
SMEs inventive performance and proﬁtability in the markets
for technology

Giovanna Padula a,n, Elena Novelli b,1, Raffaele Conti c,2

a Università “L. Bocconi”, Via G. Roentgen, 1, 20136 Milano, Italy
b City University London, 106 Bunhill Row, London EC1Y 8TZ, UK
c Católica Lisbon School of Business and Economics, Palma de Cima, 1649-023 Lisboa, Portugal

a r t i c l e i n f o

Available online 11 March 2015

Keywords:
Markets for technologies
Vertical boundaries
Firm inventive performance
Firm proﬁtability
Small medium enterprises

a b s t r a c t

This paper studies the inventive performance and proﬁtability of small and medium sized ﬁrms (SMEs) that
are “technology specialists” compared to the inventive performance and proﬁtability of SMEs that are
instead vertically-integrated. In this paper perspective, “technology specialists” are ﬁrms that specialize
upstream in generating inventions and trade those inventions in disembodied formwith other ﬁrms, usually
through licensing agreements. Instead, vertically-integrated ﬁrms are those ﬁrms that both generate
inventions and commercialize products incorporating those inventions. We argue that technology specialists
achieve a higher inventive performance than vertically-integrated ﬁrms, since they can accumulate deeper
and broader inventive experience, whilst keeping a more ﬂexible organizational structure. These ﬁrms
display a lower proﬁtability though, due to the imperfections inherent in invention market transactions and
the lower bargaining power caused by the lack of commercialization assets. The theoretical framework is
tested through a cross-industry investigation on a sample of European SMEs. Implications for the viability of
being a technology specialist as a strategy and for the development of markets for technology are discussed.

& 2015 Elsevier Ltd. All rights reserved.

1. Introduction

Recent studies have established the increasing importance of
markets for technology (e.g., Arora et al., 2001; Krammer, 2014;
Ritala and Hurmelinna-Laukkanen, 2009; Veer and Jell, 2012; Wang
et al., 2012)—hereafter, MFT—that is, markets where inventions are
traded as “free standing” entity, disembodied from individuals, orga-
nizations and products (e.g., Arora et al., 2001). In these markets ﬁrms
can exchange their inventions for a price, usually through a licensing
agreement, which is a contract where the owner of an invention
allows another party the right to use or modify it in exchange of
compensation (WIPO, 2014). Previous research on MFT has mainly
taken a policy perspective on this phenomenon, arguing that the
development of these markets allows for an efﬁcient division of
innovative labor among small and large ﬁrms according to their
comparative advantage—which is, respectively, doing research and
generating inventions for small ﬁrms, and producing and marketing
the ﬁnal products that embody new inventions for large ﬁrms (Arora
et al., 2001; Arrow, 1983; Holmstrom, 1989). This type of conﬁguration

is socially desirable, in principle, since every type of ﬁrm focuses on
the activity it performs better (Firth and Narayanan, 1996; Li and Tang,
2010); hence, a higher overall value might be generated compared to a
situation where all ﬁrms internalize both the research and ﬁnal
product commercialization activities (e.g., Arora and Ceccagnoli,
2006; Arora et al., 2001; Conceicao et al., 2012).

However, the ﬁrm-level implications of MFT in terms of ﬁrm
inventive performance (i.e. the extent to which a ﬁrm is capable of
generating valuable inventions) and proﬁtability have been largely
neglected. It is not clear whether small ﬁrms are better off exploit-
ing their comparative advantage in inventing by becoming “tech-
nology specialists”—that is, specializing upstream in the inventive
activities and then sell their inventions in the MFT—or whether they
should vertically integrate—that is, commercialize their own inven-
tions to ﬁnal customers. In particular, on the side of inventive per-
formance, previous research on MFT has largely neglected how the
interdependence between upstream invention and downstream
product commercialization activities affects the ﬁrm's capacity to
generate high quality inventions; consequently we still lack an
understanding of whether the inventive performance of technology
specialists overcomes that of vertically-integrated small ﬁrms. At
the same time, on the side of proﬁtability, the literature on MFT has
largely neglected to consider the ability of technology specialists to
appropriate the economic returns of their inventions. Indeed, beco-
ming a technology specialist and selling inventions to other ﬁrms

Contents lists available at ScienceDirect

journal homepage: www.elsevier.com/locate/technovation

Technovation

http://dx.doi.org/10.1016/j.technovation.2015.01.002
0166-4972/& 2015 Elsevier Ltd. All rights reserved.

n Corresponding author. Tel.: þ39 02 58366823.
E-mail addresses: giovanna.padula@unibocconi.it (G. Padula),

novelli@city.ac.uk (E. Novelli), raffaele.conti@ucp.pt (R. Conti).
1 Tel.: þ44 20 7040 0991; fax: þ44 20 7040 8328.
2 Tel.: þ351 217 214270; fax: þ351 217 270250.

Technovation 41-42 (2015) 38–50


require ﬁrms to incur the private costs related to search and ne-
gotiation in the MFT (e.g. Fosfuri, 2006). In addition, being a
technology specialist also implies that a ﬁrm lacks downstream,
complementary assets that have been demonstrated to be a relevant
source of bargaining power (e.g., McGahan and Silverman, 2006;
Teece, 1986). Accordingly, we still do not know the extent to which—
at the ﬁrm level—the economic beneﬁts of being a technology
specialist overcome the costs.

This study ﬁlls in these gaps by investigating the following
research question: how does the choice of being a technology
specialist (as opposed to being a vertically-integrated ﬁrm) affect
an SME's inventive performance and proﬁtability? Addressing these
issues is important because it allows for an understanding as to what
extent being a technology specialist is a viable strategy for an SME.
The rest of the paper is organized as follows. In Section 2 we present
our theory and hypotheses and in Section 3 we describe the method
that we used to test the hypotheses developed. In Section 4 we
present the empirical results, while in Section 5 we discuss their
implications to practice and theory. Finally, in Section 6, we present
the conclusions from the study.

2. Technology specialists vs. vertically-integrated SMEs:
implications on inventive performance and proﬁtability

Building on the principles of specialization and division of labor
(Smith, 1776 [1983]; Stigler, 1951; Young, 1928), literature on MFT has
argued that small and large ﬁrms are naturally endowedwith different
capabilities in inventing and commercializing; hence, they can beneﬁt
from specializing in the activity in which they are relatively more
efﬁcient (e.g., Arora et al., 2001; Ceccagnoli and Jiang, 2013). In
particular, we can represent the innovation value chain as the chain
of activities from upstream research activities—i.e., research and inven-
tions generation—to downstream activities—i.e., large-scale develop-
ment of those inventions into products, manufacturing and marketing
to the ﬁnal customers. Large, established ﬁrms, due to their highly
bureaucratic structure, have a comparative advantage in performing
downstream activities, which typically involve a high degree of routi-
nization and standardization (Allarakhia andWalsh, 2011; Holmstrom,
1989; Mangematin et al., 2011). Small ﬁrms, instead, have a compara-
tive advantage in performing upstream research activities because,
due to the low organizational distance between managers and res-
earchers (e.g. Arrow, 1983; Marion et al., 2012), they are more likely to
pursue risky but potentially extremely valuable technological trajec-
tories (Arrow, 1983; Arora et al., 2001).

These arguments suggest that, at the system level, the division of
value chain activities among ﬁrms on the basis of their comparative
advantage leads to the generation of a higher value compared to a
situationwhere every ﬁrm performs all these activities (i.e. invention,
development and commercialization to ﬁnal customers) internally.
Hence, based on this argument, it would appear preferable—from a
social welfare perspective—if SMEs specialized in upstream research
activities, i.e. if they became “technology specialists” (Arora et al.,
2001). However, existing research in this area provides only limited
insight on whether operating as a technology specialist also brings a
“private” advantage to SMEs, that is, whether technology specialists
have a better performance compared to the vertically-integrated
SMEs, i.e. those SMEs that internalize all value chain activities. More
precisely, existing research on MFT has provided only limited con-
sideration to the interdependence between upstream invention gen-
eration and downstream commercialization activities. Consequently,
existing research has not investigated the extent to which this
interdependence affects the inventive performance of small ﬁrms
that are technology specialists, and only focus on the generation of
inventions, vs. vertically-integrated small ﬁrms, which internalize
both activities.

In addition, existing research on MFT has not investigated the
extent to which SMEs' proﬁtability is affected by the choice between
upstream specialization vs. vertical integration. Becoming a technology
specialist implies undertaking search and negotiation activities in the
MFT; hence, it might require incurring additional costs that might
reduce SME's proﬁtability (e.g. Leiblein and Madsen, 2009). The extent
to which these costs overcome the beneﬁts of being a technology
specialist has been overlooked by extant literature. Furthermore, a
technology specialist lacks downstream complementary assets that a
vertically-integrated ﬁrm instead possesses, with possible implications
on its bargaining power and consequently on its proﬁtability com-
pared to a vertically-integrated SME (e.g. Fosfuri, 2006; Leiblein and
Madsen, 2009). However, these implications have been neglected by
extant studies. The goal of this paper is to ﬁll this gap and compare the
implications for an SME of being a technology specialist vs. being
vertically-integrated, in terms of both their inventive performance and
proﬁtability. In doing so this paper contributes to improving our
understanding on the performance of SMEs (Hoffman et al., 1998).

We argue that being a technology specialist (as opposed to being
a vertically-integrated ﬁrm) has a positive impact on a small ﬁrm
inventive performance for two reasons. The ﬁrst reason relates to the
deeper and broader inventive experience that technology specialists
can accumulate (Leiblein and Madsen, 2009). Technology specialists
devote all their efforts and resources to their inventive activity (Arora
et al., 2001). This makes them more likely to enjoy faster accumula-
tion of inventive experience in their technological ﬁelds compared to
vertically-integrated small ﬁrms—which instead spread their reso-
urces and attention across upstream (i.e., invention) and downstream
(i.e., commercialization) activities. While this argument holds for any
ﬁrm (regardless of its size), it is even more salient for small ﬁrms,
whose resource endowments are typically scarcer compared to those
of larger ﬁrms (Teece, 1986). This implies that technology specialist
SMEs tend to acquire a “deeper” inventive experience than vertically-
integrated SMEs (Díez-Vial, 2009; Yelle, 1979).

At the same time, because technology specialists have the
ultimate goal to sell or license their technologies to other ﬁrms
(Bianchi et al., 2011; Veer and Jell, 2012), they have the incentive to
generate inventions that target a greater variety of business applica-
tions and customer needs compared to vertically-integrated ﬁrms,
whose research activity mainly serves in-house needs (Arora et al.,
2001; Grant, 2002; Hicks and Hegde, 2005). This argument holds a
fortiori for smaller vertically-integrated ﬁrms, which, due to their
resource constraints, usually operate in a limited set of market
niches. This implies that technology specialists tend to acquire a
“broader” inventive experience than vertically-integrated ﬁrms and
this effect is even stronger in the case of SMEs (Hicks and Hegde,
2005). Both a depth and breadth of inventive experience enable
lessons learned from experience to accrue more steadily, thus
generating better inventions (Katila and Ahuja, 2002).

The second reasonwhy being a technology specialist (as opposed to
being a vertically-integrated ﬁrm) has a positive impact on a small
ﬁrm's inventive performance is related to the organizational structure
typically characterizing technology specialists vs. vertically-integrated
ﬁrms, which makes the former better positioned to generate valuable
inventions. A vertically-integrated ﬁrm is likely to display tight inte-
rdependences between upstream organizational units—focused on res-
earch and on the generation of valuable inventions—and downstream
units—commercializing those inventions embodied into products for
ﬁnal customers (Taylor and Helfat, 2009). These interdependences are
likely to inhibit the generation of path-breaking inventions and rather
favor path dependence at the expense of novelty (Powell, 1992; Taylor
and Helfat, 2009). A very clear illustration for this mechanism is
presented by Fosfuri and Roende (2009). Vertically-integrated compa-
nies are companies where an upstream R&D unit and a downstream
manufacturing unit coexist. In principle the R&D unit may select the
research trajectory to be pursued between multiple alternatives, which

G. Padula et al. / Technovation 41-42 (2015) 38–50 39


vary in their value and novelty. For instance, the R&D unit might
choose between research trajectories likely to deliver radical and extr-
emely valuable inventions, and other trajectories probably resulting in
incremental inventions. Choosing a research trajectory oriented to the
generation of radical inventions is likely to require the creation of new
sets of manufacturing routines and expertise—and so, huge adaptation
costs in the production units (e.g. Linton andWalsh, 2013). This implies
that these more radical trajectories naturally meet a strong internal
resistance (Henderson, 1993; Henderson and Clark, 1990) in vertically-
integrated ﬁrms. To avoid a costly internal conﬂict, the R&D units of
vertically-integrated ﬁrms are likely to lean towards incremental
(though probably less valuable) research trajectories.

A large bulk of empirical evidence supports the idea that vertically-
integrated ﬁrms present systemic resistance to generating radical inv-
entions that alter the relationships among different stages of the
production process (Glasmeier, 1991; Mariotti and Cainarca, 1986;
O’Connor and DeMartino, 2006; Tripsas, 1997). In contrast, technology
specialists can take advantage of a higher degree of freedom in their
decision making, which stems from the absence of the typical organ-
izational and coordinative constraints that characterize vertically-
integrated ﬁrms. Given that experimentation and risk taking are crucial
in the discovery of valuable technological solutions (e.g., Ahuja and
Lampert, 2001; Gupta et al., 2006), we suggest that the greater
opportunity of technology specialists compared to vertically-integ-
rated ﬁrms to undertake radical research paths is likely to result in a
greater ability to generate valuable inventions.

All these arguments lead us to predict:

Hypothesis 1. Technology specialist SMEs have higher inventive
performance than vertically-integrated SMEs.

While being a technology specialist may positively affect SMEs'
inventive performance, at the same time it may also hamper their
proﬁtability for two reasons related respectively to: a) the imperfec-
tions that plague the MFT functioning (e.g. Cockburn, 2007; Gans et al.,
2008) and b) the lower bargaining power of technology specialists in
negotiations due to their lack of downstream (i.e. commercialization)
assets (McGahan and Silverman, 2006; Teece, 1986).

Consider ﬁrst the imperfections that obstruct the functioning of
MFT. Existing research has emphasized how the actual volume of
technology transactions occurring in MFT is much lower than it
could be due to several imperfections in the functioning of these
markets (Gans et al., 2008; Giuri et al., 2007). This clearly hampers
the technology specialists' possibility to make proﬁts through
invention trading. For instance, it is usually quite complicated for
a company that has generated a new invention to identify the right
buyer, since this involves scanning multiple market niches and
identifying technological problems to which the invention could
constitute a solution (Ceccagnoli and Jiang, 2013; Cockburn, 2007).
This generates very high search costs and, consequently, a reduc-
tion in the proﬁts that technology specialists can generate by
selling their technologies in MFT.

Moreover, even once a potential buyer has been found, uncertainty
about the market value of an invention might obstruct the transaction
(Gambardella, 2013). Having generated the invention the seller, com-
pared to the buyer, usually has more information regarding its true
value (Gans et al., 2008). This information asymmetry leads to a classic
adverse selection problem (Beggs, 1992; Sakakibara, 2010) because the
buyers are not always capable of selecting between good and bad
inventions and they make offers that take into consideration the
possibility that the acquired invention might be a low quality one
(Cockburn, 2007). As a result, sellers of good inventions end up
receiving offers that are lower than what they know would be fair,
which reduces the likelihood of an agreement with the buyer. A
similar dynamic also occurs in the circumstance in which the invent-
ing ﬁrm itself is uncertain about the true value of its inventions—such

as in the case of very novel and path-breaking inventions. In this
situation inventing ﬁrms tend to be overoptimistic about the quality of
their own inventions (Dushnitsky, 2010; Giuri et al., 2007). This
reduces the chance to agree with the buyer on a price, because even
fair offers tend to be perceived by the inventor as too low. Overall, the
difﬁculties in reaching an agreement about the value of the invention
with any potential buyers hamper the possibility that technology
specialists will generate proﬁts from their inventions. Consistently
with these arguments, previous research has found that divergences
over the ﬁnancial terms of licensing agreements—which is the usual
way an invention is sold in MFT—are some of the major reasons why
negotiations break down (Cockburn, 2007).

Finally, the trading of inventions is plagued by possible opportu-
nistic behaviors by the transaction counterparts, especially in the
absence of “appropriate intellectual property rules, procedures, and
protection” (Gouvea et al., 2012, p. 563). Such moral hazard issues are
likely to induce prospective buyers to consider with caution the
option of buying an invention on the market (Dechenaux et al., 2011;
Dushnitsky, 2010). This is due to the fact that the knowledge und-
erlying the inventions often displays tacit components in addition to
codiﬁed components (Arora, 1996; Winter, 1987). The effective
transfer of such knowledge, therefore, requires a certain amount of
complementary effort from the inventing ﬁrm side to assist the buyer
in the complete understanding and integration of the invention in its
products (Leone and Reichstein, 2012). However, inventing ﬁrms
might display opportunistic behaviors and try to skimp on the full
effort required to transfer knowledge to the buyer (Arora, 1996). This
issue is further complicated by the fact that transactions of inven-
tions often require highly specialized complementary investments
from the buyers, who are consequently exposed to the risk of “hold
up” (Shane, 2002). The risk of moral hazard and hold up reduces
potential buyers' propensity to acquire external inventions. From the
point of view of a technology specialist, this results in a further
obstacle to proﬁt from invention trading.

Besides MFT imperfections, the second reason why technology
specialists tend to be less proﬁtable than vertically-integrated small
ﬁrms is that a vertically-integrated ﬁrm—by deﬁnition provided with
downstream assets—can sell its inventions embodied into ﬁnal
products, without having to negotiate with a counterpart; by contrast,
a technology specialist has to engage in a negotiation with a ﬁrm
provided with downstream assets to sell its inventions. In this type of
negotiation, the margins accruing to the technology specialist tend to
be squeezed due to the stronger bargaining position of the buyer that
originates from the possession of downstream (commercialization)
vis-a-vis upstream (research) assets (Chiu et al., 2008). Hence, since
the possession of downstream assets represents a critical determinant
of the ability to appropriate the economic returns of an invention (e.g.
Teece, 1986), vertically-integrated ﬁrms are better able to proﬁt from
their inventions compared to technology specialists.

Previous empirical evidence supports our line of reasoning. For
instance, Arora and Nandkumar (2012), examining the software secu-
rity industry, found thatMFT raise the value of marketing capabilities in
ensuring ﬁrm survival, and simultaneously decrease the value of
technological capabilities. In the same vein, but using a much broader
dataset on all publicly traded U.S. ﬁrms, McGahan and Silverman
(2006) show that the stock market value of ﬁrms controlling down-
stream assets in a focal industry increases when outsider players
generate inventions that could be fruitfully commercialized within the
industry. This happens because outsiders usually do not possess the
relevant downstream assets to operate in the industry. As a result,
insiders tend to enjoy a higher bargaining power in negotiations and
eventually appropriate a greater portion of the value generated through
the transaction of inventions, reducing the proﬁts accruing to ﬁrms
who do not possess downstream assets (i.e. technology specialists).

To summarize, the imperfections of MFT and the limited bar-
gaining power of technology specialists determined by their lack of

G. Padula et al. / Technovation 41-42 (2015) 38–5040


downstream assets exert a negative effect on the ability of technol-
ogy specialists to proﬁt from their inventions in MFT. Accordingly,
we hypothesize that:

Hypothesis 2. Technology specialist SMEs have lower proﬁtability
than vertically-integrated SMEs.

3. Method

The empirical investigation of this study was accomplished on
a population of European-based SMEs, across all industries, within
the timeframe 1996–2001. Coverage across all industries provides
the advantage of permitting a systematic investigation of the
study's predictions. Geographic restriction to Europe is motivated
by the fact that huge institutional differences characterize markets
for technology across different regions throughout the world, a
circumstance that may have an impact on the performance of the
ﬁrms under investigation in this study (Ginarte and Park, 1997). As
a consequence, focusing on a speciﬁc and relatively homogenous
geographical area may guarantee that many of these features rem-
ain constant across this study sample, enabling a more robust test
of the hypotheses. However, as the appropriability regime may still
be expected to vary from country to country even within the
European area, a control for the strength of patent protection was
included in the statistical analyses (Ginarte and Park, 1997).

While the 1990s were characterized by the steady increase in the
volume of market transactions of inventions and by the increase in
variance across ﬁrms in terms of their vertical boundaries and
invention-commercialization choices, the greatest changes in this
direction occurred—at least in Europe—in the second half of the
1990s, that is the temporal window on which this study is focused.

3.1. Sample and data

We used a cross-sectional dataset of Europe-based SMEs across all
industries in the timeframe 1996–2001 to test our hypotheses. The
choice of employing a cross-sectional dataset instead of a panel
dataset is motivated by the concern for the reliability of yearly data
on invention commercialization strategies, provided that our sample
is composed by SMEs. Indeed, forming a panel dataset would require
the collection of yearly data on ﬁrms' invention commercialization
strategies (i.e. yearly data on whether each ﬁrm had sold or licensed
its inventions to other ﬁrms or had embodied its inventions into
products). Having conducted an accurate and extensive pilot search
on multiple data sources (including Business & Industry, Factiva,
Zephyr and Securities Data Corporation databases as well as com-
pany web sites and specialized websites) we discovered that collect-
ing yearly data for small private companies was problematic since
these ﬁrms do not receive systematic media coverage. Therefore it is
not possible to ﬁnd each licensing agreement or each product
launched by each of these companies in each single year reported
on public sources.

However, our pilot search supported the idea that expanding our
cross-sectional analysis to a time window of six years would lead to
a reliable assessment of ﬁrms' strategies. In fact, we found that if a
company engages in a strategy of exclusively using licensing agre-
ements to commercialize its inventions, the likelihood that in a
period of six years at least one of its licensing agreements will be
announced on a website or in a corporate report is quite high. Sim-
ilarly, if a company has launched products based on its inventions,
this information is likely to appear at least once on the materials we
collected on the company in the six years window of reference.

Furthermore, the invention commercialization strategies of ﬁrms in
our sample seem quite stable in the temporal window under inves-
tigation of our study. Hence, a cross-sectional perspective seems not
only a way to bypass the reliability problem that a panel approach

would cause, but also a more appropriate approach from the stand-
point of yearly data variability. The choice of using a cross-sectional
dataset is in fact in line with other studies in the ﬁeld such as Arora
and Gambardella (1990), Fosfuri (2006) and Gans et al. (2002).

Firms that had at least one EPO-granted patent that had been
applied for within the time frame 1996–2001 were included in the
sample. Using the patent application date and not the grant date
enables us to control for differences in delays that may occur in
granting patents after the application is ﬁled (e.g. Trajtenberg, 1990).
Furthermore, the protection of patent, once granted, is retroactive
and also covers the application period. Two motivations underlie the
decision to include in the sample ﬁrms with at least one patented
invention. First, patents represent an externally validated measure of
inventive activity (Belenzon and Patacconi, 2013; Griliches, 1990).
Second, patent protection reduces several frictions that typically
characterize the trading of inventions and has a huge effect on the
likelihood of selling or licensing an invention to other ﬁrms (e.g.,
Arora and Ceccagnoli, 2006; Gans et al., 2008). Hence including ﬁrms
with at least one patented invention allows a reliable identiﬁcation of
the ﬁrms “at risk” of engaging in invention trading activities.

Company names identiﬁed from the patent database have been
matched with company names from the Amadeus database (Bureau
van Dijk); hence both listed and non-listed companies were incl-
uded in our sample. Checks for misspelling of company names were
made and corrected. Subsidiaries at the parent level were then
tracked on Amadeus, in order to exclude from the sample all ﬁrms
that proved to be subsidiaries of large ﬁrms or joint ventures. Ama-
deus was then employed to discriminate between large and small-
medium ﬁrms. As this study is concerned with SMEs, ﬁrms were
retained in the sample only if they showed no more than 250
employees in at least one year within the timeframe 1996–2001
covered by this study. As indicated by the European Commission,
250 employees is the standard cut-off point to identify SMEs in the
European context (Recommendation 2003/361/EC).

These sample construction rules provided the master list that was
employed to collect the data that we used in this study. Data on
ﬁrms' vertical integration and invention trade were collected and
triangulated through an extensive search of press releases, including
Business & Industry, Factiva, Zephyr and the Securities Data Corpora-
tion (SDC) databases as well as from company web sites. In cases
where this information was not available from current companies'
websites, or if the companies' websites were no longer active, the
Internet Archive's Wayback Machine was used to visit the past
websites (Yadav et al., 2007). Data on ﬁrms' inventive portfolios
was collected using PatStat. Data on ﬁrms' age were obtained from
company websites and Internet archives. Amadeus was employed to
collect data on ﬁrms' proﬁtability and size across the whole time-
frame covered by this study. Finally, to obtain data on the strength of
the appropriability regime across the different European countries
included in this study sample, this paper referred to publications by
Park (2008) and Ginarte and Park (1997).

The ﬁnal sample included 551 ﬁrms, of which 20 were technology
specialists. Basic characteristics of industry afﬁliation and country of
origins of the ﬁrms included in our sample are displayed in
Tables 1 and 2.

Table 1 reports the industry afﬁliation for all ﬁrms in the sample
on the basis of US SIC codes. The table is organized to allow for an
immediate comparison between the distribution across industries of
the overall sample and the distribution across industries of the
technology specialists. Table 1 shows that the overall sample of our
European innovative SMEs tends to be distributed across high and
low tech industries, though a relatively larger majority of them
actually belongs to high tech sectors. In fact, the most represented
industries where European innovative SMEs are active are SIC 35
(31.4%, Industrial and Commercial Machinery and Computer Equip-
ment), SIC 34 (11.98%, Fabricated Metal Products, Except Machinery

G. Padula et al. / Technovation 41-42 (2015) 38–50 41


and Transportation Equipment); SIC 87 (9.07%, Engineering, Account-
ing, Research, Management and Related Services); SIC 36 (7.80%,
Electronic, Other Electrical Equipment and Components); SIC 28
(7.62%, Chemicals and Allied Products); SIC 38 (5.26%, Measuring,
Analyzing and Controlling Instruments; Photographic, Medical and
Optical Goods; Watches and Clocks) and SIC 30 (4.36% Rubber and
Miscellaneous Plastics Products). Overall, ﬁrms in these sectors
constitute more than 75% of the sample, and these sectors represent
predominantly—though not exclusively—high tech business activ-
ities. Firms in the remaining sectors are fragmented across a high
number of industries, where high tech business activities are much
less represented.

By replicating the same analysis for technology specialists, we
observe that technology specialists are relatively more concentrated

in high tech industries compared to the overall sample. In particular,
we ﬁnd that the great majority of technology specialists belong to SIC
87 (65%, Engineering, Accounting, Research, Management and
Related Services). Other SIC represented include SIC 28 (15% Chemi-
cals and Allied Products); SIC 34 (10%, Fabricated Metal Products,
Except Machinery and Transportation Equipment); SIC 27 (5%,
Building Construction General Contractors and Operative Builders)
and SIC 13 (5%, Oil and Gas Extraction). In order to understand in
more detail the activity of technology specialists, which constitute
the focus of our investigation, we closely investigated the inventive
proﬁle of the companies that became technology specialists. Con-
cerning the technological area of activity of technology specialists, we
ﬁnd that among the 20 technology specialists, 55% (11 companies)
are in the biotech technological ﬁeld. Among the remaining compa-
nies, 2 focus on the generation of mechanical technologies for the
aeronautic and automotive sectors, 2 are in IT/electronics (generating
magnetic tagging technologies and technologies for switchboards),
3 companies generate chemical technologies (generating respectively
thermoplastic elastomer technologies, composting technologies and
chemical active ingredients), 1 company generates toys and 1 com-
pany generates technologies for oil and gas offshoring.

Overall, technology specialists in our sample appear to be
concentrated in high tech sectors characterized by strong appro-
priability regimes. Moreover the majority of technology specialists
are in the biotech sector. This is in line with extant studies on MFT
indicating biotechnology as one of the ﬁelds where invention trade
has developed more in the last decades (Arora et al., 2001; Bianchi
et al., 2011). Indeed, research in this area indicates that—beginning
in the 1970s, several small R&D intensive biotech companies, mostly

Table 1
Industry afﬁliation: overall sample and technology specialists.

Description US SIC All ﬁrms in the
sample

Technology
specialists

Num % Cum % Num % Cum %

Industrial and commercial machinery and computer equipment 35 173 31.40 31.40
Fabricated metal products, except machinery and transportation equipment 34 66 11.98 43.38 2 10.00 10.00
Engineering, accounting, research, management, and related services 87 50 9.07 52.45 13 65.00 75.00
Electronic and other electrical equipment and components, except computer equipment 36 43 7.80 60.25
Chemicals and allied products 28 42 7.62 67.88 3 15.00 90.00
Measuring, analyzing, and controlling instruments; photographic, medical and optical goods; watches and clocks 38 29 5.26 73.14
Rubber and miscellaneous plastics products 30 24 4.36 77.50
Miscellaneous manufacturing industries 39 21 3.81 81.31
Business services 73 12 2.18 83.48
Primary metal industries 33 10 1.81 85.30
Furniture and ﬁxtures 25 10 1.81 87.11
Transportation equipment 37 9 1.63 88.75
Paper and allied products 26 7 1.27 90.02
Lumber and wood products, except furniture 24 7 1.27 91.29
Stone, clay, glass, and concrete products 32 6 1.09 92.38
Apparel and other ﬁnished products made from fabrics and similar materials 23 5 0.91 93.28
Agricultural production 01 4 0.73 94.01
Heavy construction other than building construction contractors 16 4 0.73 94.74
Textile mill products 22 4 0.73 95.46
Food and kindred products 20 3 0.54 96.01
Printing, publishing, and allied industries 27 3 0.54 96.55 1 5.00 95.00
Building construction general contractors and operative builders 15 3 0.54 97.10
Electric, gas, and sanitary services 49 3 0.54 97.64
Leather and leather products 31 2 0.36 98.00
Oil and gas extraction 13 2 0.36 98.37 1 5.00 100.0
Building materials, hardware, garden supply, and mobile home dealers 52 2 0.36 98.73
Mining and quarrying of nonmetallic minerals, except fuels 14 1 0.18 98.91
Construction special trade contractors 17 1 0.18 99.09
Petroleum reﬁning and related industries 29 1 0.18 99.27
Transportation by air 45 1 0.18 99.46
Transportation services 47 1 0.18 99.64
Apparel and accessory stores 56 1 0.18 99.82
Personal services 72 1 0.18 100.0
Total 551 20

Table 2
Country of origin: overall sample and technology specialists.

Country All sample Technology specialists

Number % Cum % Number % Cum %

Italy 300 54.45 54.45
France 73 13.25 67.70 1 5.00 5.00
Finland 38 6.90 74.60 3 15.00 20.00
Great Britain 37 6.72 81.32 8 40.00 60.00
Netherlands 29 5.26 86.58
Spain 25 4.54 91.12 1 5.00 65.00
Norway 19 3.45 94.57 3 15.00 80.00
Germany 16 2.90 97.47 1 5.00 85.00
Denmark 14 2.54 100.00 3 15.00 100.00
Total 551 20

G. Padula et al. / Technovation 41-42 (2015) 38–5042


US-based, entered the industry. Through time the sector in the US
consolidated towards a structure of small upstream technology
specialists (Arora et al., 2001), trading their inventions to down-
stream companies. The analysis of the characteristics of our sample
indicates that also in Europe, small biotechnologies ﬁrms tend to
represent a high portion of the ﬁrms operating in MFT.

In Table 2 we report the distribution of our sample across
countries. We note that 54.45% of the sample is composed by Italian
companies, 13.25% by French companies, 6.90% by Finnish compa-
nies, 6.72% by British companies and 5.26% by Dutch companies. The
remaining 13.43% is composed by Spanish, Norwegian, German and
Danish companies. We did not impose any geographic restriction in
our sample, which included all European ﬁrms available in the
Amadeus database having been granted at least 1 patent that had
been applied at the EPO ofﬁce in 1996–2001, and having no more
than 250 employees in the same period.

Therefore the distribution of our sample is to some extent also
informative of the geographical distribution of the population of
these types of ﬁrms. The predominance of Italian ﬁrms in our
sample is consistent with the evidence that the Italian economy is
essentially based on small and medium enterprises. For instance,
in 1991, 24.2% of manufacturing ﬁrms in Italy had less than 10
employees, compared to 13.3% in the UK and 7.8% in Germany
(OECD, 1997).

It is also interesting to note that when we move to the sub-
sample of technology specialists, the distribution indicates that 40%
of the sample is composed by British companies; another 45% is
equally distributed amongst Danish, Finnish and Norwegian com-
panies and ﬁnally, France, Spain and Germany constitute 5% of the
sample each. Britain, Denmark and Norway are the countries where
the ratio specialists vs. non-specialists is the highest (specialists
constitute, respectively, 22%, 21% and 16% of the companies from
those countries in the sample) compared to the other European
countries included in our sample.

3.2. Variables

3.2.1. Dependent variables
This study employs two dependent variables corresponding to two

distinct dimensions of ﬁrm performance: inventive performance and
proﬁtability. As already speciﬁed, in order to investigate ﬁrm inven-
tive performance, we refer to patent data. However, patents substan-
tially vary in their economic and technological value (Griliches, 1984;
Sreekumaran et al., 2011; Trajtenberg, 1990). Thus, patent citations are
a better indicator of the importance or value of patents than simple
patent counts (Frietsch et al., 2014; Galasso and Simcoe, 2011; Hall et
al., 2005; Hess and Rothaermel, 2011; Kelley et al., 2013; Trajtenberg,
1990). Following extant literature in this area, we measure ﬁrm
inventive performance using a citations-based index, i.e. weighting
each patent i of the ﬁrm by the actual number of citations (Ci) that it
subsequently received (Trajtenberg, 1990). In particular, for each ﬁrm
in the sample, the Inventive performance variable was computed as
Pn

i ¼ 1ð1þCiÞ, where n is the count of the EPO-granted patents that
had been applied for by the focal ﬁrm within the timeframe 1996–
2001 and Ci is the number of citations subsequently received by each
patent. Existing research suggests that the use of a citation-based
measure of inventive activities effectively captures the value of the
inventions developed by the ﬁrm (e.g. Galasso and Simcoe, 2011; Hess
and Rothaermel, 2011; Trajtenberg, 1990), hence the use of this
indicator is consistent with the theory developed in this paper.

In calculating this variable two important issues were taken into
account. First, citation counts are inherently truncated (Hall et al.,
2005; Rosenzweig and Mazursky, 2013). Patents continue to receive
citations for long periods of time, while we observe only citations up
to a certain point in time. Moreover, citations to patents applied for
in earlier time periods (that had a longer time window to be cited)

cannot be aggregated and compared with citations to patents
applied for more recently. In order to address this concern, for each
patent of each ﬁrm in our sample, we counted the number of
citations received in the ﬁrst three years after patent grant.

Second, inventors are likely to patent their inventions in multiple
patent ofﬁces. In these cases the same invention receives a different
patent number, although the two patents are “equivalent” from an
invention standpoint. In particular extant literature suggests that unlike
US patents, a large share of EPO patents are cited indirectly through
their non-EPO equivalent (Hall et al., 2007). A proper count of forward
citations should therefore also include citations received by patent
equivalents (Harhoff et al., 2006). In order to address this issue we used
the Patstat dataset to reconstruct patent families and track all citations
received by each patent of each ﬁrm in the sample, including those to
the patents non-EPO equivalent. This variable construction provided
the measure of invention performance employed in this study.

To assess ﬁrm Proﬁtability, we calculated for each ﬁrm in the
sample the average of the company's Return on Assets (ROA)
obtained within the timeframe 1996–2001.

3.2.2. Independent variable
Our independent variable indicates whether or not a ﬁrm had

been a technology specialist within the timeframe under investiga-
tion in this study. Consistently with our theory we use the expression
technology specialist to indicate a ﬁrm that commercializes its inve-
ntions exclusively as free standing entities as opposed to integrating
these inventions into products. To identify ﬁrms that have traded
their inventions we refer to ﬁrms who have engaged in invention
licensing activities, following a large body of prior research in this
area (e.g. Arora et al., 2001; Fosfuri, 2006; Somaya et al., 2011; Leone
and Reichstein, 2012). Accordingly, for each ﬁrm a dichotomous
variable, Technology specialist, was constructed and valued 1 if we
found evidence that, in the period 1996–2001, (1) the ﬁrm engaged
in licensing activities and (2) had not embodied its inventions into
products, 0 otherwise. For each of the companies in our sample, we
extensively searched different sources available (including Business &
Industry, Factiva, Zephyr and the Securities Data Corporation (SDC)
databases as well as company websites and specialized websites) to
identify announcements and reports mentioning the name of the
ﬁrm. We used the Internet Archive's Wayback Machine to visit the
version of the websites published in the period 1996–2001 (Yadav
et al., 2007). We read the full text of all announcements. To assess
whether the company had engaged in licensing activity we referred
to the content of the announcement. For instance, we identiﬁed as
technology licensing agreements those cases in which the announce-
ment: a) mentioned the transfers of inventions from the focal ﬁrm to
other ﬁrms; b) included words such as “license” or “licensing”; or c)
mentioned that the focal ﬁrm received a payment for the transfer of
its invention (e.g., referring to some speciﬁc licensing terms such as
“royalties” or “fees”). We also reviewed these sources to assess
whether the ﬁrm, in the six years of interest, had not embodied
the invention into products. To assess this, we referred to the same
sources mentioned above. In many cases, companies explicitly spec-
iﬁed their strategy on their website or in their reports. When this
information was not available, we searched the company website to
check whether any products were advertised. We also searched news
and specialized press to identify any announcements regarding
product launches. Finally, in some cases we used the presence of
manufacturing facilities to assess whether the company was active in
the product market.

3.2.3. Control variables
There is a recognized—although controversial—relationship bet-

ween a ﬁrm's size and its inventive performance (e.g., Berends et al.,
2014; Cohen and Klepper, 1991; Feldman, 1997; Koen, 1992; Freeman

G. Padula et al. / Technovation 41-42 (2015) 38–50 43


and Soete, 1997; Revilla and Fernandez, 2012; Rothwell and Zegveld,
1982; Rubenstein and Ettlie, 1983; Shefer and Frenkel, 2005). The size
of a ﬁrm may also affect its proﬁtability in different ways (e.g. Berc-
ovitz and Mitchell, 2007; Mas-Ruiz and Ruiz-Moreno, 2011). Indeed,
compared to large ﬁrms, small ﬁrms may be less able to exploit
economies of scale and scope, or be more ﬁnancially constrained (e.g.,
Teece, 1986) which may cause a negative effect on the cost of capital
(e.g. Apitado and Millington, 1992; Beedles, 1992). Although this study
sample is formed by SMEs, a variance across the size of the ﬁrms in
the sample is present and may affect the result of the statistical
analysis. To control for these effects, we calculated the variable Size for
each ﬁrm as the minimum number of employees between 1996
and 2001.

This study also controlled for ﬁrms' age. On one hand, age may
affect the ability of a ﬁrm to build a reputation as a competent, reliable
and trustworthy inventing ﬁrm, and consequently may have a positive
impact on the chance to have its inventions accepted by the market
and proﬁt (Danneels, 2002; Dowling and Helm, 2006; Katila, 2002).
On the other hand, age may create organizational inertia and so neg-
atively affect the ﬁrm inventive performance (Katila, 2002; Sørensen
and Stuart, 2000). To control for all these effects, this study employed
an Age variable that was constructed for each ﬁrm as a count of the
years elapsed from the ﬁrm's foundation year to 2001.

Characteristics of the ﬁrms' inventive portfolio may also have an
impact on ﬁrm performance. One of the more critical characteristics in

this regard is the generality of a ﬁrm's inventive portfolio, i.e. the
attitude of a ﬁrm to generate inventions more broadly applicable to a
wide range of markets (Bresnahan and Trajtenberg, 1995; Gambardella
and Giarratana, 2013; Hall et al., 2000; Valentini, 2012). By allowing
access to a wider array of markets, a more general inventive portfolio
may provide the ﬁrms with bigger market size, with positive effects on
proﬁtability. To control for these effects, we measured the generality of
the inventions according to the procedure employed by Trajtenberg
et al. (1997). This measure accounts for the extent to which citations
received by a patent are spread across different technological classes.
Speciﬁcally, for each patent i granted to the ﬁrms in our sample and
applied in 1996–2001, the patent generality measure was calculated
for each patent i, as follows: Patent generalityi¼1�

Pn
j ¼ 1 s

2
ij where s

2
ij

indicates the share of citations received by patent i from patents
belonging to patent class j, out of n patent classes. To account for any
forward citations truncation issues (Hall et al., 2005; Rosenzweig and
Mazursky, 2013) we calculated the measure by using the citations
received by each patent in the ﬁrst three years after patent grant. The
patent generality measure was then averaged at the ﬁrm level to
obtain a Firm invention generality variable.

We also control for the strength of the appropriability regime,
which might exert an important impact not only in determining the
strategy chosen by a ﬁrm to commercialize its inventions (Teece's,
1986) but also on the ﬁrm propensity to engage in invention
activities in the ﬁrst place (Dosi et al., 2006; Laursen and Salter,

Table 3
Descriptive statistics and pairwise correlationa.

Descriptive statistics and pairwise correlation

Variables Description Obs Mean SD Min Max 1 2 3 4 5 6 7

1. Inventive
performance

Pn
i ¼ 1ð1þCiÞwhere n is the

count of the EPO-granted
patents that had been
applied for within the
timeframe 1996–2001 and
Ci is the number of
citations subsequently
received by each patent

551 3.492 7.447 1.000 106.000 1

2. Proﬁtability Mean of the company's
Return on Assets (ROA)
obtained within the
timeframe 1996–2001

551 5.230 15.050 �81.043 57.600 �0.133*** 1

3. Technology
specialist

Dummy variable taking
value 1 is the ﬁrm engaged
in licensing activity and
did not sell products in the
period 1996–2001

551 0.036 0.187 0.000 1.000 0.067 �0.333*** 1

4. Size The minimum number of
employees of the ﬁrm
between 1996 and 2001

551 55.595 54.877 1.000 248.000 0.107** 0.110** �0.132*** 1

5. Age Count of the years elapsed
from the ﬁrm's foundation
year to 2001

551 37.031 34.305 1.000 394.000 �0.056 0.107** �0.152*** 0.343*** 1

6.Firm invention
generality

Firm level mean of Patent
Generalityi. Patent
Generalityi¼1�

Pn
j ¼ 1 s

2
ij

where s2ij indicates the

share of citations received
by patent i from patents
belonging to patent class j,
out of n patent classes

551 0.365 0.167 0.000 0.775 �0.024 0.013 �0.033 �0.03 �0.093** 1

7. Patent strength For each European country
included in this study
sample, average of the
1995 and 2000 patent
protection indices
obtained by Park's (2008)
study (normalized)

551 0.898 0.026 0.788 0.921 0.025 0.082* �0.089** �0.067 �0.042 �0.051 1

a *po0.1; **po0.05; ***po0.0.

G. Padula et al. / Technovation 41-42 (2015) 38–5044


2014; Teece, 1986). Hence, we controlled for the differences in the
strength of patent rights across the European countries represented
in this study sample by constructing a Patent strength control variable
on the basis of the index of patent protection developed by Park
(2008). This study was an update to 2005 and an extension to 122
countries of a previously developed patent protection index by
Ginarte and Park (1997) covering 110 countries and referring to a
time span from 1960 to 1990. In both studies, the index of patent
protection was constructed, per country per quinquennium—within
the timeframe 1960–1990 (Ginarte and Park, 1997) and the time-
frame 1995–2005 (Park, 2008)—on the basis of ﬁve categories of
patent laws: 1) extent of coverage; 2) membership in international
patent agreements; 3) provisions for loss of protection; 4) enforce-
ment mechanisms; 5) duration. For each country and for each period,
they then scored each of these categories a value ranging from 0 to
1 and then summed up to constitute an overall value of patent index
(per country per period) ranging from 0 to 5. To construct our
measure of Patent strength, per each European country included in
this study sample, we took the average of the 1995 and 2000 patent
protection index values. These results were then normalized so that
the strongest possible level of patent protection is equal to 1.

Finally, we included a set of Industry dummies in order to
control for industry (deﬁned at the level of one digit SIC code)
speciﬁc effects. Descriptive statistics and correlations are displayed
in Table 3.

4. Results

We ﬁrst estimated the impact of being a technology specialist
through an OLS regression (Table 4). Model 4.1 estimates the inventive
performance of the ﬁrm as a function of its choice to become a
technology specialist and a set of controls, and tests Hypothesis 1 that
technology specialist SMEs display a higher inventive performance
than vertically integrated SMEs—against the null hypothesis that the
inventive performance of technology specialist SMEs is not statistically
signiﬁcantly different from the inventive performance of vertically
integrated SMEs. Results of Model 4.1 show that the coefﬁcient of the
variable technology specialist equals to 0.386, which means technology
specialists display an inventive performance about 47% greater than
the inventive performance of vertically integrated ﬁrms (p value
o0.10). Model 4.2 estimates instead the proﬁtability of the ﬁrm as a
function of its choice to become a technology specialist and a set of
controls, and tests Hypothesis 2 that technology specialist SMEs dis-
play a lower proﬁtability than vertically integrated SMEs—against the
null hypothesis that the proﬁtability of technology specialist SMEs is
not statistically signiﬁcantly different from the proﬁtability of vertically
integrated SMEs. Results of Model 4.2 show that the coefﬁcient of
interest equals to �0.490, which implies technology specialists are
about 39% less proﬁtable than vertically integrated SMEs (p value
o0.01).

To account for the possibility that ﬁrms' choice to become a tech-
nology specialist is endogenous to their performance, we emp-
loyed a two stage least square model (2SLS) (Wooldridge, 2002). In
implementing this model, we have used the variable Technology speci-
alist as the dependent variable of the ﬁrst equation, and Inventive
performance and Proﬁtability, respectively, as the dependent variables
of the second stage. We selected the average proportion of technology
specialists in the same country and similar size of the focal ﬁrm as an
instrument for the variable Technology specialist. The rationale behind
this choice is related to the fact that some exogenous characteristics of
the country's institutional environment (for instance, the Intellectual
Property Right (IPR) protection or the extent of local competition) may
affect a SMEs' decision to become technology specialists, and this
inﬂuence varies according to the ﬁrm category size. Hence, in calc-
ulating this variable we have grouped SMEs in two groups: ﬁrms with

less than 38 employees and ﬁrms with over 38 employees, where 38
employees is the median number of employees of ﬁrms in our sample.

In Table 5a and b we report the results from the 2SLS. Model
5.1 estimates the ﬁrst stage equation, which shows how the average
proportion of technology specialists in the same country and similar
size of the focal ﬁrm is positively correlated with the likelihood of the
focal ﬁrm being a technology specialist. Model 5.2 estimates the
inventive performance of the ﬁrm as a function of its choice to become
a technology specialist and a set of controls. Model 5.3 estimates the
ﬁrm proﬁtability as a function of the ﬁrm choice to become a tech-
nology specialist and a set of controls. Results from bothModel 5.2 and
Model 5.3 largely conﬁrm the results of the OLS model and show that
being a technology specialist has a positive impact on the inventive
performance of a ﬁrm and a negative impact on ﬁrm proﬁtability,
consistent respectively with our Hypotheses 1 and 2.

A possible concern regards the small number of technology
specialists in our sample (20 over 551). To increase comparability
among technology specialists and vertically integrated SMEs (and also
to further address any endogeneity issue) we replicated the analysis
on a subsample which included technology specialists and a control
group constituted by an equal number of similar non-technology
specialists. In particular, we used a propensity score matching method
to select the group of vertically integrated ﬁrms, similar to the
technology specialist ﬁrms along several important dimensions which
could determine the ﬁrm choice to become a technology specialist
(Dehejia and Wahba, 2002; Hasan et al., 2011; Rosenbaum and Rubin,
1983), including ﬁrm age, size, ﬁrm invention generality, industry
afﬁliation and appropriability at the country level. For each technology
specialist, the closest matching company among the vertically inte-
grated ﬁrms was chosen. We replicated the OLS regression analysis
using this subsample of 40 companies. Results are reported in Table 6.
Model 6.1 estimates the inventive performance of the ﬁrm as a
function of its choice to become a technology specialist and the set
of controls, while Model 6.2 estimates instead the proﬁtability of the
ﬁrm as a function of its choice to become a technology specialist and
the set of controls. The results support both Hypotheses 1 and 2.

We also used a quantile regression to estimate the relationship
between the choice of being a technology specialist and the ﬁrm's
inventive performance and proﬁtability. In fact, the distributions of
the two dependent variables (Inventive performance and Proﬁtability)

Table 4
OLS regression estimationa, b.

Model 4.1 Model 4.2
Inventive performance
(Log)

Proﬁtability
(Log)

Technology specialist 0.386* �0.490***
(0.206) (0.124)

Size (Log) 0.147*** 0.006
(0.034) (0.020)

Age (Log) �0.109** 0.072***
(0.045) (0.027)

Firm invention generality
(Log)

�0.001 �0.031

(0.057) (0.034)
Patent strength (Log) 0.129 �0.096

(1.197) (0.719)
Industry dummies Included Included
Constant 0.671* 4.182***

(0.352) (0.211)
N. Observations 551 551
R squared 0.073 0.099

a *po0.1; **po0.05; ***po0.01.
b Since the minimum of the variable ﬁrm invention generality is 0, we added

0.01 to the variable before taking the logarithm; since the minimum of the variable
proﬁtability is �81.043, we added 81.053 (|min|þ0.01) to the variable before taking
the logarithm.

G. Padula et al. / Technovation 41-42 (2015) 38–50 45


are characterized by heavy tails. Other studies, whose dependent
variables were characterized by heavy tails, have employed a quantile
regression (Coad and Rao, 2008; Koenker and Bassett, 1978). Results
(available upon request) are again consistent with our theory.

5. Discussion

These results have important implications for practitioners and
researchers.

5.1. Implications to practice

The results from this paper enhance our understanding of the
viable strategies a small ﬁrm can choose for proﬁting from its
inventions. Our ﬁndings suggest that, because of the imperfections
that plague technology markets and of the low bargaining power of
ﬁrms lacking downstream assets (i.e., technology specialists), the
choice of simply selling inventions disembodied from products in the
MFT (as opposed to directly commercializing them to ﬁnal custo-
mers) might not be the best option for SMEs. To be sure, these results
reﬂect what happens on average across all industries in all European
countries. However, our research might suggest that the viability of a
technology specialist strategy would increase in those industries and/
or countries where the strength of the IPR regime or the tendency to
engage in trust-based behaviors limits the imperfections that hamper

the well-functioning of MFT. In this respect, future research might
better elaborate on the role of environmental and ﬁrm contingencies
that make technology specialist SMEs more proﬁtable than
vertically-integrated SMEs.

The results from this paper also raise implications for policy
makers. A key conclusion of past literature of MFT is that the diffusion
of technology specialists—and the consequent development of MFT—is
socially desirable because it facilitates the division of innovative labor
amongst small and large ﬁrms, which tend to have a comparative
advantage, respectively, in generating inventions and commercializing
them (e.g., Teece, 1986). However, our study shows that while
technology specialist SMEs have better inventive performance com-
pared to vertically-integrated SMEs, they also display worse pro-
ﬁtability, an outcome that over time might reduce the overall number
of ﬁrms that choose this strategy. Hence, our ﬁndings have relevant
policy implications, because they might imply that the number of
SMEs deciding to become technology specialists might be lower than
optimal.

For policy-makers, this emphasizes the importance of designing
mechanisms that reduce the high transaction costs that plague MFT,
in order to increase technology specialists' proﬁtability. For instance,
policy makers could favor the emergence of specialized intermedi-
aries—that is, ﬁrms providing services such as patent evaluation,
patent monetization and patent management, which might contri-
bute to solve some of the imperfections affecting MFT (e.g., informa-
tion asymmetries between buyers and sellers). The investigation of

Table 5
.

a Two stage least square regression estimation: ﬁrst stagea, b.

Model 5.1
Technology specialist

Instrumental variable 1.446***
(0.177)

Size (Log) 0.000
(0.007)

Age (Log) �0.025***
(0.009)

Firm invention generality (Log) �0.010
(0.011)

Patent strength (Log) 0.240
(0.249)

Industry dummies Included
Constant 0.101

(0.069)
N. Observations 551

b Two stage least square regression estimation: second stagea, b

Model 5.2 Model 5.3
Inventive performance (Log) Proﬁtability (Log)

Technology specialist 2.765*** �2.249***
(0.694) (0.437)

Size (Log) 0.167*** �0.008
(0.038) (0.024)

Age (Log) �0.014 0.003
(0.057) (0.036)

Firm invention generality (Log) 0.015 �0.044
(0.064) (0.040)

Patent strength (Log) 1.077 �0.797
(1.363) (0.859)

Industry dummies Included Included
Constant 0.237 4.078***

(0.514) (0.324)
N. Observations 551 551

a *po0.1; **po0.05; ***po0.01.
b Since the minimum of the variable ﬁrm invention generality is 0, we added 0.01 to the variable before taking the logarithm; since the minimum of the variable

proﬁtability is �81.043, we added 81.053 (|min|þ0.01) to the variable before taking the logarithm.

G. Padula et al. / Technovation 41-42 (2015) 38–5046


the role of intermediaries on the liquidity, transparency and efﬁ-
ciency of the MFT may constitute a promising new line of inquiry for
future research.

5.2. Implications to theory

This paper also has implications to theory. First of all, this study
better speciﬁes the idea, developed by previous contributions on
MFT (e.g., Arora et al., 2001), that the division of innovative labor
amongst small and large ﬁrms is optimal for the overall economy.
Indeed, our study shows that small ﬁrms that specialize in upstream
activities, as opposed to spreading their limited resources among
research and commercialization activities, generate more valuable
inventions. However, since technology specialists are relatively less
proﬁtable than vertically-integrated ﬁrms, only a few SMEs may
decide to specialize upstream. Thus, the potential social beneﬁts
associated with the generation of better inventions by technology
specialists might not be fully realized.

Second, this paper also has implications for research on ﬁrm
survival. Recent studies have demonstrated the role of inventive
performance on ﬁrms' survival (e.g., Ceﬁs and Marsili, 2006). By emp-
hasizing that technology specialists achieve a superior inventive perf-
ormance but that these ﬁrms experience worse proﬁtability, this study
calls for the need to improve our understanding of the relationship
between inventive performance and ﬁrm survival. For instance, future
research could analyze whether the positive relationship between a
ﬁrm's inventive performance and survival only holds for those ﬁrms
that have acquired the downstream assets needed to commercialize
their inventions to the ﬁnal customers.

Finally, the results from this paper might also have implications
for research on Venture Capital (VC). It is well established that
Venture Capital (VC) is crucial for small and young ﬁrms perfor-
mance (Bottazzi and Da Rin, 2002; Samila and Sorenson, 2011).
The results of this study would suggest that the VC role could be
particularly important when MFT are not well functioning, and so
vertical integration is a better option for small ﬁrms in order to
proﬁt from their inventions. Indeed, VC might provide ﬁnancially-
constrained small ﬁrms not only with the necessary resources to
invest in the acquisition of downstream assets (e.g., Stucki, 2014),
but also with the managerial expertise required to commercialize
their products to the ﬁnal customers (e.g., Robson and Bennett,
2000). Hence, an interesting avenue for future research could be

the exploration of the role played by VC as a potential substitute
for MFT.

5.3. Limitations

This study has some limitations. First, we only considered SMEs
inventive performance and proﬁtability, but other performance dim-
ensions could be evaluated. For instance, future studies could inves-
tigate whether the decrease in proﬁtability experienced by technol-
ogy specialists is actually traded off with superior growth outcomes
in terms of company size, or if the choice of being a technology
specialist is more appropriate to foster ﬁrms' adaptability in the face
of a changing environment. In this respect, it could be interesting to
replicate this study across different time windows in order to see
how ﬁrms using different strategies react to environmental and
macroeconomic shocks.

Second, our sample of technology specialists is quite limited. Two
issues might be considered in this respect, i.e. whether (1) the data
are representative of the overall populations of technology specialists
in Europe in the time period considered; (2) the results obtained are
reliable. With regard to the ﬁrst point, it should be noted that very
limited data are available publicly on the population of SMEs who are
technology specialists. Hence, we believe that the selected sample is
valuable because it allows us to provide an analysis on the behavior
of a relevant type of ﬁrms that otherwise could not be investigated.

Regarding the second point, when the independent variable does
not display relevant variation, there is a high risk of the results not
being statistically signiﬁcant (e.g., Wooldridge, 2002). Nevertheless,
our results are signiﬁcant. Hence we could argue that what we
presented was a conservative estimate of the real effect and that our
results could be even stronger if we had more variation in our main
independent variable, that is, if we had a larger number of technol-
ogy specialists.

Third, this study only focuses on small and medium ﬁrms. How-
ever, the choice between selling an invention in the MFT and emb-
edding it into a product to be sold to ﬁnal customers might in principle
also regard other players, like large ﬁrms or users. Future research
should therefore investigate to what extent and under what con-
tingencies these players sell their ideas to other ﬁrms rather than
selling their products to ﬁnal customers. In addition, we employ a
cross sectional perspective in our analysis. The investigation of the
same issue in a longitudinal perspective could potentially lead to

Table 6
OLS regression estimation (after matching)a, b.

Model 6.1 Model 6.2

Inventive performance (Log) Proﬁtability (Log)

Technology specialist 0.732** �0.738*
(0.329) (0.366)

Size (Log) �0.128 �0.103
(0.151) (0.168)

Age (Log) �0.110 0.319
(0.204) (0.227)

Firm invention generality (Log) 0.074 �0.105
(0.222) (0.247)

Patent strength (Log) �0.382 �2.489
(3.833) (4.260)

Industry dummies Included Included
Constant 0.720 4.140**

(1.606) (1.785)
N. Observations 40 40
R squared 0.240 0.212

a *po0.1; **po0.05; ***po0.01.
b Since the minimum of the variable ﬁrm invention generality is 0, we added 0.01 to the variable before

taking the logarithm; since the minimum of the variable proﬁtability is �81.043, we added 81.053 (|min|þ
0.01) to the variable before taking the logarithm.

G. Padula et al. / Technovation 41-42 (2015) 38–50 47


insightful results, and also offer the possibility to control for ﬁrm time-
invariant heterogeneity. However, we acknowledge that the panel data
on technology commercialization strategies of small private ﬁrms
represents a challenging task since these data are not available on
public or commercial dataset. Future research may consider the possi-
bility of using a survey approach in order to obtain some insight using
a longitudinal dataset.

Finally, this paper refers to the use of licensing agreements as
evidence of the fact that a ﬁrm pursued a “technology specialist”
strategy, i.e. it proﬁted from its inventions by licensing them in
disembodied form to other ﬁrms as opposed to incorporating them
into products, and investigates the implications related to the use of
this strategy on ﬁrm proﬁtability and inventive performance. It
would be very interesting for future research to also investigate the
antecedents of (i.e. the reasons behind) the ﬁrm's choice to use
licensing agreements. In addition to a monetary reason, there might
be other strategic reasons that led ﬁrms to license their inventions
such as entering a foreign market or setting an industry standard. In
this respect, whilst the use of secondary data allows conducting such
investigation only to a very limited extent, the use of surveys or in-
depth case studies could provide new relevant insights in this area.

6. Conclusion

This study investigates the effects of being a technology specialist
on ﬁrm inventive performance and proﬁtability. In particular, the
results from this paper show that technology specialist SMEs are
better performers than vertically-integrated small ﬁrms in terms of
inventiveness, but worse performers in terms of proﬁtability. Focus-
ing their attention on inventive activities allows technology specia-
lists to learn how to generate higher quality inventions faster than
vertically-integrated ﬁrms, due to the deeper and broader inventive
experience technology specialists have the chance to accumulate
(Arora et al., 2001; Katila and Ahuja, 2002; Yelle, 1979); and to their
ﬂexible organization structure (Henderson and Clark, 1990; Fosfuri
and Roende, 2009). However, the imperfections that plague the
functioning of MFT (Cockburn, 2007), and the higher bargaining
power of ﬁrms possessing commercialization assets vis-a-vis rese-
arch assets (e.g. Arora and Nandkumar, 2012; Teece, 1986), lead
technology specialists to experience a signiﬁcantly lower proﬁtability
than vertically-integrated ﬁrms.

This study has a number of practical and theoretical implications,
as already discussed in the previous section. One of the most inte-
resting contributions is probably that it emphasizes the existence of a
conundrum between what would be socially optimal—that is, the
division of innovative labor amongst large ﬁrms, specializing in down-
stream commercialization, and small ﬁrms, specializing in inventing—
and what would be privately optimal for small ﬁrms, which instead
have the incentive to integrate downstream to better capture the
economic returns from their inventions. Hence, this study calls for the
need to design and implement institutional mechanisms aimed at
addressing this conundrum and reconciling private with social bene-
ﬁts in the context of ﬁrms' inventive activity.

Acknowledgements

Wewould like to thank the editor, Jonathan Linton, and the two
anonymous reviewers for their very constructive comments
throughout the review process. We are also grateful to Alfonso
Gambardella for his very insightful guidance in the earlier versions
of this paper. The paper also beneﬁted from the comments of the
participants at the Academy of Management Conference (2010)
and the Strategic Management Conference (2010). Giovanna
Padula and Elena Novelli wish to gratefully acknowledge the PRIN

funding support (Grant 2006135451) from the Italian Ministry of
University and Research (MIUR). Elena Novelli also gratefully
acknowledges the ﬁnancial support of the Economic and Social
Research Council (ESRC) Future Research Leaders Scheme (Grant
ES/K001388/1).

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G. Padula et al. / Technovation 41-42 (2015) 38–5050


	SMEs inventive performance and profitability in the markets for technology
	Introduction
	Technology specialists vs. vertically-integrated SMEs: implications on inventive performance and profitability
	Method
	Sample and data
	Variables
	Dependent variables
	Independent variable
	Control variables


	Results
	Discussion
	Implications to practice
	Implications to theory
	Limitations

	Conclusion
	Acknowledgements
	References