Cooperation with scientific agents and firm s innovative performance

Transcription

1 Paper to be presented at the Internatonal Schumpeter Socety Conference 2010 on INNOVATION, ORGANISATION, SUSTAINABILITY AND CRISES Aalborg, June 21-24, 2010 Cooperaton wth scentfc agents and frm s nnovatve performance Jader Vega-Jurado INGENIO (CSIC-UPV) javega@ngeno.upv.es Lney Manjarrés-Henríquez INGENIO (CSIC-UPV) lmanhe1@ngeno.upv.es Antono Gutérrez-Graca INGENIO (CSIC-UPV) aguterr@ngeno.upv.es Ignaco Fernández-de-Luco INGENIO (CSIC-UPV) fernand@ngeno.upv.es Id: 282

2 Cooperaton wth scentfc agents and frm s nnovatve performance Jader Vega-Jurado INGENIO (CSIC-UPV) javega@ngeno.upv.es Lney Manjarrés-Henríquez INGENIO (CSIC-UPV) lmanhe1@ngeno.upv.es Antono Gutérrez-Graca INGENIO (CSIC-UPV) aguterr@ngeno.upv.es Ignaco Fernández de-luco INGENIO (CSIC-UPV) fernand@ngeno.upv.es Abstract Ths paper ams to analyse the effect of nteracton wth unverstes on frm s nnovaton output, measured as the degree of novelty of product nnovaton. The analyss s based on a sample of 3257 manufacturng frms actve n nnovaton actvtes located n Span. In the analyss we dstngush between two types of nteracton mechansms: cooperaton n nnovaton actvtes and outsourcng of R&D servces. Usng data from two waves of the Spansh nnovaton survey (2004 and 2007), we examne the effect of nteracton n 2004 on subsequent product nnovaton n The results show that nether the cooperaton wth unverstes nor outsourcng of R&D servces to these agents has a sgnfcant effect on product nnovaton. In other words, for Spansh manufacturng frms the acquston of knowledge from unverstes does not represent an mportant strategy to ntroduce new products nto the market. In contrast, cooperaton wth customers and the acquston of external R&D from other frms seem to be mportant nnovaton strateges, especally for those frms pursung more radcal nnovatons. 1

3 1. Introducton Many current economc theores on and approaches to nnovaton, to a greater or lesser extent, hold that ndvdual frms are seldom capable of nnovatng ndependently and that a frm s nternal techncal capabltes are nsuffcent to cope wth the challenges of the global market. Lkewse, studes n the feld of busness management ndcate that the search for new product deas, new forms of organzaton and/or solutons to exstng problems go beyond the frm s boundares n explorng avalable capactes n other frms or nsttutons. In theory, a wder and more dverse search strategy wll provde access to new opportuntes and enable the frm to buld new organzatonal competences based on the ntegraton of complementary knowledge sets from external agents (Teece, 1986; March, 1991). These approaches emphasse relatons wth external agents as an mportant strategy, whch allows the frm to learn from other organsatons, thereby ncreasng ts nnovaton capabltes. In ths lne, for nstance, cooperaton wth unverstes has receved specal attenton becomng one of the man objectves of the nnovaton polces ntroduced by many OECD countres. Ths government nterest n unversty-ndustry collaboraton also has been supported by a large body of economc research that hghlghts the benefts of the so-called scence-ndustry relatonshp, and descrbes unversty research as one of the engnes of ndustral nnovaton (Henderson et al., 1998; Mansfeld, 1998). In ths sense, a large body of lterature has been produced that dscuss the factors and motvatons that led some frms to use unverstes n ther nnovaton actvtes. The determnants of unversty-ndustry cooperaton, for nstance, have been explored n several emprcal works usng dfferent measures and takng nto account dfferent group of explanatory varables. Thus, the lterature on ndustral organzaton has focussed on the effects of dfferent types of spllovers on the propensty of the frms to cooperate (Belderbos et al, 2004a), whle the management lterature has taken a more resources based perspectve to analyse the relatonshps between unversty-ndustry collaboraton and a set of organzatonal capabltes (Mott and Schawald, 2003; Arranz and Fernandez., 2008). However, the queston whether the nteractons wth unverstes have a postve mpact on frm s nnovatve performance has relatvely receved less emprcal attenton. Albet a number of papers have explored ths aspect n the last years, many of these studes are hndered by a focus on a lmted number of technologcal envronments and ndustral sectors (such as n botechnology n developed countres). In addton, most of these studes have been prmarly concerned wth the effect of other nnovaton actvtes (nhouse R&D, for nstance) and rarely address the broader matrx of unversty-ndustry relatonshps that not only span a broad range of ndustral sectors, but can adopt dfferent channels (collaboraton, R&D outsourcng, lcensng, etc.). Ths paper ams to analyse the role of nteracton wth unverstes on ndustral nnovaton, usng a large-scale cross-ndustry sample of nnovatve manufacturng frms located n Span. Span s a technology follower country, demonstrated by ts scence and technology ndcator scores, whch are among the lowest n the EU. Another feature of the Spansh nnovaton system that s dstnctve s the great mportance of the publc sector, whch consttutes the prncpal source of knowledge. In 2004, ths sector, comprsed of unverstes and publc research organzatons, accounted for 45% of total natonal expendture on R&D and employed more than 76% of the researchers n Span. Ths s atypcal for Europe as a whole; n other European countres almost half of all 2

4 researchers are employed by prvate frms. In addton, cooperaton between frms and research centres n Span s lower than the European average accordng to the 4 th Communty Innovaton Survey (CIS-4). In order to nvestgate the role of the unverstes on ndustral nnovaton, we buld upon prevous studes whch have explored the effects of R&D cooperaton on frm s nnovatve performance usng data come from the natonal nnovaton surveys (Aschoff and Schmdt 2008; Amara and Landry, 2005; Belderbos et al., 2004b). However, we extend these works by consderng two types of strateges thorough whch frms draw from knowledge generated by unverstes: a) cooperaton n nnovaton actvtes, and b) contractng out of R&D actvtes performed by unverstes. In dong so, we attempt to ntegrate the study of the effectveness of unversty ndustry lnks nto a framework of analyss that consder two types of strateges for acqurng external knowledge: one focusng on cooperaton and another focusng on the outsourcng of R&D. Ths s an mportant pont takng nto account that whle there are a number of studes on the effect of ndustral cooperaton wth unverstes, few studes have nvestgated the relaton between outsourced research and nnovaton output. Another novelty of ths paper s that we use data on a large sample of nnovatng frms come from two waves of the Spansh Innovaton Survey (the 2004 and 2007 surveys). The use of ths dataset allows us to more accurately analyse the effect of the relatons wth scentfc agents on nnovaton by ntroducng tme lagged varables. Ths fact represents an mportant methodologcal aspect takng nto account that most of the studes conducted so far have used cross-sectonal data (referred only to one wave of the survey), whch rase several concerns to dentfy causalty relatons. The remander of the paper s organzed as follows: Secton 2 provdes a bref revew of the lterature; Secton 3 descrbes the methodologcal aspects of the emprcal study, the data, the measures of the varables, and the econometrc specfcatons; Secton 4 presents the results; and Secton 5 offers some conclusons from the study. 2. Lterature revew The study of the role of unverstes n ndustral nnovaton has become a favourte topc for analyss n the last years. In ths lne, a large body of theoretcal and emprcal lterature has been produced regardng to the determnants of unversty-ndustry collaboraton. The studes carred out n the frame of ndustral organzaton lterature, for nstance, have focused on the relatonshps between dfferent types of spllovers and R&D cooperaton. In contrast, the management lterature have examned the mpact of dfferent frm level characterstcs (sze, age of the frm, R&D ntensty) as factors that determne the propensty of the frm to collaborate wth unverstes. In addton, the studes conducted n ths feld have provded several nsghts about the motves and problems assocated to ths type of collaboraton. In general, the results of these studes suggest that the man motvaton to collaborate wth unverstes s the possblty to access to new knowledge and ncrease the frm s nternal capacty (Hagedoorn et al., 2000). Also, the studes ndcate that the use of unverstes as knowledge sources s more wdespread n scence-based technology felds (e.g. Klevorck et al., 1995). In ths sense, t has been suggested that the technologcal capablty of the frm (measured as nvestment n nternal R&D) s drectly related to the use of unverstes as knowledge source to nnovaton (Laursen and Salter, 2004; Mohnen and Hoareau, 3

5 2003). On the other hand, the evdence s more contradctory concernng the frm s sze, wth some studes reportng a postve relatonshp (Mott and Sachwald, 2003; Bayona et al., 2002) and some a non-sgnfcant one (Abramovsky et al., 2009). The nfluence of spllovers s usually found to be postve, especally those derved form scentfc agents (Belderbos et al., 2004a) Overall, although consderable research have been devoted to analyse the determnants of unversty-ndustry collaboraton, rather less attenton has been pad to analyse the effect of these nteractons on nnovaton performance. Ths ssue has been analysed n more recent studes, usng data from CIS-type surveys. For nstance, usng data on a large sample of Dutch nnovatng frms, Belderbos et al. (2004b) fnd that frms that cooperate wth unverstes n ther R&D actvtes have a hgher growth of sales due to new products than do frms that do not cooperate. Ths result s n agreement wth those of Lööf and Broström (2008) and Aschoff and Schmdt (2008), who fnd that cooperaton wth scentfc agents (unverstes or research nsttutons) has a postve effect on the sales share of products new to the markets, usng the Swedsh and the German communty nnovaton survey, respectvely. Amara and Landry (2005), usng the 1999 statstcs Canada Innovaton Survey, regressed the degree of novelty of product nnovaton on a varable ndcatng the use of scentfc agents (unverstes ncluded) as nformaton sources and found a sgnfcant and postve relatonshp. Specfcally, these authors found that the use of unverstes as nformaton sources ncreases the lkelhood of radcal nnovatons. The above studes all renforce the dea that unverstes are more lkely to stmulate frms advanced nnovatons than other external partners. However, there are also studes that, usng data from nnovaton surveys, come up wth dfferent conclusons. Mott and Sachwald (2003), for nstance, fnd that cooperaton wth publc nsttutons has not sgnfcant effect on the share of nnovatve products n turnover. Laursen and Salter (2004), usng the UK nnovaton survey, conclude that only a lmted number of frms draw drectly from unverstes as a source of nformaton or knowledge for ther nnovatve actvtes. These authors also ndcate that, n comparson to clents or supplers, unverstes are of modest mportance and suggest that the recent lterature may tend to overestmate the role of unverstes as drect knowledge sources for nnovaton. As can be seen the studes conducted so far on the effect of unversty-ndustry lnks on nnovaton have produced contradctory results. In general, the obtaned results are, to a great extent, dependent on the defnton of the varables, the estmaton technques and even the countres nvolved. Ths fact makes t necessary further research on the role of unversty n the nnovaton processes and ndcates that t may be a mstake to take for granted the effectveness of unversty-ndustry lnks. Bearng n mnd the above, ths paper ams to analyse the effect of nteracton wth unverstes on ndustral nnovaton n the context of the Spansh manufacturng frms. In comparson wth prevous research, ths study goes a step further by dstngush between two types of nteracton mechansms: cooperaton n nnovaton actvtes and outsourcng of R&D servces. The revew of the lterature reveals that the research n ths feld has concentrated on the relaton between R&D collaboraton and nnovaton output and less attenton has been pad to the role of other strateges to acqure knowledge from unverstes. Thus, whle there are several works nvestgatng the effect on R&D cooperaton or allances and jont ventures, lttle s known on the relaton between contract R&D (outsourcng of R&D) and nnovaton performance. In ths sense, we are specfcally nterested n answerng the followng questons: ) does the acquston of 4

6 knowledge from unverstes nfluence the nnovatveness level of the frm?, ) what strategy s more effectve to mprove the frm s nnovatve performance: R&D cooperaton or R&D outsourcng? ) are lnkages to unverstes more favourable for nnovaton than lnks to other agents? 3. Methodology 3.1. Descrpton of the database The emprcal analyss uses the data from two waves of the Spansh Innovaton survey, whch s based on the OECD s Oslo Manual. These data are collected by the Spansh Natonal Statstcs Insttute (INE) and placed at the dsposal of researchers by means of the Spansh Technologcal Innovaton Panel (PITEC). PITEC s organzed as a panel data set, wth a relatvely consstent data collecton methodology over a number of tme perods and has a wde sectoral coverage ncludng both manufacturng and servce sectors. The unt of analyss (.e. each observaton) s the sngle enterprse, whether part of a larger group or ndependent. Although data are avalable from fve successve waves of the Spansh Innovaton Survey (from 2003 to 2007), n ths paper we use specfcally the data correspondng to the 2004 and 2007 surveys. As t s well known several questons n the nnovaton surveys are referrng to a three years perod, especally those related to the nnovaton outputs (product and process nnovaton) and to the cooperaton wth external agents. Ths fact generates overlap between varables taken from consecutve surveys and even from surveys conducted every two years, whch could result n an overestmaton of some nnovaton strateges (cooperaton ncluded) n the absence of approprate correctons. For ths reason we have decded to use the data from 2004 and 2007 surveys, for whch there s not overlap between the key varables that we analyse. By dong so, for nstance, we can relate the cooperaton carred out durng the perod (taken from the 2004 survey) to the ntroducton of new products nto the market durng the perod (taken from the 2007 survey) 1. The use of lagged explanatory varables allows us to partly control for unobserved frms attrbutes that are relatvely constant over tme and to address econometrc endogenety ssues. Ths s not possble when the data are of cross-sectonal nature, whch makes more dffcult to dentfy causalty relatonshps. In the survey, frms are asked whether they have ntroduced a new product or process, or whether they had ongong or abandoned nnovaton actvtes durng the perod covered by the survey. A postve answer to one of these questons classfes them as nnovators. We used ths selecton crteron to restrct our analyss to the subsample of nnovators frms. Ths decson s manly drven by the desgn of the questonnare tself, because only the nnovator frms have to answer the full questonnare, ncludng those questons related to cooperaton wth external agents. In addton we only use frms observed for the two waves of the survey mentoned above and belongng to 1 We have not consdered the data from the 2003 survey because the samplng procedure for ths year has an mportant lmtaton. For reasons of opportunty and vablty, PITEC started wth only two samples n 2003: a sample of frms wth 200 or more employees and a sample of frms wth ntramural R&D expendture. Ths lmtaton was corrected from 2004 by ncludng a sample of frms wth fewer than 200 employees, external R&D expendture and no ntramural R&D expendture; and a representatve sample of frms wth fewer than 200 employees and no nnovaton expendture. 5

7 manufacturng sector, therefore, after deletng observatons wth mssng values, we were left wth a sample of 3,257 manufacturng frms Emprcal strategy and defnton of the varables The am of the emprcal analyss s to dentfy whether the relatons that the frm establshes wth unverstes (va cooperaton or outsourcng) affect ts nnovatve performance. To ths end we use the followng econometrc specfcaton: DEGINN + α Coop _ clent + α Coop _ tc + α = α 0 + α X + α + α Coop _ un + α Coop _ comp 10 1 R & D _ un + α nhouse _ R & D + α Equpment α Coop _ group + α Coop _ consul tan ts + α Coop _ pro 7 R & D _ + α 3 15 frms Tecno + α 12 + α Coop _ sup p 4 R & D _ other 8 (1) The explanatory varables used n the analyss are measured n a precedng perod. To be specfc, whle the dependent varable s taken from the 2007 survey, the explanatory varables related to frm s cooperatve behavour as well as the use of other nnovaton strateges are taken from the 2004 survey. Ths procedure allows us to control for the tme lags n the determnants and outputs of nnovaton process. In ths sense, and followng a smlar approach to the used by Belderbos et al. (2004b), we post that the nnovaton actvtes requre some tme to translate nto nnovaton output, therefore, R&D cooperatve and R&D outsourcng may show ther man mpact on nnovaton n the subsequent 3-years perod 2. The dependent varable used to measure the nnovaton output of the frm s degree of nnovaton(deginn). Ths varables takes three values dependng on the novelty of the product nnovaton developed: 0, f the frm dd not ntroduce any new or mproved products nto the market durng the perod ; 1, f the product ntroduced nto the market n that perod was new to the frm; and 2, f the product ntroduced nto the market was new to the market. Ths varable allows us to dentfy the factors that are relevant for the development of new products and dstngush whch among them have the greatest effect on the development of major nnovatons (products new to market). In ths lne, for nstance, several studes have emphaszed the mportance of knowledge sourcng from unverstes for frms pursung more radcal nnovaton rather than ncremental nnovatons (Amara and Landry, 2005; Kaufmann and Tödtlng, 2001; Tether, 2002) We use two types of explanatory varables: those related to the nteractons between frms and external agents, and those related to the use of other nnovaton strateges. All these varables are taken from the 2004 survey. To analyse the effect of cooperaton we 2 In addton, t s mportant to take nto account that when we use cross-sectonal data t s dffcult to make statements about drectons of causalty due to that the nnovaton strateges and the nnovaton outputs may be determned smultaneously or they may be jontly dependent on thrd factors, whch we do not observe (Maresse and Mohnen, 2010). 6

8 drew specfcally on the responses to the questons about cooperaton wth external agents for R&D and nnovaton actvtes durng the perod Although our man goal s to analyse the effect of ndustry collaboraton wth unverstes, we also control for the effect of other types of cooperaton. In ths sense, we defne eght dummy varables (one for each type of collaboratve partner ncluded n the survey) takng the value 1 f the frm ndcated that had been engaged durng n actve cooperaton wth the respectve partner. Besdes to analyse the relaton between unversty-ndustry cooperaton and nnovaton output, we examne the effect of another external knowledge sourcng strategy, namely R&D outsourcng. Followng ths, we drew on the responses to a queston on the Spansh nnovaton survey that asked frms to estmate the expendtures on external R&D servces pad to other agents durng the last year covered by the survey. The questonnare dstngushes between seven types of external supplers of R&D servces and two dfferent locatons (natonal and abroad): frms wthn the group, other frms, publc bodes, research assocatons, unverstes and prvate non-proft organzatons. Ths nformaton allowed the constructon of a dummy varable representng whether the frm has outsourced R&D actvtes to unverstes (located n Span or abroad) n the 2004 year. Addtonally, we use ths nformaton to bult two varables representng whether the frm has sub-contracted R&D actvtes to other frms (wthn the same group or not) or to others agents (publc bodes, research assocatons and non-proft organzatons). In the analyss we also control for the effect of other nnovaton strateges. Specfcally, we nclude n the model three varables related to a) the development of n-house R&D actvtes, b) the acquston of machnery, equpment and software, and c) the acquston of other external knowledge (purchase or lcensng of patents and nonpatented nventons, know-how, etc.). These strateges are measured usng dummy varables that take the value 1 f the frm has used the strategy durng the perod and 0 otherwse. Fnally, the X-vector ncluded n the model conssts of other frm level control varables, such as sze, dummy varables controllng for belongng to a group, sklls of the personnel, frm age, market orentaton and three dummes controllng for the technologcal ntensty of the sector n whch the frm operates. Table 1 presents the defnton of these varables. As we restrct our analyss only to nnovator frms a selecton problem exsts. To address ths potental problem we used two-part model (Mannng et al., 1987). In the frst stage of our analyss, we ran a general (selecton) model usng all avalable observatons and consderng the ndependent varable INNOVATOR to ndcate whether or not the frm was nnovator. Ths allowed us to calculate the probabltes of each frm becomng an nnovator, (PINN). In the second stage, we ran the man model n whch the dependent varable was the degree of novelty of product nnovaton. In ths stage, non-nnovator frms were dropped from the analyss, but the PINN varable was ncluded as an addtonal ndependent varable. Accordng to Haas and Hansen (2005), ths procedure s approprate when the dependent varable n the selecton model s observed rather than estmated, and more approprate than a Heckman selecton model snce the dependent varable n the man model s not contnuous 3. 3 The INNOVATOR varable used as dependent varable n the selecton model s a dummy varable that takes the value of 1 f the frm s an nnovator and 0 otherwse. Consstent wth prevous studes, we 7

9 Table 1. Descrpton of varables Varable Descrpton Scale of Measurement DEGINN Degree of novelty of product nnovaton ntroduced n : the frms ntroduced no new product nto the market 1: products were ntroduced that were new to the frm 2: products were ntroduced that were new to the market e SIZE Frm's sze Logarthm of Frm's number of employees Equpment Purchase of Machnery and equpment Dummy varable: 1 f the frm was engaged n acquston of machnery and equpment durng perod, and 0 otherwse Dummy varable: 1 f the frm was engaged n acquston of TECNO Acquston of ntangble technology n the form of external knowledge n the form of patents, non-patented patents, trademarks, software nventons, lcenses, dsclosures of know-how durng perod, and 0 otherwse Inhouse_R&D Coop_group Coop_Clents Coop_Supp Coop_Comp Coop_consultants Coop_un Coop_pro Coop_tec In-house R&D Cooperaton wth other frms of the same group n R&D and nnovaton actvtes durng the perod Cooperaton wth clents n R&D and nnovaton actvtes durng the perod Cooperaton wth supplers n R&D and nnovaton actvtes durng the perod Cooperaton wth compettors n R&D and nnovaton actvtes durng the perod Cooperaton wth consultants, laboratores and R&D frms n R&D actvtes and nnovaton durng the perod Cooperaton wth unverstes n R&D actvtes and nnovaton durng the perod Cooperaton wth publc research bodes n R&D actvtes and nnovaton durng the perod Cooperaton wth technology centres n R&D actvtes and nnovaton durng the perod Outsourcng of R&D actvtes to unverstes Dummy varable: 1 f the frm was engaged n nternal R&D actvtes durng perod, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse Dummy varable: 1 f the frm has cooperated wth ths agent, and 0 otherwse R&D_un Dummy varable: 1 f the frm has outsourced R&D servces to unverstes n 2004, and 0 otherwse R&D_frm Outsourcng of R&D actvtes to other frms Dummy varable: 1 f the frm has outsourced R&D servces to other frms n 2004, and 0 otherwse Dummy varable: 1 f the frm has outsourced R&D servces R&D_other Outsourcng of R&D actvtes to other agents to other agents (publc bodes, non-proft organzatons, research assocatons) n 2004, and 0 otherwse Hgh_skll Frm s human captal level Percentage of employees wth hgher educaton degree Start-up Frm s age Dummy varable: 1 f the frm has been establshed after 1 January 2002 Market Export orentaton Dummy varable: 1 f the frm sells ts goods or servces n other countres, and 0 otherwse GROUP The frm belongs to a group Dummy varable: 1 f the frm belongs to a group, and 0 otherwse ncluded as explanatory varables dfferent measures related to: frm sze, export orentaton, belongng to a group, as well as ndustry dummes. We also ncluded a number of varables measurng the obstacles to nnovaton (cost, lack of resources, lack of technologcal/market nformaton, no technologcal opportuntes, lack of demand for nnovatons). 8

10 Takng nto account that the dependent varable (DEGINN) n the man model can take three values, the estmaton technque we chose was multnomal logstcal regresson. Ths mples that the probablty of occurrence for each of the categores of response (J=0,1,2), s gven by: P j = e β X j j = 0 e β X j where X s the matrx of attrbutes of DEGINN and β k s a vector of m x 1 parameters. The reference category for the analyss s the one n whch the frm dd not ntroduce any new product nto the market durng the perod (J=0), and n consequence the parameters estmated can be nterpreted as follows: β X P e ) ( β 1 β 0 X 2 ( β 2 β 0 X = = e and = = e β 0 X β 0 X P 0 e Whch s the same as: P 1 Ln ( 1 0 ) P = β β 0 X and β X P e ) P 0 P e 2 Ln ( 2 0 ) P = β β 0 Consequently, the coeffcents estmated by the regresson model represent the margnal change n the logarthm of the odds of the assessment by the frm of the ntroducton nto the market of products that are new to the frm (mnor nnovatons) or new to the market (major nnovatons) over the category assessng the non-ntroducton of a new product, due to the margnal change n the explanatory varables. X 3.3. Descrptve statstcs Table 2 reports descrptve statstcs and smple correlatons of the varables used n the regresson analyss. As can be observed from table 2, 72% of the frms have carred out product nnovatons durng the perod, 28.8% of them have ntroduced products that are new to the frm, whle 43.2% have ntroduced products new to the market. Ths hgh percentage of nnovaton performers s not surprsngly bearng n mnd that the sample conssts only of nnovator frms. Furthermore, 14% of the frms have been engaged n actve cooperaton wth unverstes. In fact, ths s the second type of collaboraton more frequent between the frms of the sample after the cooperaton establshed wth supplers. These results concde wth the patterns ponted out by Castro and Fernández (2006), and demonstrate that, n general, Spansh frms engage n low levels of cooperaton, and that those frms that collaborate tend to choose scentfc nsttutons as partners rather than clents, consultants or other enterprses. By contrast, when we consder the R&D outsourcng, unverstes do not appear as the most usual suppler of these actvtes. In ths case, the frms tend more to outsource external R&D to other frms (29%) rather than to unverstes (11%). 9

11 Table 2. Descrptve statstcs and Spearman s correlaton coeffcents Mean SD DEGINN (1) 1,09 0,84 1 Coop_group (2) 0,09 0,29,077** 1 Coop_supp (3) 0,16 0,36,145**,299** 1 Coop_clent (4) 0,10 0,30,142**,293**,427** 1 Coop_comp (5) 0,06 0,24,081**,136**,229**,246** 1 Coop_ consultants (6) 0,11 0,31,089**,205**,342**,296**,205** 1 Coop_un (7) 0,14 0,35,105**,256**,317**,307**,253**,377** 1 Coop_pro (8) 0,07 0,25,103**,181**,226**,206**,219**,281**,406** 1 Coop_tec (9) 0,14 0,35,129**,260**,357**,354**,244**,359**,353**,361** 1 R&D_un (10) 0,11 0,31 0,029,121**,070**,129**,113**,115**,400**,185**,098** 1 R&D_frms (11) 0,29 0,45,057**,169**,154**,079**,094**,165**,083**,063**,067**,104** 1 R&D_other (12) 0,14 0,35,075**,109**,079**,129**,118**,177**,166**,203**,313**,187**,074** 1 nhouse_ R&D(13) 0,89 0,32,167** 0,004,051**,081** 0,019 0,028,101**,067**,062**,051** -,166** 0,004 1 Equpment (14) 0,49 0,50,119**,076**,127**,095**,065**,070**,059**,045*,063**,062**,098**,072** -,060** 1 Tecno (15) 0,15 0,36,093**,068**,131**,064**,104**,085**,093**,075**,074**,092**,130**,074** -0,025,219** 1 Hgh_tec (16) 0,12 0,33,042* 0,022-0,021,039* 0,032,036*,101**,044* -0,016,117**,055** 0,015,068** -0,012 0,025 1 Medun_tec (17) 0,38 0,48,093**,041* -0,011,065** 0,013-0,033 0,023 0,025 0,013-0,003 -,053** -0,03,089** -,059** -0,004 -,288** 1 Low_tec (18) 0,50 0,50 -,117** -,054** 0,025 -,088** -0,033 0,009 -,088** -,053** -0,002 -,073** 0,015 0,02 -,130**,065** -0,012 -,371** -,782** 1 tecno (19) 0,40 0,49,047**,362**,103**,084**,038*,075**,103**,074**,070**,081**,118**,047** 0,044*,073** 0,004 0,011-0,013 1 Sze (20) 4,21 1,28,040*,242**,151**,060**,058**,106**,109**,087**,093**,072**,117**,063** -0,026,099**,118** -,083** -,061**,113**,504** 1 hgh_skll (21) 18,32 17,76,118** 0,017 0,007,080**,062**,038*,121**,088**,039*,133** 0,008,055**,124** 0,011,041*,294**,131** -,318** 0,008 -,248** 1 Start-up (22) 0,02 0,12 0,024 0,021 0,001 0,007 0,01,037* 0,034 0,025 0,007 0,013 0,014 0,013-0,002 0,002 0,019 0,015-0,015 0,005-0,006 -,120** 0,029 1 Market (23) 0,84 0,37,056** 0,032,068**,049** 0,024,046**,067**,050**,063**,039* 0,018,055**,057**,050**,044* -0,008,071** -,063**,123**,227**,075** -,055** *** Sgnfcance at 1%. ** Sgnfcance at 5%. 10

12 Related to the use of other nnovaton strateges, we can observe that n-house R&D s the most frequent strategy. Almost 90% of the frm has carred out ths type of actvtes durng the perod. Furthermore, 49% of the frms have been engaged n acquston of machnery and equpment for nnovaton, and 15% have acqured other external knowledge (patents, know-how, etc.). The dstrbuton of cases by sectoral classfcaton s also presented n table 2. There are 1634 frms (50%) n low technology sectors, followed by 1231(38%) frms n medum technology sectors and 392 frms (12%) belongng to hgh technology sectors. These fgures ndcate an over-representaton of the hgh technology sectors n the sample as compared to the dstrbuton of the populaton of nnovators frms n Span (around 6%). The correlaton matrx also reveals some nterestng aspects. Cooperaton wth unverstes n R&D and nnovaton actvtes s postvely related to other types of cooperaton. Actually, all types of cooperaton consdered n the survey show a postve correlaton to each other. Ths result agrees wth prevous research showng that when a frm cooperates wth an external agent s more lkely to cooperate wth other agents. Also, there s an mportant correlaton between unversty collaboraton and R&D outsourcng wth unverstes 4. Ths fact mght rase some concerns wth respect to the possblty of multcollnearty consderng that we use smultaneously these varables n the analyss. However, we have made some checks excludng these varables one by one and the results do not change n any mportant way. Table 2 also shows sgnfcant correlatons between the dfferent nnovaton strateges and the sectoral classfcatons. The varables representng the assocaton wth unverstes (va cooperaton or R&D outsourcng) are postvely correlated wth the varable ndcatng that the frm belongs to hgh-technology sectors, but negatvely related to the varable representng low-technology sectors. Thus, the use of unverstes as a knowledge source for nnovaton seems to be more wdespread n sectors of hgher technologcal ntensty, as suggested by prevous studes (Hagedoorn, 1993; Wang, 1994). In fact, 24% of frms belongng to hgh-technology sectors have cooperated wth unverstes n nnovaton actvtes and 21% have outsourced R&D actvtes to unverstes, whle the same proportons for low technologcal ntensty frms are 11% and 9%, respectvely 5. Internal R&D actvty s also postvely related to cooperaton strateges, and especally to cooperaton wth unverstes. Ths latter result may be an ndcaton of the twofold effect of nternal R&D, that the greater the effort on ths actvty, the greater the ablty of the frm to dentfy and use sources of scentfc knowledge. Ths s not to say that frms that do not cooperate wth scentfc agents fal to perform n-house R&D, but rather that those that do cooperate are generally more actve n ths respect (Bayona et 4 Accordng to Hopkns (2000), a correlaton coeffcent lower than 0.30, albet sgnfcant, has such a small effect that t can be consdered as ndcatng lttle or no correlaton. In the range 0.30 to 0.50 correlaton can be consdered moderate, and n the range 0.50 to 0.7 the correlaton s hgh. Coeffcents hgher than 0.70 ndcate a hgh level of assocaton between the varables 5 F-tests show that these dfferences are sgnfcant. Furthermore, we have found sgnfcant dfferences between these two sectoral categores along other key parameters, such as n-house R&D, personnel wth hgher educaton degree, frm s sze and acquston of machnery and equpment. Our fndngs n ths sense are qute consstent wth the lterature, showng that the more technology-ntensty the ndustry, the more frequent the development of nternal R&D actvtes and the hgher the level of educaton of the personnel. In contrast, the frms n low-technology sectors tend more to draw on the emboded purchase of machnery and equpment. These results are avalable from the authors on request. 11

13 al., 2002). A smlar relaton exsts between n-house R&D and R&D outsourcng from unverstes. 4. Results The parameters estmated for the selecton model (not reported here for reasons of space) ndcated that the frm s export orentaton and dfferent factors related to obstacles to nnovaton have a sgnfcant effect on the probablty of beng an nnovator. On the bass of ths fst model, we calculated the PINN varable, whch s ncluded n the second-stage model. Table 3 below presents results of multnomal logstc estmaton of equaton (1). In general terms, the econometrc specfcatons consdered have an acceptable predctve power, and the Ch-squared value for the degrees of freedom suggests the rejecton of the null hypothess that all parameters, except the ntersecton, are equal to zero wth a sgnfcance level of 1% 6. The varables of nterest are the two channels through whch frms draw from knowledge generated at unverstes. In ths sense, the results show that nether the cooperaton wth these agents nor R&D outsourcng have a sgnfcant effect on product nnovaton. In other words, for Spansh manufacturng frms the acquston of knowledge from unverstes does not represent an mportant strategy to ntroduce new products nto the market. In the same way, cooperaton wth publc research nsttutes has not a sgnfcant effect ether. Although these results dffer from a relatvely broad body of emprcal lterature related to the role of scentfc agents n the ndustral nnovaton (See secton 2), agrees wth prevous studes demonstratng the lmted role of the cooperaton wth unverstes and publc research organsatons on the compettveness of Spansh manufacturng frms (Alvarez et al., 2005; Vega-Jurado et al., 2008). These results are also n agreements wth Laursern and Salter s (2004) fndngs whch showed that only a lmted number of frms draw from unverstes n ther nnovatve actvtes so ts relevance as drect knowledge source for nnovaton may have been overestmated. 6 We also conduct an ordered model to check the robustness of results. The results obtaned were qute smlar to those derved from the multnomal logstc regresson. However we decde to use the latter technque because t allows us to dentfy the effect of the nnovaton strateges on dfferent levels of product nnovaton. 12

14 Table 3. Results of the multnomal logt estmaton. New to the frm/dd not nnovate New to the market/dd not nnovate Independent varables Coeffcent (β) Exp (β) Coeffcent (β) Exp (β) ntercept -3,515-5,294 Coop_group 0,173 1,188-0,113 0,893 Coop_supp 0,062 1,064 0,077 1,08 Coop_clent 0,168 1,184 0,423** 1,527 Coop_comp 0,079 1,082 0,156 1,169 Coop_consultants -0,16 0,852-0,259 0,772 Coop_un -0,114 0,892-0,042 0,959 Coop_pro 0,326 1,386 0,271 1,311 Coop_tec -0,103 0,902 0,062 1,064 R&D_un -0,039 0,962 0,143 1,154 R&D_frms 0,046 1,047 0,226** 1,254 R&D_other 0,008 1,008-0,031 0,969 nhouse_r&d 0,674*** 1,962 1,325*** 3,762 Equpment 0,129 1,137 0,261** 1,298 Tecno 0,167 1,181 0,202 1,223 Hgh_tec 0,323* 1,381 0,379** 1,461 Medun_tec 0,375*** 1,455 0,305** 1,356 Low_tec 0b. 0b. tecno -0,026 0,974 0,04 1,04 Sze 0,229*** 1,257 0,309*** 1,362 hgh_skll 0,011*** 1,011 0,018*** 1,019 Start-up 0,164 1,179 0,258 1,295 Market 0,301** 1,351 0,368** 1,445 PINN Included Included R 2 : 0,14 Ch square (d.f): 417,58 (44) *** Sgnfcance at 1%. ** Sgnfcance at 5%. * Sgnfcance at 10%. The results also ndcate that the determnants of nnovaton vary dependng on the level of nnovatveness. For ncremental nnovaton ( products new to the frm ), the carryng on of n-house R&D actvtes s the only strategy that s shown to have a postve and sgnfcant effect. In contrast, for radcal nnovatons ( products new to the market ), besdes n-house R&D, the acquston of machnery and equpment, the cooperaton wth clents or customers, and the outsourcng of R&D servces to other frms have also a postve and sgnfcant effect. Two mportant ponts emerge from these fndngs. Frst, the external knowledge sourcng seems to be more mportant for frms pursung radcal nnovaton rather than ncremental nnovatons. Ths s not surprsng, snce the former usually nvolve greater techncal and market uncertanty, makng t necessary for the frm to cooperate or outsource R&D servces n order to spread the rsks of nnovaton actvty (Tether, 2002). Actually, our results further support the dea of workng closely wth users or customers can mprove the frm s nnovatve performance (Von Hppel, 1976, Rothwell, 1977; Lausen and Salter, 2006). Nevertheless, n spte of the mportance of 13

15 some external knowledge sources, our fndngs also ndcate that the nnovaton s a process that largely bulds on the frm s nternal capabltes. In ths sense, although certan types of external knowledge sourcng strateges (e.g. cooperaton wth clents or acquston of machnery) are assocated wth certan types of nnovaton, t does not mply that the ntroducton onto the market of new products necessarly depends on the frm s ablty to buld strong lnks wth external agents. In-house R&D actvty represents a strategc asset n the development of new products and, n addton, the developng and mplementng these actvtes s sgnfcantly more mportant than employng strateges nvolvng external partners 7. Regardng control varables the proporton of employees wth hgher educaton degree, frm s sze, export orentaton and the technologcal ntensty of the ndustral sector are postvely and sgnfcantly assocated wth both ncremental nnovaton and radcal nnovaton. These results are consstent wth prevous research showng that frms wth more resources, wth hghly-sklled personnel and operatng n sectors wth relatvely hgh R&D ntensty are more lkely to develop new products (Amara and Landry 2005; Mott and Sachwald, 2003;Vega-Jurado et al., 2008). However, whether or not the frm belongs to a group or whether the frm s a start-up were found to have no sgnfcant relaton to product nnovaton. Fnally, we conduct supplementary analyses n order to test whether our results could be drven by alternatve explanatons. A man assumpton n ths paper s that the nnovaton strateges show ther man mpact n a subsequent perod. Although ths s a plausble assumpton, we can not rule that some strateges (cooperaton ncluded) may have a faster mpact on product nnovaton. To address ths pont, we carred out addtonal checks usng a new set of explanatory varables ndcatng the persstence of the nnovaton strateges. In the case of unversty cooperaton, for nstance, the new varable takes the value 1 f the frm ndcated that has been engaged n actve cooperaton wth unverstes durng both and perods. A smlar procedure s used to defne the varables related to R&D outsourcng, n-house R&D, acquston of machnery and acquston of other external knowledge. The results of these analyses were generally consstent wth fndngs reported, especally wth those related to the effect of acquston of knowledge from unverstes. In addton, we conducted group analyss for the three sectoral categores: hgh, medum and lowtechnology sectors. Overall, the results related to the effect of unversty ndustry nteracton (va cooperaton or outsourcng) hold for each of the three groups separately (although some dfferences appear related to the effect of the other nnovaton srateges) 8. Another pont refers to the role of absorptve capacty. Cohen and Levnthal s (1989, 1990) ponted out that a frm s knowledge base enhances the effectveness of external technology sourcng n provdng the means to understand and utlze the nformaton acqured. On the bass of ths concept, t has been argued that not only do the frm s nternal efforts to create new knowledge encourage the use of external knowledge sources but they also ncrease the frm s ablty to explot these sources effcently n the development of new products and processes. Thus, the greater the nternal capabltes of the frm, the greater are the effects of the dfferent external knowledge acquston strateges on nnovaton performance. In order to test ths hypothess, we carred out 7 In-house R&D s the varable wth the greatest coeffcent for the two types of nnovatons analysed. 8 Thus, for nstance, the acquston of machnery and equpment and the outsourcng of R&D servces to other frms have a sgnfcant effect on low-technology frms, whle n-house R&D s the only strategy that s shown to have a postve and sgnfcant effect for hgh-technology frms. 14

16 addtonal checks, ncludng nteracton terms between the two types of knowledge sourcng strateges from unverstes (cooperaton and R&D outsourcng) and two proxy varables for absorptve capacty (n-house R&D and percentage of employees wth hgher educaton degree). Our results do not support ths hypothess (the nteracton terms are nsgnfcant n all cases), suggestng that frm s nternal capactes do not ncrease the effect of acquston of knowledge from unverstes on nnovaton. In other words, we do not found evdence of synergstc effects between nternal knowledge development and external knowledge sourcng form unverstes. 5. Dscusson and mplcatons The mportance of external knowledge sourcng from unverstes as a determnant of ndustral nnovaton has been emphaszed n the recent lterature wthn a range of theoretcal approaches. Lkewse, the promoton of unversty ndustry relatonshps ranks hgh on the current agendas of many governments across the OECD. The am of ths paper was to emprcally analyse whether ths type of nteractons really mpact the frm s nnovaton performance, consderng the case of a technology follower country and usng a large-scale cross ndustry sample. We focused on the lnk between the degree of novelty of nnovaton and two channels through whch the frm can draw knowledge from unverstes: 1) cooperatng n nnovaton actvtes and 2) contractng out of R&D servces. The results show that the hgher the technologcal ntensty of the sector n whch the frms operates, the hgher the level of cooperaton wth scentfc agents. Furthermore, the frms n these sectors tend to nvestment more n external R&D performed by unverstes and research nsttute than frms belongng to low-technology sectors. However, the results also show that, even n hgh technology sectors, the nteracton between frms and scentfc agents has no sgnfcant effect on product nnovaton, nether through cooperaton nor by acquston of external R&D. These fndngs suggest that unverstes and research organzatons rarely act as drect source of knowledge for the frm s nnovatve actvtes, at least n the context analysed by ths research. These results support prevous research nto ths area whch ponts out that rarely does the work of unverstes drectly translate nto new products or servces for ndustry (Pavtt, 2001), specally n context as Span where most frms ncludng nnovatve ones are at a lower technologcal level than ther nternatonal compettors (Molero and Buesa, 1996). In Span, as n other OECD countres, durng the last decade the governments have launched several programs to encourage closer relatons between frms and unverstes. These ntatves could explan why Spansh frms tend to cooperate more wth unverstes relatve to other external agents (e.g. clents, consultants). However, n the lght of our results, ths type of cooperaton does not seem to be orented towards the development of key actvtes for ther nnovaton processes. It s possble, therefore, that n the Spansh context the cooperaton between frms and scentfc agents s motvated more by access to funds through partcpaton n government sponsored programmes than by mprovng nnovatve capactes based on the ntegraton of complementary knowledge from external agents. However, ths s only a hypothess and further work s requred to establsh ths. 15

17 In contrast to the role of unversty collaboraton, the results show that the lnks wth clents represent an mportant strategy to develop radcal nnovatons. In a smlar way, the acquston of machnery and equpment and the outsourcng or R&D servces to other frms were found to have a sgnfcant relaton to novelty of nnovaton n frms. These results suggest that nnovatons embodyng more radcal changes n products requre knowledge for external agents, rather than ncremental changes that can be mplemented only wth nternal knowledge come from n-house R&D actvtes. However, these latter actvtes are, n any case, the most mportant determnant of product nnovaton. The polcy mplcatons dervng from these results are very mportant. Frst, due to the nnovaton output s largely dependng on n-house R&D actvtes, strengthenng the nternal capabltes of frms mght be more benefcal than the fosterng cooperaton per se. In ths sense, ndrect nterventons such reducng the costs nvolved n hghly qualfed personnel or promote the moblty of researchers from unversty to ndustry could be more effectve ntatves. Second, n order to ncrease the novelty of nnovaton would be also mportant to promote the lnks between frms and external agents. But, n ths latter case, government polces should go beyond smple support to unversty-ndustry relatons and place more emphass on broadenng external knowledge sourcng strateges. Fnally, some lmtatons to our study should be hghlghted. Frst, n ths paper we use only one measure of nnovaton: the degree of novelty of product nnovaton. In ths sense, t would be nterestng to study whether the nteracton wth unverstes has a sgnfcant effect on other nnovaton outputs (e.g. process nnovaton, patent applcatons). Second, we have restrcted ths analyss only to manufacturng frms. Gven the sgnfcance of servces n advanced economes, t would be useful to know whether the behavour of servce frms related to the acquston of external knowledge s smlar to, or dfferent from the behavour of manufacturers. Thrd, our study s restrcted to the Spansh context. In ths sense, further comparable studes n tme and space would be welcome. References Abramovsky, L., Kremp,E., López, A., Schmdt,T., Smpson,H Understandng cooperatve nnovatve actvty: evdence from four European countres. Economcs of Innovaton and New Technology 18(3), Alvarez, I., Fonfría, A., Marín, R The role of networkng n the compettveness profle of Spansh frms. ICE workng paper WP04/05. Insttuto Complutense de Estudos Internaconales, Madrd. Amara, N. and R. Landry Sources of Informaton as Determnants of Novelty of Innovaton n Manufacturng Frms: Evdence from the 1999 statstcs Canada nnovaton Survey. Technovaton, 25, Arranz, N., Fdez, J. Carlos The choce of partners n R&D cooperaton: An emprcal analyss of the Spansh frms. Technovaton 28,

18 Aschoff, B., & Schmdt, T Emprcal evdence on the success of R&D cooperaton Happy together? Revew of Industral Organzaton, 33, Bayona, C., García, T. and Huerta, E Collaboraton n R&D wth unverstes and research centres: an emprcal study of Spansh frms. R&D Management, 32, Belderbos, R., Carree, M., Dederen, B., Lokshn, B. and R. Veugelers, 2004a, Heterogenety n R&D Co-operaton Strateges. Internatonal Journal of Industral Organzaton, 22, Belderbos, R., Carree, M., Lokshn, B. 2004b. Cooperatve R&D and frm performance. Research Polcy, 33, Castro, E. and Fernández, I La I+D empresaral y sus relacones con la nvestgacón públca española, n: Sebastán, J. and Muñoz, E. (eds), Radografía de la nvestgacón públca en España, Bbloteca Nueva: Madrd. Cohen, W.M. and Levnthal, D.A Innovaton and Learnng: The two faces of R&D, The Economc Journal, 99, Cohen, W.M. and Levnthal, D.A Absorptve Capacty: A new perspectve on learnng and nnovaton, Admnstratve Scence Quarterly, 35, Haas, M. and Hansen, M When usng knowledge can hurt performance: Thevalue of organzatonal capabltes n a management consultng company. Strategc Management Journal, 26, Hagedoorn, J Understandng the ratonale of strategc technology partnerng: Interorganzatonal modes of cooperaton and sectoral dfferences. Strategc Management Journal, 14, Hagedoorn, John, Lnk, Albert N., Vonortas, Ncholas S Research partnershps. Research Polcy 29 (4 5), Henderson, R., Jaffe, A., Trajtenberg, M., Unverstes as a source of commercal technology: a detaled analyss of unversty patentng, Revew of Economc and Statstcs, 80, Hopkns, W.G New vew of statstcs, Accessed 12 January Kauffmann A., Tödtlng F Scence-ndustry nteracton n the process of nnovaton: the mportance of boundary-crossng between systems. Research Polcy 30, Klevorck, A.K., Levn, R.C., Nelson, R.R., Wnter, S.G., On the sources and sgnfcance of nterndustry dfferences n technologcal opportuntes. Research Polcy 24, Laursen, K., Salter A Searchng hgh and low: what types of frms use unverstes as a source of nnovaton?. Research Polcy, 33, Laursen, K., Salter, A Open for Innovaton: The role of openness n explanng nnovatve performance among U.K. manufacturng frms. Strategc Management Journal 27, Lööf, H. and A. Broström, 2008, Does Knowledge D_uson Between Unversty and Industry Increase Innovatveness?. Journal of Technologcal transfer, 33,

19 Maresse, J., Mohnen, P Usng nnovatons surveys for econometrc analyss. NBER Workng Paper Seres Mannng, W.G, Duan, N. and Rogers, W.H Monte Carlo evdence on the choce between sample selecton and two-part models. Journal of Econometrcs, 35, Mansfeld, E., Academc research and ndustral nnovaton: an update of emprcal fndngs. Research Polcy, 26, March, J.G Exploraton and explotaton n organzaton learnng. Organzaton Scence, 2, Mohnen, P., Hoareau, C What type of enterprse forges close lnks wth unverstes and government labs? evdence from CIS 2. Manageral and Decson Economcs 24, Molero, J. and Buesa, M Patterns of technologcal change among Spansh nnovatve frms: the case of the Madrd regon. Research Polcy, 25, Pavtt, K.L.R., Publc polces to support basc research: what can the rest of the world learn from US theory and practce? (and what they should not learn). Industral and Corporate Change 10, Rothwell, R., The characterstcs of successful nnovators and techncally progressve frms. R&D Management 7(3), Teece, D.J Proftng from technologcal nnovaton: mplcatons for ntegraton, collaboraton, lcensng and publc polcy. Research Polcy, 15, Tether, Bruce, Who co-operates for nnovaton, and why: an emprcal analyss. Research Polcy 31, Vega-Jurado, J., Gutérrez-García, A. Fernández-de-Luco, I and L. Manjarrés- Henríquez The Effect of External and Internal Factors on Frms' Product Innovaton. Research Polcy, 37, Von Hppel, E., The domnant role of the user n the scentfc nstrument nnovaton process. Research Polcy 5(3), Wang, J. C Cooperatve research n a newly ndustralzed country: Tawan, Research Polcy, 23,