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DOCUMENTO DE TRABALHO WORKING PAPERABST 1. INT 2. BA 2.1. D BEHA 2.2. A 2.3. U FRAM 3. EM 3.1 E 3.2 D 3.3 N 3.4 N 4. RE 4.1 T 4.2 M 4.3 C 5. CO REFE TRACT ... TRODUCTION ACKGROUND DIFFERENCES AVIOUR ... ACCESSING R USING SOCIA MEWORK ... MPIRICAL SET MPIRICAL SE DATA COLLEC NETWORKS (R NETWORK AN SULTS AND D HE TOPOLOG MAIN CHARA OMPARING ONCLUSION .. RENCES ...
Underst
... N ... ... S BETWEEN B ... RESOURCES T AL NETWORK ... TTING AND M ETTING ... CTION ... RE)CONSTRU NALYSIS ... DISCUSSION GY OF INNOV CTERISTICS O NETWORKS ... ...tanding th
... ... ... BIOTECHNOL ... THROUGH SO KS TO CAPTU ... METHODOLO ... ... UCTION ... ... ... VATION NETW OF SECTORA OF THE TWO ... ...he topolo
... ... ... LOGY AND SO ... OCIAL NETW URE DIFFEREN ... OGY ... ... ... ... ... ... WORKS ... AL NETWORK O SECTORS .. ... ...ogies of in
knowle
... ... ... OFTWARE IN ... WORKS ... NCES BETWE ... ... ... ... ... ... ... ... KS ... ... ... ...nnovation
edge-inte
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... ... ... N THEIR INNO ... ... EEN SECTORS ... ... ... ... ... ... ... ... ... ... ... ...n network
ensive sec
Isabel Sala Cristina Sous arida FontesP nº 201
cember 2
... ... ... OVATIVE ... ... S: AN ANALY ... ... ... ... ... ... ... ... ... ... ... ...ks in
ctors
avisa♣ sa ♣♣ s ♣♣♣1/09
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... 2 ... 3 ... 5 ... 5 ... 9 TICAL ... 11 ... 13 ... 13 ... 15 ... 15 ... 16 ... 19 ... 19 ... 21 ... 26 ... 30 ... 32Un
ABS
The m firms teleco simila The a applie broad show of th result novel chara Portu inten KEY Innov secto JEL 1 This suppo The a Finally Confenderstand
STRACT
main goal o s from two ommunicatio arities and d analysis focu es a method d range of r w that network e resources ts shed light l insights int acteristics an uguese case. sive sectors w YWORDS vation netwo r; biotechnol CLASSIFIC s research wa ort is gratefully authors wish t y, they also w erence 2011. Tding the t
of this paper knowledge ons – to acc ifferences be uses on form ology that dr relationships ks are quite searched fo on the spec to the organ nd strategies The approa which may b ork; social n logy; softwa CATION: L as supported b y acknowledge to thank Ped wish to thank The usual disctopologies
is to compa intensive s ess resource etween netwo mal and inform
raws on a va developed b contrasted in r and the m ificities of fo nisation and d s of the fir ach provides be applied to network; form re L14, L65, L86 by the Portug ed. ro Videira and the discussan laimers apply.
s of innov
are the netw ectors – mo es required f orks to be id mal network ast array of d by the firms n and across mode of orga formal versus dynamics of rms and the s tools to stu o different na mal network 6, O32 uese Science d Carim Vali nts of a prelim .
vation ne
works mobili olecular bio for innovatio entified and s and on the data to captu s in their inthe two sect anisation of s informal n f the sectors e specificity udy the inno ational and se
k; informal n
Council (FCT for their valu minary version,
etworks in
intens
ised by youn technology on. Such a c explained. relevant typ ure the nature nnovative pro ors, due both the sectors. etworks. Fin , taking into y of the env ovative proc ectoral contex network; kno - POCI/ESC/6 uable support , presented atn knowled
sive secto
ng entrepren and softwar comparison a pes of resour re and conten ocess. The r h to the spec Furthermor nally, they pr o account bo nvironment i cess in know xts. owledge-inte 60500/2004), with the dat t the Druid Sudge-ors
1 neurial re for allows ces. It nt of a results ificity re, the rovide oth the in the wledge ensive whose tabase. ummer1. IN
The m firms teleco simila intere taking Both role a their Howe explo type by th netwo availa of the In ad condi proce availa resou types These expec Thus behav innov of the each For th proce entrep differNTRODU
main goal o s from two ommunicatio arities and d esting feature g into accoun sectors are k and often co innovation n ever, the two oited and theof resources he firms; ii) t orks are ofte able in-hous e innovation ddition to the
itions in whi ess of resour able but als urces. The co s of resources e constraints cted to give t , in order t viour betwee vative behav e type of res type of resou his purpose, esses in biote preneurship rences betwe
CTION
of this paper knowledge-ons – to acc differences be es concernin nt their speci knowledge-in onstitute the networks. o sectors als e organisation s necessary f the sources f en mobilised e, it is expec networks bu ese sector-re ich firms ope rce mobilisat so in terms ontext may s, which may s require firm the configura to capture en sectors it iour between sources searc urce; 3) cons the paper d echnology an and in inno een networks is to compa -intensive se ess resource etween netw ng the organi ific environm ntensive and majority of so display so n of the inno for innovatio for these res by young en cted that the uilt by firms elated featureerate. In fact tion, not only
of the natu therefore in y be sector-sp ms to adjust ation of the i and underst t is necessar n biotechnolo ched; 2) inv sider the spec draws on two nd in softwa ovation, in o s and their ro
are the netw ectors – mo es required f works to be id isation and d ment in Portu d in both you f the populat ome differen ovation proce on and in par sources and t ntrepreneuria ese difference in each secto es, it is also t, the context y in terms of ure of the r ntroduce part pecific or tra t their netw innovation ne tand the sim ry to 1) iden
ogy and soft vestigate the cific context o domains of are sectors; 2 order to iden ole in the acc
works mobili olecular biot for innovatio dentified and dynamics of ugal. ung entrepren ion. Thus, w nces in the n esses. These rticular on th the modes o al firms to ac es will have or. o necessary t t where firm f quantity, qu relationships ticular const ansversal to a working beha etworks spec milarities an ntify the mai tware firms a nature of th where those f literature: 2) the literatu ntify and un ess to resour ised by youn technology on. Such a c d explained. B both sectors neurial firms we expect so nature of the differences he external r f access to t cess key reso
an impact o to consider t s are embedd uality and va s established traints on th all technolog aviour accord cific traits. nd difference in difference and their imp he relationshi e relations oc 1) the literat ure on the ro nderstand th rces required ng entrepren and softwar comparison a But it also pe s to be uncov play an imp ome similarit knowledge reflect upon resources sea them. Since ources that a on the archit the environm ded influenc ariety of reso d to access he access to gy-intensive dingly and s es in netwo es in terms plications in ips built to a ccur. ture on innov ole of netwo he similaritie d for innovati neurial re for allows ermits vered, portant ties in being n i) the arched social are not ecture mental ces the ources these some firms. so are orking of the terms access vative orks in es and ion.
Comb Based differ explo The e softw opera novel the n comp variat On th and d bining contri • propo resou of tie • relate know secto • consi d on this fra rences for oratory empir empirical an ware (softwar ating in Port l methodolog nature and petences flow tion propose he basis of a differences be ibutions from
oses two sou
urce being ac
es established es difference
wledge being
or;
iders the con
amework, we the architec rical analysis nalysis is con re for teleco tugal. The in gy. This me contents of w into the fir ed: type of re an analysis o etween the tw m these two s urces of varia ccessed; and d); es in the se exploited an nditions found e put forward cture of the s. nducted on a ommunicatio nnovation ne thodology p the range rms, thus ena source and n of the recons wo sectors an streams, we b ation in the c d ii) the mod ectoral netwo nd in the org d in the envi d some expe e respective a sample of ons) and 23 etworks mob permits a vas of relations abling the co nature of the structed netw nd discuss th build an anal configuration de of access t orks with di ganisation of ironment whe ectations abo e innovation f 46 young e from biotec bilised by fir st array of da ships throug onsideration tie. works, we inv he reasons fo lytical frame n of the netwo to the resour istinctions in of innovative
ere firms ope
ut the implic n networks entrepreneuri chnology (m rms are reco ata to be ass gh which ke of the two so vestigate the or the differen ework that: orks: i) the ty rce (i.e. the n n the type o e activities in erate. cations of se and condu ial firms: 23 molecular bio onstructed us sembled cap ey resource ources of ne e main simil nces identifi type of nature of the n each ectoral uct an 3 from ology) sing a turing s and etwork arities ed.
2. B
In thi our st 2.1. THE It is innov secto and P Palm strate behav Both of kn know impac proce pursu Biote its v funda resea were The d centre collab techn (McK techn capita resea (MaleACKGRO
is section, af tudy has drawDIFFERE EIR INNOV well establi vation in bio rs (or of bio Prevezer, 19 mberg, 2007). egies, they p viour of the f sectors are h nowledge be wledge, as c ct the nature esses conduc ue them (Mal echnology is very existenc amental scie arch spin-offs key players dominant bu ed on the c boration wit nologies to Kelvey et al nologies that al and a tig arch contracts erba and Ors
OUND
fter a brief s wn, we will p NCES BET VATIVE B ished that in technology a otechnology 996; Weterin . Although n provide somefirms that can highly knowl eing exploite ompared wi e and sources cted by the lerba and Or the most co ce to the n entific disco s founded by in the develo siness mode creation of th research established l, 2004). Th could suppo ght appropri s with and/o senigo, 1993 survey and d present the a TWEEN B BEHAVIOU nnovation is and in softw and comput ngs and Pon none of these e insights in n guide our d ledge-intensi ed and also ith non-tech s of technolo firms and th rsenigo, 1993 mmon exam new technol veries in th y scientists w opment of th l adopted by knowledge organisation d firms from his model w ort a continuo iability regim r licensing o ; Coriat et al discussion of analytical fra BIOTECHN UR sector spec ware, and a nu ting) have b nds, 2009; e studies has nto the organ discussion. ive, but diffe
the role and hnological re ogical opport herefore the 3). mple of a scie logical and he field of who maintain his sector (Or y firms in thi through int ns) and the m other in was based o ous stream o me, since f or selling the l, 2003). f the most re amework ado NOLOGY A cific. A num umber of co been conduct Rampersad s specifically nisation of th erences can b d location o esources. Th tunities and h resources a ence-based o commercial molecular b ned a close r rsenigo, 1989 is industry, a tensive resea patenting an ndustries, in on the prese of developme firms’ reven e technologie levant contri opted in the r AND SOFT mber of studi mparative an ted (McKelv et al, 2009 y compared f he sectors a be found in t f scientific hese differen hence the na and competen r science-dri l possibilitie biology. Sma relationship w 9). at least in the arch activiti nd licensing n particular ence of perv ents, the avai
ues derived es to more po
ributions on research.
TWARE IN
ies have ana nalyses of th vey, 2005; S ; Luukkonen firms’ netwo and the inno
terms of the n and technol nces are like ature of innov ences necessa
iven sector, o es opened u all firms, u with the acad
e early stages ies (frequen g of the res r pharmaceu vasive “plat ilability of ve d essentially owerful cust which N alysed he two Swann n and orking vative nature ogical ely to vation ary to owing up by usually demy, s, was ntly in sulting uticals tform” enture from omers
As th 2003) adopt the c target 2011) biotec diffic in cap to ad comp Kraft variet struct scien Wall, are fr As to Some while speci with (Lipp relian techn tacit k Torri Gene oppor come actua soluti appro McK stand he sector evo ), with new ting a niche case of firm ting non-dru ). It also t chnology (L culties experi pital markets dopt more petences is i t, 2006; McK ty of new b ture (particu ntific develop , 2010). But requent and t o software, t e authors hav e others hav alised suppl the science-poldt and St nce on scien nology-intens knowledge a si, 2001; Ara erally speakin rtunities is h es to embedd al and antic ions. Oppor opriability – Kelvey, 2005 dards, copy olved, other b companies s strategy (Lu s operating ug based act tended to p Lowe and Ge ienced by fir s and cost red
integrated increasingly Kelvey, 2008 business app larly in the h pments (e.g , on the who the pace of in the character ve assigned ve labelled it ier model se -based regim tryzowski, 2 ntific advan sive sector r appears to be amand, 2008 ng, we are n high, but mo ded software cipated, indu rtunities are – greatly aff ) – firms r rights, techn business mod starting to d uukkonen, 20 outside the tivities such prevail in c ertler, 2009; rms adopting duction strat business m bundled w 8). Recent re proaches, w health sector . personalise ole, innovatio nnovation is risation of i it to the spec t simply as eems to coex me. In fact, 2009) with nces (Steinm relying on a e more releva 8). not dealing w ostly dependi e and applic uce package reinforced fected by th ely on seve no-commerc dels emerged develop and 005). The pr health sect as instrume ountries/regi ; Costa et al g the classica tegies of larg models, wher with downstre esearch poin which reflect r) and/or exp ed medicine on remains m quite rapid. its dominant cialised supp information-xist with a k it is a dive various deg mueller, 2004 complex an ant than in m with a scienc ing on user-cations. Like ed software by the per he open sour eral forms o cial strategie d (Orsenigo commerciali roduct/servic or (Valentin ents or diagn ions periphe l, 2004). On al science-ba ge companies re the dire eam service nts to the on-adjustment ploit new opp
e) (Amir-As mostly scien t technologic plier categor -intensive (T knowledge-b ersified indu grees of tech 4). Thus, w nd diversifie most biotechn ce-based sect producer rel ewise, the pe e firms to rvasiveness rce software of property p es - includin et al, 2001; M ise specialise ce focus was n and Jensen nostics (Gott eral to the n the other h sed model – s – increasing ct exploitat s or produc -going exper s to change portunities ar lani and M nce-driven, ra cal regime is y (de Jong a Tidd et al, 1 based one, be ustry, encom hnological s we may defin d knowledge nology activit
tor. The leve lationships, e erceived nee innovate in of applicati e movement protection su ng lead-time Mangematin ed products, s more frequ n, 2003) or tinger and U main centr hand, the gro
due to const gly led these tion of scie cts (Rothman rimentation w es in the de arising from r Mangematin, adical innov s less conse and Marsili, 1997). Actua earing simil mpassing seg sophistication ine software e base, but ities (Grimald el of technol especially w eds of the c n problem-so ions. In term t (Malerba, such as pate e, proliferati n et al, often uent in firms Umali, res of owing traints e firms entific n and with a emand recent 2010; vations ensual. 2006) ally, a arities gments n and e as a where di and ogical when it lients, olving ms of 2005; enting, ion of
produ custo innov The s the n biotec organ In the acade acces inten oppor to so envir equip assoc on th quite The s the ty the s partn 2009) the s relati and c devel strong inves often Thus that techn the v firms ucts (Giarrata omers. Overa vation is also specificities nature of t chnology im nisations, wh e case of so emic knowle ss to talented sive in the s rtunity in bio ftware innov ronment, cor pment suppl ciated with a he industry. relevant (M specialised an ype of busin success of f nerships with ). Power asy sector has c onships (Go commercial lopment lead gly on extern stors (Coriat n transnationa , the biotech associate w nologies or h arious playe s and large e ana, 2004) a all, innovatio o very rapid. described ab the relations mplies that hich are impo oftware, such edge is incre d highly skil sense of “em otechnology, vation. In fa rresponding liers or serv an increasing Thus, coope alerba and O nd frequently ness models a firms’ innov h other, ofte ymmetries be compelled l ttinger and U elements an d times and nal funding, et al, 2003) al (Owen-Sm hnology secto with a variet highly innov ers, the divisi established c and partnersh on can be de bove have im ships establ long-term r ortant source h relationship easingly rele led engineer mbodied” kno , stimuli from ct, software to the requ vice provide g need for mo eration amon Orsenigo, 199 y upstream n adopted and vative activi n larger com etween partn large partne Umali, 2011) nd may also high capital which can b . Given the mith and Pow
or typically e ty of other ative produc ion of labour companies fr
hips and allia escribed as mplications o lished by i relationships es of a key re ps are usual evant, unive rs (Giarratan owledge. W m customers houses try t uirements of ers. This is obility and in ng firms and 93). nature of the the characte ities is stron mpanies (Ba ners are thus ers to engag ). Partnership o involve c l requiremen be provided global natur well, 2004). encompasses organisatio cts. Despite r between re from applicat ances, both a mostly incre on the organ its firms. T s tend to b esource (Mur
lly less impo ersities are p na, 2004), sin While scientifi and the mar to adapt the f customers s an area w nterconnecte d upstream a activities pu eristics of th ngly depend aum et al, 2 s common, e ge in more ps can be mi capital (Bagc nts may forc by venture c re of biotech s a large num ons to deve the on-going esearch organ tion sectors mong softwa emental, alth nisation of th The science-be maintaine rray, 2004; B ortant. Altho particularly i nce here firm ic research i ket appear to ir products t such as tel where socia edness have and downstr ursued by bio heir main cus dent on the 000; Milano even if the re balanced a ixed, combin chi-Sen, 200 e biotechnol capitalists an nology, thes mber of speci lop and com g changes on nisations, sm is still paten
are firms and hough the pa
he sectors na -based natu ed with res Bagchi-Sen, 2 ough the acc
important to ms are knowl is a key sou o be more re to a fast cha lecommunic al transform a strong infl ream relation otechnology stomers mea establishme ov and Fernh ecent dynam and collabo ning technol 07). In fact, logy firms t nd/or by corp se partnership ialised small mmercialise n the strateg mall biotechn nt (particula d with ace of amely, ure of search 2007). cess to o gain ledge-rce of levant anging ations mations luence ns are firms, an that ent of haber, mics of orative ogical , long o rely porate ps are firms their gies of nology arly in
pharm in the In so comm impo custo outso comp the in succe is qu indiv of bi differ Nature Main s Entrep backgr Type o Domin Positio Key pa maceuticals) e complex ne ftware, smal mercial part rtant. Small omers, along ourcing and prise large co nternet (Clo ess. Consequ ite high. Ho viduals, which otechnology rentiating fea e of knowledge sources of oppo preneurs round/competen of innovation nant business m on in value chai artners (Stuart et al etworks that ll, medium a tnerships wi l firms sell gside tailored a huge spe ompanies fro oodt et al, 2 uently, they a owever, this h is critical f y and softwa atures betwee T ortunity nces model in l, 2007), wit characterise nd large firm ith other fi mostly emb d solutions ecialisation a om sectors s 2010). Talen are the subjec
phenomenon for problem are innovativ en them. Table 1 - Com Scientific k Science Scientists w backgroun More radic Technolog in technolo Product de added serv important Typically u technologi intermedia Universitie Large estab application th large firm the industry ms coexist. S irms, althou bedded softw and services are distincti such as comp nted program ct of intense n coexists w solving. Tab ve behaviour mparing biote Biotechnology knowledge with academic nd cal gy development ogy markets evelopment & h vices becoming upstream – dev ies or products t ate markets es blished firms fr n sectors ms retaining a y. Small firms t ugh technolo ware for a s. Partners i ive traits of puting hardw mmers are a dispute betw with regular “ ble 1 summar r and organi echnology and y T k i M E i M t & selling high value more P c s C N velop to T p c rom O F ( t an important end to specia ogical partn diversity of include softw f the industr ware, telecom crucial reso ween firms an “knowledge rises this brie isation, high d software S Tacit complex t knowledge “em individuals Market/Custom Engineers with in industry: tech More incremen Product develop continuous diffe sophistication Customised pro Niche strategy i Typically down products for fin customers that a Other firms from Firms from app (computing HW telecommunicat
t coordinatin
alise and est nerships are f application ware firms, ry. But they mmunication ource to bu nd labour mo bartering” a ef characteri hlighting the Software technological mbodied” in skil mers previous exper hnical & comm ntal
pment/Product’ ferentiation and oducts and serv in some segmen nstream – devel nal markets or f address final m m same sector plication sectors W, ations, Internet, ng role tablish e also ns and since y also ns and usiness obility among sation main lled rience mercial ’s d ices nts lop for markets s etc.)
2.2. The a entrep or or eleme resou acces differ young The devel netwo forme Zimm netwo the so acqui in the studie endea scien mark But w resou addre scarc one t studie provi the na Simil estab indiv ties e (Ahuj ACCESSI above discus preneurial fi rganisations ent of a firm urces searche ss these reso rences in ter g and mostly role played lopment of t orks and ent er, entrepren mer, 1986; U orks of the f ocial context isition of res e entrepreneu es have inc avours. Netw ntific and tec ket (Ozman, 2 while both s urces for en esses and/or e (Sammarra type of reso es putting pa ide a single p ature of the n larly, both li lished betwe viduals (Smit established a uja, 2000; Uz NG RESO ssion shows t irms in both that can pr m’s strategy ed, as well as ources. Thus, rms of resou y small firms d by networ technology-in trepreneurshi neurship is Uzzi, 1997). T founder(s) (p t in which th sources in the urial process creasingly hi works are de chnological 2009). streams of li ntrepreneursh compares t a and Biggie ource only ( articular emp perspective to networks. iteratures dis een organisat h-Doerr and and, in the ca zzi, 1997). B URCES TH that access to sectors. Thu rovide those . But it also s in the type o , the relevan urces lead to s to survive a rks in the a ntensive firm ip and by th a social pro Thus, firm fo personal netw he firm oper e context in to be overco ighlighted th escribed as p knowledge, terature reco hip and for the networks ero, 2008, S (knowledge, phasis on the o the underst stinguish bet tions, and mo Powell, 200 ase of the in But, once ag HROUGH o external re us, the estab resources o o suggests t of actors and nt question e o differences and to thrive access to re ms has been he literature o ocess embed ormation and works that te rates. Social which firms ome (Elfring he role of providing cri either as an ognise the n innovation, s mobilised Sousa et al, 2 capital, inf e access to kn tanding of th tween more ore informal 03). They als nnovation lite gain, empiric SOCIAL sources is cr blishment of or facilitate that there ar d the relation emerging fro in the netw in a turbulen esources nec addressed b on innovatio dded in netw d developme end to be inf networks ar s are embedd g and Hulsink networks fo itical resourc n alternative
need for and , empirical to access d 2011). Empi formation) ( nowledge (O he impact of formal, con l relationship o pay some a erature, its in cal studies t NETWOR
ritical for the relationship their access e difference nships establi om this asses works built a nt context. cessary for oth by the li on networks. work structu nt are influen formal) and m re described ded, allowing k, 2003). Lik or the succe ces to comp e or as a co the relevanc research tha ifferent type irical studies Jack, 2010), Ozman, 2009 different typ ntractual rela ps that are es attention to t nfluence on k tend to centr RKS e success of y s with indiv s is an imp es in terms o ished with th ssment is wh and maintain the creation iterature on According ures (Aldrich enced by the more genera as facilitatin g some const kewise, innov ess of innov anies, partic omplement t ce of a vari at simultane es of resour s usually foc , with innov 9). Thus, they pes of resourc ationships th stablished be the intensity knowledge a re on one ty young viduals portant of the hem to hether ned by n and social to the h and social ally by ng the traints vation vative cularly to the ety of eously rces is cus on vation y only ces on hat are etween of the access ype of
relati domi Resea (Schw rather Peder playe entrep 1197) 2010) The g this l on kn the es proce to a v 2006 netwo are ra The s of res calls This studie argue can a findin onship. In t nant (Audret arch address wartz and Ho r than those rsen, 2004). ed by entrep preneurs’ tra ). However, ). greater intere evel, with a nowledge ex stablishment ess of techno variety of tec ; Bagchi-Sen orks – either are (Fuller-L scarcity of c sources searc for research research is es and also o e that there a also provide ngs. the case of t tsch and Feld sing the actu
ornych, 2010 of entrepren Conversely preneurs’ pe ajectory and these featur est in knowl substantial p xchanges. Ho t of formal a ology develo chnological a n, 2007). Bu r taken globa ove, 2009; T omparative r ched influen that effectiv necessarily on research o appear to be insights to g the innovati dman, 2003; ual informal 0) and it is o eurs (Kreine y, the entrepr ersonal netw d grounded o res are rarely
ledge networ part of the re owever, the i lliances by y pment and c and non-tech ut once agai ally or focus Trippl et al, 2 research limi nce the confi vely addresse exploratory on the netwo some differ guide our em on literature ; Roijakkers exchanges b often concern er and Schult reneurship l works, which on loyalty an y associated rks revealed esearch on bo innovation li young techno commercialis hnological re in, comparat ing on the a 2009).
its our under iguration of t es this issue, . However, orks built to rences betwe mpirical anal e, research o and Hagedo between indi ned with the tz, 1993; Giu literature put h are descri nd reciprocit with search d by innovati oth formal an iterature has ology-intensi sation, thus o esources and tive studies ccess to spec rstanding of the networks which is one based on th access spec een them. In lysis and to on formal ne orn, 2006; C ividuals is m networks of uliani and Be ts great emp ibed as orig ty between i for particula ion studies i nd informal also address ive firms to often encomp d competence between for cific types o f how differe s mobilised b e of the purpo he few avail ific resource n addition, th support the etworks is c Cloodt et al, 2 much less fre f firms’ empl ell, 2005; Dah phasis on th ginating from individuals ar resources is also reflec networks ce sed in some support the w passing the a es (Colombo rmal and inf f resources o ences in the n by the firms oses of this p lable compa es, it is possi hese partial r discussion o clearly 2010). equent loyees hl and e role m the (Uzzi, (Jack, cted at ntring detail whole access o et al, formal only – nature s. This paper. arative ible to results of our
2.3. SEC Summ relate and t reflec relati This sectio such know impli acces them these The t netwo which resou USING SO TORS: AN ming up the es the netwo the organisa cted in the v onships estab framework, on 2.1) that as biotechn wledge being ications on t ss to externa . In other wo sectors, whi type of the r ork) and the h are also l urce access n OCIAL NE N ANALYT discussion i orks’ architec tion of the variety of re blished with depicted in despite som nology and exploited an the type of r l sources of
ords, they inf ich are likely resources wil type of relat likely to var networks buil ETWORKS TICAL FR in the previo cture at secto innovative a sources sear them. n Figure 1, st me similaritie software hav nd the organ resources re these (non-a fluence the ty y to present s ll then influe tionships tha ry. These va lt by firms in S TO CAPT RAMEWOR ous sections, oral level w activities. It rched and co tarts from th es related to ve clear-cut isation of in equired by th available in-h ype of the re some differen
ence the acto at are establis ariations wil n each sector TURE DIF RK we propose ith the natur is argued th onsequently he notion (ba their techno t differences novative act he firms, as house) resour esources sear nces.
ors that are m shed with th ll then refle . FFERENCE e an analytic re of the kno hat these tw their source ased on liter ology-intensi regarding t ivities. These well as on rces and the rched by the mobilised (c em (structur ect on the ar ES BETWE cal framewor owledge exp wo dimension es and the ty rature presen ive nature, s the nature o e differences the need to ability to mo firms operat composition re of the netw architecture o EEN rk that ploited ns are ype of nted in ectors of the s have o gain obilise ting in of the work), of the
It sho chang acces conte More natur also e • • ould howeve ges in the se ss to the sour ext dependen e specifically re of firms’ in expect that: the differ nature of developm scientific concernin exploited other sou er be pointe ector´s mode rces of requir nt. y, while we nnovative ac rences in the f the domina ment) will ha and technol ng knowledg d will have im urces; Figure 1 – ed out that d e of organisa red resource expect to fin ctivities and t origin of te ant business ave implicati ogical know ge resources, mplications o – Analytical f different env ation. Theref s, and the ch nd some sim the predomin echnological model pursu ions on the wledge and no , the differen on the relativ framework vironmental fore, the firm hannels used milarities - g nance of you opportunitie ued by the f type of reso on-technolog nces in the n ve importanc contexts m ms’ ability to to obtain the
given the tec ung entrepren es (science vs firms (techn ource needs gical resource nature of the e of research
may also intr o identify and
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3. E
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EMPIRICA analysis focu ware for teleced between chnology fir e our softwar e software s less than 50 set up betw had a turnov million. ost all compa
% of the tur 5 companie majority rel h represented or the entre neering, but ficant period er and about o ng non-techn ons on the s ole of differe nature of t to influence fic context w ccess to som them. amework pre
AL SETTI
AL SETTI used on spec communicati n 1998 and rms can be re re group corr ector, the sa employees a ween 1998 an ver (in 2007) anies (91%) rnover and a es applied pa ly on equity d only 4% of epreneurs, 37 only one ho d of time. Haone third hav
nological res specific reso ent types of s the resource the type of r where firms a me resources, sented above
ING AND
NG cific fields of ons. It was c d 2008: 23 egarded as th responds to o ample is mos and the aver nd 2003 and ) between € conduct R&D around a qu atents. Also o financing (9 f total fundin 7% of them olds a PhD. alf of them ha ve previous i sources, the ources that a sources; searched a relationship are embedde thus influen e will now gD METHO
f biotechnolo carried out u software a he most scien one of the mo stly compose rage number d are located 1 million an D activities. uarter of the only 5 emplo 90%). Eight ng, on averag m hold an M . About 65% ave conducte industrial exp differences are searched and the type that is establ ed is expecte ncing the arcuide our emp
ODOLOGY
ogy and soft sing a sampl and 23 bio nce based gro ost technolog ed of small t of workers i d in the mai nd € 5 million The average total employ oy PhDs. In resorted to s ge. MBA and 10 % have work ed research a perience. in business for (e.g. ca e of actor m lished; d to affect th hitecture of t pirical analys
Y
tware - mole le of 46 Portu otechnology oup of firms gically advan to medium s is 117. Most n metropolit n. The avera e investment yees work in terms of sou some kind of 0% hold a p ked or studi activities at s models will apital) and o mobilised are he availabilit the networks sis. ecular biolog tuguese comp companies. s within the s nced areas. sized firms – companies ( tan areas. A age turnover t in these act n R&D acti urces of fund f public ince post-graduati ied abroad o some point in l have on the e also ty and s built gy and panies . Our sector, – 68% (78%) Around was € ivities vities. ding, a entive, ion in over a n theirIn the gener them techn Not s and th of les The b R&D since avera Out o the w comp techn With resort accou As to in res numb As w firms interm resou opera respe conte stage teleco devel suppo differ e biotechnol ration of Po are still nologies/prod surprisingly, he average n ss than 100 0 biotechnolog D activities ( in a few cas age of the em of 23 compan workers. Thi panies are st nology or pro regard to th ting to vent unted on ave o the entrepr search activi ber had previ was pointed o s’ resource
mediate deve urces and the ating in the ect to some extual condit of develop ommunicatio lopment and ortive, in par rences may h logy sector, rtuguese bio in an emb ducts. Twent most of the number of em 000€. The fir gy companie 78%). Their ses R&D out mployees wo nies, 15 have s high techn till developin oduct onto th he sources of ture capital. rage for 20% eneurs, the v ties, studied ious industria out above, alt
requirement eloped econ e mode of a same count aspects rele tions may v pment and ons operator d its activitie rticular rega have some im the subset se otechnology: bryonic stag ty are researc ese companie mployees is o ms are cluste es exhibit a v r average inv tlays exceed ork in R&D a e at least one nological int ng their tech he market. f funding, 57 Half of the % of the total vast majority or worked a al or busines though secto ts and rela omy - can a ccess to them try, which p evant for the ary substant has benefite rs. Converse es take place rding the ac mpact on the elected – mo 78% have ge and onl ch spin-offs. es are very only 8. In 20 ered around very high R& vestment in turnover. In activities. Ab e PhD holder tensity can b hnologies. In 7% of the fir e companies l funding. y (65%) hold abroad for a ss experience or level deter ationships, t also have so m. However provides a b e activity of tially betwee ed from the ely, biotechn e in an indus ccess to non-networks bu olecular biol been set up ly a few small: 70% 007, 57% of the three ma &D intensity these activi terms of hum bout half of r. On averag be partly exp n fact, 30% rms had exte s have recei d a PhD and significant p e. rminants are the context ome impact u r, even if the basically sim f young tech en sectors. S e high com nology is a strial environ -technologica uilt in each se logy – belon since 2004. have fully have less th f the compan in metropoli y. The vast m ties is 107% man resource the firms (4 ge, PhDs repr plained by th have not y ernal capital, ved public nearly 86% period. How expected to where firm upon the av e firms being milar instituti hnology-inten Software is petitiveness at a more in nment that a al resources. ector. ngs to the yo . Thus, seve developed han 10 emplo nies had a tur
itan areas. majority carr % of the turn es, around 44 48%) have pa resent one th he fact that yet introduce , around one incentives, w % have partic wever, only a strongly infl ms operate vailability of g analysed a ional setting nsive firms, at a more m of the dom incipient sta appears to b . These cont ounger eral of their oyees, rnover ry out nover, 4% on atents. hird of many ed any e third which ipated small luence – an f these are all g with other mature mestic age of be less extual
3.2 D Data comp interv proje interv the e firm’ techn The d of the 3.3 N Using (re)co frame relati Cons (aggr and k the in and c and actors The n with distri netwo are d distin with sever DATA COL about the plementary m views with t cts and pate views, condu entrepreneurs s activities, nological dev
data thus obt eir respective NETWORK g the data ob onstruct the ework, netwo onship. idering the t regate) innov knowledge. T nnovation op commercial c other com s/relations us nature of the a formal/co bution of co orks are mor directly mob nction is not the same or ral authors, f LLECTIO firms (in methods, inv the founders ents and a va ucted in 2008 s’ personal n strategy a velopment an tained includ e contributio KS (RE)CO btained throu innovation orks were re type of reso vation netwo The O&A ne pportunity an channels) as mpetencies) sed to obtain relations wa odified agree ompetences, re spontaneo bilised or ac always clear rganisation a formal ties a N both sector volving both . The forme ariety of inf 8, were based networks and nd perform nd on forma de the origin ns. ONSTRUC
ugh the inter networks f constructed urce, and dr rk is divided etwork is co nd to access well as inta necessary t n scientific an as distinguish ement betwe rights and d ously formed ct as mediat r-cut. The fir at different m are frequentl rs) were co h documenta er included: p formation on d on a semi-s d their impo mance, with al cooperatio of the relatio CTION rviews and th for each se taking into a rawing on th d in two sub-mposed of a s and acquire angible resou to exploit nd technolog hed as forma een actors ( duties and a d, and are fre
tors in the rm sometime moments or ly based on ollected usin ary informat published da n the history structured qu ortance for t particular e on arrangem onships and he document ector. Based account the r he suggestion -networks: o all the actors e the tangibl urces (inform it. The kn gical knowled al or informa usually invo conflict reso equently asso access to th es establishes for different previous inf ng a novel ion and in-d ata about for of the firm uestionnaire t
he innovatio emphasis on ents with ot
the type, nat
tary sources on the pro resource type n of Castilla pportunity a s/relationship le resources mation, mana nowledge n dge. al. Formal ne olving a sys olution devic ociated with he resource. s both formal t purposes an formal relatio l combinatio depth face-to rmal collabo ms’ formation that focused on process a n innovation ther organisa ture and rele
it was possi roposed anal e and nature a et al (2000 and access (O ps used to id (capital, fac agerial know network inc etworks are r stem of auth ce) while inf h personal tie In practice l and inform nd, as stress ons (Powell on of o-face orative n. The d on: i) and ii) n and ations. evance ible to lytical of the 0), the O&A), dentify cilities wledge cludes related hority, formal es that e, this mal ties sed by et al,
1996) each So in secto inform O&A Know 3.4 N A det metho UCIN the fo Acco a mo has a exam conne we in the bi have there ). However, dyadic intera n addition to r: two O&A mal). The co wledge NETWORK tailed analys ods of Soci NET softwar ollowing asp a) Netwo ording to Bur re diverse an an impact on mple, a netw ected). In ad nclude measu iggest compo no external is a lower c our method action. (aggregate) A networks ( ontent of each Tab Funding so Facilities p Service accounting Commerci R&D Proje S&T Partn Patents (pa Origin of transferred K ANALY sis of the co ial Network re. Network
ects are cons
ork size: Th rt (2000), all nd complete n some struct work with a ddition to me ures related t onent). A co connections. capacity to ac dology allow innovation (formal and h network is ble 2 – (Re)co Formal ources providers providers g, IP, marketing al partnerships ects nerships artners; provide technology (i d) SIS mposition an Analysis (W characterisa sidered: he size is an things being set of resou tural network small num easures like t to the existen omponent is a . If a networ ccess resourc ws us to iden networks, fo informal) a presented in onstructed ne (legal, g) In In M ers) if formally In S O nd structure Wasserman ation usually an important g equal, large urces from h k characteris mber of acto the total num nce of compo a set of actor rk is compos
ces. These m
ntify the natu
our different and two know n table 2. etworks conte nformation/adv nformation to i Management kn nnovation (new S&T knowledge Origin of techno of the netw and Faust, involves se t element in er networks m is network. F stics, such as ors is more mber of actor onents (num rs that are co ed of a large measures will ure of the re networks w wledge netw ents Informal vice to build bus dentify/exploit nowledge
w ideas) e
ology (if inform
orks was co 1994) and veral aspects n the analys mean that an Furthermore s density and likely to h rs and the tot ber of comp onnected to e e number of
l allow us to
elations pres
were built for works (forma siness plan opportunities mally transferred onducted usin supported b s. In this res sis of a net n actor can re e, the networ d connectivit have two tha
tal number o ponents and s each other bu small compo compare bo ent in r each al and d) ng the by the search twork. eceive rk size ty (for at are of ties, size of ut that onents oth the
In thi the d from finan organ each usual sourc centra Faust The d centra highe the de direct is cha from strong The b node Then poten other which differ netwo ties ( analy 2 In th b) Networ is research w diagrams): in other secto ncial instituti nisations, inc type of actor c) Actors lly measured ces of resou ality measur t, 1994). degree is the al company est degree ce egree of an a ted towards aracterised b one actor. S g activity. betweenness
with few tie n, the betwee ntial for cont rs, which wou d) Netwo h the variou rent network orks with m (Granovetter yse network c his research o rk Composit we consider s nterviewed fi ors (green c ions (grey cluding prof r is analysed ’ Position: R d by centrali urces (Powel res: degree c e number of is the one w entrality are d actor has two the actor. So by a strong a So a central s measures th es (low degre enness of a n
trol over oth uld be isolate ork cohesion us actors are k configuratio any strong t r, 1973) and cohesion: de nly interviewe tion: Innovat seven types o irms (blue sq circle), univ circle); scie fessional and by consideri Regarding net ity measures ll et al, 199 entrality and direct ties o with the highe
designated hu o different el o a central ac attractiveness actor provid he extent to ee) may play node indicat ers. Brokers ed otherwise : This aspec e linked to e ons in terms ties (Colema d structural nsity and pro
ed firms have n tion network of actor (and quare), firm versities and ence and te d trade assoc ring its share
twork positio s, offer diffe 96).To chara d betweennes
one actor has est number o ubs. In direc lements: the ctor receives s2. The outde des resources which an ac y an importan tes whether a have import e. ct of the net each other. T s of cohesion an, 1988), vs holes (Burt, oportion of s nonzero indeg ks are compo d represent th s from the s d research o chnology pa ciations (pur in the total n on, it is cons erent opport acterise the ss centrality s to other ac of ties (links/ ted networks indegree me s resources f egree shows s to many fi
ctor lies betw nt intermedia an actor play tant, non-red twork structu There is som n, i.e. more d s. more “ope , 1992). Tw strong ties. gree values. sed of differ hem using dif same sector organisations arks (pink rple circle). number of ac sidered that d unities to ac actors’ posi (Scott, 2000 tors in the n /connections s, like those u easures the to from several the number irms and is c ween others ary role and s ys the role o dundant infor ure is related me debate ov densely embe en” networks wo measures rent types of fferent symb (red circle), s (yellow c circle) and The relevan ctors. different posi ccess the re ition we us 0; Wasserma network. The s). Actors wi used in this p otal number o organisation of ties that d characterised in the netw so be very ce of a broker w rmation to g d to the ext over the effe edded or “cl s with many are comput actor. bols in firms circle), other nce of itions, levant e two an and e most ith the paper, of ties ns and depart d by a ork: a entral. with a give to tent to ects of losed” weak ted to
Netw the m gener A dis of tim netwo factor organ asses ties a • • • Netw order ratio netwo struct on ac above level Cliqu all co (Scot conne three than subgr indiv other work density maximum nu
ral terms, the stinction is to me, energy a orks conside rs: the amo nisations (Zh s whether th and the existe the inform the tie is u the firm (nature). works with m r to character between thei e) Netwo ork, allowin ture that is o ctors’ centra e: degree an of centralisa f) Cohes ues are consi onnected to tt, 2000: 115 ected directl members ar one clique. roups. This viduals in the r. is computed umber of po e larger the n o be made be and money t ers that the ount of reso hao and Aram he tie is stron ence of ties o mal contacts used to acce establishes many strong t rise the stren ir number an rk Centralis g the observ organised aro ality measure d betweenne ation. ive subgroup dered to ana each other. 5), the 2-cliq ly or through re taken into . Furthermo coefficient e network, re as the ratio ossible ties. network, the l etween stron to be develo intensity of ources excha m, 1995). In ng or weak: of a different take place at ss different t both forma ties are dens ngth of the t nd the total n
ation: This r
vation of the ound its mos es, this pape ess. They var
ups: Cohesiv alyse cohesiv Since this c que concept h a common account. It ore, the clus
reveals the vealing the e
between the So network lower its den ng and weak oped/maintain f the relation anged and n this paper, the frequen t nature. In th t least once a types of reso al and infor ser than thos ties, we cons number of tie refers to cen e extent to w st central no er considers ry from 0 to ve groups ar ve subgroups concept “is r t is used, tha n neighbour. should be m stering coef e average d extent to whi number of t density is nsity. ties, since th ned. The lite ns can be d
the frequen we take a co ncy of contac
his case, a tie a month (freq ources (multip rmal relation e with a sma sider the pro es.
ntrality meas which it has odes. As cent
the two diff o 1, where 1 re groups o s. A clique is rather restric at is, a cliqu In addition, mentioned tha fficient is c density of t ich the actor
ties present i related with hey require a erature on in depicted as a cy of conta ombination o cts, the exist e is considere quency). plex tie). ns with ano aller number oportion of s sures calcula a centralise tralisation m ferent perspe is associated f mutually s a sub-set of tive for real ue exists wh , only clique at an actor ca onsidered to the groups r’s alters are in the networ h network si a different am nter-organisa a function o acts between of three fact tence of mul ed strong3 wh other organi r of strong ti strong ties, i.
ated for the w ed structure, measures are ectives ment d to the max connected a f actors, whi l social netw hen the acto es with more an belong to o study coh of actors a connected to rk and ze: in mount ational of two n two tors to ltiplex hen: sation ies. In .e. the whole i.e. a based tioned ximum actors. ch are works” ors are e than o more hesive around o each
4. R
4.1 T In thi topol prese acces netwo mark (a (aRESULTS
THE TOPO is section we logy is captu ent the diagra ss - and theorks. The di ked in the cas
a) Biotechno a) Biotechno
AND DIS
OLOGY O e present the ured by the n ams consider nature of t iagrams reve ses of formal ology ologySCUSSION
F INNOVA e actual topo network diag ring the type he relationsh eal differenc l O&A netwo Figure 2 -Figure 3 - IN
ATION NE ology of the grams sketch of the resou hips establis ces between orks and of in Formal O&A Informal O& ETWORKS innovation n hed with Net urce – knowleshed in each the two sec nformal kno A networks (b &A networks (b S networks in tdraw softwa edge vis-à-vi h case – for ctors, which wledge netw ) Software ) Software both sectors are. Figures vis opportunit
rmal and inf seem to be works. s. This 2 to 5 ty and formal more
(a (a If we each appea differ which mode these a) Biotechno a) Biotechno e aggregate a sector, the d ar to be qui rences betwe h is the only es of access two technol ology F ology
all the resourc differences b ite similar (F een the netw y one able to to these res logy-intensiv Figure 4 - Fo Figure 5 - Info ce-based netw between the Figure 6). T orks of the tw o unveil the sources are e ve sectors. ormal knowle formal knowl tworks and b diagrams ar This suggests wo sectors h sectoral spe effectively i edge network (b ledge network (b
uild the aggr re significan s two conclu have to be ca ecificities; an mportant so ks ) Software ks ) Software regate innova ntly reduced usions: first, aptured at a d nd second, t urces of net ation networ and the netw , that the ex disaggregate that resource twork variat rks for works xisting level, es and ion in
(a We c recon subse 4.2 M In thi startin netwo consi the ti 4.2.1 In ter consi of th consi netwo greate highe The c predo a) Biotechno compute and nstructed net equently con MAIN CHA is section w ng with biot orks, we poin idered in our e. Innovation rms of netwo ider the natur he number o ideration. Th orks also hav er than in in er connectivi composition ominate in O F ology analyse the tworks. Base duct a comp ARACTER e present a d technology. nt out aspect r analytical f networks in
ork size, the re of the tie. of actors and hus, innovatio ve a smaller nformal ones ity. of the netwo O&A networ igure 6 - Agg above menti ed on these arison betwe RISTICS O description o More than p ts that are dis framework: t n biotechnol data (Table Formal netw d the numbe on networks number of c s (more than orks is strong rks and univ gregate innov ioned social data, we w een the two s
OF SECTO
of the four r providing a stinct and rel the type of r logy 3) show tha works are mu er of ties, r are clearly d components a n 90% of all gly affected b versities in k vation networ (b network mea will first desc
sectors. ORAL NET reconstructed comprehensi late them wi resource and at substantial uch larger tha regardless of dominated by and the weig l actors vers by the type o knowledge ne rks ) Software asures to full cribe their m TWORKS d networks in ive descripti th the two so d the mode o l differences an informal o f the specifi y formal rela ght of the lar sus around 7 of resource. A etworks. Thi ly characteri main feature n the two se ion of each ources of var of access/natu s emerge wh ones both in fic resource ationships. F rgest compon 70%), indica As expected, is result is i ise the es and ectors, of the riation ure of en we terms under Formal nent is ating a firms in line
with with t Still netwo netwo intera S&T a grea We w The i only influe Size Comp (%) Cohes Centr actors Netwo centra (%) Cohes subgr the science-d the need to i regarding c orks. Unive orks. This m action with u parks and fi ater informal want to high interviews su on business ence of VC a N N N S position F F U S F O sion D S rality of s (average) D B ork alisation O I B sive roups C N driven nature interact with composition, rsities and may be rela universities a inancial insti lity in the int hlight the we uggest that issues but a actors therefo Table 3 – No. of actors No. of ties No. of compone Size of largest c Firms from sam Firms from othe Universities S&T Parks Financial institu Other Density (overal Strong ties (%) Degree* Betweenness* Outdegree Indegree Betweenness Clustering coef No of 2-cliques e of the secto other firms i , we can a firms from ated with th and powerfu itutions have teraction wit eight of finan some ventur also on the d ore goes bey – Innovation ents component me sector er sectors utions l) fficient (%) s or (universit in the access also find di other secto he need to a ul customers. e a stronger p th these type ncial institut re capital (V directions of yond the acce network ana Formal 229 620 3 224 14 41 24 4 4 13 0.8 14 4 (0.8) 4.4 (8.8) 2.7 20.5 0.6 68 45
ies are the m s to resources ifferences be ors are more appropriate . Inversely, c presence in i s of actor. tions in the VC) compani research to p ess to financi alysis in biote O&A Informa 43 34 12 10 44 30 7 7 7 5 2.4 71 2 (1.0) 0 (0) 5.9 5.9 0.0 0 11 main source o s to exploit o etween form e strongly p the innovati companies in informal netw informal kno ies play an a pursue in the ial resources. echnology al Forma 203 213 8 183 21 22 54 0 0 3 1.1 6 1 (0.8) 0.2 (14.2 0.9 17.9 0.1 15 25 of knowledge opportunities mal and inf present in f ion results i n the same s tworks, sugg nowledge net advisory rol e early years . Knowledge mal Infor 10 10 9 7 3 1 4 2 4 5 2. 7 ) 3 (0. 2) 0. (8. 2. 9 6. 0. 3 3 e) and s. formal formal in the sector, gesting twork. le, not s. The rmal 04 02 9 4 1 2 6 2 4 5 .5 3 3 .7) .1 .5) .1 .7 .1 3 6
Look the n becom denot forma and th The m seem O&A betwe forma netwo core-ones. The struct some case, Cons existe Takin relate highe forma Final numb comm netwo joint king at the co nature of the me visible ag ting higher l al knowledg heir high vol measures of ms to be a cro A network sh eenness cent al access to orks and me periphery w centralisatio ture is more e highly attra differences idering the ence of a cen ng the cluste ed to the na er proportion al O&A netw lly, all netwo ber of sub-se mon neighbo orks. Thus, w action of the ohesion mea tie. Therefo gain: inform levels of inte ge network is latility (Hage the actors’ c oss-over effe hows the high
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mposed of se s, all of whi mber of cliqu differences b pe and the na an see that th ntrasts betwe are denser a d trust. The v
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err and Powe ferences betw type and the ndicating a h kerage posit value of the c nness) sugge actors and te if it has ormal netwo nded by mor ularly associa either a gre again visible tworks are m ”. This situa ques, revealin nected to eac r in formal O networks wh tie. ious differen and informal igher proport roportion of logical allian ell, 2003). ween the netw
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nces are rela l biotech net tion of stron f strong ties nces in this works. Here, he tie. The f ty, and the h major role of variation f stence of a m mber of perip ed structure. g the existen actors. So i e nature of th n of values o ain differenc onnected in icularly inten y comprise a ectly or thro formal know o be caused b ated to works g ties, in the sector , there formal highest in the for all model pheral That nce of in this he tie. or the es are that a nse in a large ough a wledge by the
4.2.2 We c Starti tie. K netwo all ne of res The c the in with unive same inform Size Compo (%) Cohes Centra actors Netwo central (%) Cohes subgro Innovation
can also obs ing with size Knowledge n orks are larg etworks, but source, being composition nnovation pr the type of ersities is con sector is p mal bartering N N N S osition F F U S F O ion D S ality of (average) D B ork lisation O In B ive oups C N networks in serve differe e, the distinct networks are ger than infor the weight o g much highe of the netwo rocess of so f resource an nsiderably hi particularly g at the horiz Table No. of actors No. of ties No. of compone Size of largest c Firms from same Firms from othe Universities S&T Parks Financial institu Other Density (overall Strong ties (%) Degree* Betweenness* Outdegree ndegree Betweenness Clustering coeff No of 2-cliques n software ences betwee tive features much more rmal network of the largest er in knowle orks reflects ftware comp nd the natur igher to acce significant zontal level t e 4 – Innovati nts omponent e sector r sectors utions ) ficient (%) (n≥3) en the recon are induced e populated t ks. Data show t component dge network the fact that panies. How re of the tie ess knowledg in informal that characte ion network a Formal 86 80 7 32 39 50 2 3 3 3 1.6 27 2 (1) 0.14 (6.2) 3.0 6.6 0.1 0 21 nstructed ne d by the resou than O&A n w a very sim t differs, espe ks. firms are th wever, we ca . First, not ge. Second, t networks, rises the indu analysis in so O&A Informa 23 17 6 11 48 26 13 - 4 9 2.1 53 2 (0.9) 0.04 (4.7) 3.9 13.4 0.2 0 7 tworks in so urce type and networks. Ad milar number ecially if we e major reso an find some surprisingly, the presence indicating th ustry. ftware al Form 484 525 6 464 13 44 38 0 - 5 1.5 25 2 (0.7) 0.56 (21.1 0.7 34.2 0.1 6 48 oftware (tab d the nature dditionally, f r of compone e consider th ource provide e variation r , the relevan e of firms fro the typical s Knowledge mal Infor 4 7 5 7 6 4 6 4 2 2 -1 2. 6 ) 2 (0. 6 1) 0.5 (7. 3. 2 8. 0. 1 2 ble 4). of the formal ents in e type ers for related nce of om the strong rmal 4 3 6 0 3 6 0 - - 1 .3 3 2 .9) 58 .4) .6 .7 .7 1 6
The d relate of the inform The i powe existe netwo know resou Look forma some The c very resou All n know to the clique density value ed with the n e tie influen mal network innovation n er, as denoted ence of a m orks, but be wledge netwo urces. king at the ov al knowledg e highly centr clustering co few alters. H urce, since kn networks exh wledge netwo e nature of t es. es of the var nature of the nces the inten ks is clear-cut networks are d by the high model core-p etweenness c orks. This in verall central ge network w ral software oefficient dis However, it nowledge net hibit sub-set ork. Here we the tie: form
rious network tie: informal nsity of the t. highly heter h coefficient periphery. T centrality is ndicates a gr lisation, we c when indegre firms that ar splays very l is possible tworks are m ts of connec e can see diss mal networks ks are quite l networks a relations sin rogeneous in t of variation The average influenced b reat relevanc can observe t ee centrality re surrounded low values in to observe s more clustere cted actors, similarities r s and knowl similar. How are slightly d nce the highe
n terms of th n of the centr degree ass by the type ce of broker that a central is considere d by more pe n all networ some differe ed. which abou related both t ledge networ wever, we ca enser. Additi er proportion heir structure rality measur sumes the s of resource rs in the acc lised structur ed, suggestin eripheral acto ks, revealing ences related und particula to the type o rks exhibit a an find differ tionally, the n n of strong t e of influenc res, suggestin same value e and is high cess to know re only emer ng the presen ors. g that actors d with the ty arly in the f of the resourc a large numb rences nature ties in ce and ng the in all her in wledge rges in nce of share ype of formal ce and ber of
4.3 C As n secto the ti discu frame the m 4.3.1 As pr the s provi In bo result metho mobi those depar those amon and S We a resou more secto resou As ex are o trust intera impo the li obtain COMPARI noted before, r. These diff ie. In this s uss similariti ework, we re mode of organ Regularitie reviously sta ectoral netw ides some ins oth sectors (a t, which so odological o lised only by e that were re rts from the e studies focu ng firm empl Schultz, 1993 also found s urce, informa firms from rs and of for urces used to xpected, info ften associat and reputati actions. For rtance for th terature of e ning financin ING NETW , we can fin fferences may ection, we p ies and diff elate the diff nisation.
es across sec
ated, the natu works. Howe
sights into th and for both mewhat con options, nam y the entrepr egarded by e majority of us on knowle loyees or bet 3). some regular al networks i other sector rmal relation identify and ormal networ ted with the ion. The liter example, in he acquisitio ntrepreneurs ng through V WORKS OF nd differenc y be associa present a co ferences betw ferences with tors
ure of the tie ever, some r he characteris resources), ntradicts the mely the fa reneurs. Furth entrepreneur the studies edge flows a tween firm e rities in the nclude more s. This resul ns across sect d exploit new rks are dense trajectory o rature refers innovation on of high-va ship, Shane a VC. F THE TW es between ated with the omparison be ween the re h the type of e is an impor regularities c stics of form formal netw e innovation act that we hermore, we rs as importa examining t and on inform employees a composition e firms of the lt points to th tors. Additio w opportuniti er and chara of the individ to the impo networks, D alue knowled and Cable (2 WO SECTO
the four rec e type of the etween the t espective ne f resources n rtant source o can still be mal and inform works are big
n literature, are consid e only includ ant. Because the informal mal know-ho nd researche n of sectora e same secto he prevalenc nally, firms es. acterised by s duals and thu ortance of tru Dahl and Ped
dge through 002) stress t ORS constructed resource an two sectors. tworks. Usin eeded for inn
of variation found across mal networks ger and mor
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are the most
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networks in nd/or the natu
We identif ing our anal novation and in the topolo s sectors an s. re connected related wit nformal netw ” informal ti tions, this an networks. In ctivities that ard, 2009; K regardless o l networks in al relations w t relevant ori Informal netw ss higher lev utation in inf 4) underscore etworking. A ce of reputat n each ure of fy and lytical d with ogy of nd this d. This th our works ies i.e. nalysis n fact, occur Kreiner of the nclude within igin of works vels of formal e their And in tion in
All n existe very In kn that s obser i.e., n Altho simila we an them 4.3.2 Starti the o institu (infor requi acade As ex of op oppor resort new o Still i resou comp comp many part, and h Know natur inform networks are ence of core-central actor nowledge net some firms rve that form networks whe ough biotech arities, they nalyse them in the light o Sectoral dif
ing with com organisation utions, not o rmal O&A rements for emic spin-off xpected, the pportunity. S rtunities, sin t more to un opportunities in the contex urces throug panies favou panies resort y universities software com human resour wledge netw re of relevant mal) are dom
extremely h -periphery si rs coexists w tworks, inde rely extensi mal relations ere more firm hnology and also have re at a disagg of our analyt fferences in mposition, re of the secto only to access and knowle the develop ffs and the les composition Software firm nce customer niversities, re s. xt of O&A n h universitie r informal ti t to universit s in the Portu mpanies mob rces. works also di t knowledge minated by u heterogeneou ituations in t ith a large nu egree central ively on form to access kn ms share the d software elevant diffe regated leve tical framewo the network esults show d ors. Biotechn s tangible res edge networ pment of new sser maturity n of the O&A ms resort mo
s are the maj eflecting the
networks, we es: biotechn ies. We can ties for acce uguese Healt bilised inform isplay some in these sect universities, us in terms o the structure umber of per lisation is hi mal partners nowledge are same partne innovation erences in co el. We will n ork. ks composit differences re nology firms sources (form rks). These w biotechno y of compani A networks a ore to firms i ajor source of importance e also find str nology firms relate this r ess to labora th Cluster (w mal ties with
interesting tors: in biote while firms of centrality of power an ripheral ones
gher for form ships to acc e associated w ers. networks d omposition a now turn to tion elated with t s resort more mal O&A) bu results are ology techno
ies in this sec also reflects in the contex f new ideas, of scientific riking differe s prefer form result to the atory faciliti we will retur h universities differences, ech, knowled s play the le of actors, th nd influence. s. mal relations ede knowled with more cl display the and structure those differe the types of e to S&T pa ut also inform related to ology, the gr ctor. differences i xt of the iden and biotechn c research in ences in the mal relation fact that ma es and to th rn to this issu , mainly to a which can dge networks ading role in hus pointing . So a small s, which ind dge. We can lustered netw above ment e, especially rences and d resource and arks and fin mation and a time and c reater presen in the main s entification o nology comp the emergen mode of acc ns while sof any biotechn he participati ue later). For access inform be related t s (both form n software. to the set of dicates n also works, tioned when discuss d with nancial advice capital nce of source of new panies nce of cess to ftware nology ion of r their mation to the al and These
