The effects of knowledge sourcing strategies on science-based firms innovative performance: evidence from the Spanish manufacturing industry

Transcription

1 INGENIO WORKING PAPER SERIES The effects of knowledge sourcng strateges on scence-based frms nnovatve performance: evdence from the Spansh manufacturng ndustry Jader Vega-Jurado, Antono Gutérrez-Graca, Ignaco Fernández-de-Luco Workng Paper Nº 2008/12

2 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 The Effects Of Knowledge Sourcng Strateges On Scence-Based Frms Innovatve Performance: Evdence From The Spansh Manufacturng Industry 1 Jader Vega-Jurado 2, Antono Gutérrez-Graca, Ignaco Fernández-de- Luco Abstract Ths paper provdes emprcal evdence on the effect of the external knowledge sourcng strateges adopted by frms, on the development of both product and process nnovaton, and assesses to what extent ths effect s nfluenced by the frm s nternal technologcal capabltes. Our emprcal nvestgaton s based on a sample of more than 600 scence-based frms actve n nnovaton actvtes taken from the Spansh Innovaton Survey We fnd that the effects of the knowledge sourcng strateges dffer sgnfcantly across nnovaton types (product or process nnovaton). In addton, our results suggest that there are possble substtuton effects between external sourcng strateges and nternal R&D. Thus, the greater the frm s nternal technologcal capablty, the less mportant s the cooperaton wth scentfc agents n determnng product nnovaton. 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 1 Ths work has been presented n the GLOBELICS 2008 Conference: New nsghts for understandng nnovaton and competence buldng for sustanable development and socal justce. 2 javega@ngeno.upv.es (correspondng author) 1

3 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 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 goes 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). There s sold emprcal evdence that the use of external knowledge sources s both an mportant theoretcal ssue and a growng phenomenon. In most OECD countres, for nstance, the share of busness expendture on external R&D has gradually ncreased snce the 1980s. In countres such as the UK and Germany, busness expendture on external R&D doubled n proporton to total expendture on R&D, over a ten year perod (Howells, 1999; Bönte, 2003). Another clear ndcaton of the hgher use of external knowledge sources s the ncreasng number of nter-frm partnershps. In ths respect, Hagedoorn (2002) shows that the number nter-frm R&D partnershps recorded n the MERIT-CATI database, ncreased from 10 durng most of the 1960s to nearly 600 by the end of the 1990s. These trends have been accompaned by a decrease n the number of nternal R&D departments and an eroson of the strategc advantage of nhouse R&D actvtes (Chesbrough, 2003). Nevertheless, some researchers have warned about the rsk of overestmatng the role played by external knowledge sources, argung that n many ndustres, nnovaton efforts are not only made by frms themselves, but are n-house generated (Nelson, 2000). The studes conducted by Oerlemans et al. (1998) n the Netherlands and Freel (2003) n the UK, show that the frm s nternal resources are the man determnants of ther nnovaton performance, and that the creaton of external networks has only a lmted mpact. Some authors have even suggested that n attemptng to decentralze and outsource R&D actvtes frms may weaken ther core competences (Coombs, 1996). Lnked to these trends, a theoretcal and emprcal lterature has developed on the factors determnng external knowledge acquston and ts effects on frms nnovatve performance. Most of ths lterature focuses on the choce between external sourcng and nternal development, the so-called make or buy decson (Veugelers and Cassman, 1999; Beneto, 2003). A tradtonal approach to the analyss of ths ssue derves from 2

4 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 transacton cost theory, whch suggests that n the presence of asset specfcty, uncertanty and opportunstc behavour, transactons take place more effcently and herarchcally wthn the frm than va the market (Wllamson, 1985). Followng ths lne of nqury, external knowledge sourcng and n-house R&D are consdered as substtutes, and n consderng cost and rsks, frms opt for ether a make or a buy strategy. The later resource-based approach, however, emphaszes that competency development requres a frm to have an explct polcy on the use of external knowledge sources as an opportunty to learn, rather than as a way to mnmze costs (Robns and Wersema, 1995). Ths suggests that external knowledge should be used to complement rather than substtute for nternal R&D. Analyss of the complementarty between nnovaton strateges was extended by Cohen and Levnthal s semnal work (1989, 1990). They suggested that n-house R&D actvtes played the dual role of generatng nnovaton and mprovng the frm s absorptve capacty, that s, the ablty of the frm to dentfy, assmlate and explot the knowledge generated by compettors and extra-ndustry sources (Cohen and Levnthal, 1990). Thus, the greater the nternal capabltes of the frm, the greater are the effects of the dfferent external knowledge acquston strateges on nnovaton performance. Based on the concept of absorptve capacty, several studes followed on the relatonshps between external and nternal know-how or, n strategc terms, between external knowledge sourcng and n-house knowledge development. Arora and Gambardella (1990, 1994), for nstance, found that frms that conduct more R&D have larger numbers of external lnks (equty partcpatons, contractual and non contractual agreements, acqustons) amed at acqurng technology, whle Veugerless (1997) found that external sourcng can often stmulate nternal R&D actvty, at least for frms wth R&D departments. Thus, there s emprcal evdence on the mportance of the frm s knowledge base for enablng the frm to dentfy and acqure external knowledge, and vce versa, on the role of externally acqured knowledge n enhancng nternal R&D actvtes. On balance, however, the lterature s not conclusve about the complementarty between nternal and external technology sourcng wth respect to the mpact on frm s nnovatve performance. Such complementarty or synergy s assumed to exst f the mplementaton of one strategy ncreases the margnal returns from another (Mlgrom and Roberts, 1990). In ths lne, there has been lttle emprcal analyss and the fndngs 3

5 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 from the few studes conducted are mxed. Laursen and Salter (2006) examne the relatonshps between the number of the frm s external knowledge sources (whch they term external search breadth ) and ts nnovaton performance. They fnd an nverse U- shaped relatonshp, ndcatng that the breadth of the frm s external search strateges s benefcal only up to a certan level. They also fnd that nternal R&D negatvely moderates the relatonshp between external knowledge sources and nnovaton performance, suggestng the exstence of a substtuton effect between openness to external search actvtes and nternal R&D. In contrast, Cassman and Veugelers (2006) fnd that n-house R&D and external knowledge acquston are complementary wth respect to the mpact on nnovatve performance. In ths paper, we follow a smlar approach n analysng the effect of dfferent external knowledge sourcng strateges on frm s nnovatve performance and explorng the relatonshps between these strateges and n-house R&D. Extendng Cassman and Veugelers (2006), we nvestgate the effect of two strateges for acqurng external knowledge (buyng and cooperatng) and two types of external sources (ndustral agents and scentfc agents). Ths dstncton s mportant as knowledge from these types of agents tends to be dfferent n nature and therefore may not only serve dfferent purposes but may also relate dfferently to a frm s nternal capabltes. For nstance, Cohen and Levnthal (1990) suggest that the knowledge drawn from extra-ndustry sources such as government and unversty labs, s typcally less targeted to a frm s requrements and prortes than that drawn from materals and equpment supplers, and therefore requres more expertse from the frm to explot t effcently. In addton, we nclude n our analyss acquston of technology emboded n machnery and equpment as another external knowledge sourcng strategy. Although most of the exstng studes on the effects of external knowledge sourcng focus on dsemboded knowledge acquston strateges (R&D contractng or lcensng agreements), the role of purchase of machnery and equpment n nnovaton s by no means neglgble (Evangelsta, 1999). Fourth Communty Innovaton Survey (CIS-4), for nstance, shows that half the European frms reportng product or process nnovaton do not conduct nhouse R&D, whle approxmately 70% engage n machnery, equpment and software acquston. The analyss of external knowledge sourcng strateges uses frm level data from the Spansh nnovaton survey. Specfcally, our emprcal nvestgaton rests upon a sample 4

6 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 of 654 scence-based frms (Pavtt, 1984). We focus on ths sectoral category for two reasons. Frst, ths sectoral category ncludes those frms for whch the relatve mportance of nternal and external knowledge sources s hgher. Pavtt (1984), for nstance, suggested that n scence-based frms the man sources of knowledge are both the frms nternal R&D actvtes and scentfc research carred out by unverstes and publc research nsttutons. Lkewse, Klevorck et al. (1995), ndcated that the hgher the level of technologcal opportunty n an ndustry, the hgher the frm s ncentves to draw on external knowledge sources. Second, as Cassman and Veugelers (2006) suggest, a frm s relance on more basc types of know-how (.e., the use of unverstes and research centres as nformaton sources for nnovaton) affects the degree of complementarty between nnovaton strateges. In ths sense, t s expected that n ths sectoral category the complementarty between external knowledge sourcng and nternal knowledge development, f exsts, s more clearly dentfable. Span s a technology follower country, demonstrated by ts scence and technology ndcator scores, whch are among the lowest n the EU. For example, total expendture on R&D n relaton to GDP s half of the EU average, and cooperaton between frms and research centres n Span s lower than the European average (Castro and Fernández, 2006). Bearng n mnd these features of the Spansh nnovaton system, t s hoped that the results provded n ths paper wll facltate comparson wth and establsh dfferences n nnovaton patterns wth the technologcally leadng countres, whch tradtonally have been the focus of ths type of analyss. Also, gven that one of the prortes of Spansh nnovaton polcy s to ntensfy the relatonshps between frms and publc research nsttutons (European Commsson, 2001), the results of the present study, whch examnes the effects of cooperaton and other external knowledge sourcng strateges on frm s nnovatve performance, should have mportant mplcatons for publc polcy. The rest of the paper s organsed as follows: In secton 2 we outlne the methodologcal aspects of the emprcal study, descrbng the data used, the measures of the varables and the assessed econometrc specfcatons. In secton 3, we dsplay the results and, fnally, n secton 4 we draw the man conclusons. 5

7 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 2 Data and methodology 2.1 Data The data used n the emprcal analyss come from the 2004 Technologcal Innovaton n Companes Survey (TICS) conducted by Span s Natonal Statstcal Insttute. Ths survey s based on the Oslo Manual, and provdes nformaton on the nnovatve behavour of Spansh frms durng the perod The fnal database for 2004 ncludes 4,138 manufacturng companes, across 31 sectors based on Span s Natonal Classfcaton of Economc Actvtes (CNAE). However, we have restrcted our attenton to the subsample of scence-based frms. Ths subsample ncludes 720 frms. In addton, non-nnovator companes were excluded from our analyss, because most varables can only be constructed for frms wth nnovaton actvtes. 3 After deletng observatons wth mssng values, we were left wth a sample of 654 scencebased frms (Table 1). Table 1. Dstrbuton of nnovator scence-based frms by economc actvty. Data for TICS sample and populaton n 2004 Economc Actvty Sample Sample (%) Populaton % Populaton CHEMISTRY PHARMACEUTICAL PRODUCTS RADIO APPARATUS. TV AND COMMUNICATION ELECTRICAL COMPONENTS MANUFACTURE OF AIRCRAFT AND SPACECRAFT Total The TICS data are structured n such a way that specfc flter questons lead to the selecton of frms that are nnovators as opposed to non-nnovators. Only the former have to answer the full questonnare, ncludng questons related to cooperaton wth external agents. 6

8 INGENIO (CSIC UPV) Workng Paper Seres 2008/ Varables Dependent varables Accordng to Oerlemans et al. (1998), the effects of nternal and external resources on frms nnovaton outcomes vary accordng to the ndustry n whch the frm operates and the type of nnovaton developed. The lterature on the sources and determnants of technologcal change has tradtonally focused on the study of product nnovaton, and neglects process nnovatons (Rechsten and Salter, 2006). In our analyss we dstngush between these two types usng dchotomous varables - related to product nnovaton (PRODIN) and process nnovaton (PROCIN) - based on the responses to two questons n the survey that enqure about whether the frm has ntroduced new or sgnfcantly mproved products or processes durng the perod Explanatory varables The frst group of explanatory varables relates to the dfferent external knowledge acquston strateges. We dstngush between bought-n knowledge (buy) and knowledge acqured through cooperaton (cooperaton). Wthn the buy strategy, we further dstngush among external R&D (ERD), technology emboded n machnery and equpment (EQ), and ntangble technology n the form of patents, trademarks, software, etc. (TECNO). These strateges are measured usng dummy varables that take the value of 1 f the frm has used the strategy durng the perod and 0 otherwse. Generally speakng, R&D outsourcng s assocated wth product nnovaton, and technologcal knowledge emboded n machnery and equpment s tradtonally related to process nnovaton. The effect of ntangble technology acquston has been relatvely under researched, although a postve relatonshp between ths varable and the frm s nnovatve performance, s lkely. Strctly speakng, cooperaton s not purely related to external knowledge acquston because t bulds on externally suppled knowledge and frm s nternal capactes. The theoretcal lterature drawng on transacton cost economcs, consders cooperaton to be a hybrd between herarchcal transactons wthn the frms (make) and arms-length transactons n the market place (buy). Cooperaton allows frms to share costs and uncertanty, to realze economes of scale and scope, to explot synerges from complementartes and even to wn government support (Croser, 1998; Becker and 7

9 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 Detz, 2004; Veugelers and Cassman, 1999). To evaluate the effect of cooperaton on nnovaton performance, we have used the reples to the TICS questons about whether the frm has cooperated wth varous external agents n R&D actvtes and nnovaton durng the perod Based on prevous classfcatons relatng to the nature of external knowledge sources (Klevorck et al., 1993), we have created two varables: CI and CNI. The frst relates to cooperaton wth ndustral agents (clents, supplers, compettors, and sster companes); the second relates to cooperaton wth scentfc agents or wth agents outsde the ndustry chan (commercal laboratores/r&d frms, unverstes, publc research nsttutons and technologcal centres). These varables are measured on an ordnal scale (range 0-4) accordng to the number of collaboratve agents n each category. The second group of explanatory varables relates to the frm s nternal technologcal capabltes. We nclude two varables tradtonally consdered to be ndcators of frms efforts to create and assmlate new knowledge. The frst refers to the development of nhouse R&D. The 2004 TICS database reports whether the frms carred out contnuous or occasonal n-house R&D actvtes n Based on ths, we bult the varable IRD, whch takes the value 0 f frms dd not undertake nternal R&D actvtes n , 1 f they occasonally engaged n R&D actvtes, and 2 f they had contnuous n-house R&D. The second varable, TRAINING, refers to efforts made to tran those staff nvolved n the mplementaton of a product or process nnovaton. Ths s a dummy varable that takes the value of 1 f the frm has carred out tranng durng the perod and 0 otherwse. Both nternal R&D and nnovaton related tranng ncrease the frm s organzatonal knowledge base and ts ablty to utlze ths knowledge (Caloghrou et al., 2004). Emprcal studes demonstrate the mportance of nternal R&D as a determnant of product nnovaton, but are nconclusve about the nfluence of ths varable on new process development. Freel (2003), for nstance, found that nternal R&D expendture by scence-based frms was not assocated wth process nnovaton, whereas Rechsten and Salter (2006) found evdence n favour of a sgnfcant and postve relatonshp between these varables. Lkewse, there s no consensus on the nfluence of nvestment n staff tranng on new process development or the launch of new products. On the other hand, t has been suggested that a frm s nternal capactes condton the effects of external knowledge sourcng strateges on nnovatve performance. Thus, 8

10 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 Harab (1995) and Klevorck et al. (1995) argue that only those frms wth a crtcal mass of knowledge are able to use the knowledge that exsts n ther envronment to expand ther nnovaton capabltes. Also, Cohen and Levnthal (1989, 1990) refer to the two faces of R&D, n terms of the dfferent effects of nternal R&D actvtes on the frm s nnovaton performance. Ths suggests that there s a drect and postve effect, snce these actvtes engender new knowledge whch can be used for the development of new or enhanced products and/or processes. In addton, there s an ndrect effect resultng from the ncrease n the frm s absorptve capacty, whch facltates the acquston and explotaton of external knowledge, at least f the frm s wllng to overcome the not-nvented-here syndrome (Katz and Allen, 1982; Veugelers and Cassman, 1999; Laursen and Salter, 2006). Ths effect s partcularly relevant for scentfc or technologcal knowledge whose absorpton and use wll requre greater efforts on the part of the frm. Ths apples to knowledge acqured through cooperaton wth scentfc agents or R&D outsourcng. It would be expected, then, that the development of n-house R&D actvtes, especally f they are contnuous, would be lkely not only to ncrease the potental to generate product and process nnovatons, but also to emphasze the role of external scentfc and technologcal knowledge as determnants of nnovaton. Ths mples that the greater the frm s nternal capactes, the greater the effect of R&D contractng and cooperaton wth scentfc agents on the frm s nnovatve performance Control varables We also nclude as a control varable a measure for frm sze (SIZE). Although the mportance of sze as a determnant of nnovaton has been extensvely analysed, t s dffcult to determne a pror ts real nfluence. The Schumpeteran hypothess holds that, as large frms own the necessary resources (nfrastructure, fnancal resources, producton and marketng capabltes, R&D) to cope wth the rsks assocated wth nnovaton processes, they are more lkely than ther smaller counterparts to engage n nnovatve actvtes. Some recent emprcal works have found evdence supportng ths hypothess (Freel, 2003; Rechsten and Salter, 2006). Other studes, however, have produced contractng results. Acs and Audretsch s (1988) work, for nstance, shows that small and medum enterprses (less than 250 employees) are more nnovaton-ntensve 9

11 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 than larger frms, due, amongst other reasons, to ther lower degree of rgdty when faced wth nnovatons (Caloghrou et al., 2004). In ths analyss SIZE s measured as the logarthm of the frm s sales volume n Logarthmc specfcaton has been acknowledged to be the most approprate technque for measurng frm sze and testng the Schumpeteran hypothess (see Kamen and Schwartz, 1982; Cohen, 1995). 2.3 Econometrc specfcatons To meet the goal set n Secton 1, we have defned the followng econometrc models: d INNOV = α 0 + α1erd + α 2EQ + α3tecno + α 4CI + α5cni + α6 SIZE (model. 1) INNOV d = α + α ERD + α EQ + α TECNO + α CI + α CNI + α IRD + α TRAINING + α SIZE (model. 2) INNOV d + α IRD * CNI = α + α ERD + α EQ + α TECNO + α CI + α CNI + α IRD + α TRAINING + α SIZE + α IRD * ERD + α IRD * CI (model. 3) 3 where = 1,...,N (number of occurrences); d = PRODIN, PROCIN. In the frst model, we analyse the effect of external knowledge sources on a frm s nnovaton performance, regardless of ts nternal technologcal capabltes. In the second model, we nclude IRD and TRAINING as addtonal explanatory varables n order to determne to what extent nternal capabltes nfluence the nnovaton outcome and to ascertan ther mpact on the effects of external knowledge sourcng. To explore ths aspect further, model 3 ncludes three nteractve terms, derved by multplyng IRD (moderatng varable) by the ERD, CI, CNI (moderated) varables. 4 Each of these three models was estmated employng new or sgnfcantly mproved product ntroducton (PRODIN), and new or sgnfcantly mproved process ntroducton 4 These nteractve terms ndcate how the effect of external knowledge sources on the nnovaton outcome vares when the IRD varable s modfed by 1 unt. 10

12 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 (PROCIN) as dependent varables. Ths analyss yelded 6 logstc equatons, whch, based on the dchotomy of the dependent varables, were estmated usng bnary logstc regresson. 4 Results 4.1 Descrptve evdence Table 2 reports the basc statstcs of and correlatons between the explanatory varables used n the regresson analyss. In lne wth Pavtt s (1984) the descrptve statstcs show that scence-based frms tend to nnovate more n products that processes. The descrptve statstcs also show that these frms cooperate more wth scentfc agents, specally wth unverstes, and that the development of n-house R&D actvtes s the most frequent nnovaton strategy (93% of scence-based frms conduct n-house R&D, and 80% of them contnuously). The correlaton matrx reveals some nterestng fndngs. Frst, Internal R&D actvtes show strong correlaton wth product but not process nnovaton. Second, nternal R&D actvty s postvely related to cooperaton strateges, and especally cooperaton wth scentfc agents. 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. However, ths postve relatonshp s not observed n the case of R&D outsourcng. A possble explanaton for ths result s that R&D contractng and n-house R&D compete over the same resources n the structure of busness nnovaton expendture. Consequently, the R&D outsourcng tends to dmnsh when the frm conducts n-house R&. Fnally, n contrast to some studes (Martínez-Ros, 2000; Rechsten and Salter, 2006), we fnd that product and process nnovaton are not sgnfcantly correlated. It seems that for Spansh nnovatve frms, product and process nnovaton are ndependent of each other, and are assocated wth dfferent knowledge sourcng strateges. 11

13 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 Table 2. Descrptve statstcs and Spearman s correlaton coeffcents PRODIN 77,7% 1 Mean PRODIN PROCIN SIZE ERD EQ TECNO CI CNI IRD PROCIN 68,0% 0,034 1 SIZE 16,320 a (1,72) b 0,04 0,093(*) 1 ERD 51,1% 0,034 0,097(*) 0,262(**) 1 EQ 45,7% 0,123(**) 0,227(**) 0,052 0,180(**) 1 TECNO 14,7% 0,067 0,117(**) 0,230(**) 0,181(**) 0,218(**) 1 CI 0,524 a C-Other frms 13,9% C-Supplers 14,8% C-Clents 14,8% C-Compettors 8,9% CNI C-Labs and Prvate R&D Insttutes (0,94) b 0,126(**) 0,093(*) 0,272(**) 0,241(**) 0,122(**) 0,206(**) 1 0,642 a (1,11) b 0,130(**) 0,099(*) 0,244(**) 0,344(**) 0,115(**) 0,146(**) 0,512(**) 1 13,0% C-Unverstes 24,5% C-Publc Research 13,0% Insttutes C-Technology Centers IRD 13,8% 1731 a IRD (1) 13,5% IRD (2) 79,8% (0,57) b 0,117(**) -0,015 0,149(**) 0,049-0,034 0,015 0,084(*) 0,118(**) 1 TRAINING 55,7% 0,091(*) 0,200(**) 0,091(*) 0,124(**) 0,319(**) 0,266(**) 0,173(**) 0,184(**) 0,129(**) a Average value b Standard devaton appear n parenthess ** Correlaton s sgnfcant at the 0,01 level (blateral) * Correlaton s sgnfcant at the 0,05 level (blateral) 12

14 INGENIO (CSIC UPV) Workng Paper Seres 2008/ Econometrc analyss Because we have restrcted the analyss only to nnovator frms, the coeffcents n the logstc regressons may be based. To address ths potental problem we used two-part logt models. In the frst stage of our analyss, we ran a selecton model usng all avalable observatons and consderng whether or not the frm was nnovator as dependent varable (see Appendx 1) 5. Ths allowed us to calculate the probabltes of each frm becomng an nnovator (Prob), whch s ncluded as an addtonal ndependent varable n the man regresson models, thus controllng for selecton bas from ncludng the effects for non-nnovatve frms (Greene, 1993) 6. Table 3 presents the results of man regresson models, for process and product nnovaton. 5 Consstent wth the lterature (Veugelers and Cassman, 1999), we regress whether the frm was nnovator on the followng ndependent varables: frm sze (SIZE), export orentaton (EXPORT) belongng to a group (GROUP), as well as ndustry dummes. We also ncluded four varables measurng the obstacles to nnovaton: cost (FACcost), lack of technologcal/market nformaton (FACknow), lack of demand (FACmark) and need for nnovaton (FACneed). 6 Runnng a separate regresson for sample ncluson followed by the man regresson model s approprate when the ntermedate dependent varable s observed rather than estmated, and more approprate than a Heckman selecton model, whch uses the Mlls rato, snce the dependent varable s bnary rather than contnuous (Mannng et al., 1987, Haas and Hansen, 2005). 13

15 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 Table 3. Determnants of process and product nnovaton. Results of the regresson analyss. Independent varables Process Innovaton Product Innovaton Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Prob 0.92 (1.09) 0.92 (1.12) 1.02 (1.12) 3.51*** (1.13) 3.01* (1.15) 2.95* (1.15) SIZE 0.06 (0.06) 0.07 (0.06) 0.07 (0.06) (0.06) (0.06) (0.06) ERD 0.16 (0.19) 0.16 (0.19) (0.60) (0.22) 0.03 (0.22) 0.27 (0.56) EQ 0.90 ***(0.19) 0.74*** (0.19) 0.69*** (0.20) 0.54** (0.21) 0.58**(0.22) 0.59** (0.22) TECNO 0.48 (0.30) 0.31 (0.31) 0.29 (0.31) 0.33 (0.33) 0.35 (0.34) 0.37 (0.34) CNI 0.04 (0.10) 0.03 (0.10) 0.51 (0.53) 0.23** (0.12) 0.20* (0.12) 0.52 (0.47) CI 0.06 (0.12) 0.04 (0.12) 0.37 (0.54) 0.19 (0.15) 0.20 (0.15) 0.01 (0.44) IRD (0.16) (0.25) 0.51*** (0.16) 0.60** (0.24) TRAINING 0.61*** (0.19) 0.59*** (0.19) 0.02 (0.22) 0.02 (0.22) IRD*ERD 0.61 (0.33) (0.32) IRD*CNI (0.28) (0.25) IRD*CI (0.28) 0.11 (0.24) Industres dummes Included Included Included Included Included Included Intercept (1.21) (1.22) (1.25) (1.30) (1.31) (1.33) Ch-squared (d.f) 49.44*** (11) 59.95*** (13) 65.36*** (16) 43.57*** (11) 53.67*** (13) 54.51*** (16) Pseudo R Observatons Data nsde parenthess are the correspondng standard errors * P < 0.1 ** P < 0.05 *** P < Ch-square values for the degrees of freedom n the models seem to ndcate rejecton of the null hypothess that all parameters except the ntersecton, are equal to zero wth a sgnfcance level of 1%. Prob s not sgnfcant n most cases and when t s excluded from the models, the man varables barely change. Thus, the hypothess of sample selecton bas can be rejected. Model 1 reports the baselne model ncludng only the control varables and the external knowledge sourcng strateges. Ths model ndcates that the effect of the dfferent modaltes of external knowledge acquston on the frm s nnovaton performance vares dependng on the type of nnovaton. The results for process nnovaton show that the acquston of technologcal knowledge emboded n machnery and equpment (EQ) has wth greatest mpact. The coeffcents of the EQ varable are postve and hghly sgnfcant, ndcatng that purchase of machnery and equpment s an mportant 14

16 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 strategy to develop new processes. In contrast, nether of the cooperaton strateges has a sgnfcant effect. These results show that n Span, n contrast to other countres (see Freel, 2003 and Rechsten and Salter, 2006), the establshment of cooperaton agreements wth ndustral agents does not enhance frms producton processes. For product nnovaton, machnery and equpment acquston (EQ) and cooperaton wth scentfc agents (CNI) are the only strateges that are shown to have a postve and sgnfcant effect. Two mportant ponts emerge from these fndngs. Frst, cooperaton s a useful strategy for the development of new products. Second, the choce of cooperaton partners depends on the ndustral sector. These results are consstent wth the lterature and show that the more technology-ntensve the ndustry, the more mportant wll be the knowledge from scentfc agents for new product development. However, contrary to expectatons, R&D outsourcng (ERD) was not found to be sgnfcant. The effects of the frm s nternal capactes are ntroduced n model 2 through the varables IRD and TRAINING. The nfluence of these varables on frms nnovatve performance also depends on the type of nnovaton. In-house R&D (IRD) has a sgnfcant nfluence on product nnovaton, but ts effect s not sgnfcant for process nnovaton. Internal tranng (TRAINING), on the other hand, sgnfcantly affects only process nnovaton. Some addtonal comments are needed to clarfy these results. The hgh sgnfcance of the IRD varable on product nnovaton hghlghts that far from losng relevance, mplementaton of n-house R&D actvtes s the man strategy for developng new products. On the other hand, t s hardly surprsng that IRD was found to be not sgnfcant for process nnovaton. As t was above mentoned, studes on the effect of ths varable on process nnovaton have produced mxed fndngs. In fact, our results concde wth those found by Freel (2003) for the UK. In any case, these fndngs hghlght that n Spansh scence-based frms, mprovements to the productve process are not based on ether research or cooperaton wth external agents, but are largely drven by the purchase of machnery and equpment. Moreover, the acquston of new machnery and equpment usually requres some tranng of techncal staff n how to use the new equpment, whch explans the postve and sgnfcant effect of TRAINING. In general, the ncluson of n-house R&D actvtes n the analyss has lttle effect on external knowledge sourcng strateges. Focusng on product nnovaton (where the IRD 15

17 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 varable has a sgnfcant effect), only a change n the sgnfcance of the CNI varable s noted. Ths varable loses explanatory power when n-house R&D s consdered, although t remans sgnfcant at 10%. In ths sense, the results suggest, rather surprsngly, that a hgh level of nternal technologcal capabltes derved from nhouse R&D actvtes, reduces the mportance of external acqustons of scentfc knowledge as a determnant of nnovaton. The model 3 estmatons support ths concluson, provded that the nteractve term CNI*IRD has a negatve sgn, although t s otherwse not sgnfcant. Usng the results from model 3 n Table 3 and holdng all other covarates at ther mean values, we plotted llustratve examples of the effects of cooperaton wth scentfc agents (CNI) on product nnovaton, for varous levels of n-house R&D actvtes (IRD). Fgures 1 depcts these effects. We observe that when the IRD varable ncreases the slope of the lne that draws the relatonshp between CNI and product nnovaton dmnshes 7. Ths suggests that where frms engage n n-house R&D, and even more so when they do so contnuously, the margnal effects of cooperaton wth scentfc agents on product nnovaton tend to decrease. 7 When the IRD varable changes from 0 to 2 the slope of the lne dmnshes from 0,12 to 0,04. 16

18 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 Fgure 1. Relatonshps between cooperaton wth scentfc agents and product nnovaton. 0,70 0,60 0,50 Probablty 0,40 0,30 0,20 0,10 IRD (0) IRD (1) IRD (2) 0, CNI To summarze, our results do not support the complementarty hypothess; rather, they ndcate the exstence of a possble substtuton effect between external knowledge sourcng and nternal knowledge development. Thus, although frms that perform nternal R&D on a contnuous bass tend to cooperate more wth unverstes relatve to other external agents, ths cooperaton does not seem to be orented towards the development of key actvtes for ther nnovaton processes. Ths cooperaton wth scentfc agents mght be motvated more by access to funds through partcpaton n government sponsored programmes, than to mprovng nnovatve capactes based on the ntegraton of complementary knowledge from external agents In addton, Fgure 1 shows that when n-house R&D s contnuous (IRD=2) and the frm cooperates wth the four types of scentfc agents consdered n the analyss, the probablty of ntroducng new products s less than when frms ether do not engage n n-house R&D or do so only occasonally. Ths result ndcates that the frms could be facng an attenton allocaton problem (Ocaso, 1997). As manageral attenton s a lmted resource, the managers need to concentrate ther efforts and energy on a restrcted number of strateges. Thus, when the frm engages both nternal development and external knowledge sourcng, there may be many deas that surpass the frm s 17

19 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 capabltes for evaluatng and explotng them (Ocaso, 1997). The effectveness of external knowledge sourcng strateges to encourage a frm s nnovatve performance depends therefore not only on the acquston of knowledge but also on the frm s capablty to set prortes and concentrate resources. Fnally, we found that the SIZE varable was not sgnfcant n ether process or product nnovaton; however, n the frst-stage model (Appendx 1) frm sze had a sgnfcant and postve effect. Ths suggests that the effect of frm sze s lmted only to the decson to mplement an nnovaton actvty. Once the frm has decded to nnovate, the probablty that t wll ntroduce new products or processes does not depend on sze. 6 Conclusons Ths study has examned the effects of dfferent external knowledge sourcng strateges on product and process nnovaton and to what extent these effects are nfluenced by nhouse R&D. We found that product and process nnovatons may be ndependent of each other and, even more mportantly, that they are assocated wth dfferent knowledge sourcng strateges. For nstance, our results ndcate that process nnovaton s largely drven by the acquston of knowledge emboded n machnery and equpment and that cooperaton wth external agents has no sgnfcant effect. In contrast, cooperaton wth scentfc agents seems to be an mportant strategy to develop new products. Along ths lne, t s all the more surprsng that R&D contractng was found to be not sgnfcant n enhancng frms nnovatve performance. Our results also ndcate that n-house R&D actvty stll represents a strategc asset n the development of new products and, n addton, that developng and mplementng these actvtes s sgnfcantly more mportant than employng strateges nvolvng external partners. Moreover, our analyss reveals another more fundamental ssue. When we examned the relatonshps between external sourcng strateges and nternal R&D, we found no evdence to support the complementarty hypothess. More mportantly, our analyss ndcates nstead that there are possble substtuton effects between these actvtes. Thus, the greater the frm s nternal technologcal capablty, the less mportant s the cooperaton wth scentfc agents n determnng product nnovaton. Ths seems to run aganst the ncreasngly domnant open nnovaton model (Chesbrough, 2003). 18

20 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 These results have at least two mportant mplcatons. Frstly, they support the dea that product nnovaton s a process that largely bulds on the frm s nternal capabltes, and warns aganst the rsk of overratng external knowledge sourcng. In ths regard, the mportance of cooperaton, for nstance, should be consdered n relatve terms. As Freel (2003, p 762.) has sad: certan types of cooperaton are assocated wth specfc types of nnovaton, nvolvng certan frms, n certan sectors, and we would add certan levels of nternal technologcal capabltes. Secondly, acceptance of ths heterogenety should lead polcy makers n Span and other technology follower countres, to acknowledge the complexty of the nnovaton process and avod the promoton of one sze fts all mechansms, whch are generally only suted to the most technologcally developed countres. In the lght of our results, t would appear that polcy makers should concentrate on strengthenng the technologcal capabltes of frms and should go beyond smple support to unversty-ndustry collaboraton. 19

21 INGENIO (CSIC UPV) Workng Paper Seres 2008/12 7 References Acs, Z.J. and Audretsch, D.B. (1988), Innovaton n large and small frms: an emprcal analyss, Amercan Economc Revew, 78, Arora, A. and Gambardella, A., (1990), Complementarty and external lnkages: The strateges of the large frms n botechnology Industral Economcs, Arora, A. and Gambardella, A. (1994), Evaluatng technologcal nformaton and utlzng t: Scentfc knowledge, technologcal capablty and external lnkages n botechnology, Journal of Economc Behavor and Organzaton, 24, Becker, W. and Detz, J., (2004), R&D cooperaton and nnovaton actvtes of frms evdence for the German manufacturng ndustry, Research Polcy, 33, Beneto, P. (2003), Choosng among alternatve technologcal strateges: An emprcal analyss of formal sources of nnovaton, Research Polcy, 32, Bönte, W. (2003), R&D and productvty: Internal vs external R&D evdence from West German manufacturng ndustres, Economcs of Innovaton and New Technology, 12, Cassman, B. and Veugelers, R. (2006), In search of complementarty n nnovaton strategy: nternal R&D and external knowledge acquston, Management Scence, 52, Castro, E. and Fernández, I., (2006) 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. Caloghrou, Y., Kastell, I. and Tsakankas, A. (2004), Internal capabltes and external knowledge sources: Complements or substtutes for nnovatve performance?, Technovaton, 24, Chesbrough, H. (2003), The era of open nnovaton, Sloan Management Revew, Summer, Cohen, W.M. and Levnthal, D.A. (1989), Innovaton and Learnng: The two faces of R&D, The Economc Journal, 99, Cohen, W.M. and Levnthal, D.A. (1990), Absorptve Capacty: A new perspectve on learnng and nnovaton, Admnstratve Scence Quarterly, 35,

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25 INGENIO (CSIC UPV) Workng Paper Seres 2008/11 Appendx 1. Logt analyss results for frst-stage model (frm s decson to nnovate or not) Varables Coeffcents (standard error) SIZE 0.19* (0.11) EXPORT 0.00 (0.01) GROUP (0.22) FACcost 0.13 (0.18) FACknow 0.42 (0.28) FACmark 0.62*** (0.21) FACneed -1.10*** (0.19) Industres dummes Included Intercept (1.84) Ch-squared (d.f) 75.56*** (11) Pseudo R Observatons 720 * P < 0.1 ** P < 0.05 *** P <