Fostering_product_innovation_Differences

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Fostering product innovation: Differences between new ventures
and established firms
Raquel Antolín-López, José Céspedes-Lorente, Nieves García-de-Frutos,
Javier Martínez-del-Río, Miguel Pérez-Valls n
Universidad de Almería, Department of Economy and Business Administration, Carretera de Sacramento s/n, Almería 04120, Spain
a r t i c l e i n f o
Keywords:
Entrepreneurship
New ventures
Innovation policy
Product innovation
Competency-based view
a b s t r a c t
This study combines insights from the entrepreneurship, competency-based view and innovation policy
literature to analyze the relationships among different types of public incentives designed to foster
innovation and product innovation at both new ventures and incumbent firms. To test our hypotheses,
we ran a system of regression models on a cross-national sample comprised of 5238 firms from 29
European countries and found a different pattern for new ventures and incumbents. Our results suggest
that support for attendance or participation in trade fairs and networking with other companies are the
most effective methods of promoting product innovation for new ventures. However, for incumbent
firms, we found that the most effective policies consisted of tax reduction for R&D expenditures and
subsidies for acquiring buildings or other infrastructure(s) for innovation activities. This distinction
prompts interesting insights related to theory development in research on entrepreneurship and
innovation policy.
& 2015 Elsevier Ltd. All rights reserved.
1. Introduction
A growing body of research addresses the effectiveness of public
support instruments designed to incentivize firm innovation (e.g.,
Almus and Czarnitzki, 2003; Busom, 2000; Gonzalez and Pazo, 2008).
This research stream largely focuses on the effects of public innova-
tion programs on firms' R&D investments (e.g., David et al., 2000;
Klette et al., 2000; Lach, 2002; Wallsten, 2000) and, in particular, on
whether public R&D funding has a “crowding-out” or substitution
effect on private R&D investment (e.g., Aerts and Schmidt, 2008;
Almus and Czarnitzki, 2003; Czarnitzki and Fier, 2002; Czarnitzki and
Lopes-Bento, 2013; Yang et al., 2012). Although there are exceptions
(e.g., Cappelen et al., 2012; Czarnitzki et al., 2011; Huergo andMoreno,
2014), studies have not typically examined the effectiveness of public
R&D programs using output measures such as patents and product
innovations; as a consequence, little remains known about how
effective public policy instruments are in this regard. In addition,
although policy makers have employed a variety of innovation policy
instruments, a vast majority of this literature focuses narrowly on one
type of R&D program. In particular, there is a need for studies that
compare the effectiveness of different types of public instruments;
thus, the specific impact of such instruments on firm innovation
output remains unclear (e.g., Blanes and Busom, 2004; Woolley and
Rottner, 2008). For example, many previous studies use the Commu-
nity Innovation Survey (e.g., Aerts and Schmidt, 2008), which contains
limited information in this regard.
In this paper, we focus on an analysis of the differential effect of
a number of public funding schemes on the innovation output of
new ventures and incumbent firms. This approach is relevant
because governments employ economic rationales to support
innovative new ventures based on the reasoning that new ven-
tures generate the most new jobs in developed economies and
play a significant role in the emergence of new economic sectors
(e.g., Sine and Lee, 2009). New ventures also improve resource
allocation in the economy by identifying factors that established
players may be blind to, such as when goods or services become
unexpectedly valuable or feasible for consumers (Ireland et al.,
2003). Moreover, Arrow (1962) and Nelson (1959) indicated that
innovations by new ventures frequently generate positive external
effects that cannot be internalized by the entrepreneurs.
Public support can make a difference in a firm's early stages
(Norrman, 2008). New ventures frequently fail to develop innovative
ideas because they lack the appropriate assets and capabilities
(Arthurs and Busenitz, 2006; Norrman and Klofsten, 2009). We
contend that because new ventures may find particularly difficult
to deploy, develop and combine their innovative capabilities (Alvarez
and Busenitz, 2001), they can also get the maximum benefit from
public instruments specifically intended to facilitate the development
of such capabilities. For example, instruments intended to increase a
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/technovation
Technovation
http://dx.doi.org/10.1016/j.technovation.2015.02.002
0166-4972/& 2015 Elsevier Ltd. All rights reserved.
n Corresponding author. Tel.: þ34 950 214173; fax: þ34 950 015178.
E-mail addresses: ral252@ual.es (R. Antolín-López),
jcespede@ual.es (J. Céspedes-Lorente), gdn779@ual.es (N. García-de-Frutos),
jamartin@ual.es (J. Martínez-del-Río), mivalls@ual.es (M. Pérez-Valls).
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎
www.sciencedirect.com/science/journal/01664972
www.elsevier.com/locate/technovation
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
mailto:ral252@ual.es
mailto:jcespede@ual.es
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http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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https://www.researchgate.net/publication/268296462_Entrepreneurship_Policy_Public_Support_for_Technology-Based_Ventures?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
firm's contact networks may be particularly beneficial because they
assist new ventures in gaining access to valuable knowledge outside
of company boundaries, which is one of the most important assets
involved in product innovation(Chesbrough, 2003). Although public
administrations may support innovationwith many different types of
instruments, the most widely used in recent years in Europe include
subsidies and grants, tax incentives, financing, funding for network-
ing with companies and research institutes, and facilitating informa-
tion on market conditions (COM, 2009).
This paper thus tackles which innovation policy instruments are
better at fostering product innovation in new ventures compared
with incumbents. In seeking to answer this research question, this
paper makes two theoretical contributions: first, we provide new
theoretical insights into the notion that innovation policy instru-
ments might have different effects on new ventures than on
incumbent firms. Our current understanding of the dissimilarities
among policy instruments is weak. An important contribution of this
paper is its focus on identifying the differences among the most
common innovation policy instruments and how these instruments
affect product innovation in both new ventures and incumbent firms.
Second, this research links the competency-based view with entre-
preneurship and innovation policy literatures to suggest that these
differences involve the ability of innovation instruments to provide –
or foster the development of – key competitive capabilities to firms.
New ventures and incumbents are the result of a combination of
a diverse bundle of capabilities and competences. Consequently,
some innovation policy instruments will better fit the character-
istics of new ventures, whereas other instruments will correspond
better to the specificities of incumbent firms. Specifically, we
suggest that funding for marketing and networking activities
related to innovation are more beneficial for new ventures, whereas
grants and tax reductions are more advantageous for incumbents.
By exploring the effects' variations on new ventures and incum-
bents, we provide new perspectives and possible explanations for
the inconclusive results of previous studies regarding incentives'
general effects on innovation (e.g., Cappelen et al., 2012).
Studying the differentiated effect of public programs to promote
innovation on entrepreneurial ventures is of practical significance for
policy makers whomight otherwise fail to achieve their goals by using
the wrong instrument when attempting to support innovative entre-
preneurs. The conclusions obtained may help identify the unintended
effects of certain programs and to interpret the observed outcomes
correctly. In addition, this line of research is also valuable for manage-
rial practice because it provides guidance concerning which public
programs are more appropriate for new ventures and incumbents.
Studying the antecedents of product innovation in new ventures
is important because it represents a key dimension of entrepreneur-
ship. For example, typical new venture competences, such as flex-
ibility, the ability to recognize entrepreneurial opportunities or
entrepreneurial alertness (Burg et al., 2012; Marion et al., 2012),
may be considered complementary assets for new product develop-
ment. New products may enhance firm performance for both new
ventures and incumbents. However, these products are even more
important for the survival of new ventures (Marion et al., 2012;
Radas and Bozic, 2009) because they constitute a means of develop-
ing other relevant competitive capabilities (Danneels, 2002), of
gaining market share (Aspelund et al., 2005) and of earning revenues,
which is particularly critical for new firms (Kleinschmidt and Cooper,
1991). New ventures are more dependent on new product develop-
ment because all their products are new (Schoonhoven et al., 1990),
to an extent. Conversely, incumbents can opt to cash out on their
already current successful products.
We empirically analyze these issues using a cross-national sample
comprised of 5238 firms (new ventures and incumbents) from 29
European countries. By considering different institutional contexts,
we provide a framework that governments and managers can use to
design or adopt effective and specific public innovation incentive
portfolios aimed at both new ventures and established firms.
2. Theoretical framework
2.1. A competency-based view of new ventures' ability to innovate
The entrepreneurship literature has examined how new ventures
experience specific restrictions of resources and capabilities that may
limit their strategic choices when competing with established firms
(Aspelund et al., 2005; Bruton and Rubanik, 2002). This initial limited
endowment of assets and capabilities is frequently called “the
liability of newness” because it hinders new ventures in the devel-
opment of various competences and in their ability to compete and
prosper (Bruton and Rubanik, 2002; Stinchcombe, 1965). We posit
that the competency-based view may add theoretical insight into the
understanding of how innovation policy instruments can help new
ventures overcome the liability of newness and augment their
abilities with respect to launching new products.
The competency-based view conceptualizes firms as hetero-
geneous configurations of competences and capabilities that
determine how and whether value-creating strategies are imple-
mented and competitive advantages realized (e.g., Prahalad and
Hamel, 1990; Walsh and Linton, 2001). This perspective links a
firm's internal environment to its organizational competences to
predict economic performance. Organizational competences are
those specific assets, knowledge, skills and capabilities embedded
in the organizational structure and processes that enable the
organization to develop, choose and implement value-enhancing
strategies (Lado and Wilson, 1994), such as product innovation.
Companies' abilities to integrate, build and reconfigure corporate-
wide technologies and capabilities into core competences are
difficult to imitate and provides superior value to customers
(Lado and Wilson, 1994; Prahalad and Hamel, 1990).
New ventures and established companies differ in the config-
urations of their capabilities and competences, which impacts new
product development competences. New ventures are characterized
by important entrepreneurship-related capabilities, such as flex-
ibility, creativity, alertness and the ability to recognize opportunities
(Burg et al., 2012; Marion et al., 2012). Entrepreneurial capabilities
confer new ventures with the ability to see what established players
do not, such as identifying when goods or services become
unexpectedly valuable to consumers or feasible to produce
(Ireland et al., 2003). However, entrepreneurship research also
shows that new ventures frequently lack the internal assets
necessary to develop new products, such as experienced personnel
(Schoonhoven et al., 1990), market and technological knowledge
(Gans and Stern, 2003), marketing skills (Marion et al., 2012), social
capital (Aspelund et al., 2005; Baker and Nelson, 2005), production
equipment (Schoonhoven et al., 1990) and funding (Burke et al.,
2010; Marion et al., 2012). In general, new ventures lack the
organizational routines, skills and best practices that incumbents
possess and that enable them to develop certain types of compe-
titive advantages (Bruton and Rubanik, 2002). Moreover new
ventures cannot afford to experiment with a variety of new ideas
to the same extent as incumbents (Burg et al., 2012), and they do
not possess sufficient resources to absorb product failure (Marion
et al., 2012). Therefore, new ventures must cope with their initial
limited endowment of assets and lack of experience and time all of
them required to develop their innovation capabilities.
Based on the different endowments that characterize new
ventures and established companies with respect to developing
product innovations (i.e., which assets and capabilities they cur-
rently possess and which must be developed or acquired), public
instruments designed to encourage innovation may be expected to
R. Antolín-López et al. / Technovation∎ (∎∎∎∎) ∎∎∎–∎∎∎2
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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https://www.researchgate.net/publication/242348803_Social_Structure_and_Organizations?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
have different effects on new ventures and established companies.
From a competency-based view perspective, the effect of public
policy instruments can be understood in terms of the assets and
capabilities they provide to such companies and how these assets
and capabilities fit such companies' needs to develop product
innovation. Because there are many different types of public
incentives implemented to encourage innovation in current econo-
mies that differ in the capabilities and competences they provide –
or help to develop –, we posit that some types of instruments
would more suitable than others to supplement the capabilities and
competences portfolios of new ventures compared with established
companies todevelop product innovations. Therefore, we offer a
competency based-view of how different innovation policy instru-
ments assist new ventures to overcome the liability of newness
when developing new products, and how existing types of public
instruments affect product innovation development differently in
new ventures compared with incumbents.
2.2. Public support for innovation as a method of overcoming the
effects of the liability of newness on new product development
2.2.1. Public subsidy programs
Subsidies are common innovation policy instruments that con-
sist of economic grants that are not repaid. Keizer et al. (2002)
found that success in obtaining subsidies for innovation requires
considerable and persistent effort. The lengthy and intricate process
of applying for a subsidy typically involves elaborating complex
research project and budgetary proposals, meeting standards of
quality, passing a number of technical reviews and eventually
satisfying public economic conditions and controls regarding
expenses related to the project. When managing these complex
processes, new ventures suffer from a lack of personnel who
possess these specific skills and experience. Additionally, they are
less likely to have developed the routines and best practices (i.e., the
competence) required to succeed in the calls for projects, such as
those regarding how to structure a project, how to write a proposal
or how to address and communicate with reviewers, which are
typically acquired through “learning-by-doing” processes. Conver-
sely, even if they are small or medium-sized enterprises (SMEs),
innovative incumbents are more likely to be experienced in these
types of processes and to have had the time required to develop the
best practices and skills for handling the relevant submission
processes. Consequently, in spite of the greater effort that new
ventures devoted when applying for similar projects, this type of
process may result less efficient for new ventures.
In addition, public calls for projects typically have specific goals to
promote certain technologies or strategic sectors (Blanes and Busom,
2004; Santamaria et al., 2010). According to Nelson (1959), govern-
ments tend to support projects with the largest gaps between social
and private return (e.g., basic research), whereas private companies
are more likely to invest in R&D projects with the highest rates of
private return (e.g., applied research). Thus, firms must frequently
face a trade-off between a project that maximizes future market
success and one that maximizes public support. Companies fre-
quently encounter problems during the process and are forced to
make impromptu decisions to satisfy both public grant conditions
and technical or marketing requirements. This status quo and
decisions may ultimately challenge the technical viability of research
projects, and some already planned new products's launching may
even result a failure. Nonetheless, established firms' experience and
resources play an important role to handle this trade-off successfully.
2.2.2. Tax incentives
Through tax incentives, firms can deduct some of the resources
invested in innovation from the total amount of taxes that the
company must pay at the end of the fiscal year. This reduces the
costs of innovation, which causes managers to perceive a lower
risk in deciding to invest in new product development. This
perception causes companies to adopt innovative strategies more
frequently and invest more resources in R&D (Berube and Mohnen,
2009; Czarnitzki et al., 2011; Yang et al., 2012).
Peneder (2008) notes that tax reductions are typically related to
corporate income taxes and thus act only as incentives for compa-
nies that are profitable. In the EU, regulations frequently allow tax
reductions to be carried forward for a certain number of years until
the firm can obtain benefits from the tax incentives. However,
entrepreneurial firms frequently suffer losses during their initial
years and only obtain returns on the investments in the long term
(Oakey, 2003; Storey and Tether, 1998). The factors underlying this
circumstance include the following: the time required to access
new markets (Norrman and Klofsten, 2009), the regulatory and
technical entry barriers commonly faced by startups (Storey and
Tether, 1998), and their lack of economies of scale. Thus, the
incentive's effect may be delayed for most new ventures, which
might result in a loss of part of its effect. Therefore, new ventures
are less likely to take advantage of the positive impact of these
public mechanisms (Peneder, 2008) because they frequently do not
earn sufficient taxable profits (Hall and van Reenen, 2000).
Additionally, because of their size and limited financial
resources, new ventures might find difficult to invest the max-
imum amount allowed for tax reduction while established firms
are less likely to face this type of restriction. Consequently, this
incentive results particularly useful for incumbents.
2.2.3. Public support for networking
Being up-to-date on many diverse, complex and changing tech-
nologies are particularly difficult for new ventures because of their
lack of resources, experience and limited technical competences
(Bruton and Rubanik, 2002). In addition, startups possess more limited
networks of contacts (Aspelund et al., 2005; Zhang and Li, 2010).
Accordingly, new ventures possess only limited internal knowledge
and tend to narrow their external search scope by relying exclusively
upon their immediate personal networks to discover and recognize
opportunities (Baker and Nelson, 2005). One strategy startups can use
to overcome this constraint involves focusing on what they do best
while acquiring and co-developing knowledge within a widespread
network of firms (Nelson, 1959). Therefore, public support for coop-
eration and networking can be particularly valuable to new ventures
that are engaged in developing innovative projects.
Cooperation can be a means of skipping the problem of
innovation indivisibility and risk (Arrow, 1962). Because only fully
developed innovations can be launched in the market, R&D
investment pays off only when the entire investment is made.
Cooperation allows dividing a project into parts and avoiding
costly investment in laboratories, equipment and/or experts
(Sakakibara, 1997, 2002). R&D collaboration also allows companies
to reduce risk by investing only a small part of the total amount
required to develop a new technology and diversify new product
portfolios (Arrow, 1962) and by avoiding research duplication and
duplicative final products on the market. This risk reduction
component is particularly critical for new ventures that are
characterized by intrinsically high levels of risk.
Interfirm networks also boost firm innovativeness by providing
access to partners' technological know-how, salient market knowl-
edge and complementary capabilities that help improve new
ventures' skill base (Zahra and Filatotchev, 2004). Collaboration
with a knowledgeable partner can accelerate “learning by doing”
processes and allow innovative capabilities to be perfected.
The open innovation literature (Chesbrough, 2003) suggests that
innovation-related cooperation is also beneficial for incumbents.
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 3
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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https://www.researchgate.net/publication/228316078_Creating_Something_From_Nothing_Resource_Construction_Through_Entrepreneurial_Bricolage?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==https://www.researchgate.net/publication/4967912_Resources_of_the_Firm_Russian_High-Technology_Start-Ups_and_Firm_Growth?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
https://www.researchgate.net/publication/235700923_Open_Innovation_The_New_Imperative_for_Creating_and_Profiting_From_Technology?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
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https://www.researchgate.net/publication/227516623_Innovation_Search_of_New_Ventures_in_a_Technology_Cluster_The_Role_of_Ties_with_Service_Intermediaries?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
However, such cooperation may not be as important for established
companies because their resources are not as limited. Under certain
circumstances, firms may prefer to conduct research in-house to
gain control of the research process and ensure ownership of the
results (Sakakibara, 2002). Indeed, most established firms develop
new products without entering into innovation cooperative
arrangements with other organizations (Tether, 2002).
Although some scholars claim that universities rarely develop
market-ready innovations (e.g., Radas and Bozic, 2009; Tether and
Tajar, 2008b), networking with universities and research centers
provides access to valuable and specialized knowledge that is not
always available in markets at low cost and with low risk (Tether,
2002). Therefore, companies with scant R&D capabilities innovate
more effectively through university and research center collabora-
tion (Keizer et al., 2002; Sakakibara, 2002).
2.2.4. Marketing information
Marketing capabilities have been considered to be a comple-
mentary asset to new product innovation (Teece, 1986). Given the
paramount importance of the fit between new product features and
market needs, reliance on elaborate, abundant and accurate mar-
keting information appears to be critical to new product success.
Startups typically lack the marketing skills of incumbents (Marion
et al., 2012), and improving these skills can have a significant impact
on the level of new product success. New ventures often have scant
information on market conditions, regulatory entry barriers
(Norrman, 2008), competition rules, industry recipes (Zahra and
Filatotchev, 2004) and customer needs (Burke et al., 2010). These
information asymmetries crop up because market data and informa-
tion can be gathered through research but “also arise in the daily
course of economic life as a by-product of other economic activities”
(Arrow, 1962, 614). Therefore, market information is not perfectly
distributed. Because incumbents have more experience and market
knowledge than newcomers, public programs providing advice and
information on market conditions should reduce the higher rates of
uncertainty associated with product innovation in new ventures and
increase the success rate of their new products (Arrow, 1962).
Conversely, incumbents have typically previously tested their pro-
ducts in the market and are more experienced with regard to
marketing processes. Consequently, they typically have more
polished marketing capabilities compared with new ventures.
Public policies may also facilitate and fund attendance at trade
fairs, which constitute a feasible manner of obtaining marketing
information and acquiring social capital in the form of contacts
with potential customers and suppliers. New ventures can use
fairs to identify possible partners along the value chain – a process
that is both difficult for and valuable to new ventures (Gans and
Stern, 2003; Gilsing et al., 2010) – and to improve their opportu-
nity recognition capabilities (Ozgen and Baron, 2007). Moreover,
according to the “open innovation” paradigm (Chesbrough, 2003),
social capital is at the heart of innovation, and both internal and
external ideas (originating from suppliers, customers, and others)
are key factors in the innovation process. However, startups have
weaker external contacts (Zhang and Li, 2010) and no stable
relationships with suppliers and customers (Bruton and Rubanik,
2002), whereas incumbents tend to possess a wider range of
contacts and an established value chain. Therefore, because of
their potential for building social networks, trade fairs are
expected to have a positive impact on the innovative efforts of
new ventures (Ozgen and Baron, 2007).
2.2.5. Support for R&D project financing
Most new ventures begin with very limited financial resources
(e.g., Burke et al., 2010; Marion et al., 2012), and this limitation
constitutes one of their primary constraints (e.g., Schoonhoven
et al., 1990). However, accessing suitable financial resources and loans
is of paramount importance to excel in the new product development
process (Martin and Scott, 2000) because it typically requires costly
and time-consuming investments in R&D facilities and skilled R&D
human capital. Finding the optimal financing for their R&D projects is
comparatively more difficult for new ventures because of the higher
levels of perceived uncertainty and risk associated with them (Arthurs
and Busenitz, 2006; Oakey, 2003). Resource limitations “are likely to
make underinvestment in risky enterprises more likely than the
opposite” (Arrow, 1962, 611), and these hinder startups' ability to
attract new investors and obtain loans from banks. Therefore, direct
support in financing innovation projects under favorable conditions –
such as lower (or a lack of) enforcement mechanisms and interest
rates – might be of particularinterest to new ventures.
Established firms typically have lengthier and more stable relation-
ships with bankers and investors. Because of their proven performance
record and existing accounting information, financial institutions can
track their performance and evolution over several years. Moreover,
established companies generally have cash flows that are superior to
those of new ventures (Schoonhoven et al., 1990); thus, as a
consequence, access to financial resources is less problematic for
established companies (Bruton et al., 2010). For their part, new
ventures have not had time to demonstrate that they are viable
companies, and their performance records are limited or nonexistent
(Bruton et al., 2010; Zhang and Li, 2010), which derives in a more
difficult, costly and risky success for new ventures' prospective
projections. As a result, banks and investors perceive larger informa-
tion asymmetries that drive them to impose stricter enforcement
mechanisms on new ventures (Bosse, 2009), which means that the
entrepreneur must assume additional costs and/or higher risks. More-
over, banks typically offer rigid standard conditions to new ventures
but are more open to negotiating conditions with incumbents.
Public support mechanisms for financing innovation are fre-
quently less exigent and complex compared with public subsidies.
Although firms must typically undergo similar processes before
receiving funds, public loans frequently require the firm to
dedicate fewer resources to the control and ex post assessment
of the project. Since firms are compelled to repay the loan
received, public administrations frequently do not develop such
thoroughly technical and economic projects' assessments.
After this argumentation, we might conclude that the impact of
public support policies follows a different pattern for new ven-
tures and for established firms. Therefore, we posit the following:
Hypothesis 1. For new ventures, public support incentives that are
more relevant to foster product innovations are (1a) Public policies
supporting networking and cooperation, (1b) Public policies facilitat-
ing the obtainment of marketing information and contacts and (1c)
Public support for financing innovation projects.
Hypothesis 2. For established firms, public support incentives that
are more relevant to foster product innovations are (2a) Public
subsidy programs and (2b) Tax reductions for R&D expenditures
3. Methods
3.1. Sample
The dataset used in this study covers a sample of companies
with 20 or more employees operating within one of the 27
Member States of the EU, Switzerland or Norway. Data were
gathered from the “Eurobarometer No. 215” survey. This survey
is part of the Innobarometers series, which is regularly conducted
at the request of the European Commission to address diverse
topics related to innovation in European companies. Access to this
cross-national database was provided by the Central Archive for
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎4
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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https://www.researchgate.net/publication/227516623_Innovation_Search_of_New_Ventures_in_a_Technology_Cluster_The_Role_of_Ties_with_Service_Intermediaries?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==https://www.researchgate.net/publication/227516623_Innovation_Search_of_New_Ventures_in_a_Technology_Cluster_The_Role_of_Ties_with_Service_Intermediaries?el=1_x_8&enrichId=rgreq-c57ab579-bd28-4d38-a7a6-fd86761b6d39&enrichSource=Y292ZXJQYWdlOzI3NDczNzE3MjtBUzoyMTkxNDg2Mzk1NzYwNjRAMTQyOTI2MDUxNTgzMQ==
Empirical Social Research (University of Cologne, Germany). Use
of the Eurobarometer studies is relatively common in academic
empirical research in the management field (e.g., Kwon and
Arenius, 2010; Tether, 2005; Tether and Tajar, 2008a).
The database includes responses of 5238 companies from
innovation-intensive industry sectors. The sample contains approxi-
mately 200 cases from each country surveyed, with the exception of
Malta, Cyprus and Luxemburg (70 cases) and non-EU countries (100
cases). Sampling in each country reflected two stratification criteria:
company size and sector of activity. Therefore, sampling was con-
ducted following the recommendations of the Oslo Manual (OECD/
EUROSTAT, 2005, 121): “Given that the innovation activities of units in
different industries and different size classes can differ significantly, it is
recommended that the stratification of random sample innovation
surveys should be based on the size and principal activity of the units”.
Therefore, this type of data selection and collection eliminates the
possibility of nonresponse bias, rendering each country in the
subsample representative in terms of sector, activity and size.
The fieldwork was conducted between October 15th and Octo-
ber 23rd, 2007 through telephone interviews conducted by the
national institutes associated with EOS Gallup Europe. The person
interviewed at each company was a top-level executive responsible
for strategic decision making.
Descriptive statistics reveal that firms in the sample had an average
of 376 employees and that a total of 4361 companies were established
before the year 2000 (incumbents), whereas 864 companies were
established after that date (new ventures). Moreover, 47.5% of the firms
had introduced new or significantly improved products during the
previous two years. This ratio was similar for new ventures (47.6%) and
incumbents (47.5%). With regard to public support for innovation, 9.8%
of the firms had received subsidies for acquiring machinery, equipment
or software; 15.5% had received subsidies for buildings or other
infrastructure; 8.6% had applied for tax reductions for their R&D
expenditures; 19% had received funding for networking with other
companies; 13.4% had received funding for networkingwith universities
and research institutes; 13.9% had received public support for attending
trade fairs; 21.8% had received funding for marketing information; and
12.9% received direct support for financing innovation projects. These
percentages are similar for new ventures and incumbents. Finally,
descriptive statistics also demonstrated that all these types of public
Table 1
Variable description.
Variable name Definition Operationalization
Dependent variables
Firm performance Evolution of the firm's turnover during the previous two years (2005 and
2006).
It is represented by six categories:
(1) had decreased by over 25%;
(2) had decreased by 5–25%;
(3) approximately the same;
(4) had increased by 6–25%;
(5) had increased by 26–50%;
(6) had increased by over 50%.
Product innovation Introduction of new or significantly improved products during the previous
two years.
1 if the company has introduced new or significantly improved
products, 0 otherwise.
Independent variables
Subsidies Economic funding not requiring repayment for innovation activities. It is represented by two proxies:
1 if the company has received subsidies for acquiring
machinery, equipment or software, 0 otherwise.
1 if the company has received subsidies for acquiring buildings
or other infrastructure, 0 otherwise.
Tax incentives Reduction in the amount of taxes that a company must pay on a percentage of
its innovation spending.
1 if the company has received tax incentives for innovation
activities, 0 otherwise.
Networking support Public support to facilitate companies' establishment of formal or informal
communication channels for sharing knowledge of and resources for
innovation activities.
It is represented by two proxies:
1 if the company has received support for networking with
other firms, 0 otherwise.
1 if the company has received support for networking with
universities and research institutes, 0 otherwise.
Marketing
information support
Public support to provide elaborate, abundant and accurate information on
market conditions that will be useful for innovation activities.
It is represented by two proxies:
1 if the company has received support for attending or
participating in trade fairs or trade missions, 0 otherwise.
1 if the company has received support for acquiring information
on market needs, market conditions and new regulations,
0 otherwise.
Direct support for
financing innovation
projects
Public activities providing favorable financial conditions, in terms of lower (or a
lack of) enforcement mechanisms and interest rates.
1 if the company has received direct support to finance
innovation projects, 0 otherwise.
Control variables
Firm size Number of employees
Sector of activity OECD classification (NACE Rev.2, 2 digits level) It is represented by six categories:
(1) high technology products;
(2) medium–high technology products;
(3) medium–low technology products;
(4) low technology products;
(5) knowledge-intensive services;
(6) less knowledge-intensive services.
R&D expenditures R&D intensity Thousands of Euros spent yearly on R&D per 100 employees.
Regional R&D Regional R&D investment per capita Thousands of Euros per capita spent yearly on R&D in the region
(NUTS 2) where the company operates.
Regional GDP GDP per capita of region (NUTS 2) where the company operates.
Country A dummy variable for the country where the company operates.
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established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
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instruments were represented in every country considered, with the
exception of Norway (where tax reductions and subsidies for buildings
and other infrastructures were not represented).
Consequently, the data display sufficient variability for testing the
relationships among the different public incentive instruments and
innovation outcomes for both new ventures and established firms.
3.2. Measures
This section describes all the variables and how they were
measured (see Table 1). As indicated above, we aimed to analyze the
connection of several public support policies and firm product
innovation and performance. The hypotheses propose that new
ventures and established firms differ regarding that relationship.
Consequently, company age was used to divide the sample into two
groups as the first step in testing the two proposed models. No general
agreement among scholars can be employed to identify what con-
stitutes a new venture with respect to innovation activities. Although
some authors have considered a narrow and young age to indicate
that a firm is a new venture (e.g., Tether, 2005), most innovation
studies have considered a broader age range of up to 7–8 years (e.g.,
Antolin-Lopez et al., 2013; Schoonhoven et al., 1990; Wiklund et al.,
2010; Zhang and Li, 2010). Consistent with the latter approach, our
study considered a firm as a new venture when it was founded during
the previous seven years because new firms require some time before
being able to utilize/employ/make use of public support programs and
transform their help into successful innovations. In addition, it often
takes time for innovationto influence firm performance.
3.2.1. Dependent variables
The dependent variable in this study, product innovation, has
been measured as the introduction of new or significantly
improved products during the previous two years. Previous
studies have also used dichotomous variables (if the company
has innovated in terms of product) as measures of innovation
output (e.g., Martinez-Ros, 2000; Revilla and Fernandez, 2012).
3.2.2. Independent variables
We have considered which public instruments should be included
among the public innovation policies that are designed or provided
specifically for new ventures. Therefore, we have studied the public
instruments most frequently included in the innovation policies
examined rather than assessing a specific innovation program. In fact,
the European Competitiveness Council (2006, 2) noted the following:
“Innovation policy should be best understood as a set of instruments”.
According to the European Commission (COM, 2009), the most widely
used forms of public support over the previous three years were tax
incentives, subsidies and grants, funding for networking, and facilitat-
ing the acquisition of information regarding market conditions. As
discussed above, descriptive statistics confirm the representation of
these types of public instruments in a large number of countries.
Subsidies consist of economic funding that does not require
repayment and these have been represented by two proxies:
(1) subsidies for acquiring machinery, equipment or software
and (2) subsidies for acquiring buildings or other infrastructure
devoted to innovation activities.
Tax incentives reduce the amount of taxes that a company must
pay on a percentage of its innovation spending (Norrman, 2008).
These reductions can typically be carried forward for a certain
number of years (usually 15 years) until the company has obtained
benefits. This element has been measured using the following
dummy variable: “In the last two years, has your company
received tax reductions for R&D to support product innovation?”
Support for networking refers to the public initiatives designed to
facilitate and promote the establishment of formal or informal
channels of communication with the purpose of sharing knowledge
and resources to develop innovation activities (Schwartz et al., 2012).
To render this variable operational, two dichotomous variables were
considered: public support for networking with other firms and
public support for networking with universities and other research
institutions.
Marketing information refers to public support activities
designed to provide elaborate, abundant and accurate information
on market conditions that will be useful for conducting innovation
activities. This feature was represented by two dummy proxies:
(1) public support for attending or participating in trade fairs or
trade missions and (2) public support for acquiring information
regarding market needs, market conditions, new regulations, etc.
Finally, direct support for financing innovation projects includes
public activities that provide favorable financial conditions in terms
of lower (or a lack of) enforcement mechanisms and interest rates.
This feature was measured by asking firms whether they had
received “direct support to finance R&D-based innovation projects”.
3.2.3. Control variables
Several control variables have been included to account for
alternative explanations. First, a control variable was included for
firm size, in accordance with the innovation literature (Radas and
Bozic, 2009; Revilla and Fernandez, 2012), because our sample
exhibits size variability among new ventures and established com-
panies. Previous empirical research shows that the advantages of size
for a firm's innovation capabilities are ambiguous. On the one hand,
larger firms may possess greater financial resources and be favored
by economies of scale and scope, which thereby increases the
profitability of their innovation strategies; on the other hand, smaller
firms are more flexible and less bureaucratic, which may increase
innovation efficiency (Damanpour, 1991). Firm size was measured by
the natural logarithm of the number of employees.
A control for sector of activity was included following previous
studies that suggest that innovative firms' performance depends on
the nature of the industry in which they are operating (e.g.,
Damanpour et al., 1989). Knowledge-intensive or technology-
intensive activities may offer different technological opportunities
and thus influence the development of product innovation. There-
fore, the activity sector was broken down into six categories, in
accordance with the OECD classification (NACE Rev.2, 2 digits level):
high technology products, medium–high technology products, med-
ium–low technology products, low technology products, knowledge-
intensive services, and less knowledge-intensive services.
R&D expenditures have also been included as a control since R&D
intensity is commonly used to assess inputs to the innovation process
(Hitt et al., 1996). We have related R&D expenditures to firm size;
therefore, R&D expenditures have been measured in thousands of
Euros spent annually on R&D per 100 employees. We have standar-
dized this variable by taking the ratio of the firm R&D expenditures
to the sector (NACE 2 digits) R&D expenditures average.
Finally, some controls have been included that address firms'
geographical origins because public instruments promoting innovation
may vary significantly among European countries and regions in terms
of intensity and regulatory conditions. A dummy variable for each
country appearing in the database has been calculated to control for
differences in economic conditions, business culture and/or interpre-
tation of the different concepts investigated in the survey.
3.3. Common-method bias
A major concern in survey research is the use of perceptual data
for both independent and dependent variables (self-reported data),
which can result in common-method bias. Although common-
method bias cannot be avoided in this study, we feel confident
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎6
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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that it presents no serious problems with respect to testing the
hypotheses. Because the hypotheses tested in this paper, which
were phrased as “some relations are stronger in one subsample
than in the other,” are quite different from the European Commis-
sion's aims when the survey was designed, the likelihood that
respondents were able to determine the hypotheses tested in this
paper is extremely low. In addition, respondents could not directly
influence hypotheses' acceptance or rejection with their answers –
even if they anticipated them – because answers also depend on the
responses obtained in another subsample. However, several proce-
dures were used during both the questionnaire design and the
reporting stages to reduce the potential for common-method
variance (OECD/EUROSTAT, 2005; Podsakoff et al., 2003). Moreover,
a latent class factor analysis was run using LATENT GOLD 4.5 to
estimate the presence of common-method biases in the data. If
there were common-method variance in our data, a model consist-
ing of a single factor would emerge as the best statistical solution.
BIC and CAIC criteria were selected to compare model solutions
based on both their model fits and parsimony. The BIC criterion
exhibited better performance than other classification criteria
(Biernacki and Govaert, 1999), and CAIC is preferred over AIC2 or
AIC3 for large samples because it imposes a much larger penalty,
which leads to a smaller number of factors (Bozdogan, 1987).
Applying the minimumCAIC and BIC values rule, the optimal
number of factors in these data varied between two and three,
respectively. Thus, both approaches indicated that a model with one
factor was not the most appropriate, which suggests that common-
method bias is not a serious problem in this study.
3.4. Analysis
The main problem when analyzing the relationship between
subsidies (or financial aid instruments) and product innovation is
the potential endogeneity of the subsidy and the sample selection bias.
The allocation of these aids fails to satisfy the randomness property
that a social experiment should possess because firms may apply for
public funding if they actually innovate, and public agencies may base
their subsidizing decisions on the applying firms' capacity to innovate.
Thus, product innovation is likely to precede the allocation process,
which makes public funding an endogenous variable.
In addition, the factors taken into account to apply for a public
support program can differ, although some of them may be the
equal to those that affect the firm's product innovation. This fact
can generate a bias in the impact of these support instruments on
firms' product innovation in our sample.
This issue has previously been addressed in the literature (e.g.,
Almus and Czarnitzki, 2003; Busom, 2000; Czarnitzki and Fier,
2002; Czarnitzki and Lopes-Bento, 2011; Huergo and Moreno, 2014;
Lach, 2002; Wallsten, 2000), and several methodologies have been
proposed to address this problem. For example, Busom (2000)
developed a two-stage model in which she initially estimated the
probability of participating in a public funding program and, in the
second stage, R&D activity was regressed on several covariates,
including a selection term that incorporated a firm's tendency to
receive public funding. However, this mechanism only allows
evaluating the impact of a single funding mechanism.
Aiming to reflect the effects of a set of public policies collectively,
Almus and Czarnitzki (2003) applied a nonparametric matching
approach. In the same line, to account for the differences between
European and national funding programs, Czarnitzki and Lopes-
Bento (2014) applied a multiple treatment effect model that con-
sidered the propensity scores of 12 different change possibilities by
comparing the actual situation (m) of: not receiving funding; receiv-
ing only national funding; receiving only EU funding or funding from
both sources with a counterfactual situation with the same possibi-
lities (l). This methodology assumes that a counterfactual situation
for companies in the state m can be estimated from the sample of
companies receiving l (Czarnitzki et al., 2007).
However, the higher the amount of different sources of public
funding considered, the more complex the matching matrix
becomes. With respect to our case, accounting for eight different
types of publicly funded schemes would require handling 56
different cases and it would only consider the possibility of
receiving funds from one program at a time. Thus, this methodol-
ogy is inapplicable to our data.
All the approaches discussed have pros and cons and there are
no benchmarks to guide the selection of one methodology or
another (Almus and Czarnitzki, 2003). Finally, the econometric
model employed is driven by the characteristics of the data
analyzed (Heckman et al., 1998).
In order to account for treatment effects, in this paper we
follow Heckman's (1979) methodology, which has been used for
addressing both selection and endogeneity problems (e.g. Huergo
and Moreno, 2014). Following this two-step model, we initially
estimate a selection equation for the participation in each one of
the publicly funded schemes we assess using a multivariate probit
model. In the second step, we analyze the effect of this participa-
tion on product innovation.
Our first set of equations expresses the participation of a given
firm i in a publicly funded scheme m (m¼1,2,3,…,8). This multi-
variate probit model can be written as follows:
yimn¼ β
0
mXimþ ϵim; m¼ 1;…;8
yim ¼ 1 if yimn 40 and 0 otherwise
where A im; m¼ 1;…; 8 are error terms distributed as multi-
variate normal, each with a mean of zero and a variance–
covariance matrix V, where V has values of 1 on the leading
diagonal and correlations ρjk ¼ ρkj as off-diagonal elements
(Cappellari and Jenkins, 2003).
To account for the endogeneity problem, we first use some
regional-level and country-level variables as instruments (these
variables are not used in the second step) which are determined
outside the firm but affect the probability of receiving public support
for innovation. Public instruments promoting innovation may vary
significantly among European countries and regions in terms of
intensity and regulatory conditions. In order to address firm' geogra-
phical origins, a dummy variable for each country appearing in the
database has been included to control for differences in economic
conditions, business culture and/or interpretation of the different
concepts investigated in the survey. After an initial test, we only
retained the more significant country variables. Moreover, regional
GDP per capita and regional R&D investment per capitawere included
as an explanatory variable because the region may play an important
role in innovation policy in Europe (Radas and Bozic, 2009). Regional
GDP and R&D data were obtained from EUROSTAT Statistics.
Second, the obtained predictions of the probability of participat-
ing in each program are used as endogenous variables in the second
step to predict product innovation instead of actual participation
(Huergo and Moreno, 2014). Because our dependent variable was
measured as a dichotomous variable, we used a probit model to
estimate this equation. Country dummies variables not used in step
one were used as control variables in this step. This process is
repeated both for new ventures and established firms.
4. Results
Table 2 provides descriptive statistics and a correlationmatrix for all
the variables used in the study. Multicollinearity should not be a
concern for this sample because the correlations between the vari-
ous items are well below .70, which suggests that the variable has
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Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
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http://dx.doi.org/10.1016/j.technovation.2015.02.002
discriminant validity (Cohen et al., 2003). Moreover, variance inflation
factor tests were conducted to verify the absence of multicollinearity.
The results were satisfactory, as all values were between 1.0 and 1.6,
and tolerance values were largely distant from 0, with the lowest value
being .485. Therefore, there is sufficient evidence to rule out multi-
collinearity in the data (Hair et al., 1999).
To test our hypotheses, two models were estimated separately
for each of the two groups, new ventures and incumbent firms.
Our econometric model was applied in two steps. The results from
the multivariate probit analysis determining the probability of
participation in publicly funded schemes are shown in Table 3 for
new ventures and Table 4 for established companies.
Next, the predictions of the probability of participating in each
program were used as the input for the second probit model that
assessed the relationship between those programs and product
innovation. Table 5 shows the results of this analysis for both new
ventures and established companies.
Subsidies are not good predictors of the development of
product innovation among new ventures. However, they are
positively and significantly related to incumbents' product innova-
tion in the case of subsidies for the acquisition of buildings or
other infrastructure for innovation activities and thus provide
somesupport for Hypothesis 2a.
Tax reductions were found to be significantly and positively
related to product innovation within the incumbent subsample,
although they were not significant for new ventures. This finding
confirms the argument that tax reductions are more important to
fostering the development of product innovation in established
companies. Therefore, the results support Hypothesis 2b.
With respect to variables relating to publicly funded support for
networking, support for networking the one focused on networking
with companies is significantly related to innovation only for new
ventures. Networking with universities and research institutes
seems to be not significantly linked with the development of new
or improved products in both the new venture and incumbent
subsamples. These results provide some support for Hypothesis 1a.
Two items were proposed to measure public support for increas-
ing marketing information. The first one, “support for acquiring
information on market needs, market conditions and new regula-
tions”, exhibited a negative and non-significant relationship for both
incumbent companies and new ventures. The second variable, “sup-
port for attendance at or participation in trade fairs”, was found to be
significant and positively associated with product innovation for new
ventures, whereas it remained negative and significant for established
firms. These results provide partial support for Hypothesis 1b.
In examining direct support for financing R&D-based innova-
tion projects we observed that this type of public instrument is not
positively related to innovation in any of the samples analyzed;
moreover, it is surprisingly negatively linked related with both
established firms and new ventures. These findings do not support
Hypothesis 1c.
Finally, regarding control variables, size is not significant for new
venture subsample but it is positive and significant among estab-
lished firms. Spending on innovation has a positive and significant
coefficient in both subsamples. Considering the sector of activity, we
noted some differences between new ventures and established
companies in terms of the significance of the coefficients. For
example, new ventures operating in medium–high technology sector
are less directly associated with the development of new products
than those firms in low-technology sectors, which served as the base.
5. Discussion
This study combines insights from the competency-based per-
spective and innovation policy and entrepreneurship literatures to
analyze the effect of public support instruments on product
innovation at new ventures and at incumbent firms. We analyze a
comprehensive dataset to extend the current literature by (1) posit-
ing the notion that innovation policy instruments have different
effects on new ventures than on incumbent firms, and by (2) sug-
gesting a competency-based logic that explains these varied effects.
Consequently, this paper draws from previous studies to take the
first step in advancing knowledge regarding which innovation
policy instruments are more adequate to foster product innovation
in new ventures compared with incumbents.
With respect to our first research goal, we found that there is a
completely different pattern of relationships among diverse types of
innovation policy instruments and product innovation among new
ventures and incumbent firms. More specifically, we found that
public policies promoting networking with other companies and
public policies facilitating support for attending trade fairs and
trade missions were more important to product innovation for new
ventures, whereas subsidies for acquiring buildings and infrastruc-
tures for innovation activities, in addition to tax incentives for R&D
expenses, were more relevant to product innovation at incumbent
firms. Therefore, an important contribution of this paper is to show
that not all innovation policy instruments are equal in how they
affect product innovation in new ventures and incumbents.
With respect to our second research goal, we suggest that these
differences are related to the power of the innovation instruments to
provide key competitive capabilities to the firm. Specifically, innova-
tion policy instruments that aim at providing capabilities typically
lacking in new ventures – those that contribute to the liability of
newness –should be particularly effective at promoting innovation at
new ventures. In other words, the fit between the resources that a
given innovation policy instrument provides and a firm's capabilities
and/or weaknesses matters. Our results seem to suggest a logic in
designing public support initiatives that incentivize R&D.
The results reveal that for established firms, both tax incentives
for R&D and subsidies for buildings or other infrastructure for
innovation activities that do not require repayment were signifi-
cantly related to product innovation. Surprisingly, that was not the
case of subsidies for acquiring machinery, equipment or software.
Perhaps those types of subsidies might be more useful for the
development of other types of innovation, such as processes or
organizational innovations. However, altogether those results
suggest that public incentives aiming at generating financial
capital are especially useful for incumbent firms since they provide
funds whose use in innovative projects might be approved even in
the face of uncertainty, thus unraveling firm's capacity to experi-
ment and develop new products (Damanpour, 1991).
Public policies facilitating support for specific innovation project
financing seem to be negatively related to product innovation in
both cases. This kind of aid requires firms to repay the loan received
which may hinder new product development as it increases profit-
ability uncertainty. In addition, this negative effect may be attrib-
uted to either the loss of focus on new product development at
some stage of the process, caused by the lag time between receiving
the grant and the end of the new product innovation process or the
poor design of these incentives (Radas and Bozic, 2009).
Results confirm that for new ventures, public support for coop-
eration and networking with other firms is particularly valuable
when developing new products. New ventures possess few valuable
contacts, which limit their external search scope (Aspelund et al.,
2005; Zhang and Li, 2010). In addition, such support offers access to
partners' knowledge, technology, human capital and complementary
capabilities (Zahra and Filatotchev, 2004) that new ventures may be
unable to access in another way due to their resource limitations. We
have also found that engagement in product innovation increases if a
new venture received support for attending or participating in trade
fairs. These findings fit the so-called “open innovation” model
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎8
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
Table 2
Descriptive statistics and correlation among variables.
Variable Mean S.D. Obs. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
1 Product innovation .48 .50 5163 1
2 Performance .70 .98 4476 .048** 1
3 Subsidies for acquiring machinery, equipment or
software
.16 .36 4232 .06** .016 1
4 Subsidies for buildings or other infrastructure for
innovation activities
.10 .30 4227 .01 –.02 .42nn 1
5 Tax reductions for R&D expenditures .09 .28 4096 .12** .01 .22** .16** 1
6 Support for networking with companies .19 .39 4259 .09** .03* .20** .17** .17** 1
7 Support for networking with universities and
research institutes
.13 .34 4264 .11** .02 .20** .19** .25** .47** 1
8 Support for attending or participating in trade fairs
or trademissions
.24 .43 4240 .13** 0 .23** .20** .19** .45** .39** 1
9 Support for information on market needs, market
conditions, new regulations, etc.
.22 .41 4236 .06** –.01 .15** .17** 16** .53** .39** .51** 1
10 Direct support for financing innovation projects .13 .34 4219 .11** .03 .29** .22** .34** .24** .33** .21** .19** 1
Control variables
11 R&D expenditures 4159.30 11,402.76 3259 .08** 0 .02 .04* .01 .02 .02 .03 –.02 .06** 1
12 Size 376.11 2290.78 5169 .03* .02 .01 .03 .06** .06** .09** .01 .04* .04* –.04* 1
13 Sector: high technology .03 .17 4616 .07** .02 .03 .01 .04* .03 .03 .05** .02 .06** –.01 –.01 1
14 Sector: medium–high technology .12 .32 4616 .13** .05** .03 –.02 .09** .02 .09** .05** .02 .06** .01 .01 –.06** 1
15 Sector: medium–low technology .15 .36 4616 .06** .02 .03 –.02 .04* .01 –.02 0 –.01 .03* –.03* –.03* –.07** –.15** 1
16 Sector: low technology .16 .36 4616 .10** –.13** .06** .02 0 –.05** –.01 .04* –.02 –.01 –.02 –.02 –.07** –.16** –.18** 1
17 Sector: knowledge-intensive-based services .24 .43 4616 –.16** .08** –.05** .02 –.03 .05** .07** –.05** .01 .02 .04** .04** –.10** –.20** –.24** –.24** 1
18 Sector: less knowledge-intensive-based services .31 .46 4616 –.09** –.03 –.05** –.01 –.08** –.05** –.11** –.04* –0 –.10** 0 0 –.12** –.24** –.28** –.29** –.38** 1
19 Regional GDP 2316 1578 5236 .01 .02 –.06** –.01 .10** .06** .05** 0 .03* .04** .05** .05** –.02 –.03* –.05** –.11** .16** .01 1
20 Regional R&D 1422 1145 5225 .03* .04** -.09** -.03* 0 .04* .04* -.06** -.01 .04** .09** .08** 0 -.01 -.05** -.11** .15** -.01 .516**
Country dummies not shown.
n Po .05 (2-tailed).
nn Po .01 (2-tailed).
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http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
(Chesbrough, 2003). Many authors have argued in favor of the
benefits of opening the innovation process to external knowledge
flows, suggesting that both internal and external ideas are relevant
for the development of successful innovations (Chesbrough and
Crowther, 2006; Rigby and Zook, 2002), particularly with respect to
new ventures that lack market experience.
Research that analyzes entrepreneurship from a strategic man-
agement perspective should complete its models by considering the
Table 3
Participation in publicly funded schemes by new ventures. Multivariate Probit Model.
(1) (2) (3) (4) (5) (6) (7) (8)
Size .013 (.064) .062 (.071) .085 (.075) .022 (.058) .221nnn (.060) .051 (.056) � .030 (.055) .179** (.062)
R&D expenditures .000 (.001) .000 (.001) .001 (.001) .000 (.001) .001 (.001) .000 (.001) � .000 (.001) .001** (.000)
Sector of activity
High technology .497 (.430) .681 (.453) 1.138* (.459) .541 (.438) � .116 (.471) .686 (.437) .430 (.442) .407 (.479)
Medium–high technology � .210 (.278) � .710 (.432) � .150 (.337) .341 (.252) � .193 (.275) .036 (.258) .288 (.249) .335 (.310)
Medium–low technology � .065
(.263)
� .248 (.343) � .344 (.368) .078 (.255) � .094 (.274) � .184 (.254) � .052 (.252) .251 (.306)
Low technology Base Base Base Base Base Base Base Base
Knowledge-intensive-based services � .377 (.225) � .079 (.257) � .417 (.278) � .087 (.202) � .211 (.218) � .223 (.201) .062 (.193) .125 (.253)
Less knowledge-intensive-based
services
� .441*
(.213)
� .061 (.245) � .426 (.261) � .242 (.199) � .558* (.224) � .356 (.199) .046 (.187) � .170 (.258)
Country dummies Entered Entered Entered Entered Entered Entered Entered Entered
Regional GDP (/10,000) .062 (.069) .017 (.083) .226** (.084) .035 (.074) .109 (.076) .025 (.070) � .050 (.073) .106 (.082)
Regional R&D � .080
(.084)
� .181 (.106) � .112 (.106) .002 (.083) � .169 (.093) � .077 (.081) .038 (.080) � .002 (.091)
Constant � .894*
(.356)
�1.314**
(.404)
�1.914***
(.441)
�1.155**
(.335)
�1.841***
(.355)
� .869**
(.324)
� .674* (.314) �2.395***
(.401)
Number of observations 475
Wald chi (96) 145.36
Prob4chi2 .001
Log likelihood �1164.718
The entries in the table are coefficients, with standard errors in parentheses.
All correlation coefficients across equations are significant at .05.
(1) Subsidies for acquiring machinery, equipment or software; (2) Subsidies for buildings or other infrastructure for innovation activities; (3) Tax reductions for R&D
expenditure; (4) Support for networking with companies; (5) Support for networking with universities and research institutes; (6) Support for attending or participating in
trade fairs or trade missions; (7) Support for information on market needs, conditions, new regulations, etc.; (8) Direct support for financing innovation projects.
n Po .05 (2-tailed).
nn Po .01 (2-tailed).
nnn Po .001.
Table 4
Participation in publicly funded schemes by established companies. Multivariate Probit Model.
(1) (2) (3) (4) (5) (6) (7) (8)
Size .099nnn(.026) .093*** (.029) .171*** (.029) .116*** (.024) .204*** (.026) .047* (.024) .093*** (.024) .133*** (.027)
R&D expenditures .001* (.000) .001 (.000) .000 (.000) .001* (.000) .001* (.000) .001 (.000) .000 (.000) .001** (.000)
Sector of activity
High technology .004 (.178) � .195 (.242) .021 (.221) .283 (.186) .060 (.201) � .205 (.180) .021 (.190) .426* (.184)
Medium–high technology � .079 (.113) � .084 (.141) .435*** (.130) .016 (.120) .207 (.123) � .024 (.109) � .032 (.115) .196 (.125)
Medium–low technology � .012 (.100) � .027 (.126) .151 (.124) .164 (.105) � .161 (.121) � .085 (.097) � .030 (.102) .251* (.114)
Low technology Base Base Base Base Base Base Base Base
Knowledge-intensive-based services � .382***
(.106)
� .072 (.123) � .270* (.130) .147 (.103) .099 (.111) � .304**
(.098)
.024 (.100) � .059 (.116)
Less knowledge-intensive-based
services
� .294** (.095) � .037 (.113) � .296***
(.124)
.050 (.098) � .230* (.110) � .169 (.089) .046 (.092) � .252* (.113)
Country dummies Entered Entered Entered Entered Entered Entered Entered Entered
Regional GDP (/10,000) � .050 (.028) � .018 (.032) .182*** (.028) .059* (.024) .046 (.027) .007 (.024) .061** (.023) .055* (.028)
Regional R&D � .077* (.038) � .050 (.043) � .092* (.041) .013 (.031) .016 (.035) � .068*
(.032)
� .066* (.032) .042 (.035)
Constant �1.156***
(.144)
�1.677***
(.170)
�2.520***
(.182)
�1.796***
(.142)
�2.342***
(.159)
� .824***
(.133)
�1.433***
(.137)
�2.068***
(.162)
Number of observations 2263
Wald chi (112) 569.78
Prob4chi2 .000
Log likelihood �6094.910
The entries in the table are coefficients, with standard errors in parentheses.
All correlation coefficients across equations are significant at .05.
(1) Subsidies for acquiring machinery, equipment or software; (2) Subsidies for buildings or other infrastructure for innovation activities; (3) Tax reductions for R&D
expenditure; (4) Support for networking with companies; (5) Support for networking with universities and research institutes; (6) Support for attending or participating in
trade fairs or trade missions; (7) Support for information on market needs, conditions, new regulations, etc.; (8) Direct support for financing innovation projects.
n Po .05 (2-tailed).
nn Po .01 (2-tailed).
nnn Po .001.
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎10
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
role played by public policies in promoting and developing entre-
preneurial firm resources (e.g., knowledge) andcapabilities. New
ventures may possess certain important resources but may not have
sufficient time to develop the capabilities required to manage them.
External support might explain why some entrepreneurial firms
build and alter these capabilities more efficiently than others.
Entrepreneurship scholars have analyzed particular types of
resources to understand differences in firm performance, particu-
larly in terms of the ability to identify entrepreneurial opportunities
(Ireland et al., 2003). Information, social capital, and entrepreneurial
experiences are examples of these resources. The analysis of
complementary capabilities, such as product innovation – which
is particularly relevant to overcome the “liability of newness” – and
emphasis on developing the capabilities required to manage new
ventures' specific resources may enrich this line of research.
Finally, interest among academics and policy makers in under-
standing the efficacy and efficiency of different public incentives
that support innovation is growing (e.g., Norrman, 2008;
Santamaria et al., 2010). Although such analysis is beyond the
scope of this study, our results may provide useful insights into the
relationship between the most common public incentives that
support innovation and firms' development of new products, by
highlighting the differences between the characteristics of new
ventures and those of incumbent firms. These differences should
be considered in studies analyzing whether and how public
support incentives have long-term effects on recipient firms.
5.1. Implications for policy makers
We analyzed data gathered from 29 different countries. A
comparison of the effects of a number of incentives on product
innovation in a variety of economic and institutional frameworks
provides policy makers with information about which policies or
policy portfolios work best to achieve particular goals. The first
practical implication of our study is that public policies should make
a distinction between new ventures and established firms. Thus, the
final selection of public support instruments will depend on the goals
pursued by the policy maker. Innovation support policies are
typically assumed to affect new ventures and incumbents equally,
but our results indicate that such is not the case. Different instru-
ments have different effects on firms depending on their age,
resources and capabilities.
Policy makers should favor innovative new ventures because it
entails positive externalities for society (e.g. Arrow, 1962; Nelson,
1959). Although much remains to be learned about this relationship,
our paper sheds some light on how this goal might be achieved.
Specifically, policy makers should emphasize programs that support
networking with other companies and attending trade fairs and/or
trade missions to foster product innovation in new ventures. For
incumbents, tax reductions for R&D expenditures, subsidies for
acquiring R&D infrastructures and support for obtaining information
on market needs and trends are the most effective policies.
The conclusions of this paper may help refine the efficiency of
innovation policy instruments. For example, a particular instrument
might be effective at promoting product innovation among new
ventures, but its effect on incumbents' innovation might be negli-
gible. In this case, limiting the policy to the target group of firms
(i.e., to new ventures) might help save valuable public resources.
In addition, this line of research is also valuable to managerial
practice because it provides guidance on which public programs
are more appropriate for new ventures and/or incumbents.
5.2. Limitations and future research avenues
This study has limitations that are caused in part by its
exploratory nature and by the characteristics of the database design.
The database has been compiled using a large number of companies
over a wide variety of industrial sectors, and it covers a considerable
Table 5
Relationship between publicly funded schemes and innovation. Probit Models.
New ventures Established companies
Subsidies for acquiring machinery, equipment or softwarea �16.576 (10.809) 3.849 (2.800)
Subsidies for buildings or other infrastructure for innovation activitiesa 32.973 (18.508) 5.545nn (1.768)
Tax reductions for R&D expenditurea .991 (4.018) 2.886n (1.361)
Support for networking with companiesa 35.153n (16.333) 6.579 (3.559)
Support for networking with universities and research institutesa 4.051 (5.263) � .038 (1.937)
Support for attending or participating in trade fairs or trade missionsa 21.341nn (7.819) �11.256nnn (3.069)
Support for information on market needs, conditions, new regulations, etc. a �14.882 (8.479) �3.225 (2.700)
Direct support for financing innovation projectsa �8.234n (3.960) �7.073n (2.974)
Controls
Sector of activity:
High technology �11.820 (6.710) � .196 (.278)
Medium–high technology �1.399n (.684) .238 (.163)
Medium–low technology .086 (.601) � .399n (.173)
Low technology Base Base
Knowledge-intensive-based services .086 (.601) �1.406nnn (.233)
Less knowledge-intensive-based services 3.833 (2.060) � .846nnn (.171)
Size � .343 (.288) .141n (.069)
R&D expenditures .215nn (.074) .218nnn (.029)
Country dummies Entered Entered
Constant �12.886n (5.694) � .130 (.519)
Number of observations 502 2390
χ
2 (d.f.) 94.71 (30) 291.600 (28)
P-value .000 .000
Log likelihood �290.059 �1465.559
Pseudo R2 .162 .093
The entries in the table are coefficients, with standard errors in parentheses.
The reference category is “not to develop new or improved products”.
a The predictions of the probability of participating in each programme are obtained from Table 3 for new ventures and Table 4 for established companies, respectively.
n Po .05 (2-tailed).
nn Po .01 (2-tailed).
nnn Po .001.
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 11
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
established firms. Technovation (2015), http://dx.doi.org/10.1016/j.technovation.2015.02.002i
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
number of countries and includes a more extensive range of
different public innovation support instruments than previous
studies. These features guarantee a reasonable basis for generalizing
results. Nonetheless, this database has shortcomings: first, our data
cover only those firms with 20 employees or more to guarantee a
minimum activity and organizational structure. However, there
might be new ventures excluded from our study because they have
not had the time to achieve this minimum threshold. As a
consequence, new ventures in our study are relatively large or fast
growing. Conclusions may be carefully generalized or assumed for
small or slow-growth new ventures. Second, the database's cross-
sectional nature renders testing for causal effects over time impos-
sible. Third, this study includes subjective performance measures
through the use of direct questions for respondents. Because of the
EU's anonymity policy, correlating this information with a second-
ary objective dataset is not possible. Although the presence of
common-method bias in the dataset cannot be excluded, the nature
of the hypotheses, the application of recommendations from
Podsakoff et al. (2003) and the statistical tests applied suggest that
common-method bias is not a cause for concern in this study.
In addition, product innovation has been measured using a
dummy variable. However, this element constitutes a complex
phenomenon, and measuring innovation with a dichotomous
variable may lead to a lack of information on the new product
development process. Finally, this paper has analyzed only one
type of innovation. Therefore, our conclusions should not be
extended to other types and future work might focus on others,
such as organizational or process innovation, in order to study
possible differencesbetween new ventures and incumbents.
The following points can be viewed as possible future avenues of
research for the development of this study. It would be informative
to assess how different innovation policy instruments work
together. For example, it could be the case that specific instruments
mutually complement and reinforce each other, while other might
not exert this effect or even might counter-balance the effect of one
instrument. One long-term goal of future works on this research
stream could be to examine the suitability of specific configurations
of innovation policy instruments to foster innovation in specific
types of firms (i.e. new ventures and incumbents). Other interesting
avenue of research would consist in assessing the effect of the
innovation policy instruments differentiating between radical and
incremental product innovations and adding the frequency of new
product introductions and time to market.
Acknowledgements
The authors acknowledge financial support from the Spanish
Ministry of Economy and Competitiveness (National R&D Project
ECO2011-24921 and predoctoral grant program), the European
Regional Development Fund (ERDF/FEDER), the Ministry of Educa-
tion (FPU Program), the University of Almeria’s (UAL, ceiA3)
predoctoral grant program, and CySOC.
References
Aerts, K., Schmidt, T., 2008. Two for the price of one? Additionality effects of R&D
subsidies: a comparison between Flanders and Germany. Res. Policy 37 (5),
806–822.
Almus, M., Czarnitzki, D., 2003. The effects of public R&D subsidies on firms'
innovation activities: the case of eastern Germany. J. Bus. Econ. Stat. 21 (2),
226–236.
Alvarez, S., Busenitz, L., 2001. The entrepreneurship of resource based theory.
J. Manag. 27 (6), 755–775.
Antolin-Lopez, R., Martinez-del-Rio, J., Cespedes-Lorente, J., 2013. Cooperación y
competencia como antecedentes de la innovación de producto. ¿Aplican las
empresas nuevas y establecidas una lógica diferenciada? Investig. Eur. Dir.
Econ. Empresa 19 (1), 53–62.
Arrow, K.J., 1962. Economic welfare and the allocation of resources for invention.
In: Nelson, R.R. (Ed.), The Rate and Direction of Inventive Activity: Economic
and Social Factors. Princeton, N.J., pp. 609–625.
Arthurs, J.D., Busenitz, L.W., 2006. Dynamic capabilities and venture performance:
the effects of venture capitalists. J. Bus. Ventur. 21 (2), 195–215.
Aspelund, A., Berg-Utby, T., Skjevdal, R., 2005. Initial resources' influence on new
venture survival: a longitudinal study of new technology-based firms. Techno-
vation 25 (11), 1337–1347.
Baker, T., Nelson, R.E., 2005. Creating something from nothing: resource construc-
tion through entrepreneurial bricolage. Adm. Sci. Q. 50 (3), 329–366.
Berube, C., Mohnen, P., 2009. Are firms that receive R&D subsidies more innovative?
Can. J. Econ. 42 (1), 206–225.
Blanes, J.W., Busom, I., 2004. Who participates in R&D subsidy programs? The case
of Spanish manufacturing firms. Res. Policy 33 (10), 1459–1476.
Biernacki, C., Govaert, C., 1999. Choosing models in model-based clustering and
discriminant analysis. J. Stat. Comput. Simul. 64 (1), 49–71.
Bosse, D.A., 2009. Bundling governance mechanisms to efficiently organize small
firm loans. J. Bus. Ventur. 24 (2), 183–195.
Bozdogan, H., 1987. Model selection and Akaikes information criterion (AIC): the
general theory and its analytical extensions. Psychometrika 52 (3), 345–415.
Bruton, G.D., Ahlstrom, D., Li, H.-L., 2010. Institutional theory and entrepreneurship:
where are we now and where do we need to move in the future? Entrep.
Theory Pract. 34 (3), 421–440.
Bruton, G.D., Rubanik, Y., 2002. Resources of the firm, Russian high-technology
startups, and firm growth. J. Bus. Ventur. 17 (6), 553–566.
Burg, E., Podoynitsyna, K., Beck, L., Lommelen, T., 2012. Directive deficiencies: how
resource constraints direct opportunity identification in SMEs. J. Prod. Innov.
Manag. 29 (6), 1–12.
Burke, A., Fraser, S., Greene, F.J., 2010. The multiple effects of business planning on
new venture performance. J. Manag. Stud. 47 (3), 391–415.
Busom, I., 2000. An empirical evaluation of the effects of R&D subsidies. Econ.
Innov. New Technol. 9 (2), 111–148.
Cappelen, Å., Raknerud, A., Rybalka, M., 2012. The effects of R&D tax credits on
patenting and innovations. Res. Policy 41 (2), 334–345.
Cappellari, L., Jenkins, S.P., 2003. Multivariate probit regression using simulated
maximum likelihood. The Stata Journal 3 (3), 278–294.
Chesbrough, H., 2003. Open Innovation: The New Imperative for Creating and
Profiting from Technology. Harvard Business School Press, Boston, MA.
Chesbrough, H., Crowther, A.K., 2006. Beyond high tech: early adopters of open
innovation in other industries. R&D Manag. 36 (3), 229–236.
Cohen, J., Cohen, P., West, S.G., 2003. Applied Multiple Regression/Correlation
Analysis for the Behavioural Sciences. Erlbaum, Mahwah, NJ.
COM, 2009. Making Public Support for Innovation in the EU More Effective: Lessons
Learned from a Public Consultation for Action at Community Level. Commission
of the European Communities, Brussels.
Council of the European Union 2006. Council conclusions on a broad-based
innovation strategy: strategic priorities for innovation action at the EU level.
In: Proceedings of the 2769th Council Meeting of Competitiveness Council,
Brussels.
Czarnitzki, D., Ebersberger, B., Fier, A., 2007. The relationship between R&D
collaboration, subsidies and R&D performance: empirical evidence from Fin-
land and Germany. J. Appl. Econom. 22 (7), 1347–1366.
Czarnitzki, D., Fier, A., 2002. Do innovation subsidies crowd out private invest-
ment? Evidence from the German service sector. Appl. Econ. Q. 48 (1), 1–25.
Czarnitzki, D., Hanel, P., Rosa, J.M., 2011. Evaluating the impact of R&D tax credits on
innovation: a microeconometric study on Canadian firms. Res. Policy 40 (2),
217–229.
Czarnitzki, D., Lopes-Bento, C., 2014. Innovation subsidies: Does the funding source
matter for innovation intensity and performance? Empirical evidence from
Germany.
Czarnitzki, D., Lopes-Bento, C., 2013. Value for money? New microeconometric
evidence on public R&D grants in Flanders. Res. Policy 42 (1), 76–89.
Damanpour, F., 1991. Organizational Innovation: a meta-analysis of effects of
determinants and moderators. Acad. Manag. J. 34 (3), 555–590.
Damanpour, F., Szabat, K.A., Evan, W.M., 1989. The relationship between types of
innovation and organizational performance. J. Manag. Stud. 26 (6), 587–601.
Danneels, E., 2002. The dynamics of product innovation and firm competences.
Strateg. Manag. J. 23 (12), 1095–1121.
David, P., Hall, B., Toole, A., 2000. Is public R&D a complement or substitute for
private R&D? A review of the econometric evidence. Res. Policy 29 (4),
497–529.
Gans, J.S., Stern, S., 2003. The product market and the market for “ideas”:
commercialization strategies for technology entrepreneurs. Res. Policy 33 (2),
333–350.
Gonzalez, X., Pazo, C., 2008. Do public subsidies stimulate private R&D spending?
Res. Policy 37 (3), 371–389.
Gilsing, V.A., van Burg, E., Romme, A.G., 2010. Policy principles for the creation and
success of corporate and academic spin-offs. Technovation 30 (1), 12–23.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 1999. Analisis Multivariante.
Prentice Hall, Madrid.
Hall, B., van Reenen, J., 2000. How effective are fiscal incentives for R&D? A review
of the evidence. Res. Policy 29 (4–5), 449–469.
Heckman, J.J., 1979. Sample selection bias as a specification error. Econometrica:
J. Econom. Soc. 47 (1), 153–161.
Heckman, J.J., Ichimura, H., Smith, J., Tood, P., 1998. Characterizing selection bias
using experimental data. Econometrica: J. Econom. Soc. 66 (5), 1017–1098.
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎12
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
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http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref33
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref33
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref34
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref34
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref35
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref35
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref36
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref36
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref36
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref37
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref37
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref38
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref38
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Hitt, M.A., Hoskisson, R.E., Johnson, R.A., Moesel, D.D., 1996. The market for
corporate control and firm innovation. Acad. Manag. J. 39 (5), 1084–1119.
Huergo, E., Moreno, L., 2014. National or International Public Funding? Subsidies or
Loans? Evaluating the Innovation Impact of R&D Support Programmes. Uni-
versity Library of Munich, Germany, No. 54218.
Ireland, R.D., Hitt, M.A., Sirmon, D.G., 2003. A model of strategic entrepreneurship:
the construct and its dimensions. Strateg. Manag. J. 29 (6), 963–989.
Keizer, J.A., Dijkstra, L., Halman, J.I.M., 2002. Explaining innovative efforts of SMEs.
An exploratory survey among SMEs in the mechanical and electrical engineer-
ing sector in Netherlands. Technovation 22 (1), 1–13.
Kleinschmidt, E.J., Cooper, R.G., 1991. The impact of product innovativeness on
performance. J. Prod. Innov. Manag. 8 (4), 240–251.
Klette, T.J., Møen, J., Griliches, Z., 2000. Do subsidies to commercial R&D reduce
market failures? Microeconometric evaluation studies. Res. Policy 29 (4),
471–495.
Kwon, S.-W., Arenius, P., 2010. Nations of entrepreneurs: a social capital perspec-
tive. J. Bus. Ventur. 25 (3), 315–330.
Lach, S., 2002. Do R&D subsidies stimulate or displace private R&D? Evidence from
Israel. J. Ind. Econ. 50 (4), 369–390.
Lado, A.A., Wilson, M.C., 1994. Human resource systems and sustained competitive
advantage: a competency-based perspective. Acad. Manag. Rev. 19 (4),
699–727.
Marion, T., Friar, J.H., Simpson, T.W., 2012. New product development practices and
early-stage firms: two in-depth case studies. J. Prod. Innov. Manag. 29 (4),
639–654.
Martin, S., Scott, J.T., 2000. The nature of innovation market failure and the design
of public support for private innovation. Res. Policy 29 (4), 437–448.
Martinez-Ros, E., 2000. Explaining the decisions to carry out product and process
innovations: the Spanish case. J. High Technol. Manag. Res. 10 (2), 223–242.Nelson, R.R., 1959. The simple economics of basic scientific research. J. Polit. Econ.
67 (3), 297–306.
Norrman, C., 2008. Entrepreneurship Policy: Public Support for Technology-Based
Ventures. Doctoral dissertation, Linköping University, Linköping.
Norrman, C., Klofsten, M., 2009. An entrepreneurship policy programme: implica-
tions and expectations. Entrep. Innov. 10 (1), 33–42.
Oakey, R.P., 2003. Funding innovation and growth in UK new technology-based
firms: some observations on contributions from the public and private sectors.
Venture Cap. 5 (2), 161–179.
OECD/EUROSTAT, 2005. Oslo Manual: Guidelines for collecting and interpreting
innovation data. Organization for Economic Co-operation and Development,
and Statistical Office of the European Communities, EUROSTAT, Paris.
Ozgen, E., Baron, R.A., 2007. Social sources of information in opportunity recogni-
tion: effects of mentors, industry networks, and professional forums. J. Bus.
Ventur. 22 (2), 174–192.
Peneder, M., 2008. The problem of private under-investment in innovation: a policy
mind map. Technovation 28 (4), 518–530.
Podsakoff, P.M., MacKenzie, S.B., Lee, L.Y., 2003. Common method biases in
behavioral research: a critical review of the literature and recommended
remedies. J. Appl. Psychol. 88 (5), 879–903.
Prahalad, C.K., Hamel, G., 1990. The core competence of the corporation. Harv. Bus.
Rev. 68, 79–91.
Radas, S., Bozic, L., 2009. The antecedents of SME innovativeness in an emerging
transition economy. Technovation 29 (6–7), 438–450.
Revilla, A.J., Fernandez, Z., 2012. The relation between firm size and R&D
productivity in different technological regimes. Technovation 32 (11), 609–623.
Rigby, D., Zook, C., 2002. Open-market innovation. Harv. Bus. Rev. 80 (10), 80–89.
Sakakibara, M., 1997. Heterogeneity of firm capabilities and cooperative research
and development: an empirical examination of motives. Strateg. Manag. J. 18
(S1), S143–S164.
Sakakibara, M., 2002. Formation of R&D consortia: industry and company effects.
Strateg. Manag. J. 23 (11), 1033–1050.
Santamaria, L., Barge-Gil, A., Modrego, A., 2010. Public selection and financing of
R&D cooperative projects: credit versus subsidy funding. Res. Policy 39 (4),
549–563.
Schoonhoven, C.B., Eisenhardt, K.M., Lyman, K., 1990. Speeding products to market:
waiting time to first product introduction in new firms. Adm. Sci. Q. 35 (1),
177–207.
Schwartz, M., Peglow, F., Fritsch, M., Günther, J., 2012. What drives innovation
output from subsidized R&D cooperation? Project-level evidence from Ger-
many. Technovation 32 (6), 358–369.
Sine, W.D., Lee, B.H., 2009. Tilting at windmills? The environmental movement and
the emergence of the US wind energy sector. Adm. Sci. Q. 54 (1), 123–155.
Stinchcombe, A.L., 1965. Social structure and organizations. In: March, G. (Ed.),
Handbook of Organizations. Rand McNally, New York.
Storey, D.J., Tether, B.S., 1998. Public policy measures to support new technology-
based firms in the European Union. Res. Policy 26 (9), 1037–1057.
Teece, D.J., 1986. Profiting from technological innovation: implications for integra-
tion, collaboration, licensing and public policy. Res. Policy 15 (6), 285–305.
Tether, B.S., 2002. Who co-operates for innovation, and why: an empirical analysis.
Res. Policy 31 (6), 947–967.
Tether, B.S., 2005. Do services innovate (differently)? Insights from the European
Innobarometer Survey. Ind. Innov. 12 (2), 153–184.
Tether, B.S., Tajar, A., 2008a. The organisational-cooperation mode of innovation
and its prominence amongst European service firms. Res. Policy 37 (4),
720–739.
Tether, B.S., Tajar, A., 2008b. Beyond industry–university links: sourcing knowledge
for innovation from consultants, private research organisations and the public
science-base. Res. Policy 37 (6–7), 1079–1095.
Walsh, S.T., Linton, J.D., 2001. The competence pyramid: a framework for identify-
ing and analyzing firm and industry competence. Technol. Anal. Strateg. Manag.
13 (2), 165–177.
Wallsten, S., 2000. The effects of government–industry R&D programs on private
R&D: the case of the SBIR program. RAND J. Econ. 31 (1), 82–100.
Wiklund, J., Baker, T., Shepherd, D., 2010. The age-effect of financial indicators as
buffers against the liability of newness. J. Bus. Ventur. 25 (4), 423–437.
Woolley, J.L., Rottner, R.M., 2008. Innovation policy and nanotechnology entrepre-
neurship. Entrep. Theory Pract. 32 (5), 792–811.
Yang, C.-H., Huang, C.-H., Hou, T.C., 2012. Tax incentives and R&D activity: firm level
evidence from Taiwan. Res. Policy 41 (9), 1578–1588.
Zahra, S.A., Filatotchev, I., 2004. Governance of the entrepreneurial threshold firm:
a knowledge-based perspective. J. Manag. Stud. 41 (5), 885–897.
Zhang, Y., Li, H., 2010. Innovation search of new ventures in a technology cluster:
the role of ties with service intermediaries. Strateg. Manag. J. 31 (1), 88–109.
R. Antolín-López et al. / Technovation ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 13
Please cite this article as: Antolín-López, R., et al., Fostering product innovation: Differences between new ventures and
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http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref43
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref44
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http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref44
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref44
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref45
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref45
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref46
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref46
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref46
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref46
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref47
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref47
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref47
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref48
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref48
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref48
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref49
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref49
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref50
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref50
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref51
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref51
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref52
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref52
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref53
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref53
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref54
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref54
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref54
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref55
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref55
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref55
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref56
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref56
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref56
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref57
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref57
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref58http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref58
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref58
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref59
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref59
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref60
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http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref64
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http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref68
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref68
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref69
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref69
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref70
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref70
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref71
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref71
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref72
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref72
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref73
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref73
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref74
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref74
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref74
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref75
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref75
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref75
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref76
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref76
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref76
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref77
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref77
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref77
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref77
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref78
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref78
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref79
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref79
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref80
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref80
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref80
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref81
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref81
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref82
http://refhub.elsevier.com/S0166-4972(15)00012-7/sbref82
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002
http://dx.doi.org/10.1016/j.technovation.2015.02.002