Ž .Research Policy 26 1998 973–987

New, technology-based firms in small open economies—Ananalysis based on the Finnish experience

Erkko Autio a,), Helena Yli-Renko b

a London Business School, Faculty of Strategic and International Management, Sussex Place, Regent’s Park, London NW1 4SA, UKb Helsinki UniÕersity of Technology, Institute of Strategy and International Business, Otakaari 1 F, FIN-02150 Espoo, Finland

Abstract

Ž .This paper analyses the roles and impacts of new, technology-based firms NTBFs in a small open economy, withempirical data from Finland. It is suggested that in small open economies, NTBFs may fall into a resource trap, which mightresult in their being relatively less growth oriented than NTBFs in countries where the domestic market is larger.Consequently, in small open economies, the systemic impact of NTBFs could be emphasised rather than their organicgrowth in terms of the employment that they create. q 1998 Elsevier Science B.V.

Keywords: New technology-based firms; Finland; Innovation; Networks

1. Introduction

Ž .Schumpeter 1934 argued that the main role ofnew firms was to contribute to the processes ofinnovation in the economy. According to his Mark Imodel, new firms operate as agents of creative de-struction by introducing innovations into the econ-omy. By doing this, new firms prompt large firms torevise their practices. Although Schumpeter revisedthis view in his later Mark II model of innovation,the former view of new firms as agents of innovationhas persisted. This holds particularly for NTBFs,which characteristically base their business on ex-ploiting advanced technological knowledge. Thegeneral perception of the role of new, technology-based firms in the economy tends to be heavily

) Corresponding author. Tel.: q44-171-262 5050; fax: q44-171-724 7875; e-mail: erkko.autio@hut.fi.

based on the ‘linear model’ of innovation. Applied inthe context of NTBFs, the linear model would implythat NTBFs are typically established to commer-cialise new technologies. They would typically begrowth oriented, take risks to pursue growth, andgrow or perish with their technology. Essentially, inthe linear view, NTBFs are viewed as a kind ofinnovation projects that are established to commer-cialise new applications.

There are, of course, many NTBFs which essen-tially develop new applications and bring these tomarket. The most successful of these firms commandconsiderable publicity, and become important rolemodels for aspiring entrepreneurs. In Finland, thereare several examples of NTBFs which started small,successfully developed innovative new applications,and which have achieved rapid growth while manag-ing to remain financially independent. One of themost successful university spin-offs in Finland, PolarElektro Oy, is a perfect ‘linear’ success story. Estab-

0048-7333r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.Ž .PII S0048-7333 97 00054-1

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987974

lished by a University Professor, it develops andmanufactures cordless pulse meters for fitness andsport training purposes. Established in 1984, PolarElektro is now the global leader in its niche, and itstotal assets are approximately 200 MECU. The firmtoday employs approximately 350 employees.

Examples of phenomenal success such as PolarElektro represent only a very small minority of thetotal stock of NTBFs, however. The great majorityof NTBFs will never be other than micro firms.Growth is not even a key goal for the managers of

Žmost NTBFs. Empirical surveys e.g., Kamshad and.Hay, 1996 consistently suggest that the majority of

NTBFs do not consider growth as desirable, prefer-ring to pursue profitability through specialisation. Tofocus solely on the ‘linear’ view of NTBFs wouldtherefore represent an oversimplification of the vari-ety of contributions that NTBFs can provide withinregional and national economies.

It can even be argued that Schumpeter’s modelsof innovation no longer apply in today’s InformationSociety. It is an often repeated postulation that thediffusion of information and communication tech-nologies lowers the threshold for outsourcing ofactivities, thus encouraging flexible specialisation andnetworking between firms. In this kind of economy,growth in the size of individual firms may no longerbe a prerequisite for, or be synonymous with, suc-cess. Successful NTBFs in the Information Societycould prefer to remain small and be less concernedwith growth.

In this paper, we will review empirical data onNTBFs in Finland, and discuss it against the back-ground of such arguments. By doing so, we attemptto contribute to the understanding of possible rolesof NTBFs in industrial systems in small openeconomies such as Finland. The empirical data isderived from two of our previous studies that havelooked at different aspects of NTBFs in Finland.

In our opinion, Finland provides a good settingfor such an analysis. First, Finland is a small,export-intensive economy. It has a well coordinatedand active innovation policy. Because of the smallsize of the economy, it is possible to attempt tohighlight aspects relating to the overall impact ofNTBFs in Finland’s national innovation system. Thiswould not be possible in a similar way in a largereconomy, where different states and regions might

have very different industrial bases and industrialpolicies. In addition to providing an example of asmall open economy, Finland provides an exampleof an economy where the diffusion of informationand communication technologies is high. 1 Finland isa highly networked country: for example, the percapita density of world wide web servers in Finlandis the highest in the world. The per capita density ofmobile telephones in Finland is also the highest inthe world. 2 OECD studies suggest that FinnishSMEs are among the most active in the world interms of taking advantage of new ICT-based applica-tions.

The first part of the empirical analysis, the reviewof the population data, examines the evolution of theeconomic importance of NTBFs during a period ofeconomic recession. The evolution of the high tech-nology sector in Finland is compared with the coun-try’s ‘traditional’ manufacturing sectors. During theperiod surveyed, Finland experienced an exception-ally deep economic recession: between years 1990and 1992, the Finland’s GNP fell by nearly 20%.This decrease was more drastic than that experiencedin the USA during the Great Depression. The analy-sis of the population data will therefore enable us tosee how NTBFs fared during a period of severeeconomic downturn. The population data allows usto examine the economic impact of NTBFs in asmall open economy in terms of the change in thenumber of firms, the employment created by thefirms, and the extent of outsourcing and networkingbetween NTBFs and large firms. This analysis anddiscussion of the population data is complemented inthe second empirical part of the paper by a review ofsurvey data on NTBFs. The survey data analysed

Ž .relates to: 1 the functional contributions of NTBFs;suggesting that NTBFs often operate as ‘innovationassets’ in innovation networks, catalysing technology

Ž .flows between different actors in the network; 2networking; suggesting that NTBFs mainly service

1 ATMsAsynchronous Transfer Mode, technology geared toincreasing the throughput capacity of telecommunications net-works.

2 GSMsGroupe Speciale MobilesGeneral Standard for Mo-bile telephones, the European standard for digital mobile tele-phony.

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large firms, often becoming specialised subcontrac-tors of technology intensive inputs for these. Thepaper ends with some conclusions which attempt tointegrate the theoretical issues and the empiricalresults presented in the study.

2. Conceptual foundations

In this paper, data pertaining to NTBFs are dis-cussed from the systemic perspective, in the contextof innovation systems. This approach builds on the

Žresource-based view of the firm Wernerfelt, 1984;.Penrose, 1959; Rumelt, 1984; Winter, 1987 in the

sense that NTBFs are viewed as bundles of firm-specific technological resources. The systemic per-spective focuses on the links between NTBFs andother actors in the network and analyses the contri-butions of NTBFs in innovation systems. Examplesof their contributions could include, for example,wealth generation through rapid organic growth,wealth generation through acquisition and subse-quent growth, and various catalysing contributions tosystemic innovation processes. The catalysing contri-butions are realised by influencing the flows andaccumulation of knowledge and technology withininnovation systems.

This approach to analysing the impacts of NTBFsin innovation systems can be justified by a numberof arguments. First, NTBFs, by definition, base theiractivity on exploiting advanced technological know-how. A considerable portion of this knowledge takesthe form of human capital. For NTBFs, technologyconstitutes a highly firm-specific, inalienable re-source, with which the firm seeks to generate profit.The distinctiveness of this resource is also continu-ously enhanced during the normal activity of theNTBF, as the firm learns from its previous projects.The resource-based view of the firm should thus beparticularly applicable to NTBFs.

The transactions between NTBFs and their cus-tomers are often highly knowledge intensive andinvolve a considerable service component. The valuecreation in such transactions is often based more onfunctional contributions delivered during the transac-tion than on the transfer of unchanged goods. Fol-

Ž .lowing terminology of Christensen 1995 , NTBFs

can be considered as innovation assets operating ininnovation networks. When value creation is basedon functionalities, and as assets are firm specific,there is scope for exploiting the innovative potentialoffered by an innovative combination of resources.An important feature of the resource-based view ofthe firm is the emphasis attached to the innovativecombination of firm-specific resources as a mecha-

Ž .nism of the generation of profit Conner, 1991 .The above considerations lead to the first set of

research questions to be addressed in the review ofŽ .empirical data: 1 How do NTBFs create value?

What functional roles do they have? Do these rolesreflect a resource-based logic of operation?

The dynamic complementarities theory postulatesthat both large and small firms have advantages in

Ž .innovation Rothwell, 1983 . The innovation advan-tages of large firms are usually scale-intensive, asso-ciated with their relatively greater financial, techno-logical, and production resources. Small firms havestrengths that cannot easily be replicated by a largefirm, including entrepreneurial dynamism, internalflexibility, responsiveness to changing circum-stances, and specialised expertise. These advantages

Žcontribute to a high innovation efficiency Acs andAudretsch, 1993; Rothwell and Dodgson, 1993; For-

.rest and Martin, 1992; Lee, 1995 .The dynamic complementaries can vary consider-

Žably in different industry sectors Laamanen and.Autio, 1996 . In different industries, different modes

of cooperation between small and large firms may befavoured. This means that also the contribution ofNTBFs to collective learning and technology accu-mulation processes in innovation systems can varyŽRothwell and Dodgson, 1993; Rothwell, 1984;

.Covin and Prescott, 1990 .The second set of research questions to be ad-

Ž .dressed in the empirical analysis is: 2 How are thedynamic complementaries between NTBFs and largefirms in innovation being exploited in practice? Arethere differences between industry sectors in thisregard?

It is often suggested that NTBFs tend to operatein the border zone between established industry sec-tors. As the NTBF seeks to generate profit by apply-ing its technological skills to satisfying a variety ofneeds amongst different customers in different indus-try sectors, it is often difficult to identify a clear

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987976

Fig. 1. Illustration of the technology transfer taking place througha NTBF.

market for them. This is particularly true for thoseNTBFs whose products and services are highly cus-tomised and involve great deal of customer-specificdevelopment activity. Such NTBFs can be viewed asa mode of technology transfer, not only between thepublic sector research institutions and industryŽ .Olofsson and Wahlbin, 1993 , but also betweendifferent industry clusters. This situation is illustratedin Fig. 1.

Here, an industry cluster refers to a set of closelylinked industry sectors. Fig. 1 illustrates an examplein which the NTBF has customers in several industryclusters and a parent organisation from which it hasbeen spun off.

The technology linkages between a NTBF and itscustomers and parent organisation may change overtime. Our earlier studies suggest that, in the begin-ning, the linkages with the parent organisation arethe more important and that as the NTBF growsolder, its customer linkages become more establishedŽ .Autio, 1994 .

The third set of questions to be addressed in theŽ .review of empirical data is: 3 Do NTBFs transfer

technology in innovation networks? Specifically, istechnology transferred in the interaction with cus-tomers and parent organisations? What technologytransfer mechanisms are used?

In the following review of empirical data, Section3 reviews the population data to give an idea of thegeneral economic importance of NTBFs in Finland.The research questions outlined above are analysedthrough the use of survey data in Section 4.

3. The changing population or NTBFs in Finlandbetween 1986 and 1993

In the review of the population data on NTBFs inFinland, the databases of Statistics Finland have beenused. NTBFs are defined as small- and medium-sizedfirms operating in high technology sectors. Small-and medium-sized firms are defined as firms em-ploying up to 200 employees, and for high technol-ogy sectors we follow the definition of ButchartŽ .1987 . Butchart’s definition uses a number of indi-cators, notably R&D intensity, in distinguishing be-tween high technology from other—‘low technol-

Ž .ogy’—industry sectors Storey and Tether, 1996 .This definition has been used in several similar

Žstudies Keeble and Walker, 1994; Garnsey et al.,. 31994 .

The review of population data will compare twoyears, years 1986 and 1993. The comparison be-tween these two years gives a fairly good snapshotof the evolution of the stock of NTBFs in Finland. Italso gives an idea of how this stock has evolvedduring an economic recession. Between years 1990and 1992, Finland was hit by a particularly severe

3 In Finland, the industry classification system has been revisedseveral times during the past years. The NACE classificationsystem was not taken into use until 1994. Before the NACEclassification system, the TOL 88 classification system was used.This system can be used to extract data pertaining to years 1986until 1993. As the coverage of this classification system is reason-ably broad, we will review data pertaining to years 1986 and1993. Data from year 1994 onwards cannot be used in time seriesanalysis, since the value added tax system was changed in Finlandin year 1994. This altered the definition of the firm, as applied byStatistics Finland. The consequence of this change was that sev-eral thousands of firms disappeared from Statistics Finlanddatabases and several thousands similarly added for the 1994database. To date, no correction coefficients have been introducedto make the data until 1993 compatible with data that has beencompiled after year 1993 by Statistics Finland.

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987 977

Table 1The number of firms in high-tech and in low-tech sectors in 1986 and 1993

Size class High-tech sectors Low-tech sectors

Number of Number Number Change % of % of Number Number Change % of % ofemployees of firms, of firms, firms, firms, of firms, of firms, firms, firms,

1986 1993 1986 1993 1986 1993 1986 1993

0–4 2434 3968 63% 62% 71% 11 144 10 487 y6% 68% 71%5–9 678 853 26% 17% 15% 1555 1626 5% 10% 11%10–49 645 561 y13% 16% 10% 2674 1940 y27% 16% 13%50–499 137 170 24% 4% 3% 822 674 y18% 5% 5%500–999 12 6 y50% 0% 0% 41 54 32% 0% 0%1000– 7 11 57% 0% 0% 56 43 y23% 0% 0%Total 3913 5569 42% 100% 100% 16 292 14 824 y9% 100% 100%

Ž .Source: Autio and Parhankangas 1998 .

recession during which the country’s GNP shrank bynearly 20%.

In this section, high and low technology industrysectors will be compared. Low technology sectorsare defined to include all industrial manufacturingand technical services sectors that are not included inthe ‘high technology’ sectors, as defined by Butchart.The comparison group does not include non-in-dustrial sectors, such as agriculture, commerce andpersonal services.

3.1. The number of firms in 1986–1993

The high technology sectors in Finland experi-Ženced rapid growth between 1986 and 1993 Table

.1 . The number of firms in these sectors increased by42%, while the number of industrial firms in the‘low technology’ sectors declined by 9%. Thesechanges indicate a sharp increase in the relativeimportance of high technology sectors. The share ofNTBFs of all firms operating in industrial sectorsgrew from 19% in 1986 to 27% in 1993.

The great majority of Finnish NTBFs are tiny. In1986, the proportion of all firms in high technologysectors employing 0–4 people was 62%. In 1993,this percentage had grown to 71%. In the low tech-

Žnology sectors, a proportional increase although the.absolute number of tiny firms decreased , from 68%

in 1986 to 71% in 1993, can also be noted.The number of technology-based micro firms

Ž .firms employing less than 10 employees increasedby 55% from 1986 to 1993. In low-tech sectors, thenumber of micro firms fell by 5%.

In contrast with micro firms, the number of hightechnology small firms grew less rapidly. The num-ber of firms employing from 10 to 50 employeesactually fell during the period from 1986 to 1993.This drop may be partly due to the high rate ofacquisition of firms in this size class. 4

The most rapid growth occurred in high technol-ogy services. The three highest growth sectors were

Ž .computer programming services q702 firms , tech-Ž .nical services for construction q409 firms , and

Ž .machine and process technical services q386 firms .In these sectors, the number of micro firms grewparticularly rapidly, suggesting a recession-push ef-fect, with people who were made redundant settingup small consultancies. The sharpest decline in thenumber of firms was experienced in technical plan-ning and consulting services, in electronic householdappliances, and in computer services. Of the hard-ware sectors, the highest growth was recorded ininstruments and fine-mechanical apparatus and inelectronic and communications equipment.

3.2. Employment in the high technology sectors in1986–1993

According to the Review of New TechnologyŽ .Based Firms in Europe Storey and Tether, 1996 ,

4 Ž .Laamanen and Autio 1996 suggest that approximately 50employees may be a critical size for firm acquisitions in Finnish,technology-based industries.

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high technology manufacturing employment in Eu-rope as a whole fell during the 1980s. This waslargely due to the contraction of the electronicssector. However, in some countries, including Fin-land, Austria, Denmark, West Germany, Luxem-bourg, Ireland, and Norway, high technology manu-facturing employment increased between 1980 and1990. The following analysis of the development ofhigh technology employment from 1986 to 1993suggests that the increasing trend has continued inFinland.

The development of aggregate employment inhigh and low technology sectors is presented inTable 2. In spite of the recession, the number ofpeople employed by high technology sectors in-creased by 17% from 1986 to 1993. The severity ofthe recession is illustrated by the employment ero-sion in the low technology industrial sectors, inwhich employment contracted by 33%. Because ofthis dramatic fall, the total employment in all indus-trial sectors fell by 26% between 1986 and 1993.During the recession, the share of people employedin high technology sectors increased from 13% to17% of the total workforce in all industrial sectors.

The increase in employment was particularly im-pressive among technology-based micro firms. Theoverall employment generated by technology-basedmicro firms increased by 38% during the period1986–1993. High technology firms employing lessthan 500 employees employed 70% of the workforcein these sectors, while generating only 26% of thetotal annual sales. The seven firms in the largest sizeclass, while representing only 0.2% of the total

number of firms and employing 34.6% of the work-force, generated 71.4% of the total sales in thesesectors.

The sectors with the largest absolute increases inemployment were the electronic and communications

Ž .equipment q3960 employees , computer program-Ž .ming services q3875 employees , and the instru-

Žment and fine-mechanical apparatus sectors q3462.employees . This growth mainly occurred in firms

employing more than 20 employees. The most sub-stantial losses were recorded by construction techni-

Ž .cal services y3182 employees , electronic house-Ž .hold appliances y1231 employees , and other tech-

Žnical planning and consulting services y551 em-.ployees .

The most rapidly growing sectors for small tech-nology-based firms were computed programming

Ž .services q2003 employees and machine and pro-Ž .cess technical services q904 employees . Small

firms account for the majority of new employmentcreation in these service sectors. In these sectors,entry does not require substantial up-front invest-ment.

In general, our evidence, as well as other circum-stantial evidence, suggests that the growth in thenumber of NTBFs coincided with the growth of afew large ‘locomotive’ firms, in Finnish high-tech-nology sectors, such as Nokia, ABB Industry, ICL,and others. We have good reason to believe thatmany of the new NTBFs had been established be-cause of the ‘pull’ provided by a few large ‘locomo-tive’ firms. In Section 4, we will examine how this‘pull’ works in practice.

Table 2The number of employees in high-tech and in low-tech sectors in 1986 and 1993

Size class High-tech sectors Change Low-tech sectors Change

1986 1993 1986 1993

0–4 employees 4104 6153 50% 14 129 13 152 y7%5–9 employees 4342 5532 27% 10 333 10 806 5%10–49 employees 12 209 10 589 y13% 57 336 41 568 y28%50–499 employees 18 740 23 905 28% 110 313 94 204 y15%500–999 employees 7961 4150 y48% 29 172 38 111 31%1000– employees 18 311 26 588 45% 222 333 99 925 y55%Total 65 667 76 917 17% 443 616 297 766 y33%

Ž .Source: Autio and Parhankangas 1998 .

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987 979

4. Panel survey of NTBFs

While population data is useful in exploring thegeneral evolution trends and the overall importanceof NTBFs in a small open economy such as Finland,gaining a deeper understanding requires survey data.This paper reviews data from a panel survey con-ducted in Finland during 1994 by SITRA, the Na-

Žtional Fund for Research and Development Autio.and Yli-Renko, 1998 . The analysis explores the

functional roles of NTBFs in the Finnish nationalsystem of innovation and the technology flows catal-ysed by the firms between and within strategic indus-try clusters in Finland. 5

The review starts by introducing the basic charac-teristics of the panel. The parent organisations, cus-tomers, and the functional contributions of the panelfirms are then reviewed. Finally, the nature of thetechnology transfer between the firms and their cus-tomers and parent organisations is explored.

4.1. Basic characteristics of the panel

The basic characteristics of the panel of NTBFsare given in Table 3. The size of the firms is shownas the number of employees in 1993 and as theannual sales in 1993.

The majority of the panel firms were young andsmall. The age distribution of the panel, as well asthe sales and employee distributions, are skewedtowards the small end. These distributions are similarto the population data reviewed in Section 3.

4.2. Parent organisations

From the systemic perspective, acquisitions andspin-outs of NTBFs constitute important mechanisms

5 A target population of 1445 technology-intensive firms wasidentified by regional expert panels in different parts of Finland.The expert panels consisted of representatives from non-profitregional organizations supporting small- and medium-sized enter-prises. Responses were eventually received from 392 firms thatmet the selection criteria. The firms included in the database areindependent, small- and medium-sized firms, which base theirbusiness on exploiting advanced technological knowledge.

Table 3Basic characteristics of the panel

Characteristic Mean Median Observations

Year established 1983 1987 389Employees in 1993 24.5 8.0 378Sales 1993, US$ 2.9 million 0.7 million 366

for technology transfer and for technological accu-mulation in innovation systems. Empirical studies inFinland suggest that many NTBFs with a high poten-tial for growth are acquired by large firmsŽ .Laamanen, 1997 , and that of these acquisitionstend to be technology- rather than market-driven.This may be for many reasons. The market forexternal equity funding in Finland is small, andinitial public offerings rare. The venture capital in-dustry is also young. A trade sale is often the mostfeasible way for an NTBF to access the financialresources necessary to sustain rapid growth. In addi-tion, large firms are better equipped to access foreignmarkets, and a trade sale may be the only way for aNTBF to exploit the commercial potential of a tech-nology before the window of opportunity is closed.

The converse to acquisition is a spin-out of aNTBF from an existing organisation. Sometimes aspin-out may take place because the incentives forthe exploitation of an inalienable knowledge assetare greater within a new independent firm than in thecontext of a large firm. Such reasons may applywhen the spin-out takes place from an existing indus-trial firm. In the ‘classical’ case of a spin-out from auniversity or public sector research organisation,however, the motivation is more likely to be the‘linear’ commercialisation of public sector researchresults.

The panel firms were asked to indicate theirparent organisations. A parent organisation was de-fined as an organisation from which the firm orentrepreneurs had obtained an important part of theirtechnological know-how. The replies to this questionare summarised in Table 4.

The most interesting aspect of Table 4 is the ratiobetween industry spin-outs and spin-outs from publicsector research organisations. In the table, this ratiois approximately two to one, indicating that industryspin-outs are more commonplace.

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Table 4Parent organisations of the panel firms, 392 observations

Type of parent organisation Number of firms Percentage

Another firm 82 21%University 32 8%Technical Research Centre of 17 4%Finland VTTOther 13 3%No parent organisation 248 64%identifiedTotal 392 100%

Ž .Source: Autio and Yli-Renko 1998 .

The large share of NTBFs indicating no specificparent organisation is probably due to the way thisquestion was formulated. The definition of parentorganisation emphasised technology links: the firmhad to receive inputs to its technology base from itsparent organisation. An organisation in which the

Ž .entrepreneur s previously worked, but in which thetechnology of the new firm was not explicitly devel-oped, did not qualify as a ‘parent’ organisation.

Another reason for the high share of NTBFsindicating no parent organisation could be the re-

Ž .cency effect Tversky and Kahneman, 1974; p. 41 .This means that firms tend to focus on their recentpast, underestimating the importance of earlierevents. Older NTBFs may simply either have forgot-ten about their original technology links, or they mayunderestimate their importance. In the panel, the ageof firms indicating a parent organisation was indeedsignificantly younger than that of those which didnot. Of firms under 3 years old, 43% identified aparent organisation, whereas only 29% of firms over5 years old identified a parent organisation. 6

4.3. Links with research organisations

The panel firms were asked about the relationshipbetween their firm’s initial knowledge base and tech-nological knowledge which had been developed at auniversity or research institution. Of the 383 respon-dents, 10% indicated a direct link, 21% a partial link,25% a weak link, while the remaining 44% indicated

6 The difference is statistically very significant, the p-valuebeing 0.001.

no link. 7 This suggests that formation of approxi-mately half of NTBFs was at least partially moti-vated by the commercialisation of the results ofresearch undertaken by a university or research insti-tution. It should also be noted that even firms whichdid not indicate a parent organisation often usedtechnological knowledge developed at a university orresearch institution as part of their initial technologybase.

4.4. Customers

If NTBFs exploit dynamic complementarities be-tween small and large firms, then large firms shoulddominate their customer base. In the panel, approxi-mately 80% of the annual sales of the NTBFs sur-veyed came from private sector corporate customers.Public sector customers accounted for an average ofjust 16% of sales. The size distribution of the firms’most important corporate customers is indicated inFig. 2.

The distribution in Fig. 2 shows that the cus-tomers of NTBFs tend to be large, established firms.In the analysis of the population data in Section 3, itwas suggested that the emergence of NTBFs in hightechnology sectors may have been catalysed by thegrowth of large firms in these sectors. The popula-tion data showed that the seven firms in the largest

Ž .size class i.e., those with over 1000 employees inthe high technology sectors represented only 0.2% ofthe number of firms, but employed 34.6% of theoverall workforce and generated 71.4% of turnover.This, together with the panel survey finding thatNTBFs serve mainly large corporate customers,clearly indicates that NTBFs tend to operate as sup-pliers and service providers to the large systemsintegrators in the economy.

The patterns of small–large firm interaction aremore complicated than those shown in Fig. 2, how-

7 A direct link was defined as: ‘the firm was founded tocommercialise technological knowledge, a business idea, or aproduct developed at a university or research institution’. A partiallink was defined as: ‘technological knowledge developed at auniversity or research institution was, among others, an importantcomponent of the initial business idea of the firm’. A weak linkwas defined as ‘technological knowledge developed at a univer-sity or research institution was not directly used at the start-up ofthe firm’.

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Fig. 2. The distribution of the panel firms according to the size of their most important corporate customers, 387 observations.

ever. A closer analysis shows that the larger theNTBF, the larger its customers are likely to be.Among the firms with large customers the meannumber of employees was 28.6, while the meannumber of employees amongst the firms which didnot indicate that large firms were their most impor-tant customers was 18.6. 8

Furthermore, the chi-squared test for indepen-dence indicates that service firms were more likelyto have large firms as their most important cus-tomers. The firms with a high-technology main prod-uct were slightly less likely to have large firms astheir most important customers. 9 As service firmswere generally smaller than manufacturing firms, theresults suggest that the distribution of NTBFs sup-plying to large firms differs from those that do not.This combination, of smaller service firms with some

Žlarger, less high-tech manufacturers particularly.manufacturing subcontractors explains the larger

mean size of the firms that supplied large firms.

4.5. Functional contributions

The functional contributions of a NTBF are de-fined in terms of how the firm generates value for itscustomers. The survey asked the respondents to indi-

8 The difference is statistically significant, with a p-value of0.0317.

9 The chi-squared p-value for this difference is 0.0013, indicat-ing a high statistical significance.

cate their firms’ functional contributions from a listof eleven alternatives. The respondents were allowedto indicate multiple functional contributions. Thedistribution of responses is provided in Fig. 3.

Ž .The majority 69% of the firms in the panelfocused on increasing their customers’ productionefficiency, a functional contribution that emphasisesthe technology diffusion role of NTBFs. Nearly halfŽ .47% of the firms claimed to function as an external

Ž .R&D resource another technology diffusion role ,and 41% operated as a subcontractor or an originalequipment manufacturer for their customers. An in-dependent role developing a product and marketingit to the end-users of the product was indicated by47% of the sample firms. It is interesting to note thatover half of the firms did not recognise this function,although most research on NTBFs seems to assumethis is the primary function of NTBFs. The func-tional contributions of the firms were largely over-lapping. For example, being a subcontractor need notimply that a firm could not also have had an inde-pendent role as a producer of new products or alsohave been an external research and developmentresource for its customers.

The results of the present study indicate a highdegree of overlap between replication-intensive ac-tivities, such as operating as an original equipmentmanufacturer or producing goods for end-users, anddevelopment-intensive activities, such as acting as anR&D resource. The functional contributions suggestmany NTBFs function as innovation assets for theircustomers.

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Fig. 3. Functional contributions of the panel firms, 376 observations.

4.6. Customer industries

The survey asked the firms to identify their mostimportant customer industries. The customers of thefirms were divided into groupings of industries, fol-

lowing the categorisation developed in the nationalstudy on Finnish industry clusters which was carriedout by ETLA, the Research Institute of the Finnish

Ž .Economy Hernesniemi et al., 1995 . Again, thesurveyed firms were allowed to identify more than

Fig. 4. Distribution of panel firms according to customer clusters, 386 observations.

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987 983

one customer cluster. The distribution of customersover industry clusters is shown in Fig. 4.

It was not uncommon for the panel NTBFs tooperate in several industry clusters. While over halfŽ .54% indicated only one most important customercluster, the remaining 46% indicated an average ofthree clusters.

It is perhaps surprising that so many of the panelfirms appear to be serving traditional, low technol-ogy industries. Approximately 30% of the panelfirms serviced the forestry cluster. The metal, en-ergy, transportation, and construction clusters wereeach indicated by roughly one fifth of the samplefirms. The other customer groups identified includedmiscellaneous customers such as the armed forcesand the banking and travel industries. The largeproportion of NTBFs servicing traditional, low tech-nology industries and creating value for their cus-tomers through development-intensive activities sug-gests that these NTBFs have a role in adaptingadvanced technology to the needs of traditional in-dustries.

The evidence from the panel survey suggests thatthe higher the degree of technological sophisticationin the sector served, the younger and smaller are theNTBFs servicing it. The firms servicing the electron-

ics cluster were, on average, the youngest. Theirmean age was 7.6 years. Other clusters serviced byrelatively young firms were the medical, telecommu-nications and environmental customer clusters. All ofthese clusters are technology intensive. The firmsservicing the medical, environmental, metal, andforestry clusters were on average the smallest in thesample. The construction, transportation, and thepower generation and transmission clusters were, onthe other hand, serviced by the oldest and largestgroup of firms in the sample.

4.7. Technology transfer between the sample firmsand their parent organisations

Many firms continue to maintain technology in-tensive links with their parent organisations afterstart-up. In the case of industrial spin-outs, this maybe due to the exploitation of resource complementar-ities between the firm and its parent organisation. Inthe case of public research sector spin-outs, this maybe due to the continued exploitation of the researchpotential of the parent organisation.

The panel firms were asked to evaluate the inten-sity of the technology flows stimulated by a varietyof technology, transfer mechanisms. The intensities

Fig. 5. Technology flows between the panel firms and their parent organisations.

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987984

Fig. 6. Technology flows between the panel firms and their customers, 314 observations.

were evaluated using a five-step Likert scale. Theresults are shown in Fig. 5.

In general, the panel firms tended to receiveslightly more technology from their parent organisa-tion than they contributed to the parent. The mostintensive flows are informal technology transfermechanisms, with the more formal mechanisms—such as basic research cooperation—being less im-portant. Of the more formal transfer mechanisms, theclose-to-market mechanisms, such as cooperation inproduct development seem to be the more important.The transfer of people through recruitment does notappear to be an important technology transfer mech-anism, but the relatively high rating given for thesale or purchase of products and services indicatesthat the relationship between a firm and its parentorganisation often becomes a formal buyer–sellerrelationship.

4.8. Technology transfer between the firms and theircustomers

The technology flows stimulated by interactionswith customers were similarly assessed and are sum-marised in Fig. 6. In general, technological interac-tions with customers were relatively more intensive

than those with the parent organisations. 10 How-ever, the similar shapes of the figures reveals that therelative importance of the different technology trans-fer mechanisms was similar.

The general balance of technology flows tookplace from the sample firms towards their customers.As in the case of technological interactions with thefirms’ parent organisations, there is clear evidence oftwo-way technology interactions between NTBFs andtheir customers. While the sale or purchase of prod-ucts and services was the most important technologytransfer mechanism, other, more cooperative mecha-nisms, were given high ratings. This holds particu-larly for cooperation in product development and forsubcontracted product development. This finding canbe interpreted as a revealing evidence of activitiesthrough which the resources of the sample firms andtheir customers are combined. In the cases of cooper-ation in product development and informal discus-sions between colleagues, the evidence points to a

10 Please note that the scale used in Fig. 5 ranges from 1 to 4,whereas in Fig. 4 the scale ranged from 1 to 3; this is necessary tobring out the shape of the figures.

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987 985

balanced technology exchange process in the interac-tions between the firms and their customers.

5. Conclusions

The population data highlighted the increasingimportance of NTBFs in the Finnish economy. Dur-ing the economic recession of the early 1990s, NTBFsincreased in number faster than firms in low technol-ogy industrial sectors. This impressive increase inboth the number of firms and their employmentgeneration was due to an increase in the number ofmicro firms as well as medium-sized and large firms.Furthermore, the most remarkable growth occurredin electronics, telecommunications equipment and inthe information services sectors. This appears tosupport the hypothesis that NTBFs are increasinglyimportant economic agents in the development of theInformation Society.

In this paper, the empirical data have been inter-preted as supporting the contention that NTBFs tendto operate in innovation systems and that they seekto generate economic profit through the innovativeleveraging of their technological resources. It seemsthat NTBFs operate mainly as specialised suppliersand service providers for large- or medium-sizedfirms in different industry clusters of the Finnisheconomy, and thereby tend to become attached to theexternal technology supply networks which aremaintained by their large customers. The analysis ofthe functional contributions of NTBFs suggests thereis a tendency for NTBFs to exploit dynamic comple-mentarities with their larger customer firms. Also, itseems that, in the value-creation mechanisms ofNTBFs, replication-intensive and development-inten-sive activities are largely overlapping.

The customers of the panel of Finnish NTBFswere quite evenly scattered across Finland’s industrysectors. NTBFs do not only service the high-technol-ogy sectors such as electronics and telecommunica-tions, but are also active in providing products andservices to the traditional sectors such as forestry,metals, power generation and transmission, construc-tion, and transportation sectors. None of these tradi-tional industries can be regarded as providing afavourable environment for the growth of small firmsinto large entities. This finding, together with the

analysis of the functional contributions of the firms,points to a prevalent technology diffusion role ofNTBFs in innovation systems. It seems that NTBFshave a role in adapting advanced technology to theneeds of traditional industries.

The empirical data suggests that NTBFs constitutea channel of technology transfer between the re-search sphere and industry in Finland. Over halfŽ .56% the panel firms indicated that there was a linkbetween their initial knowledge base and technologi-cal knowledge that was being developed at a univer-sity or research institution. The surveyed firms alsoactively transfer technology to and from their cus-tomers, which are mostly industrial firms. The gen-eral balance of technology flows seems to be fromthe NTBFs to their customers. Those NTBFs whichidentified a parent organisation also actively trans-ferred technology to and from their parent, with thegeneral balance of transfer being towards the NTBFfrom the parent organisation.

The empirical data has also shown that it iscommon for NTBFs to have customers in severalindustry sectors. Thus, as was suggested in the con-ceptual foundations presented in the first part of thepaper, NTBFs often operate in the border zone be-tween the industrial clusters in the Finnish economy.NTBFs can therefore be viewed as not only a tech-nology transfer channel between the research sphereand industry, but also between and within the differ-ent industry clusters.

On the basis of the available data, it is possible todraw some conclusions for the design of industrialand innovation policy. First, the reviewed empiricaldata suggests that NTBFs tend to become closelylinked with the domestic industrial base. Instead of

Žgrowing independently by developing products and.selling them to end-users , many Finnish NTBFs

seem to grow as organic parts of technology supplynetworks maintained by large firms. This way, theyare able to use to demand pull generated by largefirms. Many policy measures that aim to induce

Žgrowth among NTBFs provision of venture capital,.soft loans, business advice, etc , are more suitable

for inducing ‘independent’ growth. Such measuresmay not be very effective among ‘networked’NTBFs. To supplement these supply side supportmeasures, it would seem useful to develop supportmeasures that seek to proactively benefit from the

( )E. Autio, H. Yli-RenkorResearch Policy 26 1998 973–987986

demand pull generated by large firms, and in whichthe active participation of large firms is sought. Suchmeasures could include assisted spin-out initiatives,by which large firms would be induced to spin outnon-core activities and to become the first customersof the new firms. They could also include the estab-lishment of technology outsourcing programs forlarge firms, through which large firms would ac-tively seek to support the emergence of positiveexternalities in the form of specialised suppliers. Asthe specialised supplier NTBFs grow, they couldgradually become more independent, and start seek-ing customers elsewhere.

Another general policy conclusion to be drawnfrom the review of Finnish data is that the economicimportance of NTBFs is not limited to their directgrowth. Most NTBFs never reach the size of 10employees, but they are still remarkably stable, thusproviding a stable employment for a number ofprofessionals. Their active engagement in technologydevelopment and diffusion activities helps improvethe efficiency of large firms, thus contributing to theinternational competitiveness of many traditional in-dustry sectors. In Finland, there are cases in whichthe very presence of a large number of small NTBFshas provided an inducement for a large firm to set upan operation in the same region, as the small NTBFscan be used effectively as specialised technologysuppliers. Many large technology-based firms are inthe process of setting up technology outsourcingprograms in Finland.

Finally, it should be noted that even the directgrowth of NTBFs is likely to be more significantthan that suggested by the basic statistics, for empiri-cal studies in Finland suggest that NTBFs with ahigh potential for growth are more likely to become

Ž .acquired by large firms Laamanen, 1997 . Thus theytend to disappear from the basic statistics, eventhough they often continue their rapid growth withinthe acquiring firm. For small open economies, suchas Finland, this growth route may be particularlyimportant because the domestic market is small. In alarge economy, it would be easier for NTBFs toreach a substantial size before going international. Ina small economy, it may often turn out to be morefeasible to sell the NTBF to a large firm, whichcould then use its international distribution channelsto rapidly scale up the acquired business.

Acknowledgements

The authors are grateful to David Storey, BruceTether and the two anonymous referees for theircomments on an earlier version of this paper. Theusual disclaimer applies.

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