MOVING ON:
FROM ENTERPRISE POLICY TO INNOVATION
POLICY IN THE WESTERN BALKANS
Working Paper No. 108
May 2010
Stephen Roper
Warwick Business School’s Small and Medium Sized Enterprise Centre
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1
Moving on: From enterprise policy to
innovation policy in the Western Balkans
Stephen Roper
Centre for Small and Medium Enterprises, Warwick Business School,
University of Warwick, Coventry, CV4 7AL, UK
Email: Stephen.Roper@wbs.ac.uk
Abstract:
Significant progress has been made in recent years in the development of enterprise
policy in the Western Balkans. Issues remain, however, in the support provided for
innovative enterprises. In this paper we use data from the 2005 Business Environment
and Enterprise Performance Survey to identify the determinants of innovation in
locally-owned firms in the Western Balkans and compare these to the other CEEE
countries and the CIS. Based on an econometric examination of the innovation
production function in each area we observe marked differences in the determinants
of innovation. First, in the Western Balkan countries (WBCs) R&D and higher-level
skills have little impact on firms’ innovation outputs, a result which contrasts strongly
with results for the CEEE, CIS and other more developed economies. Second, we find
no evidence of innovation benefits from urban locations in innovation in the WBCs or
that public support is having any positive effect on innovation outcomes. Again, this
experience is at odds with evidence from other regions. Third, innovation outputs in
the WBCs are being negatively influenced by aspects of the business environment.
These results suggest a need for an active and rather interventionist innovation policy
in the WBCs to address these system failures. A range of policy options are
developed.
Key words: Innovation, Western Balkans, innovation policy, innovation system,
transition
Acknowledgements:
I am grateful to David Storey who suggested the idea for the analysis reported in this
paper. Helpful comments were also received from the editors of this special issue and
two anonymous referees. Interpretations and mistakes are all my own work.
2
Moving on: From enterprise policy to innovation policy in the Western Balkans
1. Introduction
Since the adoption of the European Charter for Small Enterprises in 2003 the Western
Balkans Countries (WBCs) have made substantial progress in the development of
enterprise policy. As of 2010, all of the WBCs have in place the basic legal and
regulatory frameworks necessary for entrepreneurship and business development. In
terms of company registration, for example, almost all of the WBCs have made
significant progress in simplifying registration processes, and reducing the costs and
time taken to register new firms. The development of more targeted enterprise support
measures – for start-ups, export oriented firms or those led by women – remains more
uneven across the WBCs, however. And, even where such measures have been
implemented they often remain under-resourced compared to those in the new EU
Member States (OECD 2009, pp. 14-15). The ‘geography’ of enterprise policy across
the Western Balkans divides countries into three groups at different stages of
development: Albania, Bosnia and Herzegovina (BiH) and Kosovo have established
institutional and legal frameworks for enterprise policy but active policy intervention
remains limited to ad hoc and pilot projects; Macedonia, Montenegro and Serbia have
progressed further towards more comprehensive and nation-wide enterprise policy
implementation; while Croatia is most advanced in terms of enterprise policy with
policy implementation close to that of the new EU Member States1(OECD 2009, pp.
15-16.).
Alongside these developments in enterprise policy, recent studies also provide
evidence of positive attitudes to enterprise in the more economically advanced WBCs.
Comparing public attitudes to enterprise in Croatia, Serbia and Macedonia to EU and
US benchmarks suggests a positive picture with relatively high proportions of adults
in the Western Balkans seeing opportunities for entrepreneurship and feeling that they
have the necessary skill base for business start-up. For example, 53 per cent of
Croatian adults, 56 per cent of those in Serbia and 47 per cent of those in Macedonia
perceived good opportunities for start-up in the next six months in 2008 compared to
1
This is reflected in the recent establishment (January 2009) in Croatia of the South East European
Centre for Entrepreneurial learning (SEECEL) supported by the Croatian government and EU IPA
Programme. See http://www.seecel.hr.
3
48 per cent in the USA2. This is also reflected in reported levels of new business
activity which in all three countries are high by EU standards. In 2008, for example,
7.6 per cent of adults in Croatia were engaged in early stage entrepreneurial activity in
Croatia (Serbia, 7.6 per cent, Macedonia 14.5 per cent) compared to around 10.8 per
cent in the US3.
These developments in enterprise policy and positive attitudes to enterprise in the
WBCs cannot be seen, however, in isolation from the broader economic and policy
context. The most immediate concern is clearly the impact of the current global
recession which led to a sharp collapse in GDP growth rates in 2009 across the WBCs
accompanied by rapid increases in trade deficits and government borrowing (Gligorov
2009). Longer-term, however, if the WBCs are to correct their structural trade
deficits, there is a need to develop more innovative industries which can increase
productivity (Crepon et al. 1998) and compete internationally (Bleaney and Wakelin
2002). In this paper we consider the challenges which the WBCs face in moving on
from the 2003 to 2009 period of enterprise policy development to focus on innovation
policy. As a recent study by Krammer (2009) of the drivers of patenting in Eastern
Europe suggests this may require more public support for R&D and stronger
collaboration between universities and firms. The recent social and economic history
of the WBCs also suggests, however, that increasing innovation in the WBCs may
involve different challenges to those in other transition economies. Svarc (2006) for
example, emphasises the specific socio-political conditions within which innovation
policy in Croatia has developed, while Plenakovik and Pinto (2009) stress the
institutional and structural weaknesses in the Macedonian innovation system. Both
studies also stress the weakness of the innovation capability of many locally-owned
companies in the WBCs, and therefore the need to address this as a policy priority.
This suggests two key questions: First, what currently determines innovation in
locally-owned firms in the WBCs, and how does this differ from other transition and
developed economies? Second, what measures could then be adopted in order to
improve innovation capability in locally-owned firms across the Western Balkans?
Addressing these questions suggests the need for an active and interventionist
2
. Source: Global Entrepreneurship Monitor, 2008 Executive Report, Tables 1 and 2.
Source: Global Entrepreneurship Monitor, 2008 Executive Report, Tables 1 and 2.
3
4
innovation policy to improve corporate innovation capabilities as well as upgrading
nations’ innovation systems across the WBCs.
The remainder of the paper is organised as follows. In Section 2 we provide a
conceptual overview of the rationale for public intervention to support corporate
innovation (Asheim et al. 2007). This highlights the central role of firms’ innovation
capabilities in implementing innovation, and the potential for government intervention
to support such developments. Sections 3 and 4 address our main empirical question
investigating what currently determines innovation in the WBCs. Section 5 concludes
and identifies some potential policy options developed from best practice elsewhere.
2. Public policy and innovation development
Innovation occurs where firms apply new or pre-existing knowledge to introduce new
products, services or business models. This creates competitive advantage giving
innovating firms the opportunity to earn higher profits, gain new sales and potentially
enter new markets. At a fundamental level, the process of innovation or technological
development can be seen as part of an evolutionary dynamic in which products,
processes and services are steadily refined - and occasionally transformed – and
through which firms upgrade their innovation capabilities through organisational
learning (Nelson and Winter 1982). Current thinking also emphasises the social and
interactive nature of the innovation process reflecting the role of innovation
partnerships and networks and the importance of inter-organisational knowledge
flows (Chesborough 2003, 2006). This emphasises the importance of absorptive
capacity, and firms’ ability to identify and absorb external knowledge which can
complement internal knowledge resources (Zahra and George 2002; Roper and Love
2006). It also suggests the notion of an innovation system, i.e. ‘that set of distinct
institutions which jointly and individually contribute to the development and diffusion
of new technologies and which provide the framework within which governments
form and implement policies to influence the innovation process. As such it is a
system of interconnected institutions to create, store and transfer the knowledge, skills
and artefacts which define new technology’ (Metcalfe 1997, pp 461-462).
Innovation systems have been said to comprise three main elements (Autio, 1998): the
knowledge generation sub-system, the knowledge application and exploitation sub5
system, and the linkages between these two sub-systems. The first of these, the
knowledge generation and diffusion sub-system, comprises those organizations whose
corporate objectives relate either to knowledge creation (i.e. researching
organizations), knowledge sourcing, knowledge or technology transfer or regional or
national economic development (e.g. universities, third-level colleges, government
and industry research organisations, and technology transfer and technology
mediating institutions). Here, the position of the different WBCs is rather uneven with
Croatia and Serbia (and to some extent Macedonia and Albania) retaining significant
public sector and higher education R&D capabilities which are weaker elsewhere
(Svarc 2006; Machacova and Elke 2008). More positive perhaps are recent
developments in knowledge transfer and intermediary organisations such as business
centres, innovation and technology centres and inter-firm clusters (OECD 2009, pp.
124-132), although again these remain concentrated in Croatia, Serbia and
Macedonia.
The second key element of a national innovation system highlighted by Autio (1998)
is the innovation capability of firms. Filatotchev (2003), for example, argues that the
experience of a command economy might leave firms poorly equipped to cope with
the rigors of a market environment suggesting, in particular, that managers’ expertise,
flexibility and willingness to take risky decisions may be limited (Uhlenbruck, Meyer,
and Hitt 2003). Kriauciunas and Kale (2006) discuss essentially similar issues of
‘socialist imprinting’ in their study of firms in Lithuania and argue that privatisation
may be one route through which firms may acquire additional innovation capabilities:
‘Foreign Direct Investment (FDI) privatisations are likely to be associated with interfirm networks outside traditional networks, raising absorptive capacity’ (Filatotchev
et al. 2003, p. 341). Jensen (2004) in a study of Polish food producers also emphasizes
the more extensive international networks of externally-owned firms and the more
localized networks of locally-owned firms. Other aspects of firms’ resource base will
also shape their innovation capabilities. In-house R&D, for example, has a direct role
on knowledge creation and innovation {Crepon et al. 1998) and also a complementary
role in strengthening firms’ absorptive capacity (Griffith, Redding, and Van Reenan
2003). Likewise, workforce skills can play an important role in both contributing to
innovation capability (Freel 2005) and absorptive capacity (Roper and Love 2006).
6
The third key element of any innovation system highlighted by Autio (1998) is the
level of cooperation or association between the knowledge generating and knowledge
implementing elements of the system (Cooke and Morgan 1998). The value of such
co-operation in innovation is well established (Simonen and McCann 2008), although
science-industry co-operation often remains weak in transition economies (Svarc
2006; Leskovar-Spacapan and Bastic 2007). In terms of Croatia, at least, Svarc (2006)
attributes this in part to ‘socialist-style science policy’ in which R&D performing and
innovating organisations are separate, and in which innovation itself is technology
driven rather than market-led.
Weaknesses in any of these three aspects of an innovation system may generate
system failure leading to under-performance in innovation (Woolthuis, Lankhuizen,
and Gilsing 2005). This suggests a role for public policy to ‘address systemic failures
that block the functioning of innovation systems or hinder the flow of knowledge and
technology … Such systemic failures can emerge from mismatches between the
different components of an innovation system, such as conflicting incentives for
market and non-market institutions (e.g. enterprises and the public research sector), or
from institutional rigidities based on narrow specialisations or asymmetric
information’ (OECD 1999). More positively, recent thinking in the innovation
systems tradition suggests that national competitive advantage may be ‘consciously
and pro-actively constructed’ as a result of public sector intervention in an innovation
system (Asheim et al. 2007; Cooke and Leydesdorff 2006). There is substantial
evidence, for example, that public support for private sector R&D and innovation
activity can have a positive impact on firms’ innovation outputs in both developed
(Griliches 1995; Mamuneas and Nadiri 1996; Hewitt-Dundas and Roper 2009) and
transition economies (Czarnitzki and Licht 2006).
To evaluate the way in which these different factors come together to influence the
innovation capabilities of locally-owned firms in the WBCs we focus our empirical
analysis on the notion of an innovation or knowledge production function (Griliches
1992; Love and Roper 1999). This relates firms’ innovation outputs to the different
factors which might influence the innovation process both from within and outside the
firm. For firm i this can be written as:
7
I i  0  1 FCi  2 LM i  3 PS i  4ODi   i
(1)
Where Ii is an innovation output indicator, FCi is a set of firm-specific characteristics,
LMi is a set of location and market indictors, PSi indicates public support, ODi are
operating difficulties identified by the firm and εi is a random error term.
3. Data and methods
Our analysis of the determinants of innovation in locally-owned firms in the WBCs is
based on data taken from the 2005 Business Environment and Enterprise Performance
Survey (BEEPS). Financed jointly by the European Bank for Reconstruction and
Development and the World Bank this survey was undertaken between 10th March
and 20th April 2005 and included 28 countries including all of the WBCs with the
exception of Kosovo4. The survey objective was to be broadly representative of the
market-driven sectors of each country reflecting the mix of manufacturing and
services activity, but excluding those sectors of each economy subject to government
price regulation and prudential supervision (i.e. banking, electric power, rail transport,
and water and waste water)5. The target population comprised enterprises which were
established prior to 2002, and had between 2 and 10,000 employees6. The survey
achieved an overall response rate of 36.8 per cent with significantly higher response
rates achieved in each of the WBCs (Synovate 2005)7. In each country sampling
frames were constructed from official government company registers, Chamber of
Commerce membership lists and commercial sources such as the Yellow Pages.
To date the main use of the BEEPS data has been to profile aspects of the business
environment in each country and to examine the impact of criminal activity and
corruption on business development. Krkoska and Robeck (2006), for example,
demonstrate the deterrent impact of crime on FDI inflows and job creation. The
4
The 2005 BEEPS covered: Albania, Armenia, Azerbaijan, Belarus, Bosnia, Bulgaria, Croatia, Czech,
Estonia, Serbia and Montenegro, Macedonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia,
Lithuania, Moldova, Poland, Romania, Russia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine
and Uzbekistan.
5
Some other quota restrictions relating to size, ownership, exporting and location were also imposed
but probably limited in effect (Synovate 2005, p. 4).
6
This figure reflects the overall response rate to all three elements of the BEEPS 2005 survey (i.e. the
random sample, panel sample and manufacturing overlay). Overall, 26249 firms were contacted with
9655 completed interviews (36.8 per cent).
7
For the Western Balkan countries there was no manufacturing uplift and response rates were: Albania
48.1 per cent; BiH, 46.0 per cent; 50.6 per cent; Croatia, 45.8 per cent; Serbia and Montenegro, 45.8
per cent. (Synovate 2005).
8
BEEPS survey, however, also includes variables reflecting whether firms have
‘developed successfully a major new (or upgraded) product line or service over the
last 3 years’. Around 39 per cent of locally-owned firms in the WBCs reported
developing new products, slightly above the 37 per cent in the CIS countries (Table
1). More significant, however, was the difference in the level of more incremental
product/service upgrading in the WBCs undertaken by a further 29 per cent of firms
(CEEE 22 per cent, CIS 21 per cent). The extent of process innovation among firms in
the WBCs was also marginally above that in the CIS countries (39 per cent of firms
compared to 34 per cent) and significantly greater than that in the CEEE countries (28
per cent). In broad terms these comparisons suggest that the extent of new
product/service and process innovation in the WBCs is broadly in line with the CIS
countries (and above that in CEEE) with an emphasis on more incremental
product/service change.
In addition to these innovation indicators the BEEPS dataset also contains a rich set of
other variables which give an indication of firms’ internal resources and operating
environment. Firm vintage, for example, may reflect the potential for the cumulative
accumulation of knowledge capital by older establishments (Klette and Johansen
1998). Firm size (employment), in-house R&D capability and skill levels also reflect
aspects of absorptive capacity and would be expected to be positively related to firms’
innovation outputs. The BEEPS data suggests that locally-owned firms in the WBCs
were generally larger (average 108 employees) than those in either the CIS or CEEE
countries with higher levels of intermediate (high school qualifications) but generally
had lower levels of graduate employment (Table 1). In terms of their effects on
innovation outputs these factors suggest offsetting positive (firm size) and negative
(skills) effects.
The BEEPS dataset also provides details of the ownership profile of each firm, its
privatisation history and group membership, each of which may also impact on
innovation outputs. Locally-owned firms in the WBCs were also more likely to be
single proprietorships (53.1 per cent) than those in CIS or CEEE countries (Table 1).
In terms of their privatisation history, firms in the WBCs were more likely to be a
privatised firm than in the CIS but less likely to be a private start-up (Table 1).
9
Other factors are included in our estimates of the innovation production function to
reflect differences in firms’ operating environments. To reflect potential differences in
the availability of external knowledge resources – university or research institutes,
skilled labour, specialist support services – for example, we identify whether firms are
located in large city or capital or medium-sized city (Asheim and Isaksen 1996).
Firms in the WBCs seem less concentrated in large cities or the capital than in the CIS
but more strongly concentrated in urban locations than in the other CEEE countries
(Table 1). Firms in the WBCs also seem less likely to have received government
support than those in the CEE countries (Table 1). Finally, the BEEPS dataset also
includes a number of subjective indicators of the general operating difficulties which
firms perceive relating to finance, skills, regulation and corruption (Table 2). Finance,
customs and trade regulation and regulatory and judicial uncertainty were more
commonly reported as important operating difficulties in the WBCs than in the
sample as a whole and may be barriers to innovation (Roper et al. 2008).
4. Empirical results
Bivariate probit models of the innovation production function, reflecting the
probability that locally-owned firms undertook either (new or upgrading) product or
service innovation during the 2002 to 2005 period, are reported in Table 3. The table
includes three models, one each relating to locally-owned firms in the WBCs, the
other CEEE countries excluding the WBCs, and the CIS countries. In each case, the
estimated models included a series of dummy variables designed to capture industry
differences. Statistically significant variables are highlighted. Of primary interest here
are the contrasts between the determinants of innovation in the WBCs and the other
groups of transition economies which might suggest a focus for innovation policy in
the WBCs.
In terms of the impact of firm characteristics on the probability of innovating we see
some key contracts between the WBCs and both the CEEE and CIS countries. Inhouse R&D, in particular, has no significant role in shaping the probability of
innovation in the WBCs, while it increases the probability of innovating by 3.4 per
cent in the CEEE countries and 5.9 per cent in CIS (Table 3). A positive relationship
between in-house R&D is also generally found in more developed economies (Harris
and Trainor 1995; Love and Mansury 2007; Santarelli and Sterlacchini 1990;
10
Simonen and McCann 2008) emphasising the uniqueness of this result for the WBCs.
Similarly, neither high-school level or graduate level skills play any significant part in
shaping the probability of innovation in the WBCs. Again, this result contrasts
strongly with evidence from other developed economies (Freel 2005; Leiponen 2005;
Mutula and Van Brakel 2007) and also the other CEEE economies (Table 3)8.
Another striking difference between the determinants of innovation in the WBCs and
the CEEE and CIS countries is that of the legal status of the firm. While limited
company status has previously been linked to business growth (Storey 1994) it is also
strongly and positively linked to the probability of innovating in both the CEEE and
CIS countries, increasing the probability of innovating by 19-21 per cent (Table 3).
No such impact is evident in the WBCs suggesting that the innovation advantages –
and potentially also the growth advantages – of limited liability status are less evident
in the WBCs than elsewhere. For example, a lack of availability of risk capital in the
WBCs may mean that limited liability status is of less value to business owners than
in situations where external finance is more easily available.
Two important commonalities are also evident in the determinants of innovation
across the areas considered here. In common with CEEE and CIS countries, locallyowned firms in the WBCs which are exporting or which are part of a multi-plant
group are significantly more likely to be innovating than other firms (Filatotchev et al.
2003; Jensen 2004). Moreover, both effects are of similar size with exporting
increasing the probability of product or service innovation by 7.9 per cent and being
part of a multi-plant group increasing the probability of innovation by 9.8 per cent
(Table 3). Both suggest the importance of the inter-relationship between export
activity and innovation (Bleaney and Wakelin 2002; Lachenmaier and Wobmann
2006; Roper and Love 2002; Wakelin 1998) as well as the potential importance of
intra-firm sharing of knowledge or resources. These results provide support for the
arguments made by Filatotchev (2003) suggesting that export market exposure is
more important in shaping firms’ innovation activity than external-ownership.
In summary, although we see commonalities between the firm-level determinants of
innovation in the WBC and other CEEE and CIS economies – around exporting and
8
Interestingly, here for firms in the CIS countries, where graduate skills are more common than in the
WBCs (Table 1), we also find little skills effect on innovation.
11
organisational structure – it is perhaps the differences with are more striking. In
particular, the lack of significance of the R&D and graduate skills variables in the
innovation production function for the WBCs suggests the weakness of the internal
technological capabilities and absorptive capacity of many locally-owned firms’
(Filatotchev et al. 2003). The lack of any firm age or size effect on the probability of
innovating is also somewhat unexpected suggesting the weakness of organisational
learning and lack of any cumulated advantage for innovation (Table 3).
As the innovation systems literature suggests, however, firms’ innovation outputs can
also be strongly influenced by locational factors and their operating environment. In
the innovation production functions we therefore include locational dummies to
capture the potential innovation (agglomeration) advantages of more urbanised
locations (Chai and Huang 2007). For the WBCs in common with the other CEEE
countries the results are disappointing with no evidence of any innovation advantage
from either a large city or medium-sized city location (Table 3). By contrast, being in
a large city or capital in the CIS countries increases the probability of product or
service innovation by around 7 per cent. Other potential environmental effects on the
probability of innovating are reflected in a series of variables reflecting the difficulties
firms perceive in their business environment (Table 2). Perhaps most notable here is
the negative impact of customs and trade regulations on innovation in the WBCs (-10
per cent) with no such effect in either the CEEE or CIS countries. Other operating
difficulties are common across the regions with difficulties related to ‘skills and
education’ having an unexpected positive effect on innovation in each of the three
regions9. Finally, our analysis suggests that in the WBCs (as in the CIS countries)
public support from national, regional or EU sources is having no effect on the
probability of product or service innovation. This is a marked contrast with the other
CEEE countries where regional and EU support are increasing the probability of
innovation (by 13.1 and 17.1 per cent respectively).
Our comparisons suggest that there is little in the business environment in the WBCs
which can compensate for the weaknesses in the internal innovation capabilities of
9
This result is not uncommon in other innovation studies based on cross-sectional data and probably
reflects reverse causality with those firms which are innovating also more likely to be those for which
skill constraints are binding.
12
locally-owned firms. Neither the potential innovation advantages of more urbanised
areas which are evident in the CIS countries, or public supports evident in the CEEE
countries are effective in the WBCs (Table 3). Moreover, environmental factors seem
to be undermining the potential innovation advantages of limited liability status as
well as creating difficulties with customs and trade regulations.
5. Conclusions and Discussion
The proportion of firms reporting the introduction of new products or services in the
WBCs is broadly in line with that in the CIS countries, and above that in the other
CEEE economies. Our empirical analysis, however, suggests some unique features of
innovative activity in the Western Balkans both in contrast to the CEEE and CIS
countries considered here as well as more advanced economies. First, the weakness of
firms’ R&D and higher-level skills as drivers of innovation contrasts strongly with
both the other CEEE and CIS countries and more developed economies. Second, we
find no evidence of innovation benefits from urban locations in innovation in the
WBCs or effective public support. Again, this experience is at odds with that in the
CEEE and CIS countries reported here and other studies which report similar analyses
for more advanced economies. Third, innovation outputs in the WBCs are being
negatively influenced by the business environment which is both undermining the
innovation advantages of limited liability status and creating difficulties with customs
and trade regulations. Neither the internal weaknesses of firms identified here nor the
more systemic weaknesses are unanticipated, however. Svarc (2006) in her review of
innovation policy in Croatia emphasises similar concerns emphasising ‘low
technological capabilities of companies’ and the ‘lack of a stimulating environment’
for innovation.
Addressing either issue will require an acceptance that the development of national
innovation capability is a valid area for policy intervention alongside more traditional
concerns about macro-economic stability, public finance etc (Asheim et al. 2007).
This is something which Svarc (2006) argues may be particularly difficult in
transition economies where there is a danger that ‘innovation policy was perceived
not only as irrelevant but also as a relic of state interventionism inherited from
socialistic times’ (p. 157). However, the experience of Europe’s most successful
innovating economies suggests the value of an active and focussed approach to
13
innovation policy which addresses systemic failures in the innovation system
(Woolthuis, Lankhuizen, and Gilsing 2005), and potentially new institutional models
focussed on innovation system development (Fargerberg and Srholec 2008). Perhaps
the best developed example here is Vinnova - the Swedish Governmental Agency for
Innovation Systems. Established as an arms-length government body in 2001,
Vinnova has focused on developing a detailed understanding of the capabilities of the
Swedish innovation system, identifying system failures and then investing to support
collaborative innovation projects on either a network, sectoral or geographical basis10.
Recent discussion led by Serbia of establishing a collaborative innovation centre for
the Western Balkans (as a counterpart to the South East European Centre for
Entrepreneurial Learning) is potentially a positive first step in this direction.
More broadly, recent developments in enterprise policy in the WBCs since 2003,
reflected in the EU SME Charter process, have started to address some of the issues in
the business environment highlighted by our empirical analysis (OECD 2009). In
particular all of WBCs have made substantial progress in supporting export
development since the 2005 BEEPS survey was undertaken. AOFI, the export credit
and insurance agency for Serbia, for example, was formed in 2005. Such measures
may help to address the negative impact on innovation in the WBCs of customs and
trade regulation. As (OECD 2009) also notes, however, ‘most of the Western Balkan
governments are at a relatively early stage in introducing targeted policies for relevant
types of SMEs … For instance, few governments have introduced measures targeting
start-ups, targeting innovative enterprises, or supporting technological or nontechnological innovation’ (p. 15). Addressing the weaknesses in the innovation
capability of individual firms identified here – particularly the links between skills,
R&D and innovation – is likely to require policy development to support both
technological and non-technological (or hidden) innovation (NESTA 2007). The
benefits of support measures for technological innovation have been widely discussed
(Buiseret, Cameron, and Georgiou 1995; Hewitt-Dundas and Roper 2009; Martin and
Scott 2000) with a range of support mechanisms being discussed in the literature
including grants (Czarnitzki and Licht 2006), personnel subsidies, R&D tax credits
10
See Vinnova website www.vinnova.se, and review of activities in 2007 ‘Innovation and Leading
Research’ – Vinnova 2007.
14
(Mansfield 1986), innovation vouchers (Cornet, van der Steeg, and Vroomen 2007;
Cornet, Vroomen, and van der Steeg 2006) and credit guarantee schemes.
A key theme to emerge from the evaluation literature on these measures is the need to
structure such initiatives to increase innovative collaboration, something which Svarc
(2006) highlights as another key weakness of Croatian innovation system (LeskovarSpacapan and Bastic 2007). Collaboration between firms and the research-base might
also be usefully encouraged by developing Competence Research Centres (CRCs) in
the WBCs. Typically CRCs bring together enterprises and university-based research
centres in long-term collaborative relationship aimed at a particular technology. The
best established of these programmes (in Sweden) has provided overwhelming
evidence of the value of this type of initiative, a result echoed in early evaluation
results from Hungary and Estonia (Vinnova 2004). CRCs have also been seen as
contributing to internationalisation by acting as a focus for international R&D
collaboration which might also help WBC firms to overcome the barriers to trade
discussed earlier.
Public support for non-technological innovation is also likely to be important in the
future development of the WBCs both in the service and manufacturing sectors
(Czarnitzki and Spielkamp 2003; de Jong et al. 2003). Internationally, policy has
developed rapidly in this area in recent years although best practice remains less clear.
One potential policy model which might be considered by the WBCs to support the
development of non-technical innovation capacity is the Finnish ‘Serve’ scheme.
Operated by the Tekes agency this aims to encourage the development of innovative
service concepts and service business models in companies; strengthen and diversify
service related innovation activities, especially in SMEs; improve productivity and
quality of service activities in various industries; and boost academic research in the
area of service development. It does this by providing grant support to innovating
enterprises supporting a proportion of the cost of innovation projects.
Combining such targeted measures with more broadly based policies aimed at
improving the environment for innovation will both be necessary if the WBCs are to
maximise the potential economic benefits of innovation. Policy development for
innovation will also be important, however, as the WBCs work to move their policy
15
regimes closer to those operating within the EU, particularly as Europe steadily
implements the 2008 Small Business Act with its emphasis on innovation capability
in SMEs. Moving on from enterprise policy to innovation policy will therefore help to
advance both economic and political agendas for the WBCs and also mark another
phase in the transition from state socialism towards the free market.
16
Table 1: Descriptive Data: Locally-owned firms
Western Balkans
Countries (WBC)
N=1019
Mean
St. D.
CEEE (excluding
WBC)
N=4012
Mean
St. D.
CIS
Countries
N=3644
Mean
St. D.
Innovation Indicators
New product or service
Improved product or service
Process innovation
39.3
29.1
39.0
48.8
45.5
48.8
29.4
22.3
27.4
49.9
41.6
44.6
37.2
21.0
34.1
48.3
40.7
47.4
15.5
107.5
51.1
51.2
22.2
53.1
18.1
1.1
15.8
28.9
35.8
15.9
14.4
71.6
1.3
0.5
21.9
330.3
50.0
32.7
24.3
49.9
38.5
10.3
36.5
45.3
48.0
36.6
35.2
45.1
11.2
7.0
12.5
82.8
47.2
41.2
20.4
32.8
29.4
1.8
27.2
25.1
24.3
23.0
8.8
79.3
1.3
0.6
17.4
348.6
49.9
32.0
26.2
46.9
45.6
13.2
44.5
43.4
42.9
42.1
28.3
40.5
11.3
7.7
10.0
95.3
56.0
27.4
35.0
43.0
21.9
2.8
22.1
12.8
18.2
20.9
18.4
67.8
1.9
0.9
15.9
405.8
49.6
28.6
30.5
49.5
41.3
16.6
41.5
33.5
38.6
40.7
38.7
46.7
13.7
9.6
Location and Markets
Large city or capital
Medium-sized city
39.1
37.4
48.8
48.4
28.0
42.9
44.9
49.5
43.4
37.1
49.6
48.3
Public support
Subsidies from state
Subsides from region
Subsidies from the EU
5.7
2.4
0.4
23.2
15.2
6.3
6.0
3.4
3.1
23.7
18.0
17.4
1.2
1.1
0.3
10.9
10.3
5.7
Firm characteristics
Plant age in 2005
Employment (2003)
Research and development
Workforce with high school quals (%)
Workforce with graduate quals (%)
Single proprietor
Partnership
Cooperative
Limited company
Exporting firm
Part of multi-plant group
Women-led enterprises
Privatised state company
Private start-up
Private subsidiary of former state co.
Joint venture with external partner
Note: See data annex for variable definitions
Source: BEEPS 2005
17
Table 2: Descriptives: Operating Difficulties
Access to finance
Tax rates
Tax administration
Customs and trade regulations
Skills and education
Western Balkans
Countries (WBC)
N=1019
Mean
St. D.
22.6
41.8
23.5
42.4
15.3
36.0
12.2
32.7
7.4
26.1
CEEE (excluding
WBC)
N=4012
Mean
St. D.
20.2
40.1
39.8
49.0
26.8
44.3
8.8
28.4
12.4
32.9
CIS
Countries
N=3644
Mean
St. D.
16.0
36.6
28.5
45.1
22.3
41.6
10.6
30.8
9.5
29.4
32.6
46.9
28.5
45.2
20.1
25.6
43.7
14.5
35.2
9.6
Notes: Figures are the percentage of firms highlighting each factor as either a ‘very important’ or
‘fairly important’ operating difficulty. Variable definitions are in Annex 1.
Source: BEEPS 2005
Uncertainty about regulation
Functioning of judiciary
40.1
29.5
18
Table 3: Probit models for the probability of undertaking new or improved
product/service innovation in locally-owned firms
Western Balkans
Countries (WBC)
N=1019
dy/dx
CIS
Countries
N=3644
CEEE (excluding WBC)
N=4012
z
dy/dx
z
dy/dx
z
Firm Characteristics
Plant age in 2005
Employment (2003)
Research and development
Workforce with high school quals (%)
-0.002
-1.520
-0.001
-1.220
0.001
0.000
1.440
0.000
1.610
0.000
-0.017
-0.550
0.034
0.000
-0.550
0.000
Workforce with graduate quals (%)
0.000
-0.380
0.002
Single proprietor
0.984
0.400
0.093
Partnership
0.659
0.090
0.139
Cooperative
0.314
0.980
0.143
2.080
0.089
*
**
*
**
*
**
*
0.059
0.920
-0.001
5.140
0.000
1.090
0.151
1.670
0.168
1.580
0.035
2.660
0.192
4.420
0.149
3.350
-3.330
0.750
1.390
*
1.660
0.310
0.608
Exporting firm
0.079
Part of multi-plant group
0.098
2.830
0.069
3.460
Women-led enterprises
0.016
0.390
-0.027
-1.310
Privatised state company
-0.870
-0.240
0.022
0.270
-0.118
-1.070
Private start-up
-0.776
-0.080
0.000
0.000
-0.052
-0.490
Private subsidiary of former state co.
-0.721
-1.150
0.047
0.450
-0.183
-1.490
Joint venture with external partner
-0.710
-2.140
0.181
1.520
-0.044
-0.300
**
0.211
**
*
2.020
1.430
**
*
**
*
Limited company
**
**
*
0.090
**
0.760
1.960
0.121
**
**
*
**
*
-0.047
**
-2.120
5.680
5.560
Location and Markets
**
*
Large city or capital
-0.020
-0.490
0.023
1.010
0.070
Medium-sized city
0.055
1.340
0.000
0.020
0.038
2.870
1.570
-0.022
-0.310
0.052
1.390
0.055
0.640
2.750
-0.054
-0.630
3.560
-0.010
-0.060
Public Support
Subsidies from state
**
*
**
*
Subsides from region
0.089
0.960
0.131
Subsidies from the EU
-0.150
-0.600
0.171
Access to finance
-0.004
-0.100
0.017
0.780
-0.041
*
-1.670
Tax rates
-0.076
-1.550
-0.003
-0.140
0.060
**
2.530
0.021
0.390
0.008
0.370
0.023
-1.680
0.033
1.050
0.029
Operating Difficulties
Tax administration
Customs and trade regulations
-0.100
*
Skills and education
0.099
*
1.750
0.097
Uncertainty about regulation
0.090
**
2.340
Functioning of judiciary
0.077
*
1.950
Number of observations
Equation χ2
Log Likelihood
Pseudo R2
**
*
0.870
0.920
**
*
3.820
0.137
0.004
0.200
0.028
1.170
0.022
0.870
0.024
0.750
979
3886
3560
112.91
367.59
383.71
-557.791
-2507.6
-2228.6
0.0919
0.0683
0.0793
4.700
Notes and sources: Values reported are marginal values. All models include industry dummy variables
(not reported) and constant terms. Reference groups - rural enterprises, state-owned firms, other
services. See Annex 1 for variable definitions. * denotes significance at the 10 per cent level; ** at 5
per cent and *** at the 1 per cent level.
Source: BEEPS 2005
19
Annex 1: Variable definitions
Innovation Indicators
New product or service
Process innovation
Firm characteristics
Plant age in 2005
Employment (2003)
Research and development
Workforce with high school
quals. (%)
Workforce with graduate
quals. (%)
Single proprietor
Partnership
Cooperative
Limited company
Majority externally owned
Exporting firm
Part of multi-plant group
Women-led enterprises
Privatised state company
Private start-up
Private subsidiaries of former
state Company
Joint venture with external
partner
Firm ‘developed successfully or upgraded a major new product line or
service over the last 3 years’ (items 1312 and 1313)
Firm has ‘acquired new production technology over the last 36 months’ (item
1328)
Years since firm first began operations in this country (item 129)
How many full-time employees does your business have now – and how
many did it have three years ago (2003) (item 1355-1359)
Positive spending on R&D including wages and salaries of R&D personnel,
R&D materials, R&D education and R&D related training (item 1257-1263)
What percentage of the workforce of your firm has education levels up to
secondary school (item 1444-1446)
What percentage of the workforce of your firm has education levels up to
university level (item 1447-1449)
Legal status of firm: single proprietorship (items 134-135)
Legal status of firm: partnership (items 134-135)
Legal status of firm: cooperative (items 134-135)
Legal status of firm: corporation, privately held or listed on stock exchange
(items 134-135)
What percentage of the firm is owned by private foreign
individuals/companies/organisations (> 50 per cent ) (item151-153).
Does your firm currently sell its products or services directly to customers
outside the country (item 168)
How many establishments (separate operating facilities) does your firm have
in this country (item 173-174)
Is the principle owner (or one of the principle owners) female? (item 249)
How was your firm established: Privatisation of a state-owned firm (item 250)
How was your firm established: Originally private from the time of start-up
(item 250)
How was your firm established: Private subsidiary of a former state owned
firm (item 250)
How was your firm established: Joint venture with foreign partners; (item
250)
Location and Markets
EU plus region
Western Balkans location
Large city or capital
Medium-sized city
Mining
Construction
Manufacturing
Transport, storage and
communication
Wholesale and Retail trade;
repair of vehicles and
household goods
Real Estate, renting and
business services
Hotels and Restaurants
Other services
Includes: Turkey, Slovenia, Poland, Hungary, Czech Rep., Slovakia,
Romania, Bulgaria, Latvia, Lithuania, Estonia
Includes: Macedonia, Serbia, Montenegro, Albania, Croatia, BosniaHerzegovina
Located in capital city or other city with population greater than one million
(item city)
Located in city with population greater than 50,000 (item city)
Firm is in ISIC Section C: 10-14 (item ISIC DIVISION)
Firm is in ISIC Section F: 45 (item ISIC DIVISION)
Firm is in ISIC Section D: 15-37 (item ISIC DIVISION)
Firm is in ISIC Section I: 60-64 (item ISIC DIVISION)
Firm is in ISIC Section G: 50-52 (item ISIC DIVISION)
Firm is in ISIC Section K: 70-74 (item ISIC DIVISION)
Firm is in ISIC Section H: 55 (item ISIC DIVISION)
Firm is in ISIC Section O: includes motion picture and video activities, other
entertainment activities, news agency activities, washing and dry cleaning,
hairdressing, funeral and related activities, other service activities (item ISIC
20
DIVISION)
Public support
Subsidies from state
Subsides from region
Subsidies from the EU
Operating difficulties
Access to finance
Cost of finance
Access to land
Title or leasing of land
Tax rates
Tax administration
Customs and trade regulations
Skills and education
Uncertainty about regulation
Macro instability
Functioning of judiciary
Corruption
Over the last 36 months has your firm received any subsidies from the
national government? (item 1060)
Over the last 36 months has your firm received any subsidies from the
regional/local government? (item 1061)
Over the last 36 months has your firm received any subsidies from EU
sources? (item 1062)
Access to finance (e.g. collateral required or financing not available from
banks) either ‘moderate’ or ‘major’ obstacle to the operation and growth of
the business (item 1108)
Cost of financing (e.g. interest rates and charges) either ‘moderate’ or ‘major’
obstacle to the operation and growth of the business (item 1109)
Access to land either ‘moderate’ or ‘major’ obstacle to the operation and
growth of the business (item 1113)
Title or leasing of land either ‘moderate’ or ‘major’ obstacle to the operation
and growth of the business (item 1114)
Tax rates either ‘moderate’ or ‘major’ obstacle to the operation and growth of
the business (item 1115)
Tax administration either ‘moderate’ or ‘major’ obstacle to the operation and
growth of the business (item 1116)
Customs and trade regulations either ‘moderate’ or ‘major’ obstacle to the
operation and growth of the business (item 1117)
Skills and education of available workers either ‘moderate’ or ‘major’
obstacle to the operation and growth of the business (item 1120)
Uncertainty about regulatory policies either ‘moderate’ or ‘major’ obstacle to
the operation and growth of the business (item 1121)
Macro instability (inflation, exchange rates) either ‘moderate’ or ‘major’
obstacle to the operation and growth of the business (item 1122)
Functioning of judiciary either ‘moderate’ or ‘major’ obstacle to the operation
and growth of the business (item 1123)
Corruption either ‘moderate’ or ‘major’ obstacle to the operation and growth
of the business (item 1124)
21
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