Systems Thinking for Research and
Development Policy Impact Assessment in Latvia
Gints Ozolins
Public administration doctoral programme
Faculty of Economics and Management, University of Latvia
Avotu St. 6-29, Riga, LV-1011, Latvia
Phone: +371 29 488 754
E-mail: Gints_Ozolins@hotmail.com
Prof. Juris Roberts Kalnins
Ventspils University College
Phone +371 29 444 470
E-mail: simts@latnet.lv
Abstract
Following EU’s Lisbon strategy development of knowledge-based economy
has become one of the headline objectives for the government of Latvia. In this
paper we conceptualize driving forces and responses of government's
commitment towards this objective. We investigate feedback loops that underlie
dynamics of knowledge industry development. Increase in domestic Research
and Development (R&D) activities is considered as a prerequisite for
sustainable growth of knowledge economy. Dynamics of R&D supply and
demand is further analysed and leverage points for different policy measures is
identified. Scarce human resources is considered as the main impediment for
building domestic R&D capability and impact from mix of policy options is
assessed.
Key words: Knowledge-based Economy, R&D capability, Systems
Thinking.
Background
In early 2005 the European Commission proposed a new start for the Lisbon
strategy focusing the European Union’s efforts on two principal tasks —
delivering stronger, lasting growth and more and better jobs. Strategy also
highlighted one of the headline objectives set out earlier in the Barcelona
European Council - to increase spending of R&D and innovation with the aim
of approaching 3% of GDP by 2010 [EU COMM 330]. Reinforced by EU
commitment, expansion of knowledge-based economy in Latvia has become
one of the government key objectives. Currently Latvia is lagging significantly
behind developed EU countries with R&D spending estimated at only 0.44%
from GDP. One of the main reasons for that is undeveloped national innovation
system, which does not motivate active private sector participation (in 2004
private sector fraction of total R&D funding was 33.2%) [Bilinskis 2005].
Even on the EU level if current trends continue R&D investment might be
considerably lower than agreed objective (estimated at 2.2%). For Latvia to
come even close to targets set out in the Lisbon strategy radical changes in
current practices for financing R&D and innovation activities shall be done.
Lately this topic has become very high in the Ministry of Economics agenda. In
particular activities for reforming National innovation system and adoption of
EU structural funds has been initiated. It is expected that activities resulting
from these initiatives will lead to substantially increased government funding
for innovation, technology and public research institutions. This combined with
increased institutional focus and finance from EU Regional Development fund
shall boost also private sector innovation and R&D spending. However sound
and coordinated economic, science and education policies are required to
achieve optimal return from those investments.
Scope of the study
This study is carried out in two phases. Following were the main objectives
of the first phase.
¢ To conceptualize driving forces and response of government intent
for advancement of knowledge-based economy in Latvia.
e To identify high-level feedback structure of current knowledge
industry growth and its limitations.
e To analyse domestic R&D demand and supply interactions.
e To identify government policy instruments for building domestic
R&D and innovation capability.
In the second phase qualitative and quantitative analysis of key policy
options and their impact assessment shall be done. System dynamics was
chosen as a modelling methodology for this study. Summary findings and
conceptual models built in the first phase are presented in this paper.
Government commitment for knowledge-based economy
Ministry of Economy has identified five knowledge-intensive sectors that
are currently relevant in Latvia: Information and Communication Technology;
Electronics; Materials science; Wood chemistry processing; Biotechnology and
pharmacology. However for the most part, these sectors still remain marginal in
the Latvian economy. In this paper we will investigate on the conceptual level
relationships that are valid in all sectors. However for more quantitative studies
each sector should be looked separately as they are in different development
stages, levels of the main stock are diverse and might be exposed to industry
specific feedback loops. Therefore building robust cross-sector simulation
model might be very difficult task.
International experience has emphasized four pillars for developing a
knowledge economy: a labour force with a high education, a system that
favours research and development, easily accessible information technologies,
and an open economy that leads to greater trade and foreign investment
[Cleaver 2002]. Openness to international trade and investment as well as
favourable business environment are cornerstones for modern economy and
Latvia is well positioned in this sense particularly after joining EU. Therefore
in this study the main focus is on human resources development and on
technology acquiring and dissemination. Thus scientific education and training,
R&D and innovation activities as well as the level information and
communication technology penetration are identified as the main inputs for
advance of knowledge-based economy.
Even the knowledge-based economy can be considered as a value on its
own, government commitment for building it is more influenced by its outputs
- sustainable growth and high employment level. It is widely accepted that by
far the biggest growth factor of national product observed in developed
countries over the last century can be explained by innovation driven increase
in labour productivity and capital efficiency [Porter 1996]. Figure 1 shows
feedback structure for government commitment, funding and knowledge-based
economy relations. Knowledge and technology accumulation is deemed to be
the main source for increase in labour productivity. In favourable economic
environment it is also expected to increase industry competitiveness. This in its
turn stimulates employment level; expands high added value industry and
international performance, thus fuelling the growth of the national product.
a
EU
‘ Information and Communication
Commitment
Technologies
Private sector Scientific Education
motivation and Training
Innovation support
policies
Research and
Development ——a
NY
Government ¢ ——_______,..\
Commitment High value added
industry
Employment
Knowledge based
Knowledge Industry en economy
shiemanonel Competitiveness
performancesq__
Labor Knowledge and
productivity <—_______—— Technology level
Figure 1. Government commitment,
funding and knowledge-based economy.
Growing industry with high added value catalyzed by government support
policies shall also increase private sector motivation to fund further R&D and
innovation activities. Thus high level of EU funding, increasing public and
prospectively also private funding shall provide sound financial base for
development of knowledge-based economy pillars.
Technology transfer and knowledge industry
Two basic channels exist for firms that seek to upgrade their technological
capacities: either they can develop their own R&D capability, or they can
acquire new technologies from other firms and partners. Foreign technology
transfers in emerging and relatively small countries like Latvia are essential.
This is partly due to limited financial and human resources in local firms and
insufficient critical mass in industry to create lasting demand for research
institutions. In the recent survey about two-thirds of the firms indicated that
they had benefited from technology transfers over the past few years, versus
one-third that reported having developed their own R&D capacities. However
these two options are complements rather than substitutes and only 14% of
Latvian firms reported conducting R&D without receiving any external
technology transfer [World bank 2003]. It is observed that countries are in
either of the two possible phases with respect to the levels of private and public
R&D expenditure: the phase in which private R&D of the country is dormant
(i.e. insufficient private R&D) and the phase in which private R&D is at a self-
sustaining state [Giiven 2002]. In year 2003 private sector funded only 33.2 %
of total R&D activities Latvia.
The dynamics of technology level growth has been described both in
macroeconomics text books [Romer 1996] and system dynamics literature
[Weil 2005]. Here as the first step we have analyzed feedback structure of
knowledge industry development driven by the technology transfer (see Figure
2).
EU and G overnment Ss Innovations —————m» Technology.
g Funding + transfer <R&D output>
ss A
Saturation
4h.
Ms
———. e
Knowledge ~+ Atractiveness of Technology
Firms Industry level
+ Market growth
fe
z Market
Competition Growth
"
ao .
Competition ~ Profitability +
———_
~+________—_—CCoompeetitiveness
Figure 2. Technology transfer and
knowledge industry growth.
In the first step of analysis we exclude R&D output impact and assume that
technology level is determined by technology transfer, which is defined as
“acquisition of knowledge and technology results from purchases of external
knowledge and capital goods (machinery, equipment, software) and services
embodied with new knowledge or technology that do not involve interaction
with the source” [OECD 2005]. Technology level is considered as main driver
of industry competitiveness that leads to increase in profitability and market
growth (in Latvia case mainly through exports). Profitability and market size
determine industry attractiveness, which in turn cause more knowledge firms
enter the market. It’s expected that government support combined with
significant EU funding will push innovation activities significantly in the
coming years. However in longer term increasing number of knowledge firms
shall generate also higher level of private sector funding for innovation and
further technology transfers. Two balancing loops have been identified that
back off the growth of technology level and market. The first is characterised
by diminishing returns from technology transfer when the technology level in
industry reaches saturation. In the second loop growing number of knowledge
firms increase the intensity of competition, which negatively impact the
profitability and taper the attractiveness of industry.
Building R&D capability
So far we have limited the model with an assumption that in a small country
like Latvia with limited domestic R&D capability technology transfer is the
only driver for rise of technology level. This is reasonable scenario in the initial
phases of building knowledge-based industry but is considered not sustainable
for long-term growth. It’s highlighted by technology saturation feedback loop
in Figure 2. Thus building domestic R&D capabilities is considered to be a key
factor for further advancement of knowledge-based economy.
There is a long tradition in system dynamics community of modelling
complex interactions within innovation process — starting from R&D activities
[Roberts 1963], [Weil 2005] to new product introduction and diffusion [Ford
1998], [Milling 2001]. Comprehensive models for investigation of innovation
dynamics on the firm and industry level are built. In our study focus is on
leverage points and instruments that government can use to build effective
national innovation system and promote public and private R&D activities.
The key linkage from R&D supply and demand model to knowledge
industry is through R&D output (number of innovations, patents) that has
positive link to the technology level. Generally R&D output is product of R&D
activities (Figure 3). Some authors [Milling 2001] have criticized the attempts
to define production function for R&D similar to that of material goods where
output is produced by allocated resources like budgets, people and laboratory
equipment. Thus partly stochastic nature of this link shall be addressed when
simulation models are built. Increasing output of R&D activities has several
important endogenous impacts — its enhances the technology competence level
of involved stakeholders and increases motivation for research that is crucial
for keeping existing and attracting new scientists and technical personnel.
Beside that high level of R&D output informs educational institutions and help
them to adjust their programs that in a longer run influence the availability of
scientific and technical personnel with required competencies.
Motivation for
R&D Funding for public
i es
<Efficiency of IPR wan seneERED ane
management> + E
ao RD. Demand Delivery
Se , a ‘delay
+ x
Technology activities
Capability limits
5
Knowledge growth
competence A
scientific research Education Nz
programs —
a Private R&D R&D investment
finding _-
sae, growth —
‘
*Scicntsts ae
Capability Ex
” ee ap _ Passo Nepwork <Proeaiy=
ceflects Efficiency of IPR
SE ae manage:
cent ai
la v y <Knowldge Support for Guarantees and Risk
and Technology Networking industry R&D Capital measures
<R&D e. ‘meagures
Figure 3. R&D demand and supply.
Research and development capability that constitutes supply side for R&D
activities is a function from number active scientists and technical experts, their
technology knowledge and number of research centres that operate in the
respective sector. Number of scientists and technical persons is driven by
motivation of existing researchers to continue and newcomers to get involved
in R&D activities. In a long run adjustment of secondary and tertiary education
programs to industry demands will also increase the availability of human
resource with the right competence. It’s considered that one of the key leverage
points for government to increase R&D capability is to provide adequate base
funding for science and technology. This includes infrastructure investments
and running costs for public research centres (important part of it is attractive
remuneration level for key scientific personnel). Research centres provide
infrastructure, legal and intellectual property management framework for R&D
activities. Public research centres in Latvia currently fully depend on
government finance. However as links with industry, applied research and
experimental development will expand, more dynamic interactions with R&D
demand shall be establish. Thus evolution of research centres would become
more market driven, which eventually would increase their competitiveness
and lead to more effective utilization of public funding.
Public and private funding for domestic research projects constitutes the
demand for R&D activities. Public sector R&D spending is directly determined
by government policies whereas private sector contribution exhibits more
complex dynamics. It’s influenced by industry attractiveness and profitability
of the knowledge firms as well as perceived R&D investment risk. Our focus
here is on R&D activities performed within the country (knowledge import and
contracting R&D to foreign research institutions is considered as a part of
technology transfer). Therefore demand to the large extent depends on contacts
and level of cooperation between knowledge firms and local research centres.
By strengthening R&D and innovation linkages between industry and public
research organisations and stimulating inter-firm networking government can
have notable impact on increasing domestic demand. On the other hand
inadequate capability of domestic R&D performers is hampering domestic
demand and thus increase the investment risk. That in turn has adverse effect
on private sector R&D spending.
Increase of private sector R&D spending is a key objective in building
knowledge-based economy. Variety of policy instruments is available for
government to influence private sector motivation. The first set of policy
measures focus on reduction of R&D investment risk. Much R&D work is paid
for through finance supplied in the form of equity investments or certain types
of loans. Longer-term reinvestment of profits into further R&D by more
established knowledge intensive firms is typically built on this foundation.
Loan and equity guarantees are financial instruments, which transfer part or all
of the risk of investment from investors to the provider of the guarantee. The
most basic justification for guarantees is market failure in the sense that R&D
projects with favourable risk-return profiles are unable to obtain external
financing. Other direct leverage point for government to reduce the R&D
investment risk is support for research institutions and industry in managing
intellectual property rights. The policy instruments for developing favourable
intellectual property rights regime include clarification of ownership of IP;
adequate funding for the cost of protecting IP through patenting, for legal costs
and for professional intellectual property asset management [EU 2003]. Second
set of policy measures is aimed at direct advance of domestic R&D demand
either through increased funding for public sector R&D projects or through
supporting private projects (through grants, fiscal and other direct or indirect
measures).
Scarce human resources
Capability for applied research and experimental technology development
was to the large extent destroyed in Latvia together with industry demand
collapse in early nineties. Period of fundamental transformation of economy
and low public funding has significantly decreased domestic R&D activities.
This has lead to the situation where many scientists, engineers and other key
personnel have changed their occupation or even left the country. Also number
of doctoral students in natural and engineering sciences involved in research
has deteriorated. Thus significant human resource gap has evolved and it has
become one of the major impediments for rebuilding R&D capability in Latvia.
Professional
warn education
Attractivenes of
ae —————— Students in natural and
scientific research eer
engineering sciences Scientists and
ae technical experts
Scientists
Repatriation migration rate
programs
R&D
Funding for Science a , or,
Science and Research Capability
——____»
and 7 wi as
R&D
output <+—_______— abies
Figure 4. R&D resource adequacy.
Basic feedback structure for dynamics of scientific and technical experts is
shown in Figure 4. Disproportion between students in social and humanitarian
sciences vis-a-vis natural and engineering sciences has evolved during slow
down in R&D activity. Gradual increase in funding for personnel involved in
R&D activities in the long-term will motivate more graduates to start work for
10
research. However there will be significant time delay before attractiveness for
scientific research and its status in society is regained and new scientists and
technical experts are educated.
The only viable leverage that can deliver results in relatively short term is
change in (currently negative) immigration rate of key R&D personnel. This
can be achieved through repatriation programs for Latvian scientists that would
be interested to return to the country or attraction of foreign researchers in
chosen sectors. However both options require very focused increase in funding
which is difficult to achieve without explicit support from government
programs.
Conclusions and further steps
Latvia is on the way towards knowledge-based economy and government
shall have a sound economic, science and education policy to drive this
journey. Several policy instruments are available to influence the process.
Systemic approach with coordination between public institutions and industry
is required to find the right mix of policy measures and to achieve optimal
results.
Technology import and domestic R&D are the main sources of the
knowledge required for innovations. Openness and support for technology
transfer is very important for the small country like Latvia particularly in the
period of relatively low domestic R&D capability. However technology
transfer alone is not sufficient for sustainable growth. Advances in scientific
education, research and technological development are needed to sustain
competitiveness. Holistic view on complex R&D supply and demand
interactions is taken to evaluate the impact of different policy instruments.
Scarce number of scientific and technical personnel capable for competitive
applied research and experimental technology development is considered as
one of major impediment for advance in domestic R&D capability. Investments
for human resources and research infrastructure shall be balanced to achieve
adequate return. Both short and long term policy options for increasing R&D
11
capability require close cooperation between government institutions (in
particular Ministry of Science and Education and Ministry of Economics).
Further quantitative analysis for policy impact assessment is considered in
following areas.
e¢ Dynamics of R&D capability expansion — simulation model for
scientific and technical personnel development (considering age
structure) and balance between human resource and infrastructure
funding.
e Industry dynamics, innovation, R&D supply and demand in chosen
sector (electronics).
12
Figures
Figure 1. Government commitment, funding and knowledge-based economy.
Figure 2. Technology transfer and knowledge industry growth.
Figure 3. R&D demand and supply.
Figure 4. R&D resource adequacy.
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