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DOES THE INNOVATOR ROLE AFFECT THE PERCEIVED POTENTIAL FOR GROWTH? ANALYSIS OF FOUR TYPES OF NEW, TECHNOLOGY-BASED FIRMS
Erkko Autio, Helsinki University of Technology, Institute of Industrial Management
Annareetta Lumme, Regional Development Fund of Finland KERA
The present study analyzes interrelationships between systemic determinants, such as the technology applied by the firm, and the evolution of the firm. Four innovator roles of new, technology-based firms are analyzed: application innovators, market innovators, technology innovators, and paradigm innovators. The analysis of an empirical sample of 392 new, technology-based firms in Finland finds that application innovators and technology innovators are the oldest and largest among these four groups of new, technology-based firms. On the other hand, the largest potential for growth can be found among market innovators and paradigm innovators. The analysis also suggests that the contentions of the 'traditional' approach to research on new, technology-based firms apply particularly well on application innovators and on market innovators. On the other hand, the contentions of the new, systemic approach to research on new, technology-based firms may be better suited on paradigm innovators and on technology innovators.
The optimistic view of many European policymakers is that barriers hindering the growth of new, technology-based firms can be removed using hands-on policy measures. After the growth barriers would be identified and removed, automatic growth would follow, the reasoning goes, since practically all new firms are growth oriented.
Empirical evidence from, for example, United Kingdom, Sweden, and Finland shows that such views are overtly simplistic. According to empirical data, most new, technology-based firms are small. In studies carried out in different countries, the median size of new, technology-based firms has been found to be approximately 10 - 20 employees, and the mean size less than 50 employees. (Gould et Keeble, 1984; Keeble et Kelly, 1986; Rodenberger et McCray, 1981; Doutriaux et Peterman, 1982; Tyebjee et Bruno, 1982; Autio et alii, 1989, p 53). This is not surprising as such. The majority of firms everywhere are small. What may be surprising for many policymakers is that most new, technology-based firms do not even aspire for growth. Most new, technology-based firms are small and aim to stay that way. A study carried out in Finland in 1991 reported that over 60 % of new, technology-based firms in a science park did not perceive rapid or even moderate growth as a viable avenue for developing their activities (Kauranen et alii, 1990, pp 44 - 45). Kellock reports even more modest growth aspirations for small software firms (Kellock, 1992). An extensive survey carried out in Finland, focusing especially on new, technology-based firms with a high estimated potential for growth, found that the mean growth objective for these firms was less than 20 % per year for the next five years (Lumme, 1994a, pp 16 - 19; Lumme 1994b). This growth expectation can be considered as strikingly low, being an evaluation given by the firms themselves. Westhead reports that approximately 4 % of all new, technology-based firms create as much as 30 - 40 % of the total gross employment in these firms (Westhead, 1994). Reflecting on a large number of studies on new, technology-based firms, Oakey concludes that: "ÉNTBF's [new, technology-based firms]were not a simple panacea for the industrial ills of the United kingdomÉ", and: "Éit is a gross oversimplification to argue that all (or most) NTBF's [new, technology-based firms] have rapid growth potential..."(Oakey, 1994, pp 2 - 6). Focusing on small firms in general, Storey has emphasized the need 'pick the winners' and to focus policy measures on those rare examples of high growth small and medium sized firms (Storey, 1987, p 152).
In spite of the extensive empirical data pointing to the conclusion that most new, technology-based firms do not grow and do not even want to grow, the dominating view of new, technology-based firms even today is one presuming rapid growth, or at least an aspiration towards it. This is largely true both among researchers as well as among policymakers. The conceptions concerning the growth dynamics of new, technology-based firms are still largely simplistic, arguably to a degree in which the 'true' nature of new, technology-based firms is not even realized. Such conceptions of the growth dynamics of new, technology-based firms are often reflected, either explicitly or implicitly, in the settings of many studies as well as in the policy measures designed on the basis of such studies. Many books and studies, while acknowledging that most new, technology-based firms do not grow, still explicitly focus on rapid growth and largely dismiss the study of slowly growing new, technology-based firms (Slatter, 1992; Poza, 1989; Riggs, 1983; Flamholtz, 1990; Barber et alii 1990; Hull et Hjern, 1989). Even though empirical studies indicate that the conception concerning aggressive growth orientation of new, technology-based firms is largely a bubble, the general conceptions and their misleading implications remain largely unchallenged. Illustrative of this myopia is that Feeser, for example, in his otherwise excellent study on factors linked with the growth of new, technology-based firms, does not give any consideration to networks, to the use of external resources, and to the dynamic complementarities (Rothwell, 1983) between small and large firms (Feeser, 1987).
The simplistic assumptions concerning growth orientation among new, technology-based firms tend to overlook the constraining influence of systemic factors, such as the technological system (Carlsson et Stankiewicz, 1991; Carlsson et Jacobsson, 1994; Autio et Hameri, 1994) of which a new, technology-based firm constitutes an element. It has traditionally been assumed that a new, technology-based firm is free to embark on a rapid growth path, assuming that the market is there. It is the market, and the competitive environment of a new, technology-based firm, which has been viewed as the ultimate determinant of success or failure, with success often being equated with growth in sales (see, e q, Salonen, 1995). Aspiring for growth, a new, technology-based firm is assumed to be able to freely position itself in relation to its environment, as it deems appropriate.
While the above listed assumptions may apply well on many firms operating in more traditional industrial branches, their applicability on new, technology-based firms is often rather poor. Assumptions based on an explicit or implicit assumption concerning the existence of a market usually do not hold very well when the market remains to be created. This is the case of many a new, technology-based firm. Further problems are caused by the fact that traditional industry classifications often apply rather poorly on new, technology-based firms. An industry can be defined as a combination of a market and of the industrial apparatus geared to servicing it. For many new, technology-based firms, it is difficult to define the market in a traditional manner. Many a new, technology-based firm is better defined in terms of its set of customers, to which it is connected through a number of technology intensive links, and according to the special characteristics of which it shapes its technology pool. Such a relationship is only poorly reminiscent of the arms-length transaction relationship traditionally assumed in studies on new, technology-based firms.
To put it briefly, the traditional body of research on new, technology-based firms takes the market as its starting point. This approach has its roots in the neoclassical economic tradition. The new, systemic approach to research on new, technology-based firms approaches this problem from another angle. The starting point taken by the systemic approach is the technology applied by the new, technology-based firm.
The systemic approach to research on new, technology-based firms assumes the evolutionary view of a firm as a reservoir of knowledge (Fransman, probably 1993, p 2), or as a concentration of technological competencies. This view is in contrast with the neoclassical view of the firm as an input-output unit operating in a well defined market. The neoclassical view, on which many of the traditional studies on new, technology-based firms is based, focuses the attention on the market in which the firm operates. The evolutionary view of the firm focuses the attention on the technology applied by the firm. According to the systemic approach, the technological environment of a new, technology-based firm should be considered as a primary external factor exercising influences on the firm.
The present study attempts to examine the constraining effect of two systemic factors on new, technology-based firms. The factors analyzed in the present study are the novelty of technology applied by the new, technology-based firm, on the one hand, and the novelty of the customer needs targeted by the firm, on the other hand. On the basis of these two factors, it is possible to construct a tentative typology of possible innovator roles of new, technology-based firms in technoeconomic systems (Autio, 1994). It will be examined whether a relationship can be found between the early development of a technology intensive firm and its innovator role in a technoeconomic system. As the control function, growth in sales will be used.
The typology presented and tested in the present study takes into account both the novelty of technology applied by the firm and the novelty of the target market of the firm. Along each of the two dimensions, a distinction of two categories of new, technology-based firm is made, based on the relative novelty of the factor. The typology is presented in figure 1.
The four innovator roles analyzed in the present study are: application innovator, market innovator, technology innovator, and paradigm innovator. Likely relationships between the innovator role and the external influences faced by a new, technology-based firm are listed in below.
Application innovators are companies applying existing technology in an established market. Often, these companies act as agents of technology diffusion, diffusing new applications of diffusion-prone generic technologies across industrial sectors. Even though the technology applied by application innovators may be sophisticated and demanding, it is not new to the world. Many application innovators can be expected to target relatively narrow market niches, using customer specialization as an important differentiating asset. The bulk of new, technology-based companies probably belong to this category.
Market innovators excel in developing new product concepts. The technology applied by market innovators does not have to possess any radical features as such. The innovative impact is produced by a new combination of existing technologies. For example, the basic components needed for the creation of a personal computer were widely available before the introduction of the first personal computer. As the success story of Apple suggests, the new product concept may sometimes lead to the creation of completely new industries.
Technology innovators introduce new generic technologies into existing markets. The new generic technology is such that is has not been applied at the particular industrial sector before. Thus, technology innovators often directly challenge the existing status quo of the industry they try to penetrate. If the competence base needed to develop the new technologies is far enough from the competence base of the existing players, technology innovators may be able to push existing players out of the market. It seems more probable, though, that a technology innovator is either pushed to serve a narrow market niche, or the technology offered by it is rejected by the market.
Paradigm innovators are firms introducing new product concepts based on a completely new technology. Some paradigm innovators possess the potential of initiating radical innovations, changes in technological systems, and sometimes even changes in technological systems and in the prevailing technoeconomic paradigm. Paradigm innovators can be assumed to depict strong technology links with sources of advanced technology and basic research.
The empirical database analyzed in the present study was compiled in Finland during year 1994. The database covers 392 technology intensive firms from all over Finland. The size of the target population was 1 445 technology intensive firms. The compilation of the database was funded by the National Fund for Research and Development of Finland, SITRA.
Compilation of the sample
The SITRA database consists of independent small and medium sized technology intensive firms. The leading principle in forming of the database was to focus on firms deemed to possess potential for growth. In order to identify such firms, regional expert panels in different parts of Finland were used. The expert panels typically consisted of persons who knew well the population of technology intensive small and medium sized firms in their respective regions. Typically, such experts could be found from non-profit regional organizations supporting SME's. Such organizations include the SME service of the Ministry of Trade and Industry of Finland, regional offices of the Technology Development Center TEKES, Regional Development Fund of Finland KERA, and the national SME foundation. In addition, experts were invited from regional and national venture capital funds, from municipalities, and from financial institutions other than the ones listed above. All in all, 150 experts participated in the nomination of the target population of the present study.
The regional expert panels nominated a list of 1 445 SME's that were considered to be technology intensive and to possess potential for rapid growth. An effort was made to make sure that similar criteria for technology intensity were applied in all parts of Finland. Normally, a firm that would be considered an ordinary manufacturing firm in a high technology region, could well be classified as technology intensive in more remote parts of Finland. The project co-ordinator personally participated in the meetings of all regional panels to make sure that such biases were excluded from the population of the present study.
When using expert panels such as the ones described above, there is a danger that the estimation of the regional panels as to the growth potential of the proposed SME's may not be completely unbiased. It is possible that many SME's, in order to get support funding from regional support institutions, may give an unrealistically positive picture of their growth potential. In addition, due to regional politics, unrealistically high expectations may sometimes be attached to the SME sector. This could be the case of economically depressed regions in particular. In the present study, the danger of such biases is deemed to be small, however, thanks to a tight co-ordination and synchronization between the regional expert panels.
In general, the population of 1 445 technology intensive SME's is considered as very representative of the high potential SME sector in Finland.
All 1 445 technology intensive SME's were mailed a 14-page questionnaire that was addressed personally to the president of the firm. The questionnaire was in structured form, containing mainly closed-ended questions.
The first mailing was followed by a follow-up mailing a month later. After the follow-up mailing, the non-respondents were contacted by telephone and asked to complete and return the questionnaire. Up to three follow-up telephone calls were made. At the fourth time, the non-respondents were asked to specify their age, size, industry, and ownership status.
The mailing process revealed that 34 firms of the original sample of 1 445 firms had ceased operations. Another 64 firms could not be reached, in spite of checking their address data. Thus, 1 347 firms were reached by mail. Of these 1 347 firms, 457 completed the full 14-page questionnaire. Of the 457 firms that completed the 14-page questionnaire, 392 met the selection criteria, namely, independence, less than 500 employees, and a partial ownership by an entrepreneur or by a group of entrepreneurs. The final database of 392 firms corresponds to a response rate of 34 %.
Basic characteristics of the sample
The basic characteristics of the empirical sample are listed in table 1. Table 1 lists data related to the year of establishment of the firms, firm size in terms of employees, and annual sales figures.
The basic characteristics of the sample indicate that the firms were relatively small. The distributions of the size indicators were skewed towards the small end, with the skewness of the employee and sales distributions being 3,9 and 6,4, respectively. The largest firms in the sample had 350 employees and generated FIM 400 Million in sales, respectively. These figures refer to the end of the year 1993.
Distribution of innovator roles
The classification of innovator roles was carried out using Likert scales. The novelty of the technology applied by the firm was evaluated using a four-step Likert scale ranging from 1 to 4, or from 'conventional' to 'pioneering'. The novelty of the market was evaluated using a five-step Likert scale ranging from 1 to 5, or from 'mature' to 'emerging'.
The evaluation of the novelty of both technology and market was based on the subjective judgment of the interviewee. It is thus possible that the evaluation concerning the novelty of technology is overtly optimistic. It would be only natural for a high technology entrepreneur to overestimate the technological sophistication of his or her firm.
The distribution of the firms along the various categories is shown in table 2.
In table 2, the categories indicating the novelty of technology are listed from 4 to 1. This has been done in order to make table 2 compatible with figure 1.
In table 2, the different innovator roles are separated by thick lines. The firms indicating values from 1 to 3 for the novelty of market and values from 1 to 2 for the novelty of technology were classified as application innovators. The firms indicating values from 1 to 3 for the novelty of market and values from 3 to 4 for the novelty of technology were classified as technology innovators. The firms indicating values from 4 to 5 for the novelty of market and values from 3 to 4 for the novelty of technology were classified as paradigm innovators. The firms indicating values from 4 to 5 for the novelty of market and values 1 to 2 for the novelty of technology were classified as market innovators. The distribution of innovator roles is summarized in figure 2.
Figure 2 confirms the expected result that the majority of the firms were application innovators. It can be noted that the distribution of the firms along the technology continuum is approximately even. Combined, technology innovators and paradigm innovators represent 185 firms, whereas the combined number of application innovators and market innovators is 183 firms. Even the firms indicating relatively low levels of technological novelty can be considered as technologically sophisticated, compared with an average small and medium sized firm.
The share of market innovators is surprisingly small. This is probably partly due to the fact that a five step Likert scale was used to indicate the novelty of market, and that firms indicating values 1 to 3 for the novelty of market were classified either as application innovators or as technology innovators. From the point of view of the analyses to be carried out in the present paper, this scaling problem is only a minor consideration.
COMPARISON BETWEEN INNOVATOR ROLES
In the following, the different innovator roles will be compared. Two categories of comparisons are carried out. First, basic characteristics of the innovator roles are compared. These include age and size related data. Second, data related to the growth potential of each innovator role is analyzed.
A descriptive summary statistics of size related data for different innovator roles is shown in table 3. Table 3 lists the following information for each innovator role: year of establishment (mean); annual sales in 1993 (mean, median); and number of personnel in the end of year 1993 (mean, median).
The statistical significance of the age differences between the four innovator roles are listed in table 4. The significance have been calculated using Mann-Whitney U-test.
Table 4 shows that application innovators and technology innovators differ from market innovators and paradigm innovators in terms of their age. Application innovators and technology innovators are older than the market and paradigm innovators. Young firms thus seem to target new markets. As the firm grows older, the market tends to become more mature. This is a natural development.
The size related differences among the four groups of firms are shown in table 5. In the upper quadrant of table 5, the differences concerning sales data are shown. In the lower quadrant of table 5, the differences concerning employment data are shown. The statistical significance have been calculated using Mann-Whitney U-test. As the Mann-Whitney U-test calculates the ranks between data, it is not sensitive to outliar obsevations.
Table 5 shows similar differences as in table 4. Two pairs can be distinguished. Market innovators and paradigm innovators are of similar size. Application innovators and technology innovators are larger than market innovators and paradigm innovators. These findings suggest that the age of the firm is an important explanatory variable behind the firm size. In addition, the age of the firm and the novelty of the market targeted by the firm seem to be related. It is natural for new firms to tend to target new markets. A firm grows with its market. At the same time, the market becomes more mature.
It is interesting to note that even though technology innovators and application innovators are of approximately similar age, technology innovators are clearly smaller than application innovators. This difference cannot be explained by the service or manufacturing orientation of these firms. Approximately 57 % of application innovators could be classified as manufacturing firms. Approximately 59 % of technology innovators could be classified as manufacturing firms. It can only be speculated that technology innovators may experience greater difficulties in gaining market acceptance for their products than do application innovators. The technologies offered by technology innovators are less likely to demonstrate a good fit with the existing competence base of customers, suppliers, and distribution channels. Sometimes it may take a long time before the competence base of the operating environment adjusts to exploit the new technologies offered by a technology innovator (see, e q, Afuah et Bahram, 1995, pp 54 - 55). It seems probable that the smaller size of technology innovators reflects the existence of such friction causing factors.
Growth potential of the firms
The estimation of the growth potential of the firms is based on self-evaluation by the respondents. This was considered as the most reliable indicator. The growth estimation is a relative one, indicating the expected relative growth in terms of sales and in terms of employment.
The respondents were asked to provide an estimate of the best possible sales growth for the years 1993 - 1994, 1993 - 1995, and for the years 1993 - 1998. The estimation of the firms thus represents the best possible future. It is likely that the realized growth of the firms will not meet this estimate.
The growth expectations of the four groups of firms in terms of sales are shown in table 6. Table 6 shows the median expected annual growth in sales for the periods 1993 - 1994, 1993 - 1995, and for the period 1993 - 1998.
The growth expectations of the four groups of firms in terms of employment are shown in table 7. Table 7 shows the median expected annual growth in employment for the periods 1993 - 1994, 1993 - 1995, and for the period 1993 - 1998.
The statistical significance of the differences in growth expectations was calculated for each of the periods 1993 - 1994, 1993 - 1995, and 1993 - 1998. In each case, the results were similar. The trends were the most clearly visible in the analysis concerning the period 1993 - 1998. In the following, only the analysis concerning the period 1993 - 1998 will be discussed.
In table 8, the statistical significance of the differences in growth expectations for the period 1993 - 1998 are shown. In the upper quadrant of table 8, the differences are listed in terms of expected annual growth in sales for the period 1993 - 1998. In the lower quadrant of table 8, the differences are listed in terms of expected annual growth in employment for the period 1993 - 1998. The statistical significance of the differences has been calculated using Mann-Whitney U-test.
Differences between innovator roles - growth expectation for 1993 - 1998
Upper quadrant indicates differences in expectations concerning sales growth
Lower quadrant indicates differences in expectations concerning employment growth
The results shown in table 8 almost exactly mirror those presented in table 5. No difference can be found between market innovators and paradigm innovators in terms of their growth expectations. The growth expectations of these two groups of firms are clearly more optimistic than those of application innovators and of technology innovators. Technology innovators, for their part, signal clearly more optimistic growth expectations than do application innovators.
A comparison of tables 4,5, and 8 suggests that age and size are the most important explanatory variables behind the expected annual growth in terms of sales and in terms of employment. The growth expectations were indicated in terms of expected relative growth. If a firm of two employees recruits a third employee, this would be translated as a 50 % growth in employment. Intuitively, it seems much less likely that a firm of, say, 100 employees would recruit 50 more employees during a similar period. On the other hand, it is not at all evident that, for example, market innovators should depict similar growth expectations as do paradigm innovators. Remember that market innovators and paradigm innovators are of approximately equal age and of approximately equal size. On the other hand, application innovators, in spite of their similar age with technology innovators, are almost double the size of technology innovators.
The analysis in tables 4,5, and 8 thus supports the general contention that systemic factors, such as technology applied by a new, technology-based firm, indeed impose constraints on its evolution. In the case of the firms analyzed in the present study, it is likely that the constraints take the form of incompatibilities between the existing competence base among customers and the competencies required to take the new technologies into use. Introducing new technologies into an existing market often means disturbing the existing status quo in the marketplace. The existing players in the marketplace are not likely to welcome new players who threaten to render the existing competence base obsolete.
The innovator role of a new, technology-based firm does not remain unchanged throughout its life cycle. The analysis of the present study suggests that the innovator role is likely to change as a new, technology-based firm grows older. The general tendency seems to be for new, technology-based firms to drift from the right to the left in the innovation matrix. Thus, the aging of the firm and the simultaneous aging of its target market seem to be the most important determinants inducing change in the innovator role. Such a drift is illustrated in figure 3.
Likely changes in the innovator roles of new, technology-based firms over time
The strength of the drift in figure 3 is illustrated with the thickness of the arrow line. The analysis of the mean ages of different innovator groups suggests that the drift from right to left is stronger than is the downward drift. During their way to the left, paradigm innovators seem to face more friction than do market innovators. This is reflected, we believe, in the smaller size of technology innovators, as compared with application innovators.
The illustration in figure 3 does not aim to suggest that all new, technology-based firms would start their operations as market innovators or as paradigm innovators. Many a new, technology-based firm starts its operations as an application innovator or as a technology innovator. It is also perfectly possible for a new, technology-based firm to drift from left to right or from down to up in the matrix. A new, technology-based firm may start introducing new technologies into an existing market, and it may also start to create new markets.
The analysis of the present paper lends some support for the systemic approach to research on new, technology-based firms. The analysis suggests that interrelationships seem to exist between systemic determinants, such as the technology applied by the firm, and its patterns of evolution. The greater the degree of novelty of technology applied by a new, technology-based firm, the greater is the friction hindering its growth.
The analysis shows that the traditional approach to research on new, technology-based firms is perfectly applicable on an important fraction of these firms. A distinction can be made between two pairs of innovator roles in this regard. The analysis points to the conclusion that the systemic contentions are more applicable on technology innovators and on paradigm innovators. In other words, the more sophisticated the technology applied by the firm is, the more relevant the systemic contentions seem to become. On the other hand, many application innovators and even many market innovators operate in a relatively well defined market environment. For most such firms, the traditional contentions apply well.
The growth expectations analyzed in the present study represent relative growth in the best possible case. It is likely that the realized growth will not be as high as what the expectations might lead one to expect. In addition, the use of relative growth measures does not do full justice for the role of application innovators as creators of new employment. In absolute terms, the 159 application innovators in the sample expect to generate 2 460 new jobs by the end of year 1998. At the same time, market innovators expect to generate 346 new jobs (24 firms). Technology innovators expect to generate 1 383 new jobs (101 firms). Paradigm innovators expect to generate 2 076 new jobs (84 firms). It should be kept in mind that by the year 1998, many of the market innovators and paradigm innovators in the sample will have become application innovators and technology innovators. The analysis also suggests that paradigm innovators may be likely to face more difficulties in their growth than are the three other types of firms.
The empirical sample of the present study consists of independent, entrepreneurial firms. This approach does not do full justice to the role of new, technology-based firms as engines of economic growth. A recent survey that was carried out in Finland suggests that less than 20 % of medium sized technology intensive firms in Finland are independent (HyvŠrinen, 1995, p 64). A further analysis shows that the share of independent new, technology-based firms starts to fall drastically as the firm passes the size of 50 employees (Laamanen et Autio, 1995, p 6). Such findings suggest that the acquisition of new, technology-based firms is an important mechanism through which the industrial base is rejuvenated. It is even likely that the new, technology-based firms that possess the highest potential for growth are the most likely to become acquired by established industrial firms. This could hold particularly well in Finland, where both the domestic market and the venture capital industry are small. Often, the only way for a Finnish new, technology-based firm to fully realize its growth potential is to become acquired by a large, established firm, that has sufficient financial resources, and that also enjoys access to foreign market channels.
The analysis of the present study gives some pointers for future research. First, the variables underlying the classification of innovator roles correlate strongly between each other. This can be considered natural. It is easy to believe that new technologies are more likely to be applied in new markets than in mature markets. However, the strong correlation between the novelty of market and the novelty of technology decreases their value as variables underlying the taxonomy used in the present study. Even though a cluster analysis supports the conclusion that the grouping used in the present study is valid, more indicators of the novelty of both markets and technologies could be tested to check the validity of the findings of the present study.
Second, there is a strong correlation between the size of the firm and the relative growth expectations of the firm. The use of different size classes when comparing the different innovator roles could provide more information of the differences between the different groups of firms. The relatively small number of market innovators in the empirical sample of the present study prevents us from carrying out a more detailed analysis of different size classes of the firms. On the other hand, if the analysis is focused on different size classes only, this could blur the vision of the whole.
The traditional industry classifications do not always apply well on new, technology-based firms. Many a new, technology-based firm is better classified in terms of the technology it applies, not in terms of the market it serves. This is especially the case of small expert firms specializing on a particular technology. Instead of trying to analyze such firms against the framework of fixed industries and markets, a more useful approach could be to use the concept of technological systems as a framework of analysis. Further research on, for example, the role of new, technology-based firms as agents of technology transfer in technological systems could provide more insight into the economic impact delivered by these firms.
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