equipment category.
The right side of table 5 provide the OECD relative export shares, in order to provide an overview
of the exports structure in the overall organization. These figures are included to see wheter the individual countries structure can somewhat consistent with the OECDs. As can be seen only sectors
with relatively few provides worldwide can manage a relative score matching the OECDs. The US
manages this, within Air and spacecraft due to a manufacture as Boeing. The pattern would most
likely be the same for France, with Airbus as worldwide manufacture.
4.3 Danish positions of strength
The fact that a predominant part of the Danish exports is low tech products, automatically gives
association to low wages countries competition where scale returns are very scarce, hence a market
that highlights price as the overall parameter. Denmark has on this area an export niche, where Danish export products in the medium low and low technology category mainly are regarded as product
with a superior quality or design. In this connection Danish manufactures have managed to export
44% of the manufacturing goods as upmarket products (Ministry of business and economic affairs:2007).
Upmarket products are defined as products which export price is at least 15% higher than the average export price for the same product type (Benchmark average EU-15). In comparison downmarket products export price is 15% below the average, for same product type. In Denmark downmarket products holds 18% of total manufacturing export. Adding the last group middelmarket products, which comprise the remainder, 38% of the Danish manufacturing export is within these products (Ministry of business and economic affairs:2007). The gains from having an export structure
based on upmarket products, is in relation to the trade theory, the advantage of the exchange ratio.
Master Thesis
Besides obtaining better results on national level, the industries, from a microeconomic level, have
a higher productivity and a higher profit ratio in comparison to non-upmarket industries. In Denmark, manufactures in upmarket export production, represent a principal share of the whole industry. Denmark is on this behalf the second largest exporter, relative to size, in upmarket products on
EU basis with Ireland as the leading upmarket exporter.
The Netherlands and Finland, is placed lower on the list, comparing upmarket products (Ministry of
business and economic affairs:2007). The case that these two comparable countries deviate from the
Danish upmarket structure is likely, in the Dutch case, to be the result of a massive export specialization within few sectors, in this case the chemical industry and food and beverage. The result from
Finland is however of another character, where productivity increase has decreased the exchange
ratio, within especially telecommunication equipment. This is due to increased productivity lower
prices, and hence exchange ratio (Ministry of business and economic affairs:2007). From figure 6,
the shares of Danish upmarket product in each sector are sketched. A significant share of the Danish export encompass upmarket products (44%), and have from an intra industry perspective increased the exchange ratio (Ministry of business and economic affairs:2007).
Figure 6 – Danish positions of strength (Ministry of business and economic affairs:2007)
Master Thesis
The ministry of business and economic affairs (2007) finds that Danish industries producing upmarket products have a bigger relative share of employees with, social, natural, health and technical
science educations. Furthermore the ministry states that R&D could be the instigator to the development of upmarket products. A likely explanation, in the context would also be that upmarket
sectors holds twice the amount of employees with a humanistic education, thus an education with a
rather creative backbone (Ministry of business and economic affairs:2007).
4.4 Summing up
From the chapters analyzed so far, there can be found a good reason to believe that Danish low tech
manufacturing still holds a significant economic role. Danish low tech and medium low tech value
added share is 57.1% and direct employment at a 63.2% level. Danish low tech has although provided a very scare contribution to overall growth. Whether this is due to a transition process cannot
be concluded, however the slowly converge from low to high tech production measured in value
added and employment could support such a statement. In addition the large share of upmarket
products, could reveal that Danish low tech products holds what could be called a “niche production”.
This leads to the question, how can Denmark manage low tech production, when competition on
these products are meet from low waged countries. Denmark on the contrary, holds high income
and high taxes, however production still holds a specialization pattern within low technology, from
the OECD definition. Other explanatory factors could explain Danish low tech sustainability,
broader factors encompassing the whole systems of idea generation. A reasonable rationale would
be that Danish manufactures must rely heavily on the ability to 1.Innovate and 2. Sufficient production in comparison to the competitors to maintain a low tech specialization.
Explanatory factors are therefore likely to be found within 1. The National System of Innovation
(NSI) and it ability to generate and diffuse knowledge, in creation of competitive goods. 2. Vertical
specialization, and its ability the use efficient supply chain, thus letting other countries create the
‘easy’ manpower consuming processes and afterwards utilizing vertical specialization to generate
highly value added export goods. This approach could also explain the high level of upmarket products.
Master Thesis
In the following chapter NSI will be analyzed. Instead of arguing that low tech is unsustainable in
advanced nations, the chapter will try to explain why low tech have managed to succeed in advanced nations and provide the pattern to what factors determine efficient low tech production in
high income countries, hereunder the tacit knowledge at claimed by Vejrup-Hansen et al (2006) and
Laestadius (2004)
Master Thesis
Chapter 5 – Tacit knowledge and National Innovation Systems, An
Explanations to low tech Sustainability
It is from statistical estimations and analysis, proven so far, that Denmark is a low tech manufacture. Vejrup-Hansen et al (2006) and Laestadius (2004) have therefore posed the question, what
drives these low tech manufactures if not R&D activity? To provide reasoning, this chapter will
start analyzing the historical movements and tacit knowledge in Danish manufacturing. The chapter
will afterwards examine the Danish National System of Innovation (NSI) to explain the underlying
factors to creativeness and innovation.
5.1 Tacit knowledge – a hidden weapon?
National innovation systems and the interaction among institutions, private and public business’
explain some of the linkage to the Danish low tech paradox. A field necessary to analyze in this
connection and which has been predicted as a possible parameter to explain the low tech paradox, is
the level of tacit knowledge (Dalum:2006). Tacit knowledge layers cannot be measured, which
highlight the importance of analyzing the learning economy sphere. R&D can from statistical capabilities only be tangible measured by questioning firm business, governments, higher education,
institutions etc. in order to analyze R&D stock. However this catches only some of the R&D activity and sort out the whole learning economy theory.
A range of international organizations has recognized knowledge as a crucial parameter in competition and economic progress, hereunder OECD, IMF, UN and the European commission
(Lundvall:2007). The development has not only sprung from increased political focus but also
proven itself in practice from an increasing employment in the service sectors over the last century16(OECD:2007) (Christensen and Lundvall: 2004).
Knowledge is one of the fundamental cornerstones, when analyzing national growth. R&D, patents, technology diffusion, interaction among enterprises or processing of knowledge, all entail
explanation to the terminology of knowledge. Knowledge comes both as an input and output factors, in the innovation process i.e. what is generated to economic activity.
Parallel with a decrease in production sector
Master Thesis
From microeconomics, the agent would possess the ability to make rational choices, on behalf of
the information (knowledge) assigned to him/her. To understand the evolution of economics as a
constantly changing mechanism, rather than an equilibrium system, the need to identify how the
agent process knowledge therefore becomes crucial (Christensen and Lundvall: 2004).
In broad terms, an aggregated process of knowledge can be regarded as the learning economy, accounting for the ability to convert to the economy as a changing process. The shift towards ‘nonproduction’ workers is seen as a shift towards a learning economy rather than an increased
knowledge base. The “acceleration in the rate of change implies that knowledge and skills are
more exposed to rapid moral depreciation” (Christensen and Lundvall:2004). Economic changes
may therefore well be the outcome of increased ability to use competences and skills rather than an
increase in knowledge stock.
Knowing that learning connects with economic performance, a key to understand firms, regions and
nation’s economic performance lies within the interaction i.e. learning ability (Furman, Porter and
Stern:2001). Tidd, Bessant and Pavitt (2005) underline the importance of knowledge by stating,
“Innovation is about knowledge – creating new possibilities through combining different knowledge
sets”. A question in this statement is although explicit incorporated - what kind of knowledge matters to economic performance?
A convenient case to discuss is whether knowledge is public or private. In the neoclassic growth
theory knowledge is regarded as a public good. Although “in real life” most knowledge is neither
strictly private nor public (Christensen and Lundvall: 2004). When knowledge becomes an asset
and a competitive parameter the value of holding an amount of private knowledge is regarded as
necessary. Private knowledge holds the form determined as tacit knowledge. The transfer mechanism of tacit knowledge only allows if the receiver understands and is able to absorb and use the
knowledge (Davenport & Prusak;1998).
Transferring knowledge is therefore only possible if the possessor is able to make the knowledge
explicit. It has although been seen that knowledge forms such as know-what (mostly information)
and Know-why (science based knowledge) are easier to codify (make explicit) than know-how and
know-who. A competitive parameter is therefore likely to rely on the human capital in knowing
how and who, due to enhanced difficulties in the codification process, thus making is harder for
competitors to copy (Grant :1996).
Master Thesis
Public knowledge has in competitive terms the disadvantage that it can be accessed be anyone
without being diminished, and where it is difficult the exclude other users from. (Christensen and
Lundvall: 2004). Still some knowledge within the product and process innovation is kept tacit,
which from the knowledge based theory of the firm, is seen as a competitive advantage
(Grant:1996). The interactive process, in creating the tacit competitive parameter is therefore not
solely based on STI =Science-technology and innovation17, but also the abilities within DUI= doing
using and interacting.
5.2 Danish learning economy advantage
The case of interactive processes, support the earlier statement that Danish production is likely to
rely on tacit knowledge. From a historical perspective Danish production has sprung from learning
activities. In the early eighteen-century production organized by co-operative movements (andelsbevaegelse) creating an organized primary sector. (Dalum:2004)
Later on when production of crops where diminished by international supply increase, a change
towards cattle production began, hereunder pig production. This was by historical means a start of
‘know how’ creation to future Danish competitive advantage. Tidd, Bessant and Pavitt (2005) illustrate how pig production and the learning ability evolved to generate know how within insulin processing, thus being a catalyst to pharmaceutical production, a dominant part of Danish high tech
production today. Figure 7 sketches how the historical operations combined with investments in
STI have created technology accumulation leading to national competiveness in new fields.
Pig production
Natural insulin
Synthetic insulin
Discovery of insulin
Figure 7 – Technology accumulation in Denmark (Tidd, Bessant and Pavitt;2005)
Learning can by means result in specific competencies, shared routines, process and product innovation, where learning by doing provides efficiency in production, learning by using brings efficiency in complex systems and learning by interacting gives knowledge and competences from user
and producers. The Danish case in figure 7 is therefore not an isolated phenomenon.
In the linear innovation model it is seen that Scientific approach is the first step in the creation of innovation activity
Master Thesis
A similar case can be drawn for a Danish comparison country like Sweden, where iron ores combined with accumulation of technology, thus knowledge, have resulted in the national production
development in figure 8.
Mining Machines
Production machines
Iron ore
Iron and steel
Metal products
Figure 8 – Technology accumulation in Sweden (Tidd, Bessant and Pavitt;2005)
Knowledge and the combination of knowledge forms and learning modes like STI and DUI matter
to performance and thus growth. From a firm perspective the interaction with universities, suppliers
and customers etc. has shown positive results in the innovation process and models like Robert G.
Coopers (1986) Stage Gate Model has secured that the innovation activity captures the knowledge
in processing (Christensen and Lundvall: 2004).
Categorizing low tech into sectors from R&D spending can seem rather unfair in respect to learning
economic parameters creating a unmeasurable backbone in production. Danish low tech and medium low tech manufacturing accounts for 57.1% of the total manufacturing value added share and
approximately 63.2% of the employment (appendix 1 and 2). A rational approach must be that unknown and unmeasurable processes towards efficiency take place within these sectors, otherwise
they would never have survived global competition. So how low is low tech? Likely not as low as
assumed by OECD measures.
Is it sufficient to explain the low tech paradox with a hidden parameter unable to be measured? Although tacit knowledge is a hidden parameter when it comes to measuring it, a substantial part of
know how can be subscribed to this parameter. Learning capabilities and R&D projects will often
trigger problems only able to identify through know how processes, thus tacit knowledge.
(Lundvall:2008) Besides Tidd, Bessant and Pavitt; (2005) illustration of historical learning economy on an aggregated level, authors as Von Hippel and Tyre (1995) illustrate in their article “How
Learning by Doing is done: Problem Identification in Novel Process Equipment”, that both simple
and complex processes cannot be made without basic learning capabilities and collaboration.
Master Thesis
Learning by doing refers to the embedded tacit knowledge categorize know how and who.
(Lundvall:2008) Von Hippel and Tyre analyze a business producing circuts boards. Even though
production of such materials is connected with high levels of STI, problem in ‘simple’ processes
occur. Lacking comunication and colaboration with the units processing and holding high degrees
of tacit knowledge create serveral failures, thus economic impacts in the product development. In
relation Mishina (1992) examine production learning patterns associated with the B-17 airplane,
and concluded that “learning in production is more closely associated with changes to the production process than with the number of units produced over time” (Mishina:1992).
To emphasize that the above cases are not coincedence, Laestadius (2004) proves by 16 case studies
within low and medium low tech businesses, that streamline envolvement of creativity and learning,
can be mobilized in advanced economies even when staff members hold no higher education.
Laestadius explain this development by:
“The industry rely on praticians and pratical problemsolvers with a knowledge fundament relatitet
to the specific industrial context and only ocationally using general scientific knowledge” (Laestadius:2004)
This chapter has shown that learning capabilities, can explain economic succes, and that the learning economy entail a crucial part in business production, thus representing a parameter that if, could
be measurred, would be likely explain business succes. The next section will show how tacit
knowledge and knowledge in general are generated by the interplay of the innovation system, hence
allowing other parameters to determine economic performance, besides R&D.
5.3 NSI – an essential framework condition to low tech manufacturing
National innovation systems (NIS) have a long history, and have gained ground in explaining the
underling factors, omitted in economic growth models. Authors as Christensen et al (2008) have
therefore also applied NSI’ to explain how Denmark, with high wages, high taxes, a large public
sector and relatively few with higher education degrees can compete within low technology production (Christensen et al:2008).
Master Thesis
The phenomenon of NSI promote that no single factors can solely generate economic growth and
therefore tries to impart explanatory indicators on knowledge-economy and social variables. This
system approach is needed to distinguish and understand innovative driven factors, factors that are
likely to explain low technology sustainability in advanced economies, besides R&D expenditure.
To understand how NSI can explain low technology sustainability, a system approach must be specified. Even though no single definition has been assigned to NSI, the Lundvallian (1992) alternative
promotes a broad socio economic approach, where Nelson (1993) focus more narrowly, taking a
national R&D system approach. Gregersen and Johnson (2005) have set these two approaches up
against each other, linking them to economic performance.
Innovation performance
Economic performance
(Discrete performance of NSI)
(embedded performance of NSI)
Scientific publications
New high-tech products
Formation of new firms
System linkage ( Joint venture, networks, partners)
Growth of production
and productivity
Balance of payment
Export market share
Stock value
Table 6: Narrow and broad performance of National Systems of Innovation (Gregersen & Johnson:2005)
The discrete approach in table 6, illustrates the generated effects from a both narrow and broad determination of NSI, where the broad performance also include utilization of knowledge, generation
and use of new technology, number of new companies etc (Gregersen & Johnson:2005). The narrow performance can be interpreted as single factors to a specific benefit area, where the broad determination, produce a diffusion of many spillovers to other economic actors, and as a whole make
the industry and economic performance increase.
The embedded performance of NSI can be determined as those variables within the innovation processes, and parameters comprised in the social welfare function, such as “ growth of income and
wealth, employment, equity, social security, working condition and environmental standards”,
equivalent to economic performance (Gregersen & Johnson:2005). In the continuing work, elaboration of both approaches will be presented interchangeably.
Master Thesis
Although numerous of historical antecedents have been presented the main background of NSI
“should be found in the needs of policy makers and students of innovation” to combine observations
with economic theory (Lundvall:2002) (Feinson:2003). NSI should contribute to the understanding
of international competitiveness and economic development, a field where mainstream macroeconomic theory and policy had failed. (Lundvall:2002)
Gregersen and Johnson (2005) describes the contribution to mainstream economic with: “When the
economy is viewed as a process of change rather than as an equilibrium system, innovation and
learning become crucial and basic concepts” (Gregersen & Johnson:2005). As presented in 6.1
and 6.2 these learning capabilities and understanding of change is explained by a broad determination of the NSI, creating favourable framework conditions, spurring incremental innovation and
hence economic activity (Christensen et al:2008).
5.4 Evolution after List
The theory of NSI is fundamental in economic analysis and the broad lines to the phenomenon were
drawn already in 1841. Fredrich List (1841) conducted the idea behind national innovation systems, which he at time analyzed as “The National System of Political Economy “. List criticized
Adam Smiths view on national revenues, claiming that Smith was narrowed in on materialistic capital accumulation, rather than in broader terms approaching intellectual capital. List approached this
issue further, connecting it to what becomes the broad frame of national innovation systems, by
stating that interaction among institutions, private and public economic actors are necessary in
knowledge accumulation, supporting this statement by:
…“capital of the present human race, and every separate nation is productive only in the proportion in which it has known how to appropriate those attainments of former generations and to increase them by its own acquirements, (p. 113) (Fredrich List:1841) (Freeman:1995).
By historical means Lists agenda on National Systems, stimulated the political processes towards
technical and educational training systems. The fact that Bernal (1939) and Hoffmeyer (1958)
where the first to put R&D on the political agenda, as earlier stated, might therefore be misinterpreted. Already in the 1870’s German industries had set up innovative departments, where well reputed industries as BASF and BAYER at that time had thousands employed within R&D, thus
acknowledged List’ research on knowledge influence in economic performance (Freeman:1995).
Master Thesis
5.5 NSI – a ‘broad’ case
After Lists approach to NSI, a further development of the theoretical foundation should wait until
the 1980’s, where Christopher Freeman approached it again, which culminated in the terminology
“National innovation Systems” developed by the IKE-Group18 (Freeman:1987)
Using the ‘founders’ definitions to determine NSI, Freeman and Lundvall provide these:
“The network of institutions in the public- and private-sectors whose activities and interactions initiate, import, modify and diffuse new technologies” (Freeman, 1987).
“The elements and relationships which interact in the production, diffusion and use of new, and economically useful knowledge... and are either located within or rooted inside the borders of a nation
state” (Lundvall, 1992).
The focal point when studying NSI concentrates around the knowledge flow (OECD:1997). The last
two decades the knowledge economy, “economies which are directly based on the production, distribution and use of knowledge and information”, has influenced heavily on economic activities
(OECD:1997). This development has also been analyzed in neoclassic growth theory, emphasizing
the importance of knowledge and technology (Romer:2001). The motivation to study NSI originates
in identifying and measuring knowledge investments from knowledge flows. By doing so, the linkage among enterprises, institutions, universities, and private and public actors can reveal the channels of knowledge flows, and hence reveal policies and national investments to expand these areas
Research Group from Aalborg university – Bengt-Åke-Lundvall was the first person to use the expression National
Innovation systems” in public in his book of 1992. (Freeman:1995)
Master Thesis
Freeman (1995) describes the necessity of NSI by stating that: “national and regional systems of
innovation remain an essential domain of economic analysis. Their importance derives from the
networks of relationships, which are necessary for any firm to innovate. Whilst external international connections are certainly of growing importance, the influence of the national education system, industrial relations, technical and scientific institutions, government policies, cultural traditions and many other national institutions is fundamental” (Freeman:1995).
From figure 9 below, knowledge travels back and forth between public and private sectors and also
within these sectors. System linkage, Spin-off, formation of firms etc. arises from this process. The
scientist generates new ideas, from e.g. the know-how received from interaction with the automotive industry. On the other hand the automotive industry needs knowledge to improve competiveness, which improves, when interacting with university researchers occur. Furthermore a more advanced defence department is shaped, when technology and energy sectors overlap. The spillover
between the actors, generate knowledge sharing, learning and thus knowledge production. When
industries, government and academia interact, it provides a measurement of the ‘knowledge distribution power’, thus the determination of growth and competiveness (OECD:1997b).
Figure 9 - Linkage between public and private sector (Furman, Porter and Stern; 2002)
Master Thesis
F. List (1841) argues in his book, that the interaction among different knowledge forms and dispersion of these are essential. In Denmark many low and medium low tech industries base main innovation activity on these knowledge flows, being able to diffuse knowledge, innovation and ideas to
the outcome of incremental innovative activities. This activity generate high value added product
not encounter for in the research and development statistics (Christensen et al:2008). These activities have fostered Bang and Olufsen equipment, Danish furniture design, Novo Nordic medical
products, but also more creative industries has benefitted from a high level knowledge diffusion
activity (Christensen et al:2008).
As Freeman (1995) state these incremental innovation in manufacturing business rise from the mix
of different human capital, where omission of this interaction would be likely to jeopardize the innovation process in industries and thus the overall economic performance (Freeman:1995).
5.6 NSI – a ‘narrow’ case
However, the measurement of the NSI’ power is difficult to determine. Analysis from e.g. Furman,
Porter and Stern (2001) define the ability of the innovation system from a more narrow case, using
the following definition:
“National innovative capacity is the ability to produce and commercialize a flow of innovative
technology over the long term” (Furman, Porter and Stern; 2002).
A j ,t   j ,t ( X INF
) H jA,t , Aj ,t The regression equation contains parameters, such as infraj ,t , Y j , t
j ,t
structure, education, cluster activity, human capital and the linkage among these, i.e. figure 9. To
determine the rate of innovation at an economic level, the authors use A j ,t measuring the level of
patents with respect to time, also equivalent with new-to-the-world technologies (radical innovation) measured by patents granted in the specific country.
The essential of presenting the model is to emphasize, that when using technology i.e. patents to
determinate innovative capabilities, a narrow view will be taken and therefore sort out incremental
innovations activities, thus the broader understanding of NSI.
Master Thesis
Tidd, Bessant and Pavitt (2005) estimate that patents only account for 6-10 percent, which means
that this leaves a dominant part of the innovation activity to incremental innovations. In addition
R&D activity often lead to patents, which again provides a large margin for Danish firms to innovate outside the R&D statistics.
Measuring the incremental activity can however seem rather chaotic, when e.g. using revenue of
new products, by doing so this measurement can be correlated with general economic activity. If
relating to the incremental innovation definition i.e. “invention that has been introduced in the market and it thus represents knowledge that has proven its relevance for the market economy” (Christensen and Lundvall;2004). Incremental innovations measurements can seem obscure, when one
firstly need to determine the term “representing knowledge and “relevance to the market”. Representing new knowledge can be justified by the definition of innovation. When innovation entails
something, which is new, knowledge must also represent something new due to that knowledge
production is the input factor to innovation outcome (Christensen and Lundvall:2004). Furthermore
‘relevance to the market’ is defined in the sentence implicit. i.e. the invention would very unlikely
have been introduced if it had no market potential, what so ever.
Ideas in the creations of innovation can become visible randomly, or by process in order to provoke
innovation activity, also determined as R&D. However, when understanding innovation, it quickly
becomes clear that innovations are created from knowledge, thus “Innovation is driven by the ability to see connections, to spot opportunities and to take advantage of them”(Tidd, Bessant and
The question must come down to, if NSI is better to determine technology level that R&D, due to
its ability the analyze the developing of new knowledge, commercializing the knowledge by producing products or processes, diffusing the knowledge to spin off etc. When investing in R&D, the
main reason for doing so must be regarded as an investment in the interest to keep the knowledge
private, thus being able to obtain an economic yield. R&D is therefore rather not very sufficient in
the broad sense of generating and benefiting to knowledge spillovers and accumulation to other
economic actors. Although other economic actors can use informal ideas to create a similar product
type, the process of obtaining the knowledge to do so, must be made from scratch.
Knowledge effect on innovation with perspective to Danish NSI will be discussed in chapter 4
Master Thesis
The NSI interaction and knowledge sharing parameter to create new innovations can therefore seem
easier to acquire. However hard knowledge intensive product or processes, are probably more likely
to be acquired from R&D activities, where core research with allocated funds only purpose is to
search for new commercialized knowledge.
The NSI system contra R&D therefore have each their advantage. The NSI ability depends from the
NSI broad determination, of a country’s ability to utilize indicators as finance support, linkage,
economic performance, public sector etc. to benefit the learning system outcome. In 5.7 an analysis
of these parameters are presented.
5.7 Danish NSI performance
The much attention towards innovation system has encouraged to inspiration in the recent published
European Innovation Scoreboard (2008), and hence incited the authors to increase parameters on
measurements (Imitation, incremental, new knowledge combinations and technology adoption).
Although Denmark is top-ranked in R&D spending in the OECD, only exceeded by Ireland and the
US (per capita GDP $,PPPs)20, recent European Innovation Scoreboard emphasize that other factors
than R&D have been highly undervalued in economic analysis (Lisbon Scorecard Vlll:2008). Emphasizing the relevance of NSI in an empirical matter, the European Innovation Scoreboard put
forward a rather solid statement to this, in respect to the R&D measure:
“Innobarometer survey shows that while these ‘neglected innovators’ tend to have lower innovative
capabilities than R&D performing firms, the majority do invest in creative innovative activities and
are just as likely to be fast growing firms” (EIS:2008)
Elaborating on this observation, the European Innovation Scoreboard fully support the NSI approach, stating that interactive learning from creative activities and collaboration, might as well
drive growth as likely as R&D. The statement highlights that NSI’ also have gained political
ground, as was the case with technology determination in the 1980’s. From the selection of the parameters available in appendix 5, the categorization of the Danish innovation performance relative
to EU27 is given if figure 10 below. Together with other small countries and low tech performers as
Sweden and Finland, Denmark is top ranked in the overall score of innovation performance.
Total R&D expenditure. Denmark used in 2007 2,4% of GDP. In percentage share Denmark is not in top three in the
Master Thesis
Figure 10 – Innovation performance European member states (European innovation Scoreboard:2008)
The Danish innovation performance in among the innovative leaders, however Denmark has not
managed to improve over the five year estimated period. Digging deeper into the European Scorecards (2008) estimates, a brief description of the Danish innovative performance will be outlined.
The chosen parameters to measure innovative performance has been extensively debated both in
relations to what parameters can measure national innovation and if correlation in the parameters
exists. The parameters in 5.7.1 to 5.7.5 finds support by that fact that Finance and support, Human
Resource, Throughputs and Linkages, public sector support, and economic effects, would be hard to
sacrifice in the creation of innovation activity, thus the country’s ability to generate knowledge.
(Christiensen:1992) (Furman, Porter and Stern:2001) (EIS:2008) Shortly summarized finance and
support are needed to create the economic fundament fostering innovations, Human capital and the
level of idea generation comes mainly from this area, thus also the ability create linkage between
industries and produce entrepreneurial outcomes. In addition the public sector must support these
with regulations, investments etc.
5.7.1 Finance and support
Turning to the category Finance and Support, Denmark’s relative high score is driven by the subcategory, Broadband access by firms with an 80% penetration rate. The good score in Danish finance reflect a noteworthy positive development compared with the results from the Community
Innovation Survey 3 (CIS 3) from 2001, used in recent literature by Christensen et al (2008).
Master Thesis
Christensen et al (2008) finds from CIS 3, the innovation ability in Finance and Trade relative poor
in a small country comparison. The CIS 3 results are regarded as critical, and the authors state that
the linkage between finance and trade and the rest of the economy, can with poor results, be the
“Achilles heel for the Danish economy as a whole”, thus innovation intensity can risk decrease
(Christensen et al:2008). The EIS (2008) exorcise the CIS 3 results, by concluding that the last fiveyear development in Danish private crediting system driving the innovation system forward with a
7.5% increase in willingness to finance (EIS:2008).
5.7.2 Linkages
As show in the theoretical part, the interconnection between public and private actors is important
in NSI matter. The Danish SME collaboration has fallen with -8%, where a small comparison country as Finland has managed increased with 12% (EIS:2008). Although the Danish level of SME
collaboration is above the European (27), the current level is below a small country comparison.
Considering a big part of the Danish firms are SMEs, the numbers can also represent an overall picture for firm collaboration (FI:2008).
In addition the Danish clusters are facing decrease. As Michael E. Porter showed in connection to
figure 9, an interconnection from domestic markets fostered by clusters has a sound impact on
growth and innovative activity. The linkage between demanding consumers, interaction with suppliers, competition and human capital, are just few elements of advantages in the cluster theory,
making high-income countries able to compete despite high wages (Innovation council :2007).
Christensen and Lundvall (2004) support these statements with newer findings:
“The recent models of innovation emphasize that knowledge production/innovation is an interactive
process in which firms interact with customers, suppliers and knowledge institutions. Empirical
analysis shows that firms seldom innovation alone.” (Christensen & Lundvall:2004).
Danish clusters have experienced lower growth and productivity in survey findings from 20002004. Ten out of Denmark’s thirteen biggest clusters have experience job loss, with a peak in mechatronics21 on -14.883 people and a total loss of 50.000 people (Innovation council:2007).
Mechanical and Electronics engineering
Master Thesis
The innovation council (2007) point out in their strategic work towards Danish innovative sustainability, that Danish companies must look outward instead of inward. The increasing globalization
with global markets becoming local competitor, enforce to encourage international networking and
collaboration, meaning global partnerships, knowledge sharing and dispersion and ventures.
From the CIS3 survey findings show that nearly half the Danish innovative firms collaborate with
one or more partners. The CIS4 survey promote this argument, showing that especially complex
technology production such as, chemicals and ICT, exploit external knowledge in innovation activities. However nearly half of the overall manufactures does not access external knowledge nor have
any inventive in-house activity (Bloch:2008) (CIS4:2004).
From the CIS3 (table 7) survey Danish collaboration is above or close to equal with the EU average.
Especially firms within same concern are a main driver to innovation activity for the majority of
Danish firms in comparison to the EU level. The figures in CIS3 is in line with the theory of, using
collaboration to foster innovations.
Table 7 – CIS3 1998-2000 percent of firm collaboration (Christensen et 2008)
The CIS4 survey support the findings from table 7, where findings show that especially, what
should be high and medium high tech firms from the OECD definition, apply to customers and public research collaboration (Bloch:2008) (CIS4:2004).
Master Thesis
In addition a rather fast increasing area is firm collaboration with universities. In 1996-1999 the
research project DISKO22 estimated firm and university collaboration to 17% of the consulted
firms, where the numbers in the CIS3 report from 2001 had increased the number to 30% (Christensen et al:2008).
5.7.3 Human Resource - Competence building and outcomes
Comparing the Danish GDP spending on education, Denmark is spending a frequently larger proportion than the OECD average (8,5% against 5%) (Christensen et al:2008). From the European
Innovation Scoreboard (2008), the overall Danish human resource23 is well above the EU27 average. In a small country comparison the level is a little below, Sweden, Finland and Irelands. Denmark however manages to graduate a larger fraction within science and engineering (S&E), social
sciences and humanities (SSH), than Finland, Sweden and the Netherlands. On the contrary S&E
and SSH doctorate graduates and especially youth education is significantly low comparing with
other small countries, where the Netherlands holds the weakest overall score when comparing the
five small countries.
Looking at the output for the competence accumulation the publication rate has a revealed comparative advantage (Christensen et al:2008). Danish publication made between public and private institutions holds a current higher level than small comparison countries. Particularly publications encouraged from historical know-how areas as agriculture, medicine, biochemistry etc. are Danish
strongholds (Christensen et al:2008).
The throughputs as an indirect measure of increased competences show that Danish incremental
innovations dominate the overall picture. Christensen et al (2008) describes this development from
a knowledge input perspective, where flexibility, diffusion, adaption of new technologies creates
the frame conditions to this (Christensen et al:2008) .
The limited breakthrough of radical innovation is likely correlated with the distribution of Danish
firm size, where an overall majority of the firms belong to the SME category (FI:2008). The case
that bigger companies (>250 people) has easier access to larger R&D investments and can allow
tied-up-capital, is likely to influence on the results of radical innovations.
Danish Innovation System in a Comparative perspective
See appendix 5. Measured on: S&E and SSH graduates, S&E and SSH doctorate graduates, tertiary education, Life
long learning, youth education
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Among other output factors are the technology Balance of Payments flows (TBP). To understand
this linkage, TBP is defined as “money paid or received for the use of patents, licenses, know-how,
trademarks, designs, technical services (including technical assistance) and for industrial research
and development (R&D) carried out abroad, etc.” (Stats.OECD.org:2009). Denmark is on these
throughput areas in the top compared with the OECD average, (OECD STI Scoreboard:2007).
5.7.4 Public Sector
The public sector plays a noteworthy role in NSI on various levels. Besides providing free educational institutions, a non-refund financial support is given at high school and university level, allowing every social layer to obtain a higher education. That research institutions are public and furthermore allows the linkage to private firms, without assigning special attention to certain sectors,
allows a broad research field.
Supporting the public and private linkage, public funds give scholarships to study abroad, promoting the international and cross culture differences that small countries entail. Furthermore public
funds inducing private and public firms to engage in high tech findings are set up, to advance high
tech in firm activity. Similar systems are set up to promote entrepreneurial activity (The high-tech
fund:2009). The public sector has furthermore increased the R&D expenditure since in recent years,
from 0,73% of GDP in 2003 to 0,85% of GDP in 2008, where private R&D investments where at
1,69% of GDP in 2005. Comparing the public expenditure to other OECD countries Finland has
0,97% of GDP where the US reaches 1% in 2008. Countries as the Netherlands and Sweden have
an expenditure on 0,69% and 0,81% of GDP.
In relation to domestic allocation of competences, the social security system allows high labour
mobility. The Danish flexicurity model, where layoffs are relative easy, makes adjustment in relation to the state of the market, easy. Combining this with, the generous social security system allows readjustments and willingness to move to get a job, due to the monetary support. In addition to
these two factors the case that unemployed can enhance their qualifications public paid, allows to
maintain a certain competence level.
5.7.5 Economic performance
Selecting the new Achilles heel, economic effects has worsened, with a considerable decreases in
SMEs introduction of product and process innovation (-5.7%), New to the market sales (-7.7%), and
New to the firm sales (-8.5%). Although these results point out improvements areas, the current
Master Thesis
Danish ‘economic performance level’ is quite similar to Sweden, Finland and The Netherlands. A
critic could be pointed out from the indicators of growth performance. Three out of the six measures
cover 1. Employment in medium-high & high-tech manufacturing 2. Medium-tech and high-tech
manufacturing exports 3.New-to -market sales, areas that at first glance could be regarded as unfair
parameters for a low tech producers. However is has been seen in earlier chapters that, Denmark is
gaining ground and have a sound share of high tech production. The measurements are therefore
fair, and the task is to find out why Danish framework conditions to create innovation are high
while economic effects are low.
5.8 NSI - Summing up
It has been argued that increasing transformation of the world’s business structure, thus the rise of
TNC’s has undermined the importance of NSI. When boarders becomes scattered and R&D departments can be placed all over the world, a borderless situation where an interlinked economy
arises can be argued for (Ohmae:1990). Although the argument has found support, research has
found that NSI structures play a notable role when it comes to strategic placement of businesses.
Michael Porter argue against Ohmae (1990) point by following argument:
“Competitive advantage is created and sustained through a highly localized process. Differences in
national economic structures, values, cultures, institutions and histories contribute profoundly to
competitive success. The role of the home nation seems to be as strong or stronger than ever. While
globalization of competition might appear to make the nation less important, instead it seems to
make it more so. With fewer impediments to trade to shelter uncompetitive domestic firms and industries, the home nation takes on growing significance because it is the source of the skills and
technology that underpin competitive advantage”, (p. 19) (Freeman:1995).
National Systems of innovation are therefore not to be neglected. As the European Innovation
Scoreboard emphasized innovative activities and frame conditions are as likely to generate growth
as expenditure on R&D. Economists find it convenient being able to provide an estimate for industrial evolvement, hence selecting investment areas. The R&D has been set as a good indicator to
industrial performance due to its simplicity comprised from ‘one’ figure. Although, to understand
how industry layers are developing and their potential for future survival, a broader perspective
with various indicators must be applied i.e. NSI interpretation and analysis.
Master Thesis
As is the case with R&D estimation, Furman, Porter and Sterns tries to estimate innovative performance from a narrow perspective using patents as the dependent variable. Again this provides a
convenient overview, however estimations of knowledge and knowledge diffusion, collaboration
and linkage, Human resource, finance and public sector must be considered among various of independent variable. Denmark and small countries in general have an overall strength in learning ability, linkage and diffusion of knowledge, thus incremental innovation without R&D expenditure.
Laestadius (2004) research furthermore highlight that this also could be present when the business
was holding no employees with a higher education.
The empirical data of Danish national innovative compatibility, coincided with the theoretical findings, concluding that Danish human capital is topranked above EU27 average. Finance and support
are well regulated and under strict public requirements, and has improved since the CIS3 survey
allowing a more sound acommendation to private financing. Although Danish collaboration has
faced drecrease the level is still placed among the best performers compared to the EU27 average,
where interaction between firm-to-firm and firm-to-public-sector meet a high level of interplay.
Supporting these factors are a well acting public sector, with beneficial arrangements withing human capital, labour market, financing, fund to support businesses etc. NSI is therefore among one of
the explanatory factor to low tech sustanability, indicating that Danish economic frame conditions
are very suitable to low technology production, thus knowledge creation and incremental activity.
As Michael Porter stated above “the home nation takes on growing significance because it is the
source of the skills and technology that underpin competitive advantage”. The fact that Denmark
entails a solid NSI creates a good explanatory frame to the low tech sustainability and thus and explanation relying on the creation of knowledge and incremental innovation.
In a globalized world, Danish NSI can although not resist competitive markets and therefore have to
utilize sourcing processes to be competitive, due to especially high wages. The fact that’s Danish
production rely on low tech production sets higher demands to apply sourcing and supply chain
management, thus vertical specialization. To provide a supportive parameter to how Danish manufacturing process, vertical specialization is analyzed in the following chapter.
Master Thesis
Chapter 6 – Low Tech Vertical Specialization
In chapter three and four it was shown that Danish low technology manufacturing plays an essential
role in Danish economy, both in domestic and international terms. These findings therefore lead to
the wonder of “how” and additionally “why” Danish low technologies keep its high shares, and how
the sector manages to compete. The fact that NSI provide a learning economy fundament, supporting business with an efficient financial sector, high level human capital, supporting public sector,
flexible labour market etc. offer an explanatory factor to both the idea-driven incremental innovation activity and high technology activity.
Danish manufacturing has on behalf of the NSI been regarded as rather specialized in manufacturing niche goods due to the learning ability, which is supported by the high level of upmarket product (FI:2008). Research shows specialized manufactures outsource production of labour abundant
factors, leaving only a small fraction of manufacturing in the home country.
Vertical specialization i.e. imported intermediate goods in the production of goods to be exported,
has been a rather neglected when trying to answer how Danish low technology manufacturing manage to compete (Lüthje:2006) . The supply chain evolvement has created the possibility to source
basic tasks to low wage countries and afterwards import the intermediate goods, letting the
knowledge intensive tasks, stay in the home country (Dicken:2007).
The fact that import specialization of intermediate goods is possible pops the question whether Danish low tech dominance and export specialization as presented in chapter three and four gives an
accurate picture. Put simple, if Danish manufactures import low tech intermediate goods and construct these to upmarket niche products, Danish low tech would hardly be as low tech as imagined,
by solely looking at the statistical figures presented.
Lüthje (2006) define the process of intermediate goods as follows: "Intermediate goods are goods
which through the production process are transformed into goods of a greater value, whether another intermediate good or a final good” (Lüthje:2006)
Master Thesis
6.1 Smiley of the supply chain
When looking at the evolvement of manufacturing in advanced economies, it appears that highly
value added processes such as design, brand and marketing are managed from the home country.
Value and supply chains have experienced a shift from vertical integration, where the firm controlled back or forward chains through ownership, and over to cost and risk relationship in virtual
integration where the firm basically only owns the brand. (Coriat:1995)
Virtual integration has gained special attention, due to its flexibility in rapid changing markets, thus
showing increased profitability (Coriat:1995). Multinationals within car manufacturing has been a
leading example for virtual integration, although the process is commonly practised (see case studies in Dicken:2007). Giving a virtual integration example figure 11 illustrates the sourcing process
using Apples Iphone.
Figure 11 – Virtual integration in manufacturing of the Iphone (Pedersen:2009)
Global shifts in production chains have managed to create efficiency in almost every stage in production, even assembling of a product does not (always) take place in the home country and can
from a competitive advantage perspective give a rather blurry picture. Value chains have been
sliced up into a multistage process, where “imported intermediate goods are used by a country to
make goods or goods-in-process which are themselves exported to another country” (Hummels et
al: 2001). From the mid 1990 and to the early 2000s, vertical specialization has increased throughout almost every small country. The magnitude of vertical specialization is especially high in small
countries compared with bigger countries such as United Kingdom, US and Japan (OECD STI
Master Thesis
In the period 2001-2006 19% of the Danish companies moved parts of their production to another
country, in an offshoring or outsourcing matter. Compared with countries as Finland, Norway,
Germany and The Netherlands, their figures for the same period where 14-16%. Dominating these
figures is the outsourcing activity from textile, iron and metal and furniture industry, all low and
medium low technology manufacturing (FI:2008).
6.2 Vertical specialization
In order to dig deeper into the determination of vertical specialization, Hummels et al (2001) determine the concept of vertical specialization by breaking it into three main areas:
A. A good is produced in two or more sequential stages,
B. Two or more countries provide value-added during the production of the good,
C. At least one country must use imported inputs in its stage of the production process, and some of
the resulting output must be exported.
(Hummels et al:2001)
The idea behind Hummels et al (2001) bullets can be illustrate by the figure 12 below. In relation to
the HOS theory, country 1 could determine a labour abundant country, where country 2 could be
Denmark. Denmark import intermediate goods from country 1, in order to construct a final good.
Some of the final goods (could also be new intermediate goods) created from the imported intermediate goods will be sold domestically, this is however not the essential focal point of the model.
Figure 12 – Vertical Specialization Hummels et al (2001)
To create the final good it is necessary to utilize Danish high skilled labour and capital and in addition the intermediate goods created by these units.
Master Thesis
By composing ‘cheap’ intermediate goods with labour abundant factors, which could be regarded as
a knowledge intensive factor in this matter, and in addition capital, the value added embedded in the
product increases and hence it can be questioned how low tech the product therefore is.
6.2.1 Danish vertical specialization
In order to justify the extent of the degree of Danish low tech manufacturing, the composition is
analyzed in this subchapter. The idea of revealing vertical specialization, would not only present the
true comparative advantage of abundant factors, but also provide an indication of low tech degree.
Furthermore, connecting this to the Heckscher-Ohlin-Samuelson theory, where a country exports its
more abundant factor of production, a possible distortion of this assumption could be found. Although Denmark would export an abundant factor “knowledge”, the distortion term would imply the
statically measurements, presenting physically low tech goods as the specialization and thus not the
knowledge put into them.
Problems of course arise when tracking imported goods, trying to indentify which ones are to be
exported again. It could be argued that the intermediate goods imported one year would be exported
some time in the near future, and not accounted for precisely, e.g. in shipbuilding intermediate
goods take more time to apply than a microchip just waiting to be put in a cell phone and afterwards
exported. The case that input and output tables in statistically contexts provide a highly aggregated
pictures causes lack in tracking, if intermediate goods are not used in the “right” sector accounted
for. The complexity of tracking intermediate import in relation to its benefit to export has although
not stopped the authors from trying to provide estimates for the evolvement and magnitude of vertical specialization. Using the inspiration from Hummels et al (2001), calculations to vertical specialization across sectors are made from the following equation:
 imported  int ermediates 
 exp orts 
  exp orts  
  imported  int ermediates
VS ki  
gross  output
 gross  output 
Where k represents country and i represents the good or sector. From figure 12, the capital letters
assigned to each box helps to create an algebraic version of vertical specialization for country two
in sector i :
VS2i  (A/D E)) * E  (E /D E)) * A
Master Thesis
The equation shows, as earlier argued, how big a part of imported intermediates is embodied in exports. A denotes the vertical specialization calculated from the total output consisting of domestic
sales and exported goods. Multiplying the vertical specialization share with exports would yield the
dollar value of imported intermediates in exports, thus utilizing VS2i / X2i provides the share of vertical specialization in exports. The calculation is straightforward and can be applied on vector level
to obtain more aggregated vertical specialization share. In table 8 below the shares of Danish verti
cal specialization in comparison to other small and bigger countries is calculated on sector level
from the OECD input-output tables.
Although missing values are present in some of the sectors, marked with nv (no value) table 8 gives
a good indication of the percentage share of imported intermediates input embodied in the exports.
For Denmark it is mainly the higher technology sectors, which entail the highest level of vertical
specialization. Although pharmaceuticals are not included in the Danish overall high tech average,
the share still reach a level above the lower technology sectors. From an overall picture the exploration of vertical specialization has increased from 1995 to 2005 for all countries. The picture of Irelands economic model as an assembling country for many multinationals can be seen from the high
vertical specialization estimates within office, accounting and computing machinery.
Table 8 – Vertical specialization in percentage for selected OECD countries, calculated from the OECD Input-Output tables
Big economies as the US and Japan have in comparison to the European countries a smaller fraction
of vertical specialization. However both countries have a high vertical specialization in the category
Coke, refined petroleum product and nuclear fuel, which is consistent with the amount of imported
energy (oil) in the US.
Master Thesis
Oil producing countries therefore also have a smaller fraction of vertical specialization in this field.
As an example Norway’s vertical specialization share within this category would only reach 9.1%.
From Hummels (2001) equation, the share of vertical specialization is higher for small countries,
which is consistent with the OECD conclusions (OECD STI Scoreboard:2007). Findings show that
countries that are extensive users of primary goods and countries that have a technology intensive
production will utilize vertical specialization more than countries without such production. (Andersen et al:2008) A reasonable explanation to the Danish increase in vertical specialization from low
to high technology could therefore be, that Denmark is partly able to supply the low and medium
low tech from own industry, where the higher technology sectors requires a higher division of labour. Another explanation to high tech vertical specialization would also be that products are assembled in one country and thereafter exported, as is the case for Ireland in table 8.
Whether low tech vertical specialization is the driver to produce low technology in Denmark can be
partly confirmed. That the low technology vertical specialization figures could be expected to have
a higher score, have its explanation in that import content of the production is relatively cheaper for
low tech then for high tech products, which affect the ratio. Furthermore low tech industries are
using high shares of other inputs and the input shares of imported basic manufacturing part, therefore decrease.
Howells and Hedemann (2008) findings show that furniture employment and production have decreased from 2000-2007. In the same period import shares from particularly China and Sweden
have increased significantly and export has also increased by a notable share in the period. The
manufacturing process has changed from producing the whole good to only producing some of the
good, focusing on niche production and design. Production of solid furniture textiles is now being
manufactured instead of manufacturing the whole chair, thus the knowledge and specialized part is
possessed in the advanced economy (Howells and Hedemann:2008) .
The Danish furniture company KVADRAT utilizes this production method, however a large share
of Danish furniture companies outsource the whole manufacturing process and concentrate on design. Similarities from the furniture industry can be found in the textile and clothing industry, where
import and export increases parallel with an increased sourcing. The fundamental knowledge gained
from historical events as shown in chapter 5.1 again illustrates how Danish textile manufacturing,
goes from the labour abundant manufacturing processes to technology intensive processes.
Master Thesis
Danish textile producers are besides creating ‘Danish design’ also researching in intelligent textiles,
where the usage of nanotechnology, lightweight materials, stronger fibre’s and materials that can
react to surroundings are being analyzed (Danish Center for design research:2007). The vertical
specialization figures must therefore be considered in a “buy cheap sell expensive” context. If importing cheap intermediates e.g. a chair and upholster this with intelligent textiles, the value of the
output would be many times higher. As Hummels et (2001) define vertical specialization it can be
interpreted as foreign value added in exports. The vertical specialization rates in low technology
sectors may therefore imply that the value added embodied is very scarcity, which consist with
higher level of Danish value added embodied in the products and thus making the imported value
added relativity smaller. From the increased outsourcing processes in lower technology, can be
found in a shift towards a service industrial sector controlling the network system of manufactures.
In the Danish high tech sector the value added share embodied in exports are higher than for lower
technologies. Lüthje and Servais, show that 85% of Danish firms purchase internationally24 and that
intermediate purchasing is mainly concentrated in countries, producing identical products and
which geographically is placed close. Industries as pharmaceutical would, when importing intermediates automatically import a larger share of value added, than a furniture company importing a
frame to a chair, when the chair can be produced by cheap Chinese labour and an insulin pen is produced in Germany.
The sample entailed 105 manufacturing firms
Master Thesis
Chapter 7 – Discussion and Conclusion
The OECDs idea behind technology separation of manufacturing industries, was to provide a more
‘appropriate” tool when analyzing international trade. By doing so, politicians would have the opportunity to identify the ‘favourable’ sectors in industrial politics, thus having the best terms to allocate resources to the sectors with the plausible highest return. (Hatzichronoglou.OECD:1997)
Traditional European industries entail a high share of low and medium low tech manufactures, i.e.
manufactures that use lower fractions R&D expenditure. The low fractions have increased attention
towards research intensive policies, thus overshadowed beneficial policies within own competitive
model. A model based on the ability to use, distribute, generate and combining different knowledge
sets, thus creating incremental innovations. (Hirsch-Kreinsen et al:2008)
7.1 How low tech is Danish manufacturing?
The aim with analyzing Danish low technology manufacturing, was to determine its sustainability
in an advanced economy. To answer this question a fundamental field was to determine, what is
meant by technology and what parameters are applied to determine the classification of low, medium low, medium high and high technology. With an everyday word as technology, utilized by several of authors and daily by the media, the terminology should be straightforward. However the
definition should be found by creating independent technology spans from the OECD calculations.
The OECD estimation of technology, completed in cooperation with Eurostat, apply only R&D in a
ratio to production and to value added as parameter when estimating technology intensity. The
background to use R&D as the only parameter is based on the explanation that this was the best
available, due to deficiency in data in other approaches. It must although be added that additional
absence in data from the OECD ISIC rev 2 to the ISIC rev 3 have forced OECD to exclude an additional parameter from the three parameters used in the ISIC rev 2. The parameter excluded was
“R&D expenditure plus technology embodied in intermediate and investment goods divided by
production” (OECD STI Scoreboard:2005).
That OECD leaves supporting parameters out when determining technology from R&D expenditure
is debatable, however when leaving a key parameter out, allowing low technology companies to
import highly advanced technology intermediates, is a considerable defect.
Master Thesis
If incorporating a high tech intermediate into low tech, the R&D effect would not be measured,
when the third parameter is omitted. To the advantage of OECD, the magnitude of high tech intermediate products incorporation into food, textile, wood, paper etc. can be considered, however it is
not unlikely.
As shown in chapter 6.2.1 textiles are becoming more and more intelligent, the fact that e.g. a company as Danish Crown would buy intelligent clothes in the future is not unrealistic. Combinations
of stronger fibres and lightweight clothes could make the butcher suit as strong as the iron gloves
the butchers are wearing to protect their hands, and thus protect the rest of the body. If Danish
Crown imported such an intermediate as input, the R&D input would not be accounted for.
Another more likely example, which presently occurs, is when low tech manufactures apply intermediates from a high tech as Office, accounting and computing machinery, however the textile example also encircles that low technology companies can manage to exploit present technologies
without using enormous amounts on R&D, and thus still be a low tech producer. With the interpretation from table 2, the medium low tech manufacture could spend up to 0,9% on R&D when learning about e.g. nanotechnology and how to use and implement it.
R&D has difficulties in catching all spending activities, and controversies on whether high R&D
expenditure lead to higher productivity has been questioned by Jones (1995) and De Loo et al
(1999). Partly overlooking the deficiency in the parameter with respect to accuracy in measurements and controversies on whether R&D expenditure generates growth, the OECD technology
definition has been utilized as a common denominator in the calculations of the Danish manufacturing industry and must be regarded as the best indicator currently available.
Calculating value added, employment and export specialization from the OECD STAN database,
three main results emerged:
The Danish overall share of value added and employment is encompassed by low and medium low tech manufacturing. In addition low tech manufacturing is highly specialized in exports.
Danish low tech is low growth (0,5% value added growth). The other technology sectors
manage growth rates from 2.4% to 3.6% of value added.
Master Thesis
Danish manufacturing converges to higher technology sectors, increasing in shares of value
added, employment and export specialization.
Denmark’s characteristic as a low technology manufacture can from the presented calculations, be
confirmed. Denmark still encompass in comparison to other small countries a bigger low technology sector, however the Danish figures reveal a continuing transition process, where value added, is
decreasing for low technology and increasing for high technology.
The shares of value added and employment are measured in a relative term of total manufacturing.
A transition process therefore requires a relative change. A decrease in Danish low tech therefore
automatically allocates higher shares to the other sectors. A reason to this transition is outsourcing
processes of manufacturing, which have created an overall decrease in employment in manufacturing. This consists with the findings that companies have begun to specialize in less labour abundant
factors, and increased focus on supply chain management, thus moved employees from manufacturing over to the service sector, a trend which is present in the whole OECD. (OECD:2007)
7.2 NSI explanations and vertical specialization explanatory degree
From the findings of a large Danish low and medium tech sector, the question of low tech sustainability has been analyzed in a broader context, from NSI. Using the OECD definition to determine
the innovativeness and economic potential only presents a limited picture of the potential in the low
tech industry.
Setting up a sound National System of Innovation provide a broader understanding and a good reason to believe that Danish manufactures can compete with limited R&D expenditure. From a historical perspective Danish manufactures have survived through learning abilities, and literature have in
this connection shown that STI cannot solely bear the manufacturing process alone. DUI must be
implemented to obtain an underlying tacit knowledge of the process, and thus increase efficiency
and gain awareness of possible incremental innovations. In the Danish case, a utilization of present
technologies has been exploited from the DUI mode and thus developed the competitiveness of
these products. The promotions of learning and linkage policies in Danish manufacturing have accommodate competition as a changing mechanism, and can partly be concluded to entail a key factor to the Danish low tech success.
Master Thesis
M. Porters counterargument in chapter 5.8 emphasize why NSI still constitute to an essential role in
a globalized economy, and encircled the need to keep promoting national framework conditions in
small countries. Especially the rather scarcity magnitude of TNCs in Denmark, in comparison to
other small countries, emphasize the need to utilize mutual interaction among the economic actors
and create a strong public policy securing framework conditions, a flexible labour market, high level and free education, entrepreneurial support, R&D foundations etc. Empirical support to the theoretical elaboration, indicated that Danish NSI were top ranked, together with other small countries.
The Danish strength must therefore be seen in the incremental innovation area. Using supply chain
management, public research institutions, the knowledge from other enterprises and a strong human
capital does not count as high technology, however when these parameters emerge a highly innovative process is possible, supporting low technology sustainability. The creativity in setting the NSI
parameters together an exploiting supply chains was illustrated in chapter 6, where a large fraction
of Danish companies apply international sourcing in production. One could expect that Danish low
tech vertical specialization share would be high, indicating that low tech was manufactured in low
waged countries, and afterwards imported.
As examined, Danish producers concentrate in the production of niche areas in stronger fibres, intelligent clothes, organic food, eco-friendly energy etc. All these manufacturing areas create a high
value added share, and will if embodied in an imported intermediate good in Denmark increase the
value added share notably and decrease the vertical specialization figures. The fact that Danish low
tech vertical specialization is low, might therefore be positive, due to higher embodied Danish value
added. A method to calculate the value added shares more efficiently would therefore be comfortable, however this is not possible when input output tables are as aggregated as they are presently.
Setting a final conclusion to How low tech Danish manufacturing is, an equivocal picture has been
given. Measured on the OECDs research intensity parameters Danish manufacturing is still dominated by low and medium low tech in value added, employment and export specialization. However, if analyzing the sectors ability to utilize advanced technologies and exploitation of knowledge
and innovative activity, an advanced sector emerges. Turning to the explanatory factors and if Vertical specialization and National innovation systems reveal the understanding of Denmark’s degree of low technology level?, vertical specialization shows that the low tech production is sourced
and that highly advanced technologies are applied by Danish manufactures.
Master Thesis
From vertical specialization, a good reason to believe that Danish low tech manufactures have increased the activity within a more service oriented area, letting the ‘true’ low tech manufacturing
processes be performed by less advanced economies, is likely. NSI and vertical specialization as
explanatory factors can therefore be utilized as good indicators fostering an understanding to low
tech advancement from the NSI inputs, where these inputs are seen utilized in the practical process
of vertical specialization. Danish low technology is therefore probably not as low as could appear
from the OECD definition, however it is probably also not as high tech as the industries determined
as high tech from the OECD definition.
7.3 Further studies
Further studies, would imply the service sector. An ongoing increase in this sector has been evolving in decades and indirect measures could be included to measure the technology intensity of manufacturing. Although services utilized by manufactures are included in R&D measurements, the fact
that a large share of Danish manufactures characterize their activities as services create some implications when determining technology intensity (Christensen:2008). Further improvement of the
technology parameter could therefore entail manufactures utilization of service expenditure and the
share of actual employees in the ‘home company’. By creating a ratio of the sourcing degree combined with the degree of service activity could reveal, if the company is an ‘actual’ manufacture or
if it manages it processes through sourcing. Simple parameters would however be hard to create to
measure such a process, and in-depth research would be likely to apply.
The increased competition has likely made Danish manufactures more focused on the operation
system, rather than manpower manufacturing, and examination can hardly be done from aggregated
figures, but would be more sufficient to be carried out from firm-to-research-institution case studies. A firm level approach analyzing supply and value chains and thus low tech firms operation systems and operation methods would reveal how these firms compete through operations and provide
methods to how Danish manufactures handle future international competition.
Master Thesis
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Master Thesis
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Tidd, J., Bessant, J. and Pavitt, K. – “Managing Innovation – Integrating technological.
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Master Thesis
Chapter 9 - Appendix
9.1 Appendix 1
Value added growth manufacturing - selected OECD countries
2006 data from OECD STAN – current prices
Master Thesis
9.2 Appendix 2
Direct Employment manufacturing - selected OECD countries
2006 data from OECD STAN
Master Thesis
9.3 Appendix 3
Master Thesis
9.4 Appendix 4
OECD Science Technology and Innovation Scoreboard 2005. Explanation to technology definition
from OECD International Standard Industrial Classification ISIC Rev. 3 (NACE rev. 1 in Europe)
Master Thesis
9.4.1 Appendix 4.1
OECD Science Technology and Innovation Scoreboard 2005. Explanation to technology definition
from OECD International Standard Industrial Classification ISIC Rev. 3 (NACE rev. 1 in Europe)
Master Thesis
9.5 Appendix 5