Globalization, Entrepreneurship, and Public Policy: a Systems View

Industry and Innovation, Volume 10, Number 1, 103–116, March 2003

GLOBALIZATION, ENTREPRENEURSHIP,

AND PUBLIC POLICY: A SYSTEMS VIEW*

BO CARLSSON AND RAM MUDAMBI

It has been commonly observed that the activities of firms are becoming increasinglyglobalized. Not only have exports grown faster than production in the industrialized

countries; foreign direct investment (FDI) has also grown considerably faster thanexports over the last several decades (UNCTAD 1999). In recent years, an increasingshare of FDI by multinational firms has involved research and development (R&D)activities and facilities.

But globalization does not mean that local conditions no longer matter. Surveyingthe literature, three major findings stand out. First, certain geographic regions aremore dynamic and attract more economic activity than others, particularly in highlyR&D-intensive industries (Cantwell and Janne 1999). Second, high-technology firmstend to cluster in close proximity to each other (Sabety and Griffin 1996; Sabourinand Pinsonneault 1997; Walcott 1999). Third, regions expend resources competingwith each other to attract FDI and are particularly interested in R&D investment(Guisinger 1986; Young et al. 1994; Mudambi 1998).

Given these observed tendencies toward regional clustering and globalization ofthe activities of firms, how can a region leverage its resources and capabilities to shiftits comparative advantage into activities likely to yield high and sustainable growth?What is the role of public policy in this regard, particularly in creating a favorableclimate for private entrepreneurship?

We take a systems approach in dealing with these questions. We view the economicand innovative activities of firms within a framework of academic, financial, andother institutions, networks among firms and other actors, government policies andagencies, etc., and the relationships among these.

We begin by discussing globalization and its driving forces. This is followed by a briefoverview of regional clustering of economic activities and the role of technologicalspillovers. We conclude by examining the implications for public policy.

GLOBALIZATION AND ITS DRIVING FORCES

Globalization involves not only sales in foreign markets but also use of foreignresources (via FDI); these resources consist increasingly of human capital, intellectualproperty, and ideas, not only labor and natural resources. The multinational corpora-tion (MNC) operates at the hub of business networks in which clusters of value-addedactivities are organized—as a so-called ‘‘flagship firm’’ (Rugman and D’Cruz 1997). As

*We are indebted to John Cantwell and Maryann Feldman for helpful comments. All remaining errors and omissionsare the responsibility of the authors.

1366-2716 print/1469-8390 online/03/010103-14 © 2003 Taylor & Francis Ltd

DOI: 10.1080/1366271032000068122

104 INDUSTRY AND INNOVATION

noted by Rugman (1999), most activities of MNCs occur in the triad of North America,Europe, and Japan and

the process of globalization is therefore a triad and management-driven one. There areindirect fallout effects on politics, culture, law and related issues but these are second-order effects and such indirect outcomes should not be confused with the economicactivities of the MNC.

It is well known that the volume of FDI has been increasing at a rapid rate(UNCTAD 1999) and this increase has been focused, like the existing pattern ofMNC activity, on the triad (Rugman 1999). The increase in FDI is closely linked tothe strategies of firms with respect to technology acquisition, diversification, andexploitation. These strategies have varied over time. As shown by Cantwell andPiscitello (2000), in the interwar and early postwar periods, large firms tended todiversify their technological competence largely by taking advantage of scale econo-mies in the normal course of growth. Meanwhile, their internationalization was aimedprimarily at the wider exploitation in foreign markets of the basic competence theyhad already established at home. This activity was largely export-driven. R&D activitieswere internationalized only to a limited extent and mostly oriented to adaptingproducts to each market.1

By the mid-1970s, the ‘‘opportunities for integrating diverse technologies in large-scale plants had been gradually exhausted . . . Technological diversification was nowincreasingly based instead on the growing interrelatedness between formerly separatetechnologies’’ (Cantwell and Piscitello 2000: 25). Firm size started to decline in mostindustrialized countries (Acs and Audretsch 1990a, b; Loveman and Sengenberger1991; Carlsson 1992), and many firms invested heavily in broadening their competencebase for existing product lines while also expanding their product lines (Granstrandand Sjolander 1990, 1992).

In the 1990s, as the rate of technological change speeded up and it becameincreasingly difficult for firms to diversify their technology base at a sufficient pace,firms began increasingly to rely on ‘‘international networks in order to exploit thelocationally differentiated potential of foreign centers of excellence (Cantwell 1995).A newly emerging complementarity between competence accumulation and thediversification and internationalization of corporate technology is thus at work’’(Cantwell and Piscitello 2000: 44).

Thus, in the early postwar period, technology was an important driver of exportsand eventually of FDI primarily in production facilities as the companies’ presencein foreign markets increased. More recently, the desire to acquire technology hasbeen a major motive for multinational firms to locate R&D facilities abroad. Therequired investments have tended to cluster in certain geographic regions (Cantwelland Iammarino 1998). This explains why there has been a shift in attention awayfrom the MNC as a mere vehicle of technology transfer towards the crucial role itplays as a creator of innovation and technological knowledge (Chesnais 1988; Cantwell1994).

1 The main limitation was that the internationalization was largely confined to the technologically leading firms.However, many of these leading firms developed international networks to exploit the locationally differentiatedpotential of foreign centers of excellence (Cantwell 1995).

GLOBALIZATION, ENTREPRENEURSHIP, AND PUBLIC POLICY 105

AGGLOMERATION AND NETWORKS

Over the centuries, certain locations have been known for the production of particulargoods, such as Biella in Northern Italy for woolen goods (Castronovo 1996), Kishorganjin Bengal for muslin (Mason 1991) and specific locations in France for particular typesof wine. Spatial concentration of industry has been observed virtually since thebeginning of the industrial revolution (Marshall 1923; Hoover 1937, 1948).

In recent years a large literature has emerged on industry clusters concentrated incertain geographic regions (Porter 1990, is typical of this literature). A competitiveindustrial cluster may be defined as a geographic concentration of competitive firmsor establishments in the same industry that either have close buy-sell relationshipswith other industries in the region, use common technologies, or share a specializedlabor pool that provides firms with a competitive advantage over the same industryin other places (Hill and Brennan 2000). Such industry clusters are formed aroundcertain ‘‘driver’’ industries—industries in which the region has its greatest competitiveadvantage.2 It should be noted, however, that while firms may be attracted to alocation that has the relevant comparative advantage in terms of local skills and otherresources, it is by no means easy to determine historically which came first: did theleading firm(s) lead to the concentration, or vice versa?

The analysis of such industry clusters can be helpful in understanding the industryevolution and structure and the comparative advantage of regions. But such analysestend to be static and backward looking. The geographic clustering of the R&Dactivities of multinational firms at the present time seems to be much more dynamicand forward-looking, fundamentally driven by innovation and potential technologyspillovers rather than by existing industry linkages.

It is well known that R&D-intensive industries tend to be highly spatially concen-trated (Castells and Hall 1994; Saxenian 1994; Almeida and Kogut 1997). This spatialconcentration has tended to persist, even in the face of rising labor and otherinput costs. Spatial concentration has generally been attributed to economies ofagglomeration, but the exact source of these economies is difficult to isolate. This iswhere the notion of an innovation system comes in. Innovation is not necessarilysimply a function of R&D, nor is R&D necessarily sufficient for the creation oftechnology-intensive industries and the valuable economic spillovers that result inhigh value-added jobs and exports. Rather, it is a combination of factors thatcontributes to innovation, such as skills, finance, production, user-producer linkages,the capacity of organizations to learn, and multi-layered government policies (de laMothe and Paquet 1998).

One important factor contributing to geographic clustering in certain highly R&D-intensive industries, like pharmaceuticals, is the presence of a leading researchuniversity in a region (Galambos and Sewell 1996). One reason why companies locatenear an academic institution is that they expect knowledge transfers from localuniversities. Another reason is that a university can provide training for the localresearch workforce, thus deepening the skills in the local labor market and making it

2 Such clusters are identified through a variety of methods including a combination of cluster and discriminantanalysis. They are linked to supplier and customer industries with information from a region-specific input–outputmodel to form industry clusters.


more attractive for other firms to locate in the area. This enriches the labor marketand makes it attractive also to researchers in other locations.

Regardless of whether or not technology transfer is planned, or even initiated bythe supplier, the receiver must usually make a significant investment in order to beable even to identify the technology as potentially important and then to absorb andexploit it. Further, the receiver must invest in receiver competence or absorptivecapacity: the ability to scan and monitor relevant technological and economicinformation, to identify technical and market opportunities, and to acquire knowledge,information, and skills needed to develop technologies. Most R&D activities in firmsare, in fact, of this sort. Absorptive capacity is more than the ability to master a newtechnology or innovation. It is the ability to adjust the firm’s systems of coordinationand control to match the new technological opportunities. As noted by Pavitt (1998),firms rarely fail because they cannot master a new technology. They fail because theylack sufficient absorptive capacity. That is why locating R&D activities in proximity toother firms in similar industries and to universities with relevant research capabilities isimportant.

Jaffe et al. (1993), in an analysis of patent citations, find that domestic patents aremore likely to come from the same state and particularly the Standard MetropolitanStatistical Area (SMSA) as the cited patents and that this localization effect fades onlyslowly with time. But clearly not all universities are created equal: R&D-intensivefirms tend to locate near leading universities with a strong research base. The literaturesuggests that universities differ widely in the degree to which they encourage andsupport commercialization of research results both in their internal organization andincentive systems and in the way they organize, staff, and fund technology transfer(Carlsson and Fridh 2002). For example, field research indicates that through the1990s, the ‘‘commercialization gap’’ between universities and industry in biotechnol-ogy was considerably larger in Europe than in the USA, though it has been narrowingof late (SPRU 1999). This research reports that European universities are the weaklinks in the R&D system.

Thus, while good universities may be necessary to develop industrial clusters, theyare not sufficient (Becker 2000). The same university research expenditure can exerta very different impact on local innovations depending on the agglomeration ofeconomic activities in the local community. This is an important reason why certainstudies have reported an active university role in local development, while othershardly identified any meaningful economic impact at all of academic institutions(Varga 1998: 125; see also Feldman and Desrochers in this volume). The gross size ofthe direct and indirect local income generation attributable to the university is alsolikely to be a crucial factor (Bleaney et al. 1992).

Conditions in the surrounding community are equally important determinants ofthe degree of success in transforming academic research into commercially viabletechnology resulting in new products via licensing or new business startups. Importantfactors here are agglomeration factors such as concentration of high-technologyproduction, presence of business services employment, and relative importance ofsmall firms in the metropolitan area economy. In addition, an important factor forsuccessful commercialization of university research is the local presence of financing.Finally, the lack of a key networking or mediating organization critically retards the


development of this potential growth engine (Walcott 1999). The role of such‘‘bridging institutions’’ has been examined by Carlsson (1995, 1997, 2002).

In many industries innovation is characterized by a high level of codifiable researchand tangible specification and is typically carried out in large firms in-house. Bycontrast, high-technology industries tend to be characterized by much more collabo-ration and networking. This is because innovation is either closely linked to scientificresearch (e.g. biotechnology and pharmaceuticals) or involves drawing upon expertisein a wide variety of fields (e.g. telecommunications). In such industries, even largefirms are dependent on collaboration with outside entities (universities and otherfirms). In many cases the firms with which they collaborate are spin-offs from theirown companies. They may also be university spin-offs. Thus, small firms in suchsectors are highly dependent on the large firms from whence they sprang (especiallyin software) and on universities (in biotechnology).

The presence of spin-off small and medium-sized enterprises (SMEs) is cruciallydependent upon a culture that is supportive of entrepreneurial activity. Hence, wherethe entrepreneurial culture is particularly poor (e.g. in France and Germany), R&Dand innovation may continue to occur in large, leading firms, even in areas where itwould be more efficient for SMEs to do it. However, economic theory would predictthat such regions would be outperformed by other countries or regions with strongentrepreneurial cultures. Hence the USA and the UK are miles ahead of France andGermany in software and biotech.

There is evidence that MNCs have a great deal of interest in clusters. Cantwell(1995) provides evidence suggesting that MNCs are evolving into ‘‘network’’ firms,leveraging their competencies in managing geographically dispersed activities andsynthesizing information. Indeed, he argues that the strength that allows a firm toinvest and govern its operations across national boundaries is its ability to innovateand to take advantage of such innovation in different clusters. The result is that MNCshave been increasingly dispersing their R&D activities (Pearce 1999). Further, localMNC R&D operations are increasingly viewed as strategic assets that contributesignificantly to the longer term evolution of the core technology of the MNC(Papanastassiou and Pearce 1997).3

Most entrepreneurial firms are SMEs. Their interest in clusters differs from that ofthe large MNCs in that their innovation focus tends to be complementary to that oflarge MNCs. It has been pointed out that networks are a key success factor forentrepreneurial firms (Casson 1997; Sanchez and Perez 1998). Locating in clustersincreases greatly the opportunities for forming and capitalizing on inter-personal andinter-firm networks. They can also be viewed as a means of developing a ‘‘credible’’

3 These factors may be called ‘‘pull’’ factors towards decentralization. There are also ‘‘push’’ factors. For example,Vonortas (1997) argues there is extensive anecdotal evidence suggesting that strongly dominant firms prefer theextremes of market or hierarchy. They shun collaborative agreements due to the implied loss of control ofresources and strategies. Consequently, the rapid increase in such agreements (in particular, in research jointventures—RJVs) must indicate an equally rapidly deflating expectation of being able to dominate an industry for aperiod of time long enough to recoup the requisite expense of domination. Thus, firms are ‘‘pushed’’ into RJVnetworks by complexity, uncertainty, and the speed of change in the technological environment. For example, ininformation technology and advanced materials the fluid stage of technology development, lack of dominantdesigns, and ill-defined technological trajectories make complete contracts impossible to write because of thedifficulty in determining contingencies.


profile with buyers, suppliers, and sources of financial support (Deeds et al. 1999).For example, these network factors have been estimated to strongly influence equityas well as non-equity financial support from foreign partners in the US biotechnologyindustry (Coombs et al. 2000).

Thus, for different reasons, both MNCs and entrepreneurial firms are increasinglyrelying on networks. As noted above, MNCs are also becoming increasingly decentral-ized in terms of their approach to R&D. These network factors have led to thedistinctions between established and entrepreneurial firms4 becoming blurred in manydimensions, as noted by Saxenian (1999).

Since SMEs do not possess firm-specific financial or reputation collateral theconventional capital market is rarely able to support their activities. In addition tohigh risk, in many industries like biotechnology they are faced with long gestationperiods (Eliasson and Eliasson 1997; DeCarolis and Deeds 1999). Financing is thereforea crucial factor in the innovatory process in SMEs. The information asymmetryinherent in the R&D (and innovation) process within small, entrepreneurial firms,leads to significant adverse selection and moral hazard problems. It is not surprisingthat conventional debt financing tends to flow toward supporting R&D activities ofestablished firms.

Entrepreneurial finance

The organized market for entrepreneurial finance is relatively new and comprises anumber of players. These players include business ‘‘angels’’, venture capitalists andinvestment bankers and underwriters. This market has emerged to service preciselythe small, entrepreneurial firms that have trouble attracting traditional debt finance.

Traditionally, the first round of funding for startup companies came from theentrepreneur’s own resources or from friends and family. Over the last decade,informal investment by private individuals—so-called ‘‘angel’’ financing—has becomeincreasingly important, first in the USA and more recently in Europe (Fenn and Liang1998). This financing has become a crucial source of first-round funding for highgrowth potential entrepreneurial firms (Prowse 1998). The existence of a pool ofangel capital is a major source of competitive advantage for a locality.

Once an entrepreneurial firm is established, venture capital (VC) comes into play.Whilst the VC market, particularly in the USA, has received considerable publicity, itactually plays a minor role in startup finance and basic innovation (Zider 1998). Themajority of VC finance in the USA goes to post startup firms. These are firms that areat the stage of commercializing their innovation, so that VC finance is typicallymezzanine or second stage finance (see Figures 1 and 2).

Venture capitalists have some fundamental characteristics (Gompers and Lerner1999): (a) They back a portfolio of enterprises so that risks are diversified. (b) Theytake equity stakes to ensure that the rate of return distribution is asymmetric, i.e. up-side gains are potentially unbounded, while down-side losses are bounded by theamount invested. (c) They undertake a more active monitoring and management rolethan traditional debt finance managers, albeit a less active role than entrepreneurs.

4 What Kenney and von Burg (1999) call ‘‘Economy 1’’ and ‘‘Economy 2’’.


FIGURE 1: THE ENTREPRENEURIAL FINANCE CYCLE—1©.

FIGURE 2: THE ENTREPRENEURIAL FINANCE CYCLE—2©.

(d) Exit is an important consideration from the outset and their horizon is essentiallyshort term. The idea is to invest in a company’s balance sheet and infrastructure untilit reaches sufficient size and credibility so that it can be publicly floated in an IPO orsold to a large MNC.

These characteristics, along with the fact that often 9 out of 10 ventures fail, meanthat there must be a sufficient number (critical mass) of angel investors and venture


capitalists to support a wide variety of ventures. The presence of multiple actorsrepresenting a variety of competencies and different networks is even more importantthan the total amount of funding they can provide. This diversity is the most crucialelement in generating a virtuous cycle of increasing availability of finance for startupfirms as depicted in Figures 1 and 2 (Deeds and Mudambi 1999).

Spillovers and firm strategies

R&D investment is generally recognized to be of high value to the location in whichit is sited. This is because R&D-intensive activities tend to be associated with highlyskilled workforces and high value-added. Firm operations that include substantial R&Deffort tend to have high levels of responsibility in other areas as well. However, all ofthese benefits tend to be associated with the particular firm or operation. In an eraof increasingly mobile capital, it is recognized that gains associated with a particularfirm or unit can be transitory, in the sense that the operation is essentially portable,even in the medium term.

Hence, one of the most important aspects of R&D-intensive operations is thepresumption of ‘‘spillovers’’, i.e. benefits that flow from a particular firm or unit toother firms or units in its proximity (for example, Raut 1995; Odagiri et al. 1997; VanReenen 1997, among others). Thus, a clear understanding of the manner in whichsuch spillovers occur is of crucial importance in the efforts to gain the most benefitsout of R&D investments.

In the literature, R&D spillovers have typically been modeled as occurring in arelatively deterministic and uncontrolled manner (Choi 1993; De Bondt 1997; Edenet al. 1997; Muniagurria and Singh 1997, etc.). Often an element of stochasticity isadded, so that only the expected value of the actual level of spillover is determined.However, it is possible that a significant part of the spillovers actually occurs as aresult of conscious networking rather than random chance.

This question is of considerable importance for public policy. If random chance isthe major determinant of the level of spillovers, then the optimal strategy is to attemptto maximize the stock of R&D activity in a region. On the other hand, if consciousnetworking is the predominant determinant of spillover levels, then the optimalstrategy involves viewing the industry or activity as a system and working towardsfacilitating system development and growth. We subscribe to the latter view. Withoutthe requisite absorptive capacity, little or no spillover will occur. It follows that inany region the cross-firm distribution of R&D and the form and extent of inter-firmlinkages matters as well as the absolute level of R&D in the aggregate. A region witha relatively even distribution (hence: a wide dispersion of absorptive capacity) andgood linkages stands to gain a lot from spillovers, whereas one with a highly skeweddistribution and weak intra-regional linkages may host few spillovers, however muchR&D the leaders may be doing.

In this context, terminology is important. The term ‘‘spillovers’’, for instance,connotes unplanned activity and suggests an analytical approach that is based onexternalities. Further, it is particularly misleading, since it suggests that no effort isnecessary on the recipient’s part. A competing and better term, first used in theliterature on economic development, is ‘‘technology transfer’’, where the transfer is


typically planned by the supplier. However, even this term connotes a stable andplanned flow between economic agents or entities. In either case, a successfultransfer requires substantial investment of time and effort by the party acquiring thetechnology.

Actual inter-firm R&D activities are likely to be more systematic than is capturedby the term ‘‘spillovers’’ and more stochastic than captured by the term ‘‘technologytransfer’’. What is occurring is a constant drive by firms to both create and acquiretechnology. The creation versus acquisition decision is driven by relevant transactioncosts of technology. Firms can be predominantly technology ‘‘acquirers’’ or technology‘‘creators’’. The market creates a technology supply chain from creators to acquirers,beginning with basic or core technologies and stretching forward into increasinglyapplied technologies.

Inherent in the systems approach is the resolution of the potential conflict betweenfirm and societal goals. The firm’s objective is often viewed as the maximization of aone-way flow, i.e. a maximization of the inflow of knowledge and information and acorresponding minimization of the outflow of non-appropriable knowledge andinformation. The objectives of society (or the region or other political entity) is themaximization of a two-way flow, i.e. the maximization of overall flows to maximizethe value of the entire R&D node. Because of the importance of absorptive capacity,innovative firms realize that they can only take from the pot roughly in the sameproportion to what they contribute to it. Thus, the firms that provide the most don’thave to worry too much about the free rider problem because they’re also able totake the most. Partly due to the complementarity but differentiation of technologicalspace, and partly due to the complexity of modern technological systems, no oneautarkic firm can ever hope to absorb all of even its own creations—so it mustcontribute to the pot of an integral system, and can never attempt to monopolize thesystem. Organized exchange and cooperation is essential for all parties if their ownindividual efforts are not to be wasted.

POLICY IMPLICATIONS

Understanding that there is a system in operation is not the same as trying to createit. A successful high-technology cluster with considerable entrepreneurship andinnovatory activity is a complex network system with many inter-linking components.It incorporates both MNCs seeking to tap into local competencies and SMEs seekingthe benefits of networks and credibility. Even its smaller firms act as multinationals,forming links to import resources that are locally scarce. Thus, its growth is notconfined by the local or national innovation system. Its greatest strength is its openarchitecture that powers learning and growth, which in turn reinforces cooperativestrategies. Good policy decisions can only be made on the basis of recognizing allthese characteristics.

Thus, cluster formation can be facilitated, but not directed. Planning cannotreplace the imaginative spark that creates innovation. However, once clusters form, acomprehensive set of facilitating policies, from information provision and networkingto tax codes and labor laws, are necessary. These policies must recognize both the


requirements of cluster development as well as the life cycles of individual firms (seeFigure 2).

Policy should focus on making entrepreneurship easy. The higher the opportunitycost of entrepreneurship, the lower the quality of entrepreneur, since the processbecomes driven by adverse selection—the only agents willing to undertake entrepre-neurship are those who cannot do anything else. This requires, for example, easingthe effects of bankruptcy (trying to emulate the Silicon Valley ‘‘badge of honor’’ 5). Itmeans NOT giving out subsidies, but conversely weakening the laws protecting thebenefits of seniority and ‘‘time-related’’ benefits in established firms. This is exactlythe reverse of the ‘‘social market’’ experiment policies still advocated in manyEuropean countries.

There is a literature indicating that firms that received government financial supportunder programs like the Small Business Investment Company (SBIC) and SmallBusiness Innovation Research (SBIR) have done better than firms that did not in termsof growth and obtaining venture funding (Lerner 1998). However, while this type ofsupport has been found to be positively associated with subsequent success in theprivate market, the causality here is unclear. It is quite possible that good entrepre-neurs are good ‘‘grantrepreneurs’’. It is possible that these firms would have done justas well without government financial assistance. It is interesting to note that thesuperior performance of government awardees was confined to areas with substantialVC activity and was pronounced in high-technology industries (Lerner 1999), indicat-ing that at best, the government support served as certification. This reinforcesconcerns regarding causality, as other studies have found that location is the mainfactor underlying the ability of startup firms to raise support from foreign investors(Coombs et al. 2000).

However, not all government support is the same. Facilitating support like ACE-Net(Angel Capital Electronics—see Acs and Tarpley 1998) is valuable, since it addressesproblems highlighted in several studies of angel funding. Angels tend to be aheterogeneous group in terms of their abilities and objectives (Freear et al. 1994).Most studies indicate that one of the key policies that would improve the functioningof this market is improving the information flow between angels and potentialentrepreneurs (Prowse 1998). This is the function of bridging institutions. A secondkey policy is the provision of suitable tax advantages to investors (Harrison and Mason1993).

Even in investments in facilitation and core public functions (where significantexternalities can lead to market failure) such as basic research and university funding,evidence suggests that there are strong critical mass effects. Thus, expenditures inareas that are considerably below the critical mass are unlikely to yield a meaningfulreturn (Varga 1998).

National innovation systems and technological specialization of countries changeonly very gradually and—especially in newer and rapidly evolving sectors—muchslower than the technological needs of firms (Narula 2000). Thus, firms need toacquire the best technology from wherever it is available. Public policies that impede

5 This is the idea that only those who have tried and failed in previous attempts have learned enough from theexperiences to merit new funding.


this process—ranging from tariffs and non-tariff barriers to curbs on the laborcertification of foreign workers—are not conducive to the nurturing of successfulclusters. Government attempts to micro-manage the economy by picking winningand losing sectors is doomed to failure over the long run, because by definition,technological trajectories are highly unpredictable. On the other hand, policies thatstimulate and support the build-up of absorptive capacity in key technologies on aregional basis can be highly effective.

REFERENCES

Acs, Z.J. and Audretsch, D.B. 1990a: The Economics of Small Firms: A European Challenge.Dordrecht and Boston: Kluwer Academic Publishers.

Acs, Z.J. and Audretsch, D.B. 1900b: Innovation and Small Firms. Cambridge, MA: MITPress.

Acs, Z.J. and Tarpley, F.A., Jr 1998: The angel capital electronic network (ACE-Net), Journalof Banking and Finance, 22(6–8) (August): 793–797.

Almeida, P. and Kogut, B. 1997: The exploration of technological diversity and the geographiclocalization of innovation, Small Business Economics, 9: 21–31.

Becker, G.S. 2000: Global Silicon Valleys? First kill all subsidies, BusinessWeek, 3674(27 March): 26.

Bleaney, M.F., Binks, M.R., Greenaway, D., Reed, G.V. and Whynes, D.K. 1992: What does auniversity add to its local economy?, Applied Economics, 24(3) (March): 305–311.

Cantwell, J.A. 1994: Transnational Corporations and Innovatory Activities. London:Routledge.

Cantwell, J.A. 1995: The globalization of technology: what remains of the product cyclemodel?, Cambridge Journal of Economics, 19(1) (February): 155–174.

Cantwell, J.A. and Iammarino, S. 1998: MNCs, technological innovation and regional systemsin the EU: some evidence in the Italian case, International Journal of the Economics ofBusiness, 5(3): 383–408.

Cantwell, J.A. and Janne, O. 1999: Technological globalization and innovative centers: therole of corporate technological leadership and locational hierarchy, Research Policy,28(2–3) (March): 119–144.

Cantwell, J.A. and Piscitello, L. 2000: Accumulating technological competence: its changingimpact on corporate diversification and internationalization, Industrial and CorporateChange, 9(1): 21–51.

Carlsson, B. 1992: The rise of small business: causes and consequences, in W.J. Adams (ed.),Singular Europe: Economy and Polity of the European Community after 1992. AnnArbor: Michigan University Press.

Carlsson, B. (ed.) 1995: Technological Systems and Economic Performance: The Case ofFactory Automation. Boston, Dordrecht and London: Kluwer Academic Publishers.

Carlsson, B. (ed.) 1997: Technological Systems and Industrial Dynamics. Boston, Dordrechtand London: Kluwer Academic Publishers.

Carlsson, B. (ed.) 2002: Technological Systems in the Bio Industries: An International Study.Boston, Dordrecht and London: Kluwer Academic Publishers.

Carlsson, B. and Fridh, A.-C. 2002: Technology transfer in U.S. universities: a survey andstatistical analysis, Journal of Evolutionary Economics, 12(1–2): 199–232.

Casson, M.C. 1997: Entrepreneurial networks in international business, Business andEconomic History, 26(2): 811–823.


Castells, M. and Hall, P. 1994: Technopoles of the World: The Making of 21st CenturyIndustrial Complexes. New York: Routledge.

Castronovo, V. 1996: Biella: history runs along a woolen thread, Arrividerci, VII(75): 32–37.Chesnais, F. 1988: Technical co-operation agreements between firms, Science Technology

Industry Review, 4: 57–119.Choi, J.P. 1997: Herd behavior, the penguin effect and the suppression of informational

diffusion: an analysis of informational externalities and payoff interdependency, RandJournal of Economics, 28(3): 407–425.

Coombs, J.E., Deeds, D.L. and Mudambi, R. 2000: An examination of the antecedents ofequity and non-equity investments into US biotechnology firms by foreign and domesticcorporate partners. Proceedings of the Academy of Management Meetings, Toronto.

De Bondt, R. 1997: Spillovers and innovative activities, International Journal of IndustrialOrganization, 15(1): 1–28.

de la Mothe, J. and Paquet, G. (eds.) 1998: Local and Regional Systems of Innovation.Boston, Dordrecht and London: Kluwer Academic Publishers.

DeCarolis, D. and Deeds, D.L. 1999: The impact of stocks and flows of organizationalknowledge on firm performance: an empirical investigation of the biotechnology industry,Strategic Management Journal, 20: 953–968.

Deeds, D.L. and Mudambi, R. 1999: A model of the entrepreneurial finance cycle. WorkingPaper, Case Western Reserve University.

Deeds, D.L., Frandsen, M. and Mang, P. 1999: The impact of industry and organizationallegitimacy on the flow of capital into high technology new ventures. Working Paper, CaseWestern Reserve University.

Eden, L., Levitas, E. and Martinez, R.J. 1997: The production, transfer and spillover oftechnology: comparing large and small multinationals as technology producers, SmallBusiness Economics, 9(1): 53–66.

Eliasson, G. and Eliasson, A. 1997: The pharmaceutical and biotechnology competence blocand the development of Losec, in B. Carlsson (ed.), Technological Systems and IndustrialDynamics, pp. 139–168. Dordrecht and Boston: Kluwer.

Fenn, G.W. and Liang, N. 1998: New resources and new ideas: private equity for smallbusinesses, Journal of Banking and Finance, 22(6–8) (August): 1077–1084.

Freear, J., Sohl, J.E. and Wetzel, W.E., Jr 1994: Angels and non-angels: are there differences?,Journal of Business Venturing, 9: 109–123.

Galambos, L. and Sewell, J.E. 1996: Networks of Innovation: Vaccine Development at Merck,Sharp & Dohme, and Mulford, 1895–1995. New York: Cambridge University Press.

Gompers, P. and Lerner, J. 1999: The Venture Capital Cycle. Cambridge, MA: MIT Press.Granstrand, O. and Sjolander, S. 1990: Managing innovation in multi-technology corporations,

Research Policy, 19: 35–60.Granstrand, O. and Sjolander, S. 1992: Internationalization and diversification of multi-

technology corporations, in O. Granstrand, L. Hakanson and S. Sjolander (eds.),Technology Management and International Business. Internationalization of R/D andTechnology. Chichester: John Wiley.

Guisinger, S. 1986: Do performance requirements and investment incentives work?, TheWorld Economy, 9(1): 79–96.

Harrison, R. and Mason, C. 1993: Finance for the growing business: the role of informalinvestment, National Westminster Bank Quarterly Review (May): 17–29.

Hill, E.W. and Brennan, J.F. 2000: A methodology for identifying the drivers of industrialclusters: the foundation of regional competitive advantage, Economic DevelopmentQuarterly, 14(1): 65–97.


Hoover, E.M. 1937: Location Theory and the Shoe and Leather Industries. Cambridge, MA:Harvard University Press.

Hoover, E.M. 1948: The Location of Economic Activity. New York: McGraw-Hill.Jaffe, A.B., Trajtenberg, M. and Henderson, R. 1993: Geographic localization of knowledge

spillovers as evidenced by patent citations, Quarterly Journal of Economics, 108(3):577–598.

Kenney, M. and von Burg, U. 1999: Technology, entrepreneurship and path dependence:industrial clustering in Silicon Valley and Route 128, Industrial and Corporate Change,8(1): 67–103.

Lerner, J. 1998: ‘‘Angel’’ financing and public policy: an overview, Journal of Banking andFinance, 22(6–8) (August): 773–783.

Lerner, J. 1999: The government as venture capitalist: the long-run impact of the SBIRprogram, Journal of Business, 72(3) (July): 285–318.

Loveman, G. and Sengenberger, W. 1991: The re-emergence of small-scale production: aninternational comparison, Small Business Economics, 3(1): 1–37.

Marshall, A. 1923: Industry and Trade: A Study of Industrial Technique and BusinessOrganization, and of their Influences on the Conditions of Various Classes and Nations.London: Macmillan.

Mason, N. 1991: Muslin dress: 18th century, Poetry Wales, 27(1): 60.Mudambi, R. 1998: The role of duration in MNE investment strategies, Journal of

International Business Studies, 29(2): 239–262.Muniagurria, M.E. and Singh, N. 1997: Foreign technology spillovers and R&D policy,

International Economic Review, 38(2): 405–430.Narula, R. 2000: Explaining ‘inertia’ in R&D internationalization: Norwegian firms and the

role of home-country effects. Working Paper, Centre for Technology, Innovation andCulture, University of Oslo.

Odagiri, H., Nakamura, Y. and Shibuya, M. 1997: Research consortia as a vehicle for basicresearch: the case of the fifth generation computer project in Japan, Research Policy,26(2): 191–207.

Papanastassiou, M. and Pearce, R.D. 1997: Technology sourcing and the strategic roles ofmanufacturing subsidiaries in the U.K.: local competences and global competitiveness,Management International Review, 37(1): 5–25.

Pavitt, K. 1998: Technologies, products and organization in the innovating firm: what AdamSmith tells us and Joseph Schumpeter doesn’t, Industrial and Corporate Change, 7(3):433–452.

Pearce, R.D. 1999: Decentralized R&D and strategic competitiveness: globalised approachesto generation and use of technology in multinational enterprises, Research Policy, 28(2–3)(March): 157–178.

Porter, M.E. 1990: The Competitive Advantage of Nations. New York: The Free Press.Prowse, S. 1998: Angel investors and the market for angel investments. Journal of Banking

and Finance, 22: 785–792.Raut, L.K. 1995: R&D spillover and productivity growth: evidence from Indian private firms,

Journal of Development Economics, 48(1): 1–23.Rugman, A. 1999: Multinational enterprises and the end of global strategy. Proceedings of the

25th European International Business Association (EIBA) Conference, UMIST,Manchester.

Rugman, A.M. and D’Cruz, J.R. 1997: The theory of the flagship firm, EuropeanManagement Review, 15(4) (August): 403–411.

Sabety, J.P. and Griffin, J.M. 1996: Pro-competitive alliances: new vehicles for regional, state,


and community based economic development, Economic Development Review, 14(2)(Spring): 2–6.

Sabourin, V. and Pinsonneault, I. 1997: Strategic formation of competitive high technologyclusters, International Journal of Technology Management, 13(2): 165–178.

Sanchez, A.M. and Perez, O.U. 1998: Entrepreneurship networks and high technology firms:the case of Aragon, Technovation, 18(5): 335–345.

Saxenian, A. 1994: Regional Advantage: Culture and Competition in Silicon Valley andRoute 128. Cambridge, MA: Harvard University Press.

Saxenian, A. 1999: Comment on Kenney and von Burg, Industrial and Corporate Change,8(1): 105–110.

SPRU 1999: Annual Report. University of Sussex: Science Policy Research Unit.UNCTAD 1999: World Investment Report: FDI and the Challenge of Development. Geneva:

UNCTAD.Van Reenen, J. 1997: Employment and technological innovation: evidence from UK

manufacturing firms, Journal of Labor Economics, 15(2): 255–284.Varga, A. 1998: University Research and Regional Innovation: A Spatial Econometric

Analysis of Academic Technology Transfers. Boston, Dordrecht and London: KluwerAcademic Publishers.

Vonortas, N.S. 1997: Cooperation in Research and Development. Boston, Dordrecht andLondon: Kluwer Academic Publishers.

Walcott, S.M. 1999: High tech in the deep South: biomedical firm clusters in metropolitanAtlanta, Growth and Change, 30(1): 48–74.

Young, S., Hood, N. and Wilson, A. 1994: Targeting policy as a competitive strategy forEuropean inward investment agencies, European Urban and Regional Studies, 1(2):143–159.

Zider, B. 1998: How venture capital works, Harvard Business Review, 76(6) (November–December): 131–139.

Globalization, Entrepreneurship, and Public Policy: a Systems View

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