University-related science parks - 'seedbeds' or 'enclaves' of ...

0. Felsensteina supportive environment for the development ofinnovation, creativity and entrepreneurship.The above description stresses the seedbed roleof the science park in a behavioural sense.However, another set of expectations of scienceparks relates to their function in a regionaleconomic development sense. Science parks areinvariably associated with more than just a rolein promoting innovation and entrepreneurialism,and a successful science park is viewed as morethan an innovation-generating environment. It isoften - wishfully - ascribed with the propertiesof a growth sector leading the area under questioninto a spiral of propulsive expansion [4, 51. Thefew success stories notwithstanding, the reality israther more mundane. The science park as acatalyst in urban and regional growth is not a welltroddenpath and, despite public policy rhetoric tothe contrary, few examples exist of science parkledlocal economic development [6].The common ground between the behaviouraland spatial conceptions of the seedbed lies in thenotion of the seedbed as creating an environment.This environment, while occupying dimensions ingeometric space, is not exclusively spatial. Itrepresents a ‘milieu’ in both the functional andbehavioural sense, as well as the geographic.Amongst the principal factors of production inscience park development are information andknow-how which are inherently unconstrained byspatial boundaries. The science park as a seedbedfor innovation is more than just a physical concentrationof units of production benefiting from thelinkages and economies of scale and scope thatagglomeration affords. As will be seen below,these advantages are not often realized and theinnovation process does not seem to be contingenton them.There must therefore be a further aspect of theseedbed environment that is related to behaviouralfactors and is also important in understanding therelationship between science park location andinnovation. This relates to the network environmentof the firm that comprises the informaland non-institutionalized flows of information,knowledge and collaboration based on contacts,work experience, education and so on. Thesefactors, while difficult to quantify, add a furtherdimension to the seedbed function of the sciencepark and also transcend its narrow spatial confines.This paper examines the relationship betweeninnovation and science park location and, in sodoing, highlights these different conceptions of theseedbed function. An empirical analysis, based onevidence from science parks in Israel, is presented.While no attempt is made to determine thedirection of causality between level of innovationand location on a science park (does science parklocation make for more innovative firms, or dothe more innovative tend to cluster in scienceparks?), we are interested in unravelling some ofthe relationships between innovation, location andthe behavioural characteristics of science parkcompany entrepreneurs and managers. This willshed light on the seedbed functions of the sciencepark, both behavioural and spatial.More specifically, the paper proceeds in thefollowing manner. The main tenets of the seedbedenvironment, from both a behavioural and a spatialperspective, are highlighted in the next section,and the empirical evidence for science parks asseedbeds is presented. This is followed by ashort description of the context within which theempirical work is set, and a formulation of themain hypotheses. Data limitations and issues ofmethod are then discussed and this leads on tothe empirical findings. On the basis of a surveyof over 160 Israeli high-technology firms and threemajor university-related science parks, some of therelationships between behavioural characteristics,science park location and innovation level areestimated. The significance of these findings withrespect to the role of science parks in the innovationprocess, and their policy implications, are presentedin the concluding section.2. The seedbed environmentIn defining the conditions that give rise to theseedbed environment, a distinction needs to bedrawn between the spatial and the behavioural94 Technovation Vol. 14 No. 2

Science parks - seedbeds or enclaves of innovation?approaches. From a spatial perspective, theexogenous factors nurturing and promoting innovationat a given location are integral componentsof the seedbed environment. Much effort has beenexpended in identifying those areas that have‘good’ incubator conditions based on city size,level of urbanization, institutional structures andcommunity characteristics [7, 81. While the evidenceon the impact of these influences oninnovation is mixed, it does seem to suggest thaturban areas are not particularly important marketsfor the development of innovative activity. In fact,a study of the incubator function of the Raandstadcities in Holland has shown these locations to beunder-represented in terms of innovative activity[9]. The spatial seedbed hypothesis of an indigenousregional impact supporting innovation could thereforenot be supported and the study suggestslooking at intra-firm characteristics for furtherexplanation.While this spatial approach relates to the determinantsof innovative activity, other approacheshave looked, from this same perspective, at thedeterminants of the incidence of industrial andscience parks. The presence of industrial parks ingeneral has been related to city (or community)size and age, population densities and populationgrowth rates [lo]. Looking more specifically atscience parks, Luger and Goldstein [ll] havedemonstrated the importance of size of metropolitanarea, linkage to a local university and level ofservice offered, in explaining science park successas measured by employment generation. Conversely,parks located in small areas and withoutuniversity connections are the most likely to fail.This identification of seedbed characteristics hasnot been without its critics. As an approach tounderstanding location tendencies it has beentermed ‘analytically sterile’ [12 (p. 219)] and it isclaimed that innovative places cannot be ‘read-offon the basis of the ‘right’ exogenously determinedcharacteristics. Furthermore, such an approach, itis argued, misses the subtle role played by industrialorganizations and overlooks the social divisions oflabour that have allowed the seedbed to emerge.In essence, a behavioural component of seedbedformation is missing. This would include the roleof exogenous organizations or institutions such asuniversities, the role of other firms in promotingor discouraging spin-offs, previous work and educationalbackground of entrepreneurs, and so on.From a behavioural perspective, the seedbedenvironment is composed of a knowledge infrastructure(such as a university or research institute)that creates positive externalities that becomepublic goods. These institutions can also includelocal chambers of commerce, banks, venture capitalcompanies and so on. These are all milieu-creatingorganizations [13] in that, when they occur withina given area, they create an information- andtransaction-intensive complex that not only provideseconomies in scale and scope and cost savingsin transactions but also reduces risk [14].Other firms also have an important role to playin fashioning the behavioural environment. Theyare sources of knowledge and externalities no lessthan the institutions mentioned above. As Acs andAudretsch [15] point out, other firms (competitors,collaborators) are repositories of know-how andwork experience. Some of this is accessed throughformal sources such as contracts and licensingagreements while some is generated through meetings,trade fairs, informal contacts and intermediariessuch as suppliers and consultants. Where allthis occurs in a given environment such as ascience park, the spatial and behavioural factorsinterchange. However, as Birley [16] has pointedout, in a local environment one of the maininformational shortcomings is the lack of kncwledgeas to what information is in fact available.This would seem to suggest, for example, thatfirms choosing to locate on a science park maynot necessarily be exercising this choice becauseof its perceived seedbed function. They often setupwithout a proper screening process of theenvironment, and their location choice may bepart of a ‘social signalling’ process [17]. Theseedbed properties of the environment (access toinformation, networks etc.) are then probably onlyrealized at a later stage. This could also seem tosuggest that initially the innovative capacities of anew firm in an environment such as a science parkTechnovation Vol. 14 No. 2 95

D. Felsensteinare not fully exploited. This is because innovationis related to the seedbed environment, which ishypothesized to be an unknown quantity at theearly stages of firm development.3. Science parks as seedbedsEvidence exists suggesting that, in spatial termsat least, universities do have a seedbed effect ontheir local economies. A series of aggregateanalyses on the effects of universities on metropolitanareas or regions in the United States hasshown this effect to be wide ranging. ThusJaffe [18] has found a relationship between firminnovation rates (measured by patents) and thelevel of local university research. This suggests theexistence of technological ‘spillovers’ that benefitfirms in proximity to universities. Further evidenceof this aggregate spillover effect comes from Bania,Eberts and Fogarty [19], who attribute higherlevels of .new firm formation rates to those placeswith concentrations of highly skilled universitylabour, and from Beeson and Montgomery [20],who suggest that this spillover effect can alsoaffect occupational composition. They show thatthe level of R&D funding at a local universityincreases the odds of being employed locally as ascientist or engineer or being employed in a localhigh-technology industry. This seedbed functionalso serves to entrench future rounds of growthas evidenced by universities’ ability to attractscientific infrastructure. For metropolitan areas, ithas been shown that industrial R&D labs tend toconcentrate in those areas where levels of universityresearch are highest [21]. This relationship hasalso been found on the basis of case-study analysis[22].1It should be noted, however, that evidence fromoutside the US is more equivocal. In the case ofJapan, for example, Eto and Fujita [28] reject thehypothesis that universities are instrumental ingenerating high-tech firm growth. They find strongevidence of the self-entrenching effects of hightechgrowth and that scientific-industrial agglomerationswill tend to reproduce themselves. This canoften take place in proximity to leading universities,although they find no real causality in this process.Similarly, Florax and Folmer [29] show that, inthe case of Holland, the diffusion of knowledgeis not necessarily a function of spatial clusteringaround universities. This seems to imply littlespillover effect, in small countries at least.Overall, however, the claims for a significantuniversity seeding effect on the local economy,with respect to innovation level, new firm startuprates, occupational composition and so on,seem to be well founded. Evidence attributing asimilar role to science parks, however, is rathermore mixed. In terms of new firm formation,Massey et al. [6] find mixed evidence for Britishscience parks. On the one hand, new start-upsform a clear minority (less than 30%) of firms onscience parks and in much celebrated seedbeds,such as Cambridge, this figure is less than 10%.On the other hand, new start-ups on science parkshave a much lower mortality rate than that of newfirms in general (less than 2.5% a year). Thiscould however reflect a screening process forscience park entry that selects only firms withgood survival chances. In the US, case studyevidence shows great variation. On the ResearchTriangle Park, for example, over 70% of firms arepart of multi-plant organizations whose existencecannot be attributed to the park. The Universityof Utah Research Park, on the other hand, haslocal, single-plant organizations comprising morethan half the park population [ll].Science park-based spin-offs that trace their rootsto the university are another seedbed characteristic.While much attention traditionally has beenfocused on existing firms spawning new firms [30],spin-offs emanating from a university environmenthave received much less attention [31]. Nevertheless,accounts of locally based company genealogiesnearly always put the local university or sciencepark at the apex of any ‘family tree’ account ofseedbed growth.Survey evidence from firms located on Dutchand Belgian science parks indicates that only 37%of firms in the former and 16% in the latterattribute their origins to universities [32]. In the96 Technovation Vol. 14 No. 2

Science parks - seedbeds or enclaves of innovation?US, again the variation across individual parks isvery great. Thus, Luger and Goldstein [II] havefound that over 120 spin-off companies in thevicinity of the Stanford Research Park haveuniversity antecedents whereas for the ResearchTriangle Park the number of university spin-offsis virtually nil. Massey et al. [6] show that, forUK science parks, on aggregate 25% of firms mayhave their beginnings in academia although someof these are likely to be analytic service units ortechnical troubleshooting operations that, prior tothe establishment of the science park, were locatedwithin the university. Even at the level of theindividual park unit, while a location such as theCambridge Science Park is much heralded as aspin-off incubator and (in 1987) nearly 400 localfirms owed their ultimate origin to the localuniversity in one way or another, direct universityinvolvement in their establishment was much morecircumspect. Segal Quince Wicksteed [33] reportsthat less than 20% of new companies were formedby direct university entrants.If the science park functions as an effectiveseedbed, it is assumed that the level of R&Dconducted by firms located on science parks isgenerally higher than that of off-park firms andthat this reflects the level of (close) interactionpresumed to exist between science park firms andthe local university. The science park is thusperceived as an important conduit in technologytransfer out of the university and into the localeconomy.Van Dierdonck et al. [32] present a ratherdifferent picture based on science parks in Belgiumand Holland. They show rather low levels ofinteraction performance between park tenants andlocal universities, with the overall level of R&Dactivity performed on the park being lower thanpopularly anticipated. Only 32% of Dutch firmsand 57% of Belgian firms surveyed reported inhouseR&D, and little R&D interaction wasreported with either local (science park) firms orthe local university. In fact, for many science parkfirms, external research linkages were not locallydefined and were conducted on an internationalscale, pointing to the existence of research networksunconstrained by national boundaries. Similarly,Massey et al. [6] find science park tenant firms inthe UK less ‘leading edge’ than generally imagined.On the inputs side, over 40% of employees onparks were scientists and engineers2 and R&Dexpenditures in relation to sales were very high.On the outputs side, despite a greater propensityto patent amongst on-park than off-park firms,most firms were found to be engaged in modificationof existing technologies rather than thedevelopment and production of totally new innovations.Complementing this picture is the evidencepointing to the generally low level of links betweenscience park firms and local universities. Mostaccessing of academic resources relates to lowlevelcontacts based on recruiting university graduates,or informal contacts [6]. Joint research orsubcontracting relations are much less profuse.For UK science parks only 14% of companiesreported such links, and a survey of two majorparks in Israel reported a similar figure [34]. Firmson US science parks have also indicated thatrecruitment of graduates and use of universityfacilities form their main points of contact withuniversities. Thus, for both the Research TrianglePark and the University of Utah Research Park,technology transfer to local firms (both on- andoff-park) was low [ll]. For these firms the localuniversity was not a particularly important sourceof R&D inputs or innovations. Even for theStanford Research Park, generally accredited withbeing an archetypal ‘seedbed’, local firms did notreport a significant seeding effect. Thus, while80% of on-park firms reported links with Stanford,over 70% of off-park firms said they had noconnection.These observed levels of university-science parkinteraction have led to suggestions that hightechnologyfirms are more dependent on linkagesand information flows from other similar firmsthan on interaction with universities [35]. If thisis the case, there should be evidence of sciencepark firms seeding the local economy throughtheir material input-output patterns. However,examining the external purchase and sales linkagesTechnovation Vol. 14 No. 2

D. Felsensteinthat science park firms have with local off-parkfirms, it becomes apparent that in many cases thesestructures are limited. This is hardly surprising inview of the increasingly national and internationalmarkets that high-technology firms are serving [36,371. When the local market is also a leadingmarket nationally, science park firms are likely toseed the local economy in terms of inputs andoutputs. Thus, while firms located on the StanfordResearch Park have heavy reliance on Californiafor non-labour inputs, firms in the ResearchTriangle Park have little interaction with eachother or with off-park firms [ll]. Limited salesand purchase links with the local economy havealso been reported in the case of Cambridge, withover 70% of local firms reporting either no linkagesor interactions of minor significance [38]. Similarevidence with respect to external material linkagesexists for science park complexes in both Canada[39] and Australia [40].The level of inter-firm linkage is of courseheavily contingent on factors exogenous to thescience park, such as firm organizational structureand market structure. Science parks characterizedby branch plants are likely to have less localproducer-supplier relations than parks composedof independent, single-facility units [41]. Marketstructure, similarly, is likely to dictate the level oflocal linkage. Customized production rather thanmass production is more likely to have a localseeding effect in terms of external linkages andspin-offs [42].It should be noted that, even if local linkagestructures are weak, this does not mean that thetotal impact of the science park on the localeconomy is negligible. Input-output studies thathave tried to capture the induced effect onlocal incomes, output and employment point toconsiderable impacts attributable to the sciencepark. In employment terms, Luger and Goldstein[ll], for example, estimate total employmentimpact (direct and indirect) as ranging from over4000 jobs for Utah to 75000 jobs in the case ofStanford3. While this represents much more thana seeding effect, it does indicate the growthpotential of a process that expands by a fixedmultiple of its initial injection.While the behavioural factors inducing seedbedformation have been examined in relation toinnovation and the entrepreneurial process ingeneral [l, 161, they have not been studied withrespect to science park firms in particular. If thescience park does function as a seedbed forinnovation, then we might expect to find differencesin these behavioural factors between on- and offparkfirms. However, a case study of the CentralFlorida Science Park and its environs could notsupport this contention. The behavioural milieu,from which chief executive officers (CEOs) ofboth science park and non-science park firmsemerged, was very similar with respect to workexperience, educational background and managementskills [37].4. The setting and hypothesesUniversity-related science parks in Israel are aresult of a government decision taken at theend of the 1960s to improve university-industryinteraction through the establishment oftechnological-industrial complexes in proximity tomajor universities. Over the 197Os, four suchcampuses were constructed, associated with theWeizmann Institute of Science at Rehovot (a citysouth of Tel Aviv but lying within the Tel Avivmetropolitan area), the Technion - Israel Instituteof Technology - at Haifa, the Hebrew Universityof Jerusalem and Tel Aviv University. Firms fromthree out of these four major parks are surveyedhere (the exception being the Technion).These parks were constructed with the help ofliberal government assistance administered underthe Law for the Encouragement of Capital Investment, Israel’s principal vehicle for assisting industry[43]. Prospective tenants for the parks were to bescreened by the Office of the Chief Scientist atthe Ministry of Industry and Trade, and the finaldecision on acceptance was to be in the hands ofthe local park authorities. In practice, a lack ofclear selection criteria resulted in a more haphazardentry process [43] and each park eventually createdits own set of entry qualifications in line with thegeneral objectives and character of the specificpark.98 Technovation Vol. 14 No. 2

Science parks - seedbeds or enclaves of innovation?Site development and park management varyfrom case to case. In all parks there is formalassociation with the university although, in practice,academic involvement in management anddevelopment is minimal. Thus, in Rehovot, theuniversity has vested all its authority in a privatedevelopment company. In Jerusalem, responsibilityfor the park is divided between local government,a recently privatized city development corporationand the various large tenants in the park whogenerally deal directly with central government.Needless to say, this situation is not withoutproblems [34] and in recent years the universityhas reduced its involvement in the park to aminimum. In Haifa, the city’s economic developmentcorporation has set up a subsidiary tomanage, develop and promote the park; and inTel Aviv, park management is similarly in the handsof a joint local authority-university subsidiary.The parks therefore represent planned environmentsinitiated and originally promoted by centralgovernment but whose development trajectoryhas, over time, devolved to local government andits institutions. Only in one of the four cases havedevelopment and management been handed overto private interests.Physically, all parks have been developed inmajor urban centres but on sites distinct fromexisting industrial areas and generally in proximityto residential neighbourhoods.Turning now to the hypotheses, this paperexamines the contention that, in practice, scienceparks function more as enclaves of innovationthan as seedbeds. The empirical evidence reviewedabove has served to stress the rather limitedseedbed role that most parks play, especially inrespect to linkages with local universities, newfirm formation, incidence of spin-offs and linkageswith the local economy. The performance of parksin all these spheres and their rather constrainedinteraction patterns suggest that parks may functionas ‘islands’ of innovation (see [6], p. 53) or ascollections of firms with no real links betweenthem. While we are not proposing that the physicalconfiguration of the park has any role to play inits functional sense as a seedbed, we can hypothes-ize that the geographic separation that characterizesall parks serves to buttress their enclave-typecharacter. This suggests that if location on ascience park is not that important an input forinnovation, its importance to tenant firms may liein the status and prestige effect that it generates.More specifically, this major hypothesis is testedvia an examination of those interactions andrelationships (both direct and indirect) that existbetween science park location, innovation andvarious characteristics likely to relate to the firm’sinnovation level and associated with the seedbedfunction in a behavioural sense (for example,relationship with universities, spin-off history ofthe firm, education and work experience of theentrepreneur or manager). Thus, in relation tothe innovation level of the firm, we would expectto find the CEO’s educational background anduniversity linkages related to the level of innovation.This would illustrate the classic humancapital influences on innovation. If the sciencepark fulfils a seedbed function for innovativeactivity, then we would expect to find science parklocation related directly and indirectly to thesecharacteristics and to others such as CEO workexperience, firm’s spin-off history etc. Conversely,absence of these relationships would suggest theenclave function of the science park.5. Data and method5.1. DataThe data source for the empirical analysis thatfollows is a questionnaire survey of 162 Israelihigh-technology firms. The survey endeavoured tocover all firms located on the three target scienceparks (some 110 firms). In practice, responseswere received from 73 firms (66% of the targetpopulation). The remainder of the firms weredrawn on a stratified basis from off-park locationsin the vicinity of the science parks (the Herzliya,Petach Tikva and Holon industrial zones forscience parks in the Tel Aviv metropolitan area),the various industrial zones in Jerusalem for theTechnovation Vol. 14 No. 2 99

0. Felsensteinpark in that city and a further group of ‘other’(generally metropolitan) locations (Table 1).On a sectoral basis, we can point to a certainlevel of local specialization (Table 1). Thus, firmsin the Tel Aviv area would seem to be concentratedin the electronics and software sectors while theRehovot area is characterized by a large collectionof biotechnology and chemical firms and Jerusalemby chemicals, electronics and electro-optics. Ineach location, the sectoral composition of on- andoff-park firms is very similar, as are their industrialand employment characteristics.The industrial and employment profile of thesurveyed firms is outlined in Table 2. As theaverage figures belie the importance of the smallfirm sector in the sample, the means for this subgroupare presented separately. Small independentfirms form the vast majority of the sample (65%of firms surveyed have less than 50 employees and67% are of independent ownership). In generalthey are younger and more technology intensivein terms of inputs (percentage of R&D employees,R&D expenditures etc.) but, as expected, lesscapital intensive and production oriented.In the present analysis, approximately 12% ofresponses were incomplete in one way or another,leaving a total of 142 usable responses. Theseprovided data relating to (a) firm characteristicsand (b) the characteristics of the entrepreneurs ormanagers of the firms surveyed. In most cases theowner-manager of the firm was interviewed. Failingthat, the data relate to the characteristics of thesenior company executive that responded to thequestionnaire. All the data used are categoricaland the variables are defined in Table 3.Firm characteristics refer here to the firm’slocation, innovation level, location of main markets,level of interaction with university and spinoffantecedents. Entrepreneur/manager characteristicsdescribe the education level and work experienceof the firm’s owner-manager and also theextent to which the entrepreneur or manager isengaged in production of products with which hehas prior experience.In view of the relatively limited number ‘ofobservations and the prospect of empty cells whenusing n-dimensional cross-tabulations, the variablesabove have been coded into a minimal number ofTABLE 1. Location and sectoral composition of firms surveyedn % % located % % % % optical % % Totalon chemicals and electrical and transportation and software otherscience pharma- electronic equipment3 precision engineering’ branchespark ceuticals’ equipment* equipment’Tel Aviv Metropolitan Area 62 39.0 24.0 2.3 52.3 4.6 20.5 20.3 100(Herzliya, TA, Petach Tikva)Rehovot 36 22.0 91.0 39.3 35.1 10.7 10.7 3.6 100(Nes Ziona and Rehovot)Jerusalem 35 21.0 52.0 30.5 30.8 3.8 23.1 7.7 4.1 looelsewhere 29 18.0 15.8 45.3 4.5 2.3 12.4 19.7 looTOTAL 162 100‘Includes Israeli 3-digit SIC codes: 200 (basic chemicals), 201 (pharmaceuticals), 204 & 205 (paints, varnishes, insecticides, fungicides).-‘Includes Israeli 3digit SIC codes: 250 (electrical motors, transformers), 251 (electrical equipment), 255 & 256 (communications equipment, electronicequipment for control, scientific and medical uses).‘Includes Israeli Migit SIC codes: 262 & 263 (aircraft parts and Sight control equipment).‘Includes Israeli 3-digit SIC codes: 280 & 2SfJ (scientific measuring and controlling instruments, optical instruments and photographic equipment).51ncludes Israeli 3-digit SIC codes: 733 & 738 (data processing and research consultancies).100 Technovation Vol. 14 No. 2

Science parks - seedbeds or enclaves of innovation?TABLE 2. Industrial and employment characteristics of surveyed firmsage of 8rm (years)no. of employees% academics% technicians% skilled labour% non-skilled labour% female labour% R&D employees% productionFirm characteristics(alI firms)revenue per employee (ThS)% exportscapital stock per employee (ThS)wages as % total expenditureraw materials as % total expenditureR&D expenditure as % of salesN Mean C.V.’ Mean of smaUfirms (

Science parks - seedbeds or enclaves of innovation?PROFILEAFig. 1. Innovation profiles based on entrepreneurs’ education level (E), university linkage ((I) and innovation level of firm (I).FGHnot significant). Seventy-five percent of firms haveno high-level linkage to universities at all, althougha PhD-level background does seem to breed someform of interaction (over half the companiesfounded by PhDs have intensive connections withuniversities).This low-key relationship, however, could beindicative of the generally low-level interactionbetween university and industry existing in Israelthat has been alluded to in other studies [45, 461.This is grounded in the fact that university research(even in an applied form) is often not ‘ripe’ enoughto be taken up by industry. In addition, academicresearch is unaware of the true problems facingindustry, and industry does not always want toreveal these problems to academia. Only when theuniversity engages in industrial ‘troubleshooting’(generally in the field of applied scientific services)does it meet industry’s needs. Industry, for its part,has a conservative attitude to funding universityresearch (conditioned by a shortage of capital)and wants immediate results. The upshot is thatthe university-industry relations that do exist arerather limited, especially in terms of intensiverelations such as joint research and funding [47].In general, the simple distribution outlined inFig. 1 seems to suggest that high-level educationalbackground does not say very much about theability to exploit innovations commercially. Furthermore,the level of interaction with universitiesis generally low, and where this interaction doesexist, it results in only marginally more innovativefirms; one-quarter of all firms with intense universityconnections are ‘significant’ innovators asagainst 21% of firms with low-level connections.Putting these relationships in a log-linear framework,we arrive at similar conclusions. The reduced-formmodel of the 3-way cross-tabulationbetween the variables in Fig. 1 results in thefollowing equationln(M,J = a + YEi + Y”j + ?lk(30*09/l) (7*51/l) (9-39/l)(i, j, k = 1,0)+ YEI,, f YEUij(1*96/l) (544/l)where ln(M& = the expected cell frequency,a = overall mean of the log of expected cellfrequencies, YEi = effect attributable to the ithTechnovation Vol. 14 No. 2 103

D. Felsensteincategory of education, rU_ = effect attributableto the jth category of university interaction,yZ, = effect attributable to the kth category ofinnovation level, y,?& = effect attributable to theinteraction between the ith category of educationand the kth category of innovation level, andyEVij = effect attributable to the interactionbetween the ith category of education and the jthcategory of university interaction.Figures in parentheses are chi-square statisticsand degrees of freedom, all significant at thep < O-05 level, except for the TEZik term that wasforced into the model.Likelihood ratio chi-square value for estimatedmodel = 4.64 (p = O-0106, 2 degrees of freedom).This is the most parsimonious model fitted tothe data. While it shows that education, universitylinkage and innovation are all significant in theirown right, for our purposes the interaction effectsare of greater interest. Although the second-orderrelationship between university interaction andeducation level of the entrepreneur/manager issignificant, this does not necessarily lead to innovativeactivity (the E*I relationship is not significant,but was forced into the model). The third-orderinteraction E*Z*U is also not significant. All thiswould seem to suggest that the ability to realizethe commercial potential of innovations (throughestablishing an innovative firm) is not necessarilyrelated to academic education or university linkage.Success in innovation and its commercial exploitation(i.e. the ability to sell the innovation andkeep the firm going on this basis) are probablyrelated to other supply conditions (such as theentrepreneur’s work history and experience) andresult from demand factors such as market structure(foreign or local, barriers to entry and so on).An exhaustive examination of these factors isbeyond the scope of this analysis, but a cursoryexamination of some of these factors does notyield any significant relationships. Supply factors,taken here as entrepreneur’s work experience asmeasured by the relationship between presentproduct and previous product experience (P),show no significant relationship to innovation.This holds true even when this relationship isstratified by previous employment position (R&Dvs. sales/administration/production). This wasexpected to add a further dimension to the depthof work experience, but the x2 statistics are allinsignificant. Market factors, as measured by thelocation of main market (foreign or local) (M),where foreign markets are expected to be moreinnovative, competitive and with higher entrybarriers, also yield no significant relationship toinnovation. However, there is a confounding effecthere with innovation and location, which will bediscussed below.6.2. Seedbed effects and science parklocationNearly half the firms surveyed here are locatedon science parks. This begs the question as towhether there is any significant difference ininnovative activity between on- and off-park firms( i.e., does the park have a seedbed effect?) andwhether this relationship is confounded by anyother factors. In view of the popular perception ofthe science park as facilitating university-industryinteraction, and in the light of the paucity ofempirical evidence supporting this claim, it isimportant to try to gauge the importance of sciencepark location in the innovation process.When turning to the features associated withlocation on a science park (and presumed toenhance innovative activity), the most obviousstarting-point is university interaction. In commonwith the many studies cited earlier, this is foundto be low amongst all science park firms surveyed.High-level interactions (joint research and industryfunding of university research) were reported by13% and 9% of firms respectively. Mid-levelinteractions are not much more prevalent, withreceipt of university consultancy services reportedby less than 20% of science park firms, and keyemployees holding faculty positions reported byonly 8%. As expected, low-level interactions basedon recruitment of local university graduates (28%)and use of university facilities (24%) were moreuniversal. This pattern, while not illustrating particularlyhigh-level interactions, was nevertheless104 Technovation Vol. 14 No. 2

Science parks - seedbeds or enclaves of innovation?significantly different to that observed for nonsciencepark firms (x2 = 3.947, p = O-047).If science park firms have higher level interactionswith universities, does this result in technologytransfer and, as a consequence, high levels ofinnovation (the ‘seedbed’ hypothesis)? This causalrelationship is not particularly significant(x2 = 2.438, p = 0.118). However, the possibilitydoes exist that the relationship is mediated throughthe effect of some other factor. As illustratedabove, innovation is interrelated with informationand much of this flows through channels that aregrounded in work experience, academic educationand the like. In this instance, therefore, we testfor the interrelationship between the factors sciencepark location (L), innovation level of the firm (Z)and work experience of the entrepreneur/manager(w).These relationships are depicted in Fig. 2. Ascan be seen, no clear pattern can be observed forthe relationship between innovation and sciencepark agglomeration. When adding the work experiencedimension, we arrive at a series of profiles.The conventional path is represented by profileA; an entrepreneur with a background in R&Dsets up a high-tech firm producing unique productson a science park. This development trajectory,however, accounts for only 5% of all firmssurveyed. The majority of science park firms(nearly 70%) fall into profile G, which representsthe science park firm engaged in the productionand modification of existing products and foundedby an entrepreneur from a non-R&D background.When stratifying the relationship between sciencepark and innovation by work experience, wefind that the seedbed hypothesis can be upheldindependently of work experience. Thus, forfirm founders with an ‘R&D background, thisrelationship is marginally significant (x’ = 2.93,p = 0.083). For entrepreneurs with technical andproduction backgrounds this relationship is slightlystronger (x2 = 5.99, p = O-013). This suggests thatwork experience might have a direct input intothe innovation capabilities of the firm (i.e. through‘learning by doing’ [48]). If this experience istechnical and managerial, this could lead to morecommercially viable innovative products than thoseproduced by firms where the main entrepreneurshave an R&D orientation. In other words, commerciallyexploitable innovations call for more than justPROFILEABCDEFGHFig. 2. Firm profiles based on entrepreneur’s wbrk background (w), innovation level of the firm (l) and science park location (IL.).Technovation Vol. 14 No. 2 105

D. Felsensteintechnological prowess and innovation prompted by science park location, this latter factor can servesupply-push conditions.to entrench existing seedbed interactions.The complete system of these interrelationships The question now arises as to whether otheris examined more formally in the log-linear model. factors exist that could impact on location. AreThe reduced-form model of the relationships other seedbed-promoting processes related to scibetweenW, I and L takes the formln(M,iJ = (Y + YWi t YZj + rWZij(18*18/l) (853/l) (4.5411)(i,Z, k = 1,O)+ YWZLij~(8*14/l)where ln(Mij,) = the expected cell frequency, OL= overall mean of the log of expected cellfrequencies, yWi = effect attributable to theith category of work experience, YZj = effectattributable to the jth category of innovation level,YWZij = effect attributable to the interactionbetween the ith category of work experience andthe jth category of innovation level, and YWZL,,= effect attributable to the third-order interactionbetween the ith category of work experience, thejth category of innovation and the kth category oflocation.Figures in parentheses are chi-square statisticsand degrees of freedom, all significant at thep < O-05 level.Likelihood ratio chi-square value for estimatedmodel = 5.76 (p = 0.0461,3 degrees of freedom).The results show that only one second-orderand one third-order interaction term are significant.Both these terms express the interaction effectsof work experience with innovation. There wouldthus seem to be an information flow basedon employment background that is related toinnovation level. This also interacts with location,suggesting that while work experience is relatedto innovation this may be contingent on location.However, this latter three-way interaction is theonly way in which location shows up in the results.All the two-way interactions that include locationare not ‘significant, and even the direct effect ofscience park location by itself is not included inthe model. All this would seem to imply that whilethe seedbed effect is not necessarily contingent onence park location? As noted earlier, the spin-offprocess is often associated with spatial clustering,the assumption being that spin-off firms remain inthe local area once they have broken away andcontinue to interact formally (e.g. subcontracting)or informally (social exchange) with their formerplaces of employment [49].Amongst the firms surveyed, the pattern ofspin-off was distributed across: (1) local firms,both Israeli and local foreign subsidiaries (36%of firms attributable to this source); (2) foreigncompanies abroad (22%); (3) universities (nearlyall local) (26%); and (4) the defence industry(including former army officers) and a ‘miscellaneous’category (16%). This distribution highlightedthe relatively large number of firms thathave spun-out of foreign companies abroad. Workexperience abroad would seem to expose thepotential entrepreneur to the possibilities of settingup an independent operation. It could also be thatnew firms starting up in this way have a guaranteedmarket in the form of their former company. Thismitigates some of the risk generally involved inspinning-off [49].A significant relationship is found to existbetween spin-off (P) and science park location(L) (x2 = 4@07, p = 0X)451). However, whenstratifying the relationship between innovationand location by type of spin-off, no significantrelationship exists. This would seem to show thatthe (rather weak) relationship between innovationand location, outlined above, is not contingent onthe type of spin-off. Thus, unlike the case forwork experience, we cannot conclusively say thatformer companies are an apparent source of inputthat will influence the firm’s innovation level. Assuch, there does not seem to be any reasonfor conscious science-park clustering of spin-offsaround ‘incubator’ organizations. They might clusterdue to inertia, prestige considerations associatedwith the location or simply through lack of106 Technovation Vol. ?4 No. 2

Science parks - seedbeds or enclaves of innovation?information about alternative locations. However,we have little evidence to suggest that they clusterfor information and interaction purposes or that theincubator organization is an inherent component ofthe seedbed effect. In addition, the surprisinglyhigh number of spin-offs attributable to foreignfirms, thereby discounting the option of locationalclustering around incubators, would seem to supportthis contention.Type of market (M) (export or local) washypothesized as exerting an influence on innovationlevel. Here we address the issue of whether firmswith similar markets are likely to choose a sciencepark for its seedbed effect. On the basis offirms surveyed, there is no evidence of a directrelationship between science park location (L) andmarket orientation (M). However, the relationshipbetween type of location and innovation level isagain mediated by type of market. Thus, for firmsoperating in local markets this relationship exists(x2 = 6.397, p = O-012), while it is not apparentfor firms serving export markets. In view of therelationship between market and innovation level,this might suggest that for those firms operatingin local markets science park clustering as aninteraction strategy is more important than forfirms operating abroad. The latter probably havealternative information networks connected withtheir markets and are thus less contingent on thescience park and its seedbed effects.7. ConclusionsThis paper has examined the case for theexistence of seedbed conditions on science parksthat promote innovation. The basic questions thatthe paper attempts to answer are, first, whetherthese effects are an important input to the firm’sinnovation level and, second, the extent to whichthese effects are contingent on the physical proximityand clustering afforded by the science park.The evidence seems to indicate that the informationflows and knowledge networks associatedwith university interaction and an entrepreneur’seducation level do not necessarily translate intoinnovation. We suggest that the influences oninnovation might lie somewhere else: in bothsupply conditions (such as the work experience ofthe entrepreneur) and the structure of demand(market conditions). Thus, the results presentedin this paper provide further support for theargument in much of the business literature to theeffect that technical knowledge without businessskill does not necessarily make for innovativelysuccessful products or firms [l, 2, 501. To this wemust add that the particular nature of hightechnologymarkets (competition, imperfect knowledgeat the early stages and high barriers to entryat later stages) also means that the informationnetworks likely to arise on the basis of universityinteraction and educational level are not necessarilythose needed for innovation (in contrast toinvention).The ‘seedbed’ hypothesis, that forms the centralfocus of this paper, is supported only undercertain conditions. In common with other empiricalevidence [6, 35, 39, 401, the level of interactionbetween firms located on science parks and localuniversities is generally low. It is higher, however,than the level of interaction exhibited by companiesthat are not science park tenants. This of itself,however, is no indication of a seedbed effectarising from science park location. Testing thisproposition more directly, we find that thelocation-innovation connection is strengthenedwhen stratified by work experience. This wouldseem to indicate that science park location, ratherthan being seedbed-inducing, could be seedbedentrenching.In common with other studies, wehave suggested that the choice of a science parklocation is due as much to the status and prestigeeffect that these exclusive locations confer [5, 11,351, as it is to the perceived benefits in termsof innovative edge. Science park location couldtherefore be the outcome of a process of ‘socialsignalling’ and ‘swarming’ [ 171.The policy implications of these findings suggestthat alternative vehicles for technology transfer,university-industry interaction and inter-firm flowsof information and materials need to be developed.Universities are slowly beginning to developTechnovation Vol. 14 No. 2 107

D. Felsensteininnovative new forms of relations with industry,based on alternative technology transfer mechanismsand synergistic relationships such as limitedpartnerships, R&D seed funds and generic researchcollaboration [31, 461. Firms are exploring newchannels for cooperation, alliances, network formationand diagonal integration in an attempt todisperse risk, cope with technological complexityand in reaction to perceived external threats [51].Faced with the magnitude of the task of innovation,appendixing to the science park the role ofinnovation ‘seedbed’ or regional development‘growth pole’ may be an unrealistic expectationfrom a project that in many instances is not muchmore than a real-estate development. Thus, ifthere is some disappointment in the fact thatscience parks are often not much more thanhigh-tech ‘islands’ with minimal interactions bothbetween themselves and with their neighbouringuniversities, it could be that hopes were pitchedtoo high in the first place.From the public policy perspective, the ‘seedbed’metaphor allows officials and policy makers tooperationalize their expectations of science parks.Therein lies its appeal. The science park is, ofcourse, just one of a collection of policy instrumentsthat aim to encourage the development of seedbedsof innovation. However, it is often uncriticallyaccepted as such - a position that this paper hassought to re-evaluate. While, for didactic purposes,we have characterized science parks in terms of aan enclave/seedbed dichotomy, in reality most ofthem probably lie somewhere along the continuumrunning between these two polar positions. Thechallenge therefore lies in the development ofpolicy tools that will encourage them to developinto more than just a ‘collection of firms’.AcknowledgementsFunding for this research was supported in partby a grant from the Israel Trustees Foundation.The work was completed while the author was avisiting scholar at the Center for Urban Affairsand Policy Research, Northwestern University,Evanston, Illinois, USA, and in receipt of a grantfrom the Lady Davis Fellowship Trust.Notes’ All these effects exist, of course, over and abovethe regular income, employment and output effects ofuniversities on local economic growth. On this issue,research has shown a particularly profound effect onlocal service sectors induced by university purchasing,staff and student expenditures [23,24]. Impact studies ofindividual universities have reached similar conclusionsalthough methodologies and consequently outputs varygreatly (see for example [25-271).2 In contrast, scientists and engineers as a percentageof the total science park labour force are reported as23% in the case of the University of Utah Researchpark, 31% for Research Triangle Park and 33% forStanford Research Park [ll].3 Braun and McHone [37] report income, output,employment and value-added multipliers for sciencepark firms located on the Central Florida ResearchPark. These lie in the range of 1~59-1~87. Interestingly,multipliers for Central Florida firms off-park are generallyhigher, ranging from 1.65 to 2.07.4 This ratio (~5~) is defined aswhere h4, = observed frequencies in each cell, andticijkj = expected frequencies in each cell.ReferencesA.C. Cooper, The role of incubator organizationsin the founding of growth-oriented firms. Journal ofBusiness Venturing, 1 (1985) 75-86.A.C. Cooper and W.C. Dunkelberg, Entrepreneurshipand paths to business ownership. StrategicManagement Journal, 7 (1986) 53-68.R.N. Cox, Lessons from 30 years of science parksin the USA. In: J.M. Gibb (ed.), Science Parks andInnovation Centres: Their Economic and SocialImpact. Elsevier Science Publications, Amsterdam,1985, pp. 17-25.R. Miller and M. Cote, Growing the next SiliconValley, Harvard Business Review, 63(4) (1985)114-123.108Technovation Vol. 14 No. 2

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