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2014.02.13

WORKING

PAPER

"University knowledge, open innovation and technological capital in

Spanish science parks: Research revealing or technology selling?"

Manuel Villasalero

University of Castilla-La Mancha

manuel.villasalero@uclm.es

Submitted to the Journal of Intellectual Capital on February 13, 2014 (accepted for

publication on July 3, 2014).

Cite as: Villasalero, M. (2014), "University knowledge, open innovation and

technological capital in Spanish science parks: Research revealing or technology

selling?", Journal of Intellectual Capital, 15(4): 479-496. [DOI: 10.1108/JIC-07-2014-

0083].

University knowledge, open innovation and technological capital in

Spanish science parks: Research revealing or technology selling?

Manuel Villasalero Associate Professor Department of Business Administration University of Castilla-La Mancha Ciudad Real (Spain) Corresponding author: Manuel Villasalero manuel.villasalero@uclm.es The author would like to thank the Editor and anonymous reviewers for their constructive and helpful comments on the paper. Manuel Villasalero is an Associate Professor in the Department of Business Administration at University of Castilla-La Mancha (UCLM), Spain, from which he received his PhD. He has experience as a director in several firms and currently serves as vice chancellor for economics and planning at UCLM. His research interests include corporate strategy, knowledge management and human resource management. He has published articles in International Journal of Human Resource Management, Journal of Knowledge Management, Journal of the Knowledge Economy, Journal of Euromarketing, and others. Manuel Villasalero can be contacted at: manuel.villasalero@uclm.es

Purpose This study investigates the connection between university research and technological capital

developed by science park firms in order to elucidate whether the causal linkage is owing to

non-pecuniary research spillovers or pecuniary technology transfer activities.

Design/

methodology/

approach

Two publicly available surveys, one dealing with the research and transfer activities of 45

Spanish universities and another with the patenting activities of 44 Spanish science parks, are

matched in such a way that hypotheses can be tested using regression analysis.

Findings The patenting performance of science park firms is positively related to the competitive R&D

projects undertaken by the universities to which they are affiliated and negatively related to the

technology transfer activities carried out by those universities. These findings suggest that the

scientific knowledge produced by universities principally contributes to private technology-

based firms’ technological capital through non-pecuniary research spillovers, whereas the

pecuniary technology transfer agreements remain uncertain or may even prove to be

detrimental.

Practical

implications

Firms that are considering locating or remaining in a university-affiliated science park should be

aware that the university’s pecuniary orientation when managing its intellectual capital may

become a barrier as regards the firm filling its technological capital shortages. From a university

administrator perspective, the complementary or substitute role of technology transfer offices

vis-à-vis science parks should be considered in the light of the selling or revealing approach

adopted by the university in order to commercialize and diffuse potential inventions.

Originality/

value

This study contributes to existing literature by shedding light on the causal linkage between

university research and firm innovation, obtaining evidence in favor of an upstream, non-

pecuniary and revealing role of universities in support of the accumulation of technological

capital amongst science parks tenant firms.

Intellectual capital, knowledge transfer, knowledge spillovers, tacit knowledge, patents, licensing income,

contract research, scientific publications, academic research, technology transfer.

Empirical paper.

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University knowledge, open innovation and technological capital in

Spanish science parks: Research revealing or technology selling?

1. INTRODUCTION

Knowledge, creativity and innovation have become increasingly important for those

firms that wish to remain competitive in the marketplace (Schiavone and Villasalero 2013),

thus pushing them to tap into knowledge networks, either within or outside organizational

boundaries (Büchel and Raub 2002, Inkpen and Tsang 2005). Firms can rely on intra-

organizational knowledge networks such as those arising in multi-business firms (Villasalero

2014a), multinational corporations (Williams and Lee 2009), multidivisional organizations

(Nerkar and Paruchuri 2005), team-based organizations (Hoegl et al. 2003) or combinations of

the above (Hansen et al. 2005). On the inter-organizational level, firms may benefit from

geographically dispersed knowledge networks as is the case of international alliances and

partnerships (Hagedoorn 2002) or geographically bounded knowledge networks consisting of

countries (Villasalero et al. 2012), industrial districts (Boschma and ter Wal 2007), business

clusters (Giuliani 2007), innovative milieus (Todtling and Trippl 2007), regional innovation

systems (Cooke 2008), science parks (Koçak and Can 2014) and business incubators (Soetanto

and Jack 2013).

The studies dealing with the performance advantages of being located within a science

park (SCP) abound with predominantly mixed results, particularly when on-park firms are

compared with matched samples of off-park firms (Link and Scott 2014, Phan et al. 2005).

These findings run counter to the theoretically grounded claims concerning the value added

contributions of SCPs to tenant firms’ physical, financial and intellectual capital. With regard

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to the latter, it is argued that tenant firms may benefit from high quality human resources

(human capital), key technologies and innovation-related knowledge (technological capital)

and highly regarded corporate reputation (relational capital) derived from being located in an

SCP with preferential access to the university’s graduates, staff, research projects, patent

portfolios, public recognition and social legitimacy, aside from more the tangible advantages

of housing (physical capital) and venture capital (financial capital) (Massey et al. 1992). These

studies revolve around the tenant firms’ behavior but overlook the university side. In fact, the

behavior of the focal universities in SCPs remains a largely neglected issue in this field of

research (Link and Scott 2003).

This study explores the overlooked issue of how the focal university’s behavior

conditions SCPs tenant firms’ accumulation of technological capital. In particular, the

university strategy used to manage its technological capital is argued to impact on the tenants’

ability to improve their own technological capital. Taking an open innovation perspective

(Chesbrough 2003, 2006), SCPs and technology transfer offices (TTOs) are conceptualized as

alternate intermediaries through which research-based knowledge may become a potential

innovation, with SCPs favoring non-pecuniary knowledge spillovers and TTOs fostering

pecuniary transfer efforts. The university could therefore use the best known classification of

open innovation strategies (Dahlander and Gann 2010) in order to adopt either a “selling”

strategy based on R&D contracts and TTOs or a “revealing” strategy based on R&D projects

and SCPs. According to this open innovation theoretical framework, it is hypothesized that

selling hampers tenant firms’ accumulation of technological capital, whereas revealing

improves it.

The findings support the hypothesized relationships between the tenant’s accumulation

of technological capital and the strategy used by the university to manage intellectual capital.

The tenants’ patenting outcomes increase with university R&D projects and decrease with

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university R&D contacts and the size of the university TTO, thus suggesting that a selling

strategy is detrimental to tenants’ technological capital whereas a revealing strategy is, on the

contrary, beneficial to it. These findings are based on two matched samples of 44 SCPs and 45

universities in Spain that account for the vast majority of universities and SCPs.

This study contributes to the ongoing debate concerning the best the way in which

university research-based knowledge can be absorbed by private firms in order to foster

innovations for the wellbeing of society as a whole (Mowery et al. 2001, Nelson 2001). In the

Spanish case, the results suggest that knowledge spillovers through SCPs are preferable to

research transfer through TTOs, at least as regards the technological capital accumulation of

tenant firms. This study also makes theoretical contributions to the fields of intellectual capital

and open innovation by showing the new horizons that open innovation models may open up

with regard to furthering the understanding of firms’ intellectual capital accumulation in a

context specific situation, as is the case of SCPs.

2. THEORY AND HYPOTHESES

The underlying logic for SCPs is that «[…] universities have many brilliant people

making new discoveries but that they lack the means or the will to reach out to the market.

SCPs constitute a channel by which academic science may be linked to commerce. Thus SCPs

are there to promote, not ‘science’, but its application to technology» (Massey et al. 1992: 56).

More specifically, SCP tenant firms are argued to be in a position to build up intellectual capital

from three types of networks: (1) the ties with the universities (Colombo and Delmastro 2002,

Dettwiler et al. 2006, Fukugawa 2006, Löfsten and Lindelöf 2003, 2005); (2) the ties among

tenants (Chan et al. 2010, Colombo and Delmastro 2002, Koçak and Can 2014); and (3) the

ties between tenant firms and stakeholders outside the SCP boundaries (Löfsten and Lindelöf

2003, Chan et al. 2010).

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2.1. SCPs and intellectual capital

The three types of networks mentioned above allow on-park firms to accelerate the

accumulation of intellectual capital beyond the more visible benefits derived from premier

housing (physical capital) and available venture capital (financial capital). Their preferential

access to universities’ graduates and staff, research projects and patent portfolios, along with

public recognition and social legitimacy are levers for the accumulation of human,

technological and relational capital, respectively.

Universities are the recipients of talented people, explore the frontiers of scientific

knowledge, have cutting-edge technologies and enjoy widely held social legitimacy (Huggins

et al. 2008). On-park firms may benefit from these valuable assets as a result of their geographic

proximity to and collaborative climate with the university to which the SCP is affiliated

(Sorenson et al. 2006). Tenant firms are thus in a position to accumulate intellectual capital at

a greater pace than similar firms located elsewhere, which may in turn create and sustain

performance differentials between on-park and off-park firms. The evidence amassed to date

is, however, contradictory in this regard (Link and Scott 2014, Phan et al. 2005, Siegel et al.

2003b). Some studies have found that on-park firms outperform off-park firms in final

performance outcomes such as survival, growth and profitability (Westhead and Storey 1995),

whereas other studies have detected that negligible advantages are derived from SCP

membership (Ferguson and Olofsson 2004, Lindelöf and Löfsten 2003, 2004, Westhead and

Storey 1994, Westhead et al. 1995). Leaving aside the final performance outcomes, the existing

evidence on differentials between on-park and off-park firms in intellectual capital indicators

is also mixed.

The study of relational capital in SCPs has attracted considerable attention over the last

few years (Martínez-Cañas and Ruiz-Palomino 2010), but the most frequently studied

component of intellectual capital in SCPs is technological capital, which has been widely

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proxied through the tenant firms’ R&D activities and patenting behavior. Some studies have

found that on-park firms outperform off-park firms in patenting outcomes (Squicciarini 2008,

Yang et al. 2009) and research productivity (Siegel et al. 2003a), whereas the results derived

from other studies do not detect such differentials (Chan et al. 2011, Lindelöf and Löfsten

2002).

Various theoretical explanations have been advanced to account for the fact that SCP

membership does not always entail the advantages predicted in terms of performance outcomes

or intellectual capital accumulation, such as the excessive dependence on the SCP’s knowledge

network (Broekel and Boschma 2012, Howells 2012), the lack of heterogeneous and external

knowledge inflows for tenant firms (van Geenhuizen and Soetanto 2012), the unintended

dissemination of knowledge between tenant firms (Breschi and Lissoni 2001) or the frictional

assimilation of knowledge by tenant firms (Hansson et al. 2005, Schillaci et al. 2012). The first

two explanations are rooted in a social network perspective and can be summarized within the

problem of over-embeddedness (Andersen 2013) or, more generally, the issue of the optimal

level of network embeddedness (Andersen 2011) which also includes the possibility of very

low levels of networking and their corresponding disadvantages as regards under-

embeddedness. The last two explanations, which are based on knowledge and organizational

learning perspectives, revolve around the issue of knowledge stickiness and the problems linked

to knowledge transfer such as the unintended dissemination and defective assimilation of

knowledge (Villasalero 2013).

The aforementioned explanations only considers the SCP side of the coin and leave aside

the university side. In almost all studies in this field of inquiry the universities’ behavior is

simply overlooked in order to focus interest on the SCP dynamics as regards either the tenant

firms’ behavior or the SCP’s influence on them. Put in other terms, current research into SCPs

neglects how the knowledge source’s behavior impacts on the receiver’s knowledge stock. It

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is as if all the responsibility for the research-based knowledge transference lies downstream,

thus assuming that the upstream source has nothing to do but simply passively play its role of

knowledge provider. This biased research trajectory is evident when existing empirical studies

are classified according to the unit of analysis (as in Fukugawa 2006: 386), which reveals that

the predominant choices are the tenant firm or the SCP with only one study adopting the

university as the unit of analysis. In this unique case (Link and Scott 2003) the research

question is how having an SCP impacts on the university rather than the other way around,

which is the research question posed in this study.

Another related gap in the research on SCPs is that of the theoretical perspective adopted.

As indicated previously, social network, knowledge-based and organizational learning

perspectives are frequently used in the analysis of the upstream side of the phenomenon.

Surprisingly, and despite its notable development in recent years (Chesbrough 2003, 2006,

2011), no attempt has been made to apply an open innovation approach to the analysis of the

upstream side, that is to say, the universities’ behavior in innovation-related issues. The two

intended contributions of this study are therefore to bring universities back into the picture in

the research on SCPs and to do so by adopting an open innovation paradigm.

2.2. Universities strategies for open innovation

The open innovation paradigm advocates a more porous means to allow firms to manage

innovations in order to remain competitive in the marketplace (Schroll and Mild 2011). Rather

than vertically integrating the production and commercialization of innovations as was the rule

in the past, the open innovation perspective considers the advantageous separation of both

stages in such a way that firms can innovate by relying on outside technologies and ideas and

to make it possible for others to innovate by using the firms’ own technologies and ideas

(Villasalero 2014b).

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University research-based knowledge is an important external source of innovation for

firms in an open innovation context (West and Bogers 2014) since universities are major

producers of technologies and new ideas, while they are not interested in the commercialization

of the innovations that are based on them to the same degree. Despite the fact that universities

around the world are increasingly profiting from research-based knowledge in various ways

(Perkmann and West 2014), they are not, nor can nor should probably be, commercial

enterprises (Nelson 2001, Sterckx 2011). The imbalanced profile of universities as powerful

producers of innovation-related knowledge and poor marketers of commercial innovations

leaves room for private firms to tap into university knowledge as a key external source of

innovation. In fact, industrial innovation has always been based on academic research, which

has also laid the foundations for corporate and government research in some industries (Furman

and MacGarvie 2009). Overall, academic research accounts exclusively for more than 10% of

corporate innovations and plays a determining role in more than 20% of them, with peak

contributions being as high as 25% and 35%, respectively, in industries such as those that

produce drugs and medical products (Mansfield 1991, 1998).

The fact that academic research is an external source of innovation for private firms is

not new. What is new is the dramatic change in the mechanisms that allow innovating firms to

gain access to university research-based knowledge. Before the 1980s, universities hardly had

patents, licenses or spin-offs, and even the amounts of R&D contracts were quite modest. From

the 1980s onwards, the number of patents, licenses, spin-offs and R&D contracts expanded

exponentially around the world, first in the US and later in Europe and Japan. The reasons

behind this radical change in the way that universities manage their intellectual capital are

somewhat controversial, with some studies adducing normative changes in the intellectual

property system such as the Bayh-Dole Act in the US (Fabrizio 2006), others referring to the

maturity of some academic disciplines such as biochemistry or computer science (Mowery et

8

al. 2001, Nelson 2001), and others even attributing it to a more applied orientation in the recent

academic research carried out at universities (Cohen et al. 2002, Mansfield 1998). Leaving

aside the reasons behind these fundamental changes, this study is interested in their

implications for universities and, specifically, how universities confront the issue of managing

their intellectual capital and what, if any, the consequences are for private firms that are willing

to tap into university knowledge-based research. Using the widely known classification of

strategies for open innovation advanced by Dahlander and Gann (2010), according to which

the organizations that produce technologies in excess of those which can be commercialized

may opt for the pecuniary selling or non-pecuniary revealing of their technological capital, it

follows that universities have massively changed from revealing (before the 1980s) to selling

(from the 1980s onwards), and that this change has and currently entails considerable

implications for those private firms that are seeking to accumulate technological capital from

academic research.

2.3. Universities strategies and technology transfer

In accordance with its principles and academic missions (Link and Scott 2003, Sterckx

2011), a specific university may choose a strategy with which to manage its technological

capital along the continuum between the extreme positions of pure revealing and pure selling.

This choice has implications for the channels and conduits used by private firms to access such

technological capital and the predominant form that the technology transfer takes.

The paradigmatic technology transfer channels in a revealing strategy are those of

scientific publications and informal interactions. Academic scientists are accustomed to

sharing their findings in scientific publications and conferences in the open domain. Evidence

suggests that publications and reports represent by far the largest channel through which

industrial research benefits from public research, as indicated by 41.2% of industrial R&D

managers in a large US sample study. Other non-pecuniary industry-university channels that

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are highly related to publications in the open domain include informal interactions and

meetings and conferences, which have the second and third largest impact on industrial

research. What is more, the flow of recent graduates from universities to industry is also an

important non-pecuniary channel (Cohen et al. 2002). These findings are parallel to those

obtained from European firms, according to which publications, informal contacts, hiring and

conferences are the most important sources of industrial innovation from public research

(Arundel et al. 1995). Knowledge spillovers are the mechanism used by private firms to access

research findings, prototypes and techniques that are openly available in published research

and conferences and are complemented with informal contacts and the recent hiring of

university graduates (Salter and Martin 2001).

Alternatively, the paradigmatic technology transfer channels in a selling strategy are

those of licensing and contact research. In both cases, the private firms have to pay to access

university research-based knowledge, the only difference being whether the knowledge

transferred is protectable or non-protectable, respectively. Patents and licenses were considered

as significant transfer channels by more than 10% of US industrial R&D managers, whereas

contract research and consulting agreements were mentioned by more than 25% of them

(Cohen et al. 2002). In a parallel European study, contract research was rated as important by

36% of respondents (Arundel et al. 1995). Knowledge trade is the mechanism used by private

firms to access the research-based codified knowledge in the form of patents and licenses, or

tacit knowledge in the form of contract research and consulting agreements.

Not only do the transfer channels and mechanisms differ depending upon the revealing

or selling strategy adopted by universities in order to manage their intellectual capital, but so

do the organizational arrangements set up to intermediate the university-industry relationships.

A selling strategy requires the university to have a well-developed TTO in charge of the task

10

of protecting, marketing and brokering the research-based knowledge in order to generate R&D

contract revenues and licensing income (Caldera and Debande 2010).

A revealing strategy, however, involves organizational arrangements that promote

knowledge spillovers to interested firms. Research on knowledge spillovers has uncovered that

this type of knowledge transfer is unintended, untraded and geographically localized (Salter

and Martin 2001). Many studies indicate that the results of academic research do not flow

geographically in a regular manner, but tend to be locally concentrated since the tacitness of

knowledge requires face-to-face interactions amongst the people who embody the

technological knowledge to be transferred (Storper 1995). These interactions are usually

untraded, and this creates a social environment in which the reciprocal sharing of knowledge

between entrepreneurs and scientists flourishes, thus resulting in place-specific and context-

dependent technology transfer flows. Consistent with this view of localized knowledge

spillovers, Mansfield and Lee (1996) found that firms which are less distant from where

academic research occurs are more likely to be the first to apply the findings of this research

than more distant firms. SCPs are among the organizational arrangements that are designed to

promote and enhance knowledge spillovers between university research and industrial

innovation (Massey et al. 1992).

In accordance with the view described above, in which SCPs are typical organizational

arrangements for the fostering of knowledge spillovers and TTOs play the counterpart role for

knowledge trade, this study contends that the university contribution to the tenants’

technological capital accumulation cannot be adequately analyzed without taking the university

strategy for managing its intellectual capital into account as an endogenous variable (Table 1).

-------------------------------

Insert Table 1 about here

-------------------------------

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In particular, the adoption of a revealing strategy is predicted to be beneficial for the

tenant firms’ technological capital accumulation, whereas the application of a selling strategy

is expected to be detrimental. The following two hypotheses are thus put forward:

H1: A university’s revealing strategy has a positive impact on SCP tenant firms’

technological capital accumulation.

H2: A university’s selling strategy has a negative impact on SCP tenant firms’

technological capital accumulation.

3. METHODS

An exploratory testing of the hypotheses was designed by using Spanish SCPs and the

universities to which they are affiliated.

3.1. Setting and research design

Two publicly available databases were matched in order to bring university behavior

back into the analysis of the relationship between SCP membership and tenant firms’

technological capital accumulation. One database is compiled by the national association of

Spanish universities, formally called the Conference of Spanish University Rectors (CRUE),

and includes self-reported information on the research and knowledge transfer activities of

almost all Spanish universities (CRUE 2011). Another database is elaborated by the national

association of Spanish SCPs, formally called the Association of Science and Technology Parks

in Spain (APTE), which includes self-reported information on patents granted by the Spanish

Patent and Trademark Office (OEPM) to tenant firms located in almost all Spanish SCPs

(APTE 2011).

Both databases refer to the year 2010. Although it would have been preferable to

introduce a lag between university research and knowledge transfer activities and SCP tenant

firms’ patenting outcomes, it was impossible to do so because the latter information was only

12

available in 2010 and the former information before 2010 is not as complete as in 2010. The

use of a contemporary cross-section sample was therefore imposed by data availability.

3.2. Measures

The procedure used to match the two databases was straightforward, resulting in 44 SCPs

paired with the corresponding 45 universities to which they are affiliated. The dependent

variable is the tenant firm’s technological capital accumulation on the SCP database (APTE

2011) and the independent variables are the research and knowledge transfer activities

undertaken by the university to which the SCP is affiliated on the university database (CRUE

2011).

Technological capital accumulation

The patenting performance of SCP tenant firms was used as a proxy of technological

capital accumulation. Despite the known shortcoming of disregarding the accumulation of non-

protectable technological knowledge, it is a widely accepted measure of technological capital.

The final measure is the simple count of the number of patents granted by the Spanish Patent

and Trademark Office (OEPM) to the tenant firms sampled.

Revealing strategy

Three indicators were chosen to approximate the level to which a concrete university is

committed to a revealing strategy as regards managing its intellectual capital, these being

competitive funded research projects, scientific publications and PhD graduates. As indicated

above, major channels of university knowledge spillovers to private firms include scientific

publications and the recent hiring of university graduates, which are in turn based on the basic

research undertaken at the university (Arundel et al. 1995, Cohen et al. 2002, Salter and Martin

2001). Of the three, the most robust measure of knowledge spillovers in the Spanish university

system is that of competitive funded basic research, since the distribution of publicly funded

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research follows a rigorous and time-consuming procedure that produces highly efficient

allocations of funds. The remaining indicators are used with caution in this study, because the

number of scientific publications is a gross measure that is unadjusted to the quality of the

publication, whereas the number of PhD graduates could make little sense in this study given

the scant valuation of PhD degrees in Spain-based industry. They are, nonetheless, retained in

this study in order to ensure comparability with similar studies. These three measures were

taken from the self-reported figures contained in the university database (CRUE 2011).

Selling strategy

The university’s commitment to a selling strategy was measured by using license

revenues, contract research income and the size of the TTO. Given that Spanish universities

are just beginning to patent and obtain license revenues, contract research income is a much

better indicator of knowledge trade than license revenues in this regard, but the license revenue

variable was retained on the grounds of comparability issues. Similarly, TTOs are also

widespread organizational solutions that are adopted in the Spanish university system to

promote knowledge trade. These three measures were also taken from the self-reported figures

provided in the university database (CRUE 2011). The license revenues and contract research

income were measured in thousands of euros, while the size of the TTO was measured as the

natural logarithm of the full-time equivalent number of employees working in these offices

(Caldera and Debande 2010).

Control variables

Three variables were used to control for the varying impact of universities on SCP tenant

firms other than those derived from research and knowledge transfer activities. The public or

private property, the generalist or polytechnic character and the number of academic scientists

of the focal university were considered. The first two variables were dummy variables

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indicating whether the university is a private and/or polytechnic university, respectively. The

last variable accounts for the scientific size of the university by counting the number of

academic scientists. Again, the property and character of the university would be non-

meaningful because the numbers of private and polytechnic universities are very small in

comparison to other countries’ university systems.

3.3. Statistical analysis

Given that the dependent variable is a count measure (number of patents granted to tenant

firms), a negative binomial regression is preferable to an ordinary least square (OLS)

regression. The results of the OLS regression are, however, the same as those derived from the

best-fitted negative binomial regression (negative binomial parameter free and logarithm

linkage function). Since the statistics and goodness of fit tests of the OLS regression are more

familiar than those resulting from negative binomial regressions, the former results are

subsequently reported in this study in order to facilitate the interpretation of the findings.

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4. RESULTS

Multicollinearity is an issue, since some correlations are above 0.4, particularly those

representing the university size effect and the polytechnic university effect on the research and

knowledge transfer variables (Table 2).

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Insert Table 2 about here

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Only two independent variables significantly correlate with the dependent variable SCP

tenant firms’ technological capital accumulation, and these are the number of academic

scientists and the amount of competitive funding raised for basic research. With regard to the

correlations amongst the independent variables, the size effect is that the greater the scientific

base of the university, the greater the university research and knowledge transfer outcomes.

Both private and polytechnic universities have a well-differentiated profile. Private universities

in Spain are smaller, raise less competitive funding for research, publish less scientific findings,

educate less PhD graduates and have smaller TTOs than their public counterparts. Polytechnic

universities attract greater amounts of competitive funding for research, collect more licensing

revenues, have more contract research incomes and have larger TTOs than generalist

universities. The potential multicollinearity issue was confronted by inspecting the Variance

Inflation Factors (VIF) in the regression models.

The dependent variable technological capital accumulation is regressed in all the

variables in Model 1, whereas scientific publications and licensing revenues have been exclude

from Model 2 in order to improve the overall goodness of fit and to keep all the VIF values

below the 5.0 threshold above which regression estimators become unstable (Cohen et al.

2003). The results from both models are basically the same, with the exception of that of

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academic scientists, which attains marginally statistical significance in the best-fitted model

(Table 3).

-------------------------------

Insert Table 3 about here

-------------------------------

Partially consistent with the first hypotheses concerning the effects of a university

revealing strategy, the results show that the amount of competitive funding for basic research

raised by the university has beneficial effects on tenant firms’ technological capital

accumulation, in contrast with the unexpected negative effect that PhD graduates have on it.

The results conform with the second hypothesis which contends that a university selling

strategy is detrimental to SCP tenant firms’ technological capital accumulation, with significant

and negative signs for contract research income and TTO size.

5. DISCUSSION

Consistent with the literature review, the revealing strategy was proxied by using the

amount of funding raised for basic research, the number of scientific publications and the

number of PhD graduates. Consistent with the first hypothesis and in conformity with

expectations, the amount of funding raised for basic research is the best indicator of knowledge

spillovers in this study sample. As indicated in the methods section, the system used to allocate

funds to basic research in Spain produces near-efficient results and is thus a good indicator of

the level to which a university can contribute toward expanding publicly available scientific

knowledge to society. The number of scientific publications did not eventually enter the best-

fitted regression model, probably because the measure used failed to adjust for the quality of

the publications.

Contrary to the first hypothesis, the impact of the number of PhD graduates has a negative

impact on SCPs tenant firms’ technological capital accumulation, which is not, however, an

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unexpected result in light of the singularities of the Spanish labor market and university system.

In Spain, the fact of being a PhD graduate is of virtually no significance in the labor market,

even amongst high-tech firms. As a result, in the last decade most PhD graduates have followed

an academic career in universities and research centers rather than breaking into the labor

market and spilling leading-edge knowledge regarding scientific findings, modern techniques

and prototyping experience amongst employer firms. Rather than promoting knowledge

spillovers with PhD graduates, the situation is just the opposite in Spain; most talented people

who qualify for a PhD are retained within the university and research system and prevented

from going to industrial R&D laboratories. This does not mean that the education of PhD

graduates is detrimental to technological capital accumulation or innovation, but that the locus

in which these outcomes are collected have, to date, been principally universities, and that the

knowledge transfer mechanism based on knowledge spillovers has been fairly limited in this

regard. Future studies may investigate whether PhD graduates are more related to the

knowledge transfer mechanism based on the knowledge trade in Spain and what, if any, are the

effects of the recent incorporations of PhD graduates into the labor market as a consequence of

their limited remaining opportunities as regards following an academic career in the current

Spanish university system.

The selling strategy was measured by using licensing revenue, contract research income

and the size of the TTO. As expected, licensing revenue is still not a good indicator given the

limited experience of Spanish universities in this respect and the uneven distribution of licenses

and licensing income amongst them. With the exception of polytechnic universities, Spanish

universities are just starting to patent and sign licensing agreements, and are therefore quite

inexperienced in comparison with their German, Japan and US counterparts. In contrast,

contract research income and TTOs are well-developed phenomena in the Spanish university

system, thus appropriately representing the emphasis placed by a concrete university on selling

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its research-based knowledge. Consistent with the hypothesis, this emphasis is

counterproductive to the SCP tenant firms’ technological capital accumulation.

The findings deriving from this study have implications for research on SCPs, intellectual

capital and economics of science. The studies on SCPs’ consequences for tenant firms have

placed too much emphasis on the SCP side, whilst leaving the university side unexplored

(Fukugawa 2006). This study is the first to consider the impact of focal university policies on

tenant firms located in the SCP to which that university contributes (Link and Scott 2014). Put

in other terms, the recipients (tenant firms; SCPs) are not the only important entities as regards

inter-organizational knowledge transfer taking place, and the providers (research groups;

universities) are also at least as important as them. The type of multi-level approach adopted

in this study is illustrative of the new horizons that may be opened up by combining both sides

of the knowledge transfer process and different actors within each side.

Research efforts on intellectual capital and open innovation have remained surprisingly

isolated from one another, when they are in fact dealing with a common core issue which is the

access to and accumulation of valuable intangible resources. This study shows how the research

on the technological component of intellectual capital can be enriched by using an open

innovation perspective around the options of revealing and selling (Dahlander and Gann 2010).

Future studies may explore the consequences of building technological capital derived from

the remaining open innovation options based on sourcing and acquiring.

Although this study focuses on the limited-scope issue of technological capital

accumulation within SCPs, its findings are relevant to the so-called economics of science, i.e.,

how science dynamics impacts on innovation and economic development (Stephan 1996).

Central to the present study is the idea that knowledge transfer from universities to interested

parties in society can take at least two forms, such as knowledge spillovers and knowledge

trade, and that the former is sometimes preferable to the latter. Contrary to the movement which

19

advocates more applied research and a strong emphasis on technology transfer in universities,

the findings derived from the this study indicate that knowledge spillovers are in fact a

technology transfer mechanism, something that is usually overlooked by the aforementioned

advocates, and is that which renders benefits for private firms when coupled with appropriate

organizational solutions such as SCPs. There would appear to be no contradiction between

untraded publicly funded basic science in the open domain and an efficient knowledge transfer

to make university research-based knowledge a powerful driver of technological innovation

undertaken by private firms. In this respect, this study adds to the growing evidence-driven

literature that questions whether a strong emphasis on selling technology amongst universities

could better serve the interest of economic advancement than their performing the traditional

strategy of revealing technologies and retaining their dominant role in the upstream of the

science, technology and innovation value chain (Mowery et al. 2001, Nelson 2001, Sterckx

2011).

CONCLUSION

These results support the view held in this study that research on SCPs should consider

the innovation-related behavior of the university to which the SCP is affiliated. Given that

SCPs are organizational solutions that are designed to promote knowledge spillovers rather

than knowledge trade, it follows that a university strategy that stresses the untraded free

revealing of academic research has beneficial effects on the SCP tenant firms’ technological

capital accumulation. On the contrary, a university emphasis on the knowledge trade by selling

its research through well-developed TTOs hampers SCPs as regards meeting their objectives

of spreading the university knowledge-based research amongst tenant firms in order for them

to accelerate the process of technological capital accumulation.

20

This study has limitations owing to the secondary databases on which the testing of

hypotheses is based. Despite the advantage of relying on objective information from almost all

the universities and SCPs in Spain, the data imposed unavoidable restrictions such as those

derived from the contemporary cross-sectional design, the limited availability of control

variables, the lack of SCP variables other than patents granted to tenant firms and the crude

measures of some of the variables. Future studies may supplement the data used in this study

with additional secondary databases or even survey information collected from universities,

SCPs and tenant firms.

The findings of the study reported herein should be interpreted by bearing in mind that

the Spanish university system is, in many respects, singular, i.e., the low proportion of private

and polytechnic universities, the atypical profile of private universities, the very early phase

that universities are at in terms of patenting, licensing and spinning off, or the scant valuation

of PhD graduates amongst firms. Given that most of the studies on technology transfer are

based on the US, Central and Nordic European countries and Japan, the results derived from

this study provide a different picture of the phenomenon in comparison to those which can be

found in other studies and should, in this respect, be viewed within the context described.

Future studies may pursue comparisons of multiple countries in order to discern whether

technology transfer is notably conditioned by the features existing in each country.

21

TABLE 1

Open innovation strategies used by universities to manage technological capital

Key

Differences

Revealing

Strategy

Selling

Strategy

Nature of knowledge transfer Knowledge spillovers Knowledge trade

Logic of knowledge transfer Non-pecuniary Pecuniary

Knowledge transfer channels Scientific publications

Research projects

Ph.D. graduates

Contract research

Licensing income

Spinning off

Position on the value chain Upstream Downstream

Organizational arrangements Science parks (SCPs) Technology transfer offices (TTOs)

22

TABLE 2

Descriptive Statistics and Pearson Correlation Coefficients (n=47)

Descriptives Pearson Correlation

Variable Mean SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

1. Technological capital accumulation 3.043 3.155 1

2. Private university(1) 0.110 0.312 -.005 1

3. Polytechnic university(1) 0.060 0.247 -.031 -.090 1

4. Academic scientists 02,080.890 01,457.819 .315* -.386** .138 1

5. Competitive basic research funding 13,000.210 11,389.212 .386* -.346* .325* .794** 1

6. Scientific publications 921.880 883.727 .137 -.390* .128 .827** .670** 1

7. PhD graduates 165.560 167.064 .161 -.319+ .147 .890** .726** .776** 1

8. Licensing revenue 052.968 083.331 .060 -.167 .586** .461** .360* .424* .405* 1

9. Contract research income 08,549.510 12,328.976 .040 -.224 .642** .494** .688** .452** .388* .540** 1

10. Technology transfer office size(2) 0.793 0.295 -.057 -.428** .284+ .503** .510** .563** .503** .284+ .371* 1

** p<.01 (two-tailed); * p <.05 (two-tailed); + p <.10 (two-tailed).

(1)Dummy variable (Kendall and Spearman correlation coefficients provide similar results to those shown).

(2) Natural logarithm transformation to correct for skewness.

23

TABLE 3

OLS Regression (Dependent Variable: Technological capital accumulation)

Unstandardized coefficients with

standard errors in parentheses

Effect Variable Model 1

Full Model

Model 3

Best Model

Control

Constant 3.200

(.400)

3.200

(.390)

Private university .285

(.460)

.290

(.449)

Polytechnic university .351

(.653)

.466

(.550)

Academic scientists 1.510

(1.064)

1.664+

(.930)

Revealing strategy

Competitive basic research funding 2.900**

(.888)

2.792**

(.816)

Scientific publications .022

(.865)

PhD graduates -1.878+

(.965)

-1.861*

(.889)

Selling strategy

Licensing revenue .290

(.622)

Contract research income -1.821*

(.737)

-1.773*

(.698)

Technology transfer office size -.908+

(.524)

-.917+

(.498)

Goodness of Fit

R2 adjusted .244 .280

R2 .392 .390

F 02.653* 03.562**

N 047 047

** p <.01; * p <.05; + p <.10

24

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