Technological entry, exit and survival: an empirical analysis of patent data

Research Policy 28 Ž1999. 643–660 www.elsevier.nlrlocatereconbase

Technological entry, exit and survival: an empirical analysis of patent data Franco Malerba b

a,)

, Luigi Orsenigo

b

a UniÕersity of Brescia and CESPRI, Bocconi UniÕersity, Milan, Italy Department of Economics, Bocconi UniÕersity, Via Sarfatti 25, 20136 Milan, Italy

Received 18 August 1997; received in revised form 9 March 1998; accepted 19 January 1999

Abstract This paper provides new empirical evidence on the patterns of technological entry and exit across sectors and over time. We define ‘new’ innovators—firms which innovate for the first time, and ‘ex’-innovators—previous innovators that do not innovate any more. We distinguish also between ‘real’ and ‘lateral’ entry and exit. The analysis is based on patent data ŽEuropean Patent Office. for 49 technological classes in six countries ŽUSA, Japan, Germany, UK, France and Italy. over the period 1978–1991. We find that innovative turbulence is relevant and that it is a composite phenomenon, in which real innovative entrantsrexiters and lateral entrantsrexiters play different roles. We then examine the patterns of survival of innovative entrants and find that most of the entrants are occasional innovators, while persistent innovators are few in number but large in terms of patents. Subsequently, we analyze differences in the patterns of technological entry and exit at the sectoral level. Finally, the role of national systems of innovation in affecting innovative entry and exit is examined. q 1999 Elsevier Science B.V. All rights reserved. Keywords: Innovation; Industrial dynamics; Entry and exit; Patents

1. Introduction A key issue in the economics of innovation— and more generally in the study of industrial dynamics—concerns the role of new innovators in affecting the rate of technological change and the patterns of industrial evolution. Schumpeter stressed their funda-

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Corresponding author. Tel.: q39 2-5836-3391; Fax: q39 2-58363399; E-mail: [email protected]

mental importance in The Theory of Economic DeÕelopment ŽSchumpeter, 1912.. Later on, however, in Capitalism, Socialism and Democracy ŽSchumpeter, 1942., he changed perspective claiming that large established firms have become key actors in the process of technological change because they have internalized and ‘routinized’ entrepreneurship and the innovativeness associated with it. However, these established firms are related to established technologies and old ways of doing things, and are continuously threatened by new innovators associated to new technologies, as clearly emphasized in Business Cycles ŽSchumpeter, 1939..

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F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

This tension between new innovators and established innovators got lost in the debate on the ‘Schumpeterian hypotheses’ of the 1960s and 1970s. Economists concentrated their attention on two rather different Žalbeit indirectly related. questions: the role of concentration and of firm size in determining the rates of innovation of industries ŽKamien and Schwartz, 1982.. The analysis of the role of ‘new’ innovators has been largely neglected. In more recent years, however, a renewed interest in the dynamics of industry structures has brought this issue back to the front. Several case-studies of specific new technologies Žsuch as auto, computers, semiconductors, biotechnology among others. have emphasized the major role of new innovators in the various stages of the development of an industry. In addition, Klepper Ž1996. and Utterback Ž1994. have provided several examples of the role of new innovators during the life-cycle of specific industries, particularly in the period following a technological discontinuity. Moreover, in the last decade, economists have paid increasing attention to industrial demography. While not directly concerned with innovators, 1 this literature has shown that the processes of firms’ entry, exit and growth are quite complex. In particular, empirical studies in this field Žsee Dunne et al., 1988; Acs and Audretsch, 1991; and Baldwin, 1995, among others. have shown that industrial evolution is characterized in the aggregate by high degrees of turbulence, with high rates of entry and exit. Moreover, entry and exit are strongly related to each other and a large fraction of the entrants exits the industry within 2–3 years after birth. Despite this background, no systematic cross-sectoral and cross-country study exists that analyzes the relevance of new innovators and the patterns of entry into and exit from the population of innovators. Empirical questions such as: what is the relevance of new innovators and of ex-innovators in various

1

In fact, this body of research has found that new firms are not necessarily new innovators. On the contrary, only a minority of new firms are created because of the launch of an innovation: most new firms use rather established production processes and do not have very innovative products Žfor a survey, see Geroski, 1994 and Audretsch, 1997..

technologies? Have they previously been innovative in other technologies? Are new innovators small firms or large corporations? Do they innovate only once or do they continue to innovate after their initial innovation? Are there differences across countries and across sectors in the patterns of innovative entry and exit? These are extremely important questions for a full understanding of the innovative process, firms’ evolution and industrial dynamics. This paper aims to examine these questions by using patent data at the firm level for six countries ŽUSA, Japan, Germany, France, the UK and Italy. over the period 1978–1991. The aim of this work is primarily descriptive. However, it touches upon on three sets of broad issues which bear important interpretative implications: turbulence of innovators, persistence of innovators and sectoral and countries specificities of innovative patterns. As far as turbulence of innoÕators is concerned, this paper aims to shed light on the degree and characteristics of turbulence. It will provide quantitative evidence on the phenomenon of technological entry and exit, computing the rates of entry and exit and the relative size of new and ex-innovators Žin terms of patents and in terms of number of employees.. Moreover, we distinguish among different types of entry and exit. We define ‘new’ innovator firms that innovate for the first time, and ‘ex’-innovators previous innovators that do not innovate any more. Please note that new innovators may be firms that have been in existence for quite some time. Thus, we analyze technological, rather than economic, entry and exit. 2 In this paper, we introduce a further distinction: we decompose entry and exit Ž‘gross’ entrants and exiters. into ‘real entrants’, ‘real exiters’ and ‘lateral entrants’ and ‘lateral exiters’. When analyzing various sectors Žand not the economy as a whole., we consider ‘real’ entrants those firms that did not innovate previously in any one technological class and ‘real’ exiters firms that ceased to innovate. On the contrary, we consider ‘lateral’ entrants and exiters those firms that innovated in the past in a different technology. These firms are ‘established’

2

We thank Keith Pavitt for this observation.

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

innovators engaged in a process of technological diversification. As a consequence of this diversification, some of these firms may exit from the technological classes in which they were previously active. Others may keep their technological diversification quite broad and continue to innovate also in other technological classes. 3 As far as the persistence of innoÕatiÕe actiÕity, this paper aims to assess whether new innovators tend to become persistent innovators or not. It will analyze the patterns of technological entry and exit and link them with the degree of persistence of innovative activities at the firm level. Recent studies on the subject ŽCefis, 1996; Geroski et al., 1997; Malerba et al., 1997. have attempted to measure the degree to which past innovative activities influence current innovative activities and to assess whether innovators are occasional in that they innovate only once and then disappear from the innovation scene, or are persistent in that they show continuity in their innovative activities. These studies have used different methodologies and have yielded somewhat different results and interpretations. In this paper, we inquire whether entrants and exiters tend to be large or small innovators and whether entrants tend to continue to innovate after their first innovation Žpatent.. In this paper, therefore, we also analyze the survival and post-entry innovative performance of new innovators, by asking whether they are occasional or persistent, how long they continue to innovate after entry and how much their innovative activities change with age. As far as the sector specificity and the country specificity, this paper aims to examine whether the patterns of technological entry and exit are affected by the type of sector or of country in which they take place. We will analyze entry and exit in a large number of technological classes in six advanced countries and we will examine whether major similarities exist across technologies and countries. This issue can be related to a broader view of the factors affecting the sectoral and the country pattern of

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innovative activities Žand therefore also innovative entry and exit.. Basically, this view emphasizes two factors. First, the key role of the technological and learning environment in terms of the properties of the ‘technological regimes’ defined in terms of combination of Žtechnological. opportunity, appropriability and cumulativeness conditions and the specific features of the knowledge base underpinning innovative activities Žfor a discussion see Malerba and Orsenigo, 1995, 1996.. Direct econometric corroboration to the hypothesis that the sectoral patterns of innovation are influenced by the nature of technological regimes is provided in Breschi et al. Ž1997.. Second, the role of national systems of innovation ŽLundvall, 1993; Nelson, 1993. as the set of institutions and organizations that characterize a country and that affect innovative activity in that country. Our analysis is based on firm-level patent applications from the European Patent Office. These patents have been classified by CESPRI ŽBocconi University. into 49 technological classes for six countries ŽUSA, Japan, Germany, UK, France and Italy. for the period 1978–1991. The paper is organized as follows. In Section 2, the dataset, methodology and main measures are presented. In Section 3, we tackle the first question, namely how much turbulence is present in innovative activities. We assess the technological relevance of new innovators and ex-innovators, and we distinguish between real entrants and lateral entrants, and between real exiters and lateral exiters. Then in Section 4, we turn to the second main issues the persistence of innovative activities of the new innovators. We examine whether new innovators are occasional or persistent innovators and we assess the post-entry performance of entrants. Subsequently, we address the third broad issue: the sector or country specificity of the patterns of innovative entry and exit ŽSections 5 and 6.. Finally, in Section 7, we provide some general conclusions stemming from our empirical analysis. 2. Data and measures

3

In a companion paper ŽMalerba and Orsenigo, 1999., we examine the intersectoral patterns of lateral entry and exit Žfrom which technological classes lateral entrants come and to which technological classes lateral exiters go..

2.1. Data Our analysis is based on patent data, specifically on European Patent Office ŽEPO. data for the period

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1978–1991. 4 The data refer to EPO patent applications of firms and institutions of various countries, with the exclusion of individual inventors. 5 Patents that are applied for by more than one firm Žcopatents. have been attributed to each one of the co-patentees Žand therefore have been counted as many times as the number of co-patentees.. The EPO data base has been elaborated at the firm level Žexcluding individual inventors. for six countries: the United States, Japan, Germany ŽFederal Republic., France, the United Kingdom, Italy. As far as the United States are concerned, 133,475 patents and 11,476 firms have been considered; for Germany 108,118 patents and 8495 firms; for France 43,986 patents and 5671 firms; for the United Kingdom 35,175 patents and 6055 firms and for Italy 15,175 patents and 3803 firms; for Japan 81,217 and 3990 firms. The small number of Japanese firms compared to the United States and Germany may imply that the data concerning this country have to be considered with great care. Conversely, German firms are in a very large number and therefore may be overrepresented in the sample because EPO is in Germany and firms located in Germany may patent more frequently than firms of other countries. However, since

4 Criticisms of the use of patent data are well known. Here only a brief discussion is presented Žsee Griliches, 1990 for a more detailed discussion.. Not all innovations are patented by firms. Patents cannot be distinguished in terms of relevance unless specific analyses on patent renewals or patents citations are done. Finally, different technologies are differently patentable and different types of firms may have different propensities to patent. However, patents represent a very homogeneous measure of technological novelty across countries and are available for long time series. They also provide very detailed data at the firm and the technological class levels. As a consequence, they are an invaluable and unique source of data on innovative activity. 5 Although some of these individual inventors work for a firm or an institution, the majority of individual inventors includes individuals who do not work in firms or institutions and owners of small firms who record the patent in their name. Thus, the exclusion of individual inventors means an underestimation of the innovative activities of smaller companies. The share of the patents held by private individuals is usually larger in technological classes and countries where the role of small firms is higher. In the paper we will use the term firms for both firms and institutions. Institutions such as universities and research centers however have a small share of total patents in the six countries considered.

our aim is not to discuss technological performance, but the structure of innovative activity at the industry level, we think that Japan underrepresentation and Germany overrepresentation do not create serious distortion in our results. In addition, for the four European countries data on the economic size of the innovating firms has been gathered. The economic data cover 56% of the German patenting firms, 49% of the French firms, 34% of the British firms and 51% of the Italian firms. Economic data on firms applying for patents concerns size in terms of employees in 1991. Therefore, a bias may be present in the analysis in favour of firms active during the early 1990s. Firms that are part of business groups have been treated in the present analysis as individual companies. Forty-nine technological classes are considered in the analysis Žsee Appendix A.. These classes have been created starting from the various subclasses Ž4 digits. of the International Patent Classification ŽIPC. and grouping them according to specific applications. 6 This dataset is likely to provide an overestimation of the rates of entry. Given the novelty of the European Patent Office, only recently several firms have begun to patent at EPO. Thus, many firms appear as new innovators in the database, although they might appear as persistent innovators in other datasets Žfor instance, US patents.. Moreover, the EPO system is quite similar to the German system. Thus, in the early years, German patents constitute a significant share of total European patents, while in the following periods, other countries begin to catch up. This would result in lower rates of entry for Germany as compared to other countries. Hence, the values of entry rates should be considered with great care. For this reason, we have divided the data set in two sub-periods Ž1978–1986 and 1987–1991., which correspond, roughly, to an equal number of patents in each sub-period. However, the extent of the bias discussed above should have limited importance because we are more interested in the relationships that exist between the various indicators of entry and exit across sectors

6

Details on the procedures of construction of the classification are available on request.

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

and across countries, rather than to their absolute values. Finally, comparisons with similar data computed on the OTAF-SPRU data base for US patents ŽMalerba and Orsenigo, 1995., whilst confirming that the absolute values of the measures of entry are somewhat lower as compared to the EPO data, suggest also that sectoral and country differences between EPO and USPO patent data are quite small. In other words, the bias operates in a similar way across most sectors and countries. 2.2. Measures We have calculated measures of the patterns of entry and exit which take into account both the number of entries and exits and their relevance on total patenting activities. The following variables have been used in the analysis: NE i Ž t .

Number of firms that patented for the first time in technological class i in the period 1987–1991 NTi Ž t . Total number of firms in technological class i in the period 1987–1991 NX i Ž t y 1. Number of firms that patented in technological class i in the period 1978–1986 and did not patent in technological class i in the period 1987– 1991 NTi Ž t y 1. Total number of firms in technological class i in the period 1978–1986 PE i Ž t . Number of patents held by firms that patent for the first time in technological class i in the period 1987–1991 PX i Ž t y 1. Number of patents held by firms that patented in technological class i in the period 1978–1986 and did not patent in technological class i in the period 1987–1991 PTi Ž t . Total number of patents in the period 1987–1991 PTi Ž t y 1. Total number of patents in the period 1978–1986 NLE i Ž t . Number of lateral entrants in the pe riod 1987–1991: firms that were patenting in technological classes different from i in the period 1978–86 and that innovated in i in the period 1987–1991

NLX i Ž t .

PLE i Ž t . PLX i Ž t .

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Number of lateral exiters in the pe riod 1987–1991: firms that patented in technological class i in the period 1978-86 and did not patent in that technological class in 1987–1991, but patented in other technological classes in 1987–1991 Patents of lateral entrants Patents of lateral exiters

On these bases we computed the following indicators, dropping the subscript i for simplicity of notation. 2.2.1. Gross entry and exit rates Using these variables, we define the gross entry rate, ERŽ t ., and gross exit rate, XRŽ t y 1., for technological class i between the periods 1978–1986 and 1987–1991 as, respectively, the number of firms that patented for the first time in technological class i in the period 1987–1991 over the total number of firms in technological class i in the period 1987– 1991 and as the number of firms that patented in technological class i in the period 1978–1986 and did not patent in technological class i in the period 1987–1991 over the total number of firms in technological class i in the period 1978–1986: ER Ž t . s NE Ž t . rNT Ž t . XR Ž t y 1 . s NX Ž t y 1 . rNT Ž t y 1 . 2.2.2. Patent shares of entrants and exiters Gross entry and exit rates, however, say very little about the contribution of technological entries and exits to innovative activities. Hence, we define the patent share of firms that enter, PESHŽ t ., or exit, PXSHŽ t y 1., the population of innovators as, respectively, the number of patents held by firms that patent for the first time in technological class i in the period 1987–1991 over the total number of patents in the period 1987–1991 and as the number of patents held by firms that patented in technological class i in the period 1978–1986 and did not patent in technological class i in the period 1987–1991 over the total number of patents in the period 1978–1986: PESH Ž t . s PE Ž t . rPT Ž t . PXSH Ž t . s PX Ž t y 1 . rPT Ž t y 1 .

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2.2.3. RelatiÕe size in terms of patents of entrants and exiters We define the average size in terms of patents of entrants relative to persistent innovators Žor incumbents. ŽPERSŽ t .. and the average size of exiting firms relative to non-exiting firms, ŽPXRSŽ t y 1.. as: PERS Ž t . s

PE Ž t . rNE Ž t .

bents. ŽPLERSŽ t .. and the average size of lateral exiting firms relative to non-exiting firms, ŽPLXRSŽ t .. are defined as: PLERS Ž t . s

PLE Ž t . rNLE Ž t .

Ž PT Ž t . y PE Ž t . . r Ž NT Ž t . y NE Ž t . .

PLXRS Ž t y1 .

Ž PT Ž t . y PE Ž t . . r Ž NT Ž t . y NE Ž t . .

PLX Ž t y1 . rNLX Ž t y1 .

s

Ž PT Ž t y1. yPX Ž t y1. . r Ž NTi Ž t y1. yNX i Ž t y1. . PXRS Ž t .

s

PX Ž t y 1 . rNX Ž t y 1 . Ž PT Ž t y 1 . y PX Ž t y 1. . r Ž NT Ž t y 1. y NX Ž t y 1. .

These measures allow us to compare the average size of entrants and incumbents Žpersistent innovators. and the average size of exiting firms in terms of patents. The denominator of PERSŽ t . includes accordingly all firms innovating in period t except the entrants, and the denominator of PXRSŽ t y 1. includes all firms present in the period t y 1 except those who exited in the same period. 2.2.4. Lateral entry and exit We define the relevance of lateral entry and lateral exit in two ways: LER Ž t . s NLE Ž t . rNE Ž t . share of lateral entrants over the total number of new innovators in the period 1987–1991 and LXR Ž t y 1 . s NLX Ž t y 1 . rNX Ž t y 1 . share of lateral exiters over the total number of exiters in the period 1987–1991;

The average size of real entrants ŽPRERS. and real exiters ŽPRXRS. relative to persistent innovators is computed in the same way, i.e., substituting the numerator of the previous expressions with, respectively, ŽPE y PLE.rŽNE y NLE. and ŽPX y PLX.rŽNX y NLX.. 2.2.6. RelatiÕe size in terms of number of employees of entrants and exiters We also developed measures of the average economic size of entrants and exiters relative to persistent innovators for the four European countries for which data are available. The economic size of a firm is calculated in terms of the firms’ number of employees in the year 1991. The indicators are computed in the same way as the previous ones, except that we consider here the number of employees instead of the number of patents. Hence, the relative economic size of entrants and exiters is calculated as: SERS Ž t . s

SE Ž t . rNE Ž t .

Ž ST Ž t . y SE Ž t . . r Ž NT Ž t . y NE Ž t . .

PLESH Ž t . s PLE Ž t . rPE Ž t . share of patents by lateral entrants over the total number of patents of new innovators in the period 1986–1991; PLXSH Ž t y 1 . s PLX Ž t y 1 . rPX Ž t y 1 . share of patents by lateral exiters over the total number of patents of exiters in the period 1987–1991. 2.2.5. RelatiÕe size in terms of patents of lateral entrants and exiters The average size in terms of patents of lateral entrants relative to persistent innovators Žor incum-

SXRS Ž t y 1 .

s

SX Ž t y 1 . rNX Ž t y 1 .

Ž ST Ž t y 1 . y SX Ž t y 1. . r Ž NT Ž t y 1. y NX Ž t y 1. . where S ji Ž t . s number of employees of firm j holding patents in technological class i; j s 1 . . . J; j STi Ž t . s Ý Js1 S ji Ž t . s total number of employees of firms holding patents in technological class in the j period 1987–1991; STi Ž t y 1. s Ý js1 S ji Ž t y 1. s total number of employees of firms holding patents in technological class in the period 1987–1991;

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

SE i Ž t . s number of employees of firms that patented for the first time in technological class i in the period 1987–1991; SX i Ž t y 1. s number of employees firms that patented in technological class i in the period 1978–1985 and did not patent in the period 1987–1991. The average economic size of lateral entrants ŽSLERS. and lateral exiters ŽSLXRS. relative to persistent innovators is calculated as: SLERS Ž t . s

SLE Ž t . rNLE Ž t .

Ž ST Ž t . y SE Ž t . . r Ž NT Ž t . y NE Ž t . .

SLXRS Ž t y 1 . SLX Ž t y 1 . rNLX Ž t y 1 .

s

Ž ST Ž t y 1 . y SX Ž t . . r Ž NT Ž t y 1 . y NX Ž t y 1 . . where SLEŽ t . s number of employees of lateral entrants and SLXŽ t y 1. s number of employees of lateral exiters. Similarly, the average size of real entrants ŽSRERS. and real exiters ŽSRXRS. relative to persistent innovators is computed in the same way, i.e., substituting the numerator of the previous expressions with, respectively, ŽSE y SLE.rŽNE y NLE. and ŽSX y SLX.rŽNX y NLX..

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3. The turbulence of innovators 3.1. Gross entry and exit The first step in our analysis is the assessment of the relevance of gross technological entry and gross technological exit. This has been done with the measurement of the average entry and exit rates across the 49 technological classes for the six countries considered in this study ŽTables 1 and 2.. The data suggest that innovative entry in terms of firms ŽER. is a significant phenomenon in the six countries. A large proportion of innovators patents for the first time in the period 1986–1991: the average rate of innovative entry varies from 0.63 in Germany to 0.80 in Italy. The technological relevance of the new innovators in terms of share of total patents ŽPESH. is much smaller but still substantial, varying from 0.30 in Germany to 0.61 in Italy. This suggests that new innovators are much smaller than incumbents in terms of patents. Indeed, the relative size of the new innovators Žcompared to incumbents. in terms of patents ŽPERS. ranges from 0. 32 in the USA to 0.51 in Italy. The firms that patent for the first time in the period 1986–1991,

Table 1 Technological entry Germany

France

United Kingdom

Italy

United States

Japan

Average

S.D.

Technological entry in terms of number of firms Entry rate ŽER. Lateral entryrgross entry ŽLER.

0.63 0.46

0.69 0.38

0.70 0.35

0.80 0.26

0.67 0.38

0.69 0.52

0.70 0.39

0.05 0.05

Technological entry in terms of patents Entrants share ŽPESH. Patents of lateral entrantsrpatents of entrants ŽPLESH.

0.30 0.48

0.40 0.42

0.43 0.41

0.61 0.31

0.32 0.43

0.38 0.59

0.41 0.44

0.11 0.09

0.39 0.58 0.32

0.40 0.65 0.35

0.51 0.98 0.48

0.32 0.46 0.24

0.35 0.53 0.29

0.39 0.60 0.32

0.09 0.21 0.07

AÕerage size of entrants in terms of number of employees relatiÕe to incumbents Entrants relative size ŽSERS. 0.73 0.73 1.70 Lateral entrants relative size ŽSLERS. 0.90 4.19 4.01 Real entrants relative size ŽSRERS. 0.25 0.21 0.08

0.75 1.56 0.51

0.98 2.91 0.26

0.48 1.38 0.18

AÕerage size of entrants in terms of patents relatiÕe to incumbents Entrants relative size ŽPERS. 0.35 Lateral entrants relative size ŽPLERS. 0.41 Real entrants relative size ŽPRERS. 0.26

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Table 2 Technological exit Germany

France

United Kingdom

Italy

United States

Japan

Average

S.D.

Technological exit in terms of number of firms Exit rate ŽXR. Lateral exitrgross exit ŽLXR.

0.62 0.45

0.70 0.36

0.74 0.32

0.67 0.26

0.68 0.40

0.53 0.55

0.65 0.39

0.07 0.10

Technological exit in terms of patents Exiters share ŽPXSH. Patents of lateral exitersrpatents of exiters ŽPLXSH.

0.27 0.46

0.46 0.40

0.47 0.36

0.49 0.28

0.34 0.45

0.26 0.56

0.38 0.42

0.10 0.10

0.47 0.66 0.38

0.43 0.66 0.34

0.52 0.64 0.44

0.33 0.51 0.27

0.39 0.40 0.32

0.41 0.55 0.33

0.08 0.13 0.07

AÕerage size of exiters in terms of number of employees relatiÕe to incumbents Exiters relative size ŽSXRS. 0.83 1.29 1.33 Lateral exiters relative size ŽSLXRS. 1.76 8.08 2.22 Real exiters relative size ŽSRXRS. 0.07 0.12 0.17

0.73 1.66 0.50

1.04 3.43 0.21

0.31 3.11 0.19

AÕerage size of exiters in terms of patents relatiÕe to incumbents Exiters relative size ŽPXRS. 0.33 Lateral exiters relative size ŽPLXRS. 0.39 Real exiters relative size ŽPRXRS. 0.24

however, are not necessarily small firms. Indeed, the economic size of new innovators measured in terms of employment ŽSERS. Žavailable only for the four European countries. is still less than the size of incumbents, but it is much larger as compared to the relative size of new innovators in terms of patents: around 0.75 of the average economic size of the incumbent for Germany, France and Italy. Only in the case of the UK new innovators are much bigger than the average incumbent Ž1.7.. 7 The patterns of innovative exit Žsee Table 2. are remarkably similar to those of innovative entry. Exit rates ŽXR. are of the same magnitude of entry rates, varying from 0.53 in Japan to 0.74 in the UK. In each country, except Italy and Japan, exit rates are almost equal to entry rates. The share of patents held by firms which have ceased to innovate in the second period Ž1986–1991. ŽPXSH. is relatively small Žranging from 0.26 in Japan to 0.49 in Italy. and their relative size in terms of patents ŽPXRS. varies from 0.33 in Germany and in the USA to 0.52 in Italy. The values of both these indicators are strik-

7 Entrants are indeed small-medium sized firms in absolute terms. Entrants have on average 38.7 employees in Germany, 104.9 in France, 80.6 in the UK and 10.7 in Italy.

ingly similar to the ones of the corresponding entry variables Žagain, except Italy and Japan.. Again, exiters are not necessarily small firms. Indeed, they are bigger than persistent innovators in term of employment ŽSXRS. in the UK and in France and slightly smaller in Germany and Italy. 8 In sum, this first evidence indicates forcefully that technological activities are characterized by high degrees of turbulence in terms of firms: the population of innovators changes substantially over time, through entry and exit processes. Entrants are slightly smaller firms than incumbents in economic terms, while exiters are sometimes bigger. These conclusions change if patents and not firms are considered: in this case both entrants and exiters have a limited relevance compared to established innovators. 3.2. Lateral and real entry and exit The previous results suggest that, albeit numerous in terms of firms, innovative entry and exit occur in the ‘fringe’ of technological activities: a stable core of larger and persistent innovators account for the

8

Exiters have on average 50.4 employees in Germany, 105.3 in France, 115.4 in the UK and 19.7 in Italy.

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

bigger share of patents. In this section, we move the analysis one step further by asking whether the entrants and the exiters in a technological class are ‘really’ new innovators. In fact, one has to consider that entrants in any one technological class may well have innovated before in a different technological class. Similarly, exiters may well start Žor continue. to innovate in a different technology. Thus, gross entry Žexit. has to be decomposed in two components: ‘real’ entry and ‘real’ exit and ‘lateral’ entry and ‘lateral’exit. Overall, lateral entry is usually less relevant than real entry in terms of firms and patents. In terms of firms, lateral entry ŽLER. accounts for 0.39 of gross entry Žranging between 0.26 in Italy and 0.52 in Japan. and a marginally larger fraction of the patents of gross entrants ŽPLESH. 0.44 Žsee Table 1.. On the contrary, lateral entrants are on average larger innovators Žin terms of patents. and larger firms Žin terms of employment. than real entrants. In general, lateral entrants are firms of relatively large economic size: Table 1 shows that in terms of relative economic size, lateral entrants are 2.91 the size of persistent innovators ŽSLERS.. Conversely, real entrants are essentially firms of small economic and innovative size. On average, in terms of employment real entrants are 0.26 the economic size of incumbents ŽSRERS. and 0. 32 the innovative size of incumbents ŽPRERS.. Italy is a major exception, with rates respectively of 0.51 and 0.48. Again, the patterns of lateral exit and real exit are quite similar to the patterns of lateral entry and real entry ŽTable 2.. In each country, the ratio of lateral exit over gross exit is almost the same of the corresponding ratio calculated for entry, both in terms of number of firms ŽLXR, on average 0.39. and in terms of patent shares ŽPLXSH, on average 0.42.. Similarly, lateral exiters are much bigger than incumbents in economic terms Žon average 3.43. but smaller in terms of patents Žon average 0.55.. Real exiters, instead, are smaller firms in terms of patents ŽPRXRS, 0.33 on average. and employment ŽSRXRS, 0.21 on average. than incumbents. 3.3. Turbulence as a composite phenomenon From the previous analysis we may conclude that turbulence in innovative activity is a composite phe-

651

nomenon. Turbulence is generated by four types of actors: real entrants, lateral entrants, real exiters and lateral exiters. We have shown that the patterns of real entryrexit and lateral entryrexit are very similar to each other. Conversely, real entryrexit are quite distinct from lateral entryrexit. In fact real entrantsrexiters are usually firms of small economic size with few patents each. On the contrary lateral entrantsrexiters are usually firms of large economic size engaged in a process of technological diversification, expanding the range of technologies in which they are active and eventually abandoning old technologies. 4. The survival of the new innovators: persistent or occasional innovators? The second set of issues examined in this paper refers to the innovative persistence of new innovators. In fact, in assessing the performance implications of the entry of new innovators, it is important to know whether new innovators are occasional or not. In the first case, new innovators provide a sporadic and transitory contribution to innovative activities in an industry. In the second case, once entered they become continuous and established innovators. Thus, we explored whether and for how long they continue to patent after entry and whether they tend to increase or decrease their technological performance over time. Our analysis has reached the following results. First, a large fraction of the new innovators ceases to innovate soon after entry: most entrants are therefore occasional innovators Žsee Table 3.. Most innovative entrants in fact have only one patent. The relevance of firms having one patent on the total number of firms in the EPO-CESPRI database is 59%. This share falls significantly if we look at the share of total patents held by firms with only one patent: 11%. Differences among technological classes are significant, with mechanical technologies in general showing higher shares and chemicalpharmaceuticals lower shares than the average. In this paper, we examine the number of firms that innovated for the first time in a given period and continued to innovate subsequently as a percentage of the total initial number of entrants in that period. We subdivide our data in four periods: 1978–1982,

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

652

Table 3 Patterns of survival Ž% on the number of firms in each cohort of entrants. ŽAverages on 49 technological classes. 1978–1982 1983–1985 1986–1988 1989–1991 Germany Entry cohorts 1978–1982 100.00 1983–1985 57.53 1986–1988 46.92 1989–1991 34.94

– 100.00 37.12 24.51

– – 100.00 25.81

– – – 100.00

United Kingdom Entry cohorts 1978–1982 100.00 1983–1985 38.33 1986–1988 29.98 1989–1991 20.67

– 100.00 27.19 15.71

– – 100.00 20.08

– – – 100.00

United States Entry cohorts 1978–1982 100.00 1983–1985 51.01 1986–1988 39.71 1989–1991 29.38

– 100.00 58.34 45.09

– – 100.00 21.99

– – – 100.00

France Entry cohorts 1978–1982 100.00 1983–1985 45.55 1986–1988 35.17 1989–1991 25.44

– 100.00 31.92 19.75

– – 100.00 22.66

– – – 100.00

Italy Entry cohorts 1978–1982 100.00 1983–1985 42.25 1986–1988 37.24 1989–1991 24.44

– 100.00 31.99 21.79

– – 100.00 21.19

– – – 100.00

Japan Entry cohorts 1978–1982 100.00 1983–1985 64.50 1986–1988 57.62 1989–1991 48.19

– 100.00 52.07 47.93

– – 100.00 31.51

– – – 100.00

1983–1985, 1986–1988 and 1989–1991. The figures in Table 3 are the means across the 49 technological classes in each time period. The number of firms that were still patenting 3 years after entry Ži.e., after one period. over the total number of entrants was on average 49.9% for the 1978–1982 cohort. It declines to an average of around 39.8% for the 1983–1985

cohort and to 23.9% for the 1986–1988 cohort. Survival after two periods was on average 41.0% for the 1978–1982 cohort and 29.1% for the 1983–1985 cohort. A second result emerges from these data: survival decreases in the latest entry cohorts. This is due to two reasons: early entrants may accumulate innovative capabilities, technological knowledge and competitive advantages over later entrants and therefore show persistence in innovative activities. In addition, because EPO was established in 1978, it is possible that the already most persistent innovators entered soon and continued to be innovators thereafter. 9 Third, major country differences exist in the survival rates. For example, the survival rates of the firms that patented in the period 1978-82 and were still patenting in the period 1989–1991 range between 48.2% in Japan and 20.7% in the UK Žsee Table 3.. Fourth, as a result of the processes of entry and exit, the age distribution of innovators is strongly skewed towards the youngest and the oldest cohorts. On average, in the period 1989–1991 the 1978–1982 cohort was responsible for 16.6% of total innovators, the 1983-85 accounted for 11.3%, the 1986–1988 cohort for 13.7% and the 1989–1991 for 58.3% of total innovators ŽTable 4.. These results are confirmed by an analysis of the patent shares of firms that survived after entry ŽTable 5.. The patent share of each entry cohort declines over time in each period as the population of firms increases: the patent share of each cohort of entrants in the first period after entry declines over time Žfrom an average of 49.7% for the 1983–1985 cohort to 40.6% for the 1986–1988 cohort to 34.2% for the 1989–1991 cohort.. However, the patent share of the 1978–1982 cohort Žthat is to say, the firms who were already present in the first period. remains the largest one in each subsequent period. Thus, the age distribution of patent shares in each period is highly

9

The decline in survival rates in the latest entry cohorts may be biased because some of the exiters in the latest periods may well patent again in the future. However, preliminary investigations show that the probability of innovating again after 3 years of the last patent is quite low and it tends to decrease with the length of the gap.

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660 Table 4 Age distribution of innovators: Surviving firms as a percentage of the number of firms patenting in a given period ŽAverages on 49 technological classes. Birth cohorts 1978–1982 1983–1985 1986–1988 1989–1991 Germany 1978–1982 1983–1985 1986–1988 1989–1991

100.00 42.56 29.25 22.71

– 57.44 18.06 12.34

– – 52.69 13.93

– – – 51.02

United Kingdom 1978–1982 100.00 1983–1985 32.53 1986–1988 23.05 1989–1991 15.72

– 67.47 16.34 9.25

– – 60.61 18.75

– – – 56.28

United States 1978–1982 100.00 1983–1985 34.88 1986–1988 20.68 1989–1991 16.67

– 65.12 28.61 24.49

– – 50.71 11.80

– – – 47.03

France 1978–1982 1983–1985 1986–1988 1989–1991 Italy 1978–1982 1983–1985 1986–1988 1989–1991 Japan 1978–1982 1983–1985 1986–1988 1989–1991

100.00 36.91 23.97 17.97

100.00 24.21 15.73 7.43

100.00 34.77 21.09 15.05

– 63.09 17.60 11.39

– 75.79 16.44 9.98

– 65.23 20.50 12.92

– – 58.43 13.49

– – 67.83 13.04

– – 58.41 15.09

– – – 57.15

– – – 69.55

– – – 56.94

skewed, with the oldest and youngest cohorts holding a far larger share of patents than the intermediate classes Žthe only exception being Italy.. 10 On average, in the period 1989–1991, the 1978–1982 cohort was responsible for 35.9% of total patents in that 10

The largest share of patents held by the older cohort might be due simply to the fact that this cohort comprises a longer period of time than the other ones Ž5 years instead of 3 years.. However, as it will be shown in the next paragraph, the relative size in terms of patents of these firms is consistently higher as compared to younger firms.

653

period, the 1983–1985 and 1986–1988 cohorts has both 14.4% and the youngest cohort Ž1989–1991. had 34.2%. However, those innovators that survive and continue to innovate become rather large innovators. The greater innovativeness of the surviving established innovators with respect to the new innovators is shown by Table 6 in which we calculate the relative size of the surviving cohort members Žin terms of patents. relative to the size of all firms present in the technological class. Table 6 shows that the average size in terms of patents of survivors tends to increase over time for each cohort. The

Table 5 Patent share of survivors ŽAverages on 49 technological classes. Birth cohorts 1978–1982 1983–1985 1986–1988 1989–1991 Germany 1978–1982 1983–1985 1986–1988 1989–1991

100.00 65.12 56.79 51.89

– 34.88 14.01 12.09

– – 29.20 11.20

– – – 24.83

United Kingdom 1978–1982 100.00 1983–1985 44.81 1986–1988 40.89 1989–1991 36.85

– 55.19 16.67 13.93

– – 42.44 12.26

– – – 36.97

United States 1978–1982 100.00 1983–1985 56.24 1986–1988 49.15 1989–1991 47.30

– 43.76 17.29 14.70

– – 33.57 10.81

– – – 27.18

France 1978–1982 1983–1985 1986–1988 1989–1991

100.00 51.53 41.36 38.17

– 48.47 16.19 14.62

– – 42.45 14.62

– – – 32.58

Italy 1978–1982 1983–1985 1986–1988 1989–1991

100.00 28.92 22.44 15.58

– 69.63 18.46 15.15

– – 59.10 15.77

– – – 53.50

Japan 1978–1982 1983–1985 1986–1988 1989–1991

100.00 54.03 44.92 40.44

– 45.97 18.03 15.53

– – 37.05 13.75

– – – 30.29

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Table 6 Relative size in terms of patents of survivors Žaverages on 49 technological classes. Birth cohorts 1978–1982 1983–1985 1986–1988 1989–1991 Germany 1978–1982 1983–1985 1986–1988 1989–1991

1.00 1.37 1.77 2.28

– 0.54 0.71 0.98

– – 0.51 0.80

– – – 0.49

United Kingdom 1978–1982 1.00 1983–1985 1.25 1986–1988 1.65 1989–1991 2.19

– 0.74 0.95 1.41

– – 0.65 0.61

– – – 0.61

United States 1978–1982 1983–1985 1986–1988 1989–1991

1.00 1.48 1.92 2.44

– 0.62 0.49 0.52

– – 0.54 0.79

– – – 0.50

France 1978–1982 1983–1985 1986–1988 1989–1991

1.00 1.25 1.56 2.12

– 0.69 0.83 1.28

– – 0.66 1.08

– – – 0.57

Italy 1978–1982 1983–1985 1986–1988 1989–1991

1.00 1.11 1.29 2.10

– 0.85 1.02 1.52

– – 0.79 1.21

– – – 0.77

Japan 1978–1982 1983–1985 1986–1988 1989–1991

1.00 1.41 1.96 2.69

– 0.64 0.81 1.20

– – 0.58 0.91

– – – 0.53

‘older’ firms are indeed larger in terms of patents than the ‘younger’ ones. Thus, in the period 1989– 1991, the average size in terms of patents of the firms in the 1978–1982 cohort was 2.30 with respect to all innovators, against 1.15 for the 1983–1985 cohort, 0.90 for the 1986–1988 cohort and 0.58 for the 1989–1991 cohort. Thus, the decline in the patent share of each cohort as the cohort ages is the result of two conflicting forces: the change in the size Žin terms of patents. of surviving members of the cohort and the exit of firms. The first one has a positive effect on the share, the second a negative one.

These results suggest that indeed a large fraction of new innovators is composed by occasional innovators. These firms innovate once and then retreat soon from the innovative scene. These firms represent a large fraction of the whole population of innovators. However in terms of patents, they hold a small share of total patenting activity in a year. The fraction of entrants that is able to survive as innovator continue to innovate over the years and become a persistent innovator. Over time, these firms grow larger in terms of patents as the result of accumulated knowledge and cumulativeness of technical advance. Thus, these persistent innovators end up to hold a significant share of total patenting activities in any period. 5. Sectoral differences in the patterns of entry and exit Are the patterns of technological entry and exit sector-specific? This is a major question because it focuses on the possibility of major differences among sectors in the intensity and mode of entry and exit exist. In order to answer to this question, we will first examine whether technological entry is closely related to technological exit in each technological exit, and then whether it is possible to identify groups of sectors that have similar features. 5.1. Patterns of correlation among the indicators of entry and exit across technological classes The average statistics examined so far obscure the substantial diversity of the patterns of entry and exit across technological classes as one can notice from an analysis of the heterogeneity across technological classes Žsummary measures are not reported here and are available upon request.. Despite this diversity, the entry variables and the exit variables are systematically related to each other within any one technological class. Table 7 reports the correlation coefficients between these variables across technological classes for the six countries considered jointly. 11 11 We performed correlation analysis also for each of the six countries. Results Žnot reported here. strongly confirm that the pattern of correlation is very similar across countries.

Table 7 Correlation between entry and exit variables Žsix countries considered jointly. Pearson coefficient

Entry rate Average size of gross entrantsr incumbents ŽP.

Average size of lateral entrantsr incumbents ŽP.

Average size of lateral entrantsr gross entrants ŽP.

y0.26935 y0.10278

0.79113 0.74908

0.14541 0.17218

0.81702 0.79800

1.00000 y0.06934

0.50978

y0.34078

y0.06934

1.00000

0.57842

0.44737

0.63354 0.59840

0.50978

0.57842

1.00000

y0.27373

0.00452 0.07149

y0.34078

0.44737

y0.27373

1.00000

0.66649 0.61926

y0.41696 y0.20208

0.63354 0.59840

0.00452 0.07149

0.66649 0.61926

1.00000 0.81233 0.81233 1.00000

0.54794 y0.30705

0.00176

y0.14216

0.40486

y0.13604

0.64713

0.82358 0.78075

y0.02973 y0.15671

y0.18653

0.09318

0.57818

0.06461

0.60460

y0.36681

y0.22728

Average size Exit Rate of net entrantsr incumbents ŽP.

Average size of gross exitersr incumbents ŽP.

Lateral mortalityr gross mortality ŽP.

Average size of lateral exitersrgross exiters ŽP.

y0.26898 y0.21814

0.65513 0.55624

y0.01403 y0.03829

0.70326 0.62298

0.54794 y0.36681

y0.02973

y0.22728

0.40486

y0.15671

0.57818

0.00176 y0.13604

y0.18653

0.06461

y0.14216

0.64713

0.09318

0.60460

y0.30833 y0.12007

0.82358 0.78075

0.12230 0.10495

0.85922 0.89017

1.00000 y0.11114

0.47179

y0.20539

y0.11114

1.00000

0.48524

0.68878

0.12230 0.10495

0.47179

0.48524

1.00000

y0.07851

0.85922 0.89017

y0.20539

0.68878

y0.07851

1.00000

0.80095 0.70191 0.63468 0.66526

y0.41696 y0.20208

y0.30833 y0.12007

y0.30705

Average size of lateral exitersr incumbents ŽP.

Average size of net exitersrgross exiters ŽP. F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

Entry rate 1.00000 0.85448 Average size of 0.85448 1.00000 gross entrantsr incumbents ŽP. Lateral natalityr y0.26935 y0.10278 gross natality ŽP. Average size of 0.79113 0.74908 lateral entrantsr incumbents ŽP. Average size of 0.14541 0.17218 lateral entrantsr gross entrants ŽP. Average size of 0.81702 0.79800 net entrantsr incumbents ŽP. Exit Rate 0.80095 0.63468 Average size of 0.70191 0.66526 gross exitersr incumbents ŽP. Lateral mortalityry0.26898 y0.21814 gross mortality ŽP. Average size of 0.65513 0.55624 lateral exitersr gross exiters ŽP. Average size of y0.01403 y0.03829 lateral exitersr incumbents ŽP. Average size of 0.70326 0.62298 net exitersr gross exiters ŽP.

Lateral natalityr gross natality ŽP.

655

656

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

All the indicators measuring the importance of innovative entry are positively correlated to each other and to the corresponding indicators of exit. In other words, technological classes which are characterized by high entry rates are also characterized by a high patent share of entrants, high relative size Žin terms of patents. of entrants as well as high exit rates, high patent share and large size of exiters in terms of patents. Gross entry and exit are negatively correlated with lateral entry and exit. High lateral entry is associated with low gross entry and exit rates and patent shares, low relative size Žin terms of patents. of exiters Žin particular lateral exiters. and real entrants and real exiters. Conversely, high lateral entry Žon gross entry. is positively correlated with high lateral exit Žon gross exit. and the relative size in terms of patents of lateral entrants. No correlation is observed with the relative size of entrants. That is to say, technological classes characterized by high turbulence show simultaneously and consistently a lower relative role of lateral entry and exit.

ance Ž0.61 in Germany, 0.49 in France, 0.58 in the UK, 0.37 in Italy, 0.60 in the USA and 0.54 in Japan.. In all countries, this first component discriminates between technological classes characterized by high Žlow. lateral entry and exit and high Žlow. relative size Žin terms of patents. of lateral entrants as compared to total entrants, and low Žhigh. patent shares and low Žhigh. relative size in terms of patents of gross entrants and exiters. Moreover, in most countries turbulent and stable technological classes tend to be the same: 21 technological classes are consistently stable and 12 classes tend to be consistently turbulent. Sixteen remaining classes show more variation across countries or do not fit neatly into these two categories. The stable group comprises most of the chemical and electronic technologies, vehicles and aircraft; the turbulent group includes mechanical technologies, traditional technologies Že.g. furniture. and agriculture ŽTable 8..

5.2. Two types of technological classes: stable and turbulent

6. Country differences

In sum, two different types of technological classes emerge. Ža. One group is composed by turbulent classes: high gross entry and exit with most of the entry generated by real innovators and most of the exit by firms which stop patenting. Žb. A second group is composed by stable classes: low gross entry and exit with entry and exit mostly associated to processes of technological diversification of firms. In these technological classes, lateral entrants tend to be relatively big Žand real entrants small.. Conversely exiters Žespecially real exiters. tend to be smaller innovators. In order to control for the robustness of these results, we performed principal components analysis for each of the six countries for which we have the data. 12 In each country a first principal component emerges which captures a large proportion of vari-

12

Detailed results of principal component analysis are available from the authors on request.

Despite these similarities among sectors, are significant cross-country differences observable in the patterns of technological entry and exit? If this is so, it would mean that differences in the national systems of innovation do play a role in affecting differences in the patterns of entry and exit. At the aggregate level, country-specific differences are indeed visible. Inspection of Tables 1 and 2 reveals that Germany and Japan are ‘stable’ countries: entry and exit rates are low, the patent share and the relative sizes of entrants and exiters are small, while the role of lateral entry and exit is significant. At the other extreme, Italy is a ‘turbulent’ country, with a lot of ‘real’ entry and limited ‘lateral’ entry and exit. The other countries fall in between these two extremes, although the USA are not too different from Germany and Japan. Inspection of the patterns of survival confirm these results. Again, Germany, Japan and the United States are characterized by high rates of survival and high relative size of the ‘oldest’ firms and Italy by low rates of survival and low relative size of the ‘oldest’ firms ŽTables 3–6..

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

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Table 8 Stable and turbulent technological classes Stable 6 7 8 9 10 11 12 15 21 26 27 36 37 38 39 40 41 42 43 44 45 48

Turbulent Gas, hydrocarbons, oil Inorganic chemicals Organic chemicals Macromolecular compounds New materials Adhesive, coatings, synthetic resins Bio-chemicals, bio and genetic engineering Drugs Metallurgy Vehicles, motorcycles, other land vehicles Aircraft Measurement and control instruments Laser technology Optics and photography Computers, data processing systems Other office equipment Electrical devices and systems Electrical components Consumer electronics Telecommunications Multimedial systems Nuclear technology

At the technological class level the similarities across countries are very strong. At a disaggregated level, we performed correlation analysis for each of the indicators of the patterns of innovative entry and exit across the six countries. That is to say, we investigated how the level and ranking of the value of each indicator over the 49 technological classes in one country is correlated across the other countries. Results Žnot reported here. show significant differences across countries Ži.e., small values of the correlation coefficients. only in relation to the variables measuring lateral exit and the relative size of real entrants. Japan and Italy, however, appear to diverge relatively more frequently than other countries from the general patterns of correlation: for many variables, the values of the correlation coefficient of these two countries are lower than those of the other four countries. However, no systematic differences in the patterns of entry and exit appear. However, specific technological classes show a different behaviour across countries. For example, food and tobacco is a ‘stable’ sector only in the UK and Japan; clothing and shoes is a stable sector in Italy and the USA; mining is a stable sector in

3 4 16 17 22 23 28 29 30 33 35 46 49

Furnitures Agriculture Medical preparations Natural and artificial fibres, paper Machine tool Industrial automation Railways, ships Materials handling apparatus Civil engineering, infrastructures Mechanical and electrical technologies Lighting systems Decorative and figurative arts, sports, toys Others

France and Japan; agricultural machinery is a turbulent sector in the UK and USA; household electric appliances does not show any consistent pattern. In sum, from the aggregate and disaggregate analysis it is possible to propose the following taxonomy of countries: Ža. countries with high stability, high survival rates and high diversification processes: Germany, Japan and to a lesser extent the USA; Žb. countries with high turbulence, low survival rates and limited diversification processes: Italy, and, to a lesser extent, France and the UK.

7. Conclusions This paper has shed light on the features and dynamics of new innovators and ex-innovators on a wide number of technologies and countries over a period of 13 years. The results of this analysis provide better and deeper understanding of innovative entry and exit and are quite useful for comparisons with the patterns of production entry and exit in industries and industrial demography Žrecently examined by several scholars..

658

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

What are the basic conclusions that have been obtained by this analysis? First, innovative activities are characterized by high degrees of turbulence. The population of innovators changes substantially over time, through processes of entry and exit. Entrants have the same average size of incumbents, while exiters are sometimes bigger. Both entrants and exiters, however, are relatively small innovators. Second, the turbulence of innovators in a given technology is a composite phenomenon, because new entrantsrexiters are of a quite different types: real and lateral. These last ones are established innovators coming from, or moving into, other technological classes. These two types of firms have different characteristics and effects. Real entryrexit usually generates higher turbulence than lateral entryrexit. In addition, real entrantsrexiters are small firms with few patents each, while lateral entrantsrexiters are usually large firms engaged in a process of technological diversification into new technologies. Third, most innovative entrants are occasional innoÕators, but some of them become persistent innoÕators. Our results show that a large fraction of new innovators is composed by occasional innovators that exit soon from the innovative scene. They constitute a significant part of the whole population of innovators and—to a lesser extent—of the total number of patents at any given time. Only a fraction of entrants survives and grows larger Žin terms of patents. as times goes by: they become persistent innovators. Older firms who survive and continue to patent are few in number but represent an important contribution to total patenting activities in any period. Here, cumulativeness of knowledge and competencies play a major role in affecting the continuity of innovative activity of these firms. Fourth, disaggregation of the patterns of innovative entry and exit at the sectoral level provides a clear indication of the similarity of these patterns for each technological class across countries. Thus there are strong forces at the sectoral level that shape the patterns of entry and exit across countries. Fifth, a closer and finer grained analysis of the 49 technological classes allows to distinguish between two broad types of classes: Ži. Turbulent: in which most of entry is composed by real innovators and most of the exit is composed by firms which stop

patenting; Žii. Stable: in which entry and exit are associated to processes of technological diversification and lateral entrants tend to be relatively large. Finally, national systems of innovation exert their effects on the patterns of entry and exit. Ž1. Germany and Japan are stable countries: entry and exit rates are relatively small, the patent share and the relative sizes of entrants and exiters are small, whilst the role of lateral entry and exit is significant. Ž2. Italy is a turbulent country, with small lateral entry and exit. Ž3. The other countries fall in between these two extremes. The implications of these results for the conceptual issues mentioned in the Introduction are straightforward. This paper has shed new understanding of the Schumpeterian patterns of innovative activities ŽMalerba and Orsenigo, 1995.. While Schumpeter Mark I classes are rather turbulent by definition, also Schumpeter Mark II Žto a lesser extent, of course. do present some technological entry and not only in terms of lateral entry. Schumpeter Mark II classes, in fact, are turbulent at the margin: there is room for new entrants and fringe firms that remain rather occasional on the innovative scene and in general do not reach the core. 13 The issue of persistence is also better clarified. These results suggest that although turbulence is a pervasive and quantitatively important phenomenon. A good part of innovative activities are generated—in general—by a relatively stable core of large Žboth in terms of patents and employees. and persistent innovators, who account for a very large share of total patents. Moreover, persistent innovators are active in a variety of technological classes, which they continuously enter and exit through processes of lateral technological diversification. Around this core, one observes a large turbulent fringe of small, occasional innovators, who often patent only once and cease to patent thereafter. Thus, the emerging picture suggests that persistence is much lower when measured in terms of firms than in terms of patents. Moreover, large innovators

13

We thank a referee for drawing our attention to this point.

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

tend to remain large for long periods of time and only few of the new innovators succeed in remaining innovative after their first patent. When they do, however, their technological performance improves consistently in the following years. 14 In this perspective, these results seem to support the view that, despite high levels of turbulence and the intrinsically random nature of innovative activities, innovation stems to a significant extent from cumulative processes of construction of technological and organizational capabilities over long periods of time. Only few firms innovate and only a small fraction of them is able to innovate again. But those who succeed produce the bulk of patents consistently over time. 15 The evidence presented in this paper provides further corroboration to the notion that technologyspecific factors invariant across countries Žsuch as the technological regimes discussed in the Introduction. are important determinants of the ease and modalities of technological entry and exit and more generally of the patterns of innovative activities. Direct econometric analysis of how technological regimes as well as other variables determine the patterns of entry and exit and the measurement of persistence at the sectoral level would therefore greatly improve our knowledge of this important subject. 16 Finally, the intriguing and complex relation between technology-specific factors and national systems of innoÕation come clearly at the forefront of future analysis in this area of research. How these

two forces interact in shaping the actual patterns of innovative entry and exit and more broadly the patterns of innovative activity in a sector across countries remains on the top of the agenda for further research and requires detailed case studies and historical, qualitative and econometric analyses.

8. Further reading Malerba, F., Orsenigo, L., 1993. Technological regimes and firm behaviour. Industrial and Corporate Change 2 Ž1. 45–71.

Acknowledgements We thank John Cantwell, Keith Pavitt, Peter Swann, the participants to the Human Capital and Mobility Workshop and to the EMOT Workshop, as well as two anonymous referees for their suggestions. We also thank Monica Soana for her research assistance. Usual disclaimers apply. Support from the Human Capital and Mobility Program of the EU and from the Italian National Research Council ŽCNR. is gratefully acknowledged.

16

14 It is worth noting the close analogy between these results and the evidence on industrial demography that shows that entrants in a given industry in any particular year tend to be small firms and do not survive for long. When they do, however, either they tend to grow at very fast rates or they have an initial larger size. See, for a survey, Audretsch Ž1997.. At this stage of the analysis, we cannot pursue further the issue of the extent to which and how the two phenomena are related. 15 This interpretation of the evidence is compatible, in our view, with the results of Cefis Ž1996. and Geroski et al. Ž1997., at least in the sense that being non-innovators and large innovators are absorbing states and there is a minimum threshold in patenting activities below which innovations occur only occasionally. Whether this threshold is defined by 1 or more patents is a matter of considerable interest for future research.

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A further important field for future research concerns the analysis of the relationships between technological entry, exit and persistence on the one hand and countries innovative performance. Preliminary correlation analysis shows that the degree of turbulence seems related to technological growth and technological specialization. In turbulent technological classes technological growth is associated with high gross entry as well as high new entry and real exit, while in stable technological classes it is associated with high gross entry and low gross exit, taking place mainly through technological diversification in terms of lateral entry and lateral exit. This indicates that technological growth in turbulent classes occurs through new innovators, while in stable classes it takes place through established innovators coming from other technological classes. Similarly, in turbulent classes technological specialization takes place with high gross entry and also high new entry and real exit, indicating that new innovators are a major source of specialization. On the contrary, in stable classes specialization is associated with limited gross entry and exit and high cumulative advancements of large established innovators within that technological class. See also Malerba et al. Ž1997..

F. Malerba, L. Orsenigor Research Policy 28 (1999) 643–660

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r EPO) Appendix A. Technological classification (CESPRIr 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Food tobacco Clothing, shoes Furnitures Agriculture Mining Gas, hydrocarbons, oil Inorganic chemicals Organic chemicals Macromolecular compounds New materials Adhesives, coatings, synthetic resins Bio-chemicals, bio and genetic engineering Miscellaneous chemical compounds Chemical, analytical, physical processes Drugs Medical preparations Natural and artificial fibres, paper Chemical treatment of natural or artificial fibres and paper Agricultural chemicals Chemical processes for food and tobacco Metallurgy Machine tools Industrial automation Industrial machinery and equipment

References Acs, Z., Audretsch, D.B., 1991. Technological Regimes, Learning and Industry Turbulence, WZB, Berlin, mimeo. Audretsch, D., 1997. Technological regimes, industrial demography and the evolution of industrial structures. Industrial and Corporate Change 6 Ž1., 49–82. Baldwin, J., 1995. The Dynamics of Industrial Competition. Cambridge Univ. Press, Cambridge. Breschi, S., Malerba, F., Orsenigo, L., 1997. Technological regimes and Schumpeterian patterns of innovation. CESPRI, Working Paper. Bocconi University, Milano. Cefis, E., 1996. Is there any persistence in innovative activities? Working Paper No. 6, Department of Economics, University of Trento. Dunne, T., Roberts, M.J., Samuelson, L., 1988. Patterns of firm entry and exit in the US manufacturing industries. Rand Journal of Economics 35, 567–581. Griliches, Z., 1990. Patents statistics as economic indicators: a survey. Journal of Economic Literature 28. Geroski, P., 1994. Market Structure, Corporate Performance and Innovative Activity, Clarendon Press, Oxford. Geroski, P.A., Van Reenen, J., Walters, C.F., 1997. How persistently do firms innovate? Research Policy, forthcoming 26, 1, 33–49. Kamien, M., Schwartz, N., 1982. Market Structure and Innovation. Cambridge Univ. Press, Cambridge.

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

Agricultural machinery Vehicles, motorcycles, other land vehicles Aircraft Railways, ships Materials handling apparatus Civil engineering, infrastructures Engines, turbines, pumps Mechanical engineering Mechanical and electric technologies Household electric appliances Lighting systems Measurement and control instruments Laser technology Optics and photography Computers, data processing systems Other office equipments Electrical devices and systems Electronic component Consumer electronics Telecommunications Multimedial systems Decorative and figurative arts, sports, toys Ammunitions, weapons Nuclear technology Others

Klepper, S., 1996. Entry, exit and innovation over the product life cycle. American Economic Review 86, 562–583. Lundvall, B.A., 1993. National System of Innovation, Frances Pinter, London. Malerba, F., Orsenigo, L., 1995. Schumpeterian patterns of innovation. Cambridge Journal of Economics 19 Ž1., 47–65. Malerba, F., Orsenigo, L., 1996. Schumpeterian patterns of innovation are technology specific. Research Policy 25, 451–478. Malerba, F., Orsenigo, L., 1999. Technological entry and diversification in Europe, the United States and Japan: 1978–91. In: Gambardella, A., Malerba, F. ŽEds... The Organization of Innovative Activity in Europe. Cambridge Univ. Press, Cambridge. Malerba, F., Orsenigo, L., Peretto, P., 1997. Persistence of innovative activities, sectoral patterns of innovation and international technological specialization. International Journal of Industrial Organization 15 Ž6., 801–827. Nelson, R., 1993. National Innovation System. Oxford Univ. Press, Oxford. Schumpeter, J.A., 1912. Theory of Economic Development, published in 1934. Harvard Economic Studies, Cambridge. Schumpeter, J.A., 1939. Business Cycles. McGraw-Hill, New York. Schumpeter, J.A., 1942. Capitalism, Socialism and Democracy. Harper and Brothers, New York. Utterback, J., 1994. Mastering the Dynamics of Innovation. Harvard Univ. Press, Boston, MA.