Industrial dynamics and innovation:

progress and challenges

Franco Malerba CESPRI - Bocconi University

Via Sarfatti 25 - 20136 Milan Italy franco.malerba@unibocconi.it

Presidential Address delivered at the 32nd Conference of the European Association for Research

in Industrial Economics (EARIE)

Porto, 1-4 September 2005

ABSTRACT

Within the growing field of industrial dynamics, the analysis of innovation has witnessed major progress in several areas. Contributions at the empirical and modelling levels have greater advanced our understanding of innovation within industrial dynamics. The main point of the paper is that in order to have a deeper and clearer view of the relationship between industrial dynamics and innovation, research has to progress on three fronts: the analysis of demand, knowledge and networks.

I wish to thank Stefano Breschi, Alfonso Gambardella, Francesco Lissoni and Lorenzo Zirulia for useful comments to an earlier draft.

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1. Industrial dynamics as a growing research field

Since the late 1970s industrial dynamics has emerged as a major area of inquiry in industrial

economics. The analysis of birth, growth and decline of firms and industries and the factors

affecting them has generated a very rich empirical and theoretical literature. And most of these

contributions have recognised the central role of innovation for firms and industries.

In this Address I will start by recognising the major recent growth of research in the area of

industrial dynamics and then concentrate on the major progresses in the analysis of the relationship

between industrial dynamics and innovation and on the challenges that lie ahead. In the first part of

the paper I will discuss the progress, while in the second I will focus on three big research topics

that I think require in-depth research scrutiny: demand, knowledge and networks.

In the discussion I will not focus on the literature of transaction costs or on strategic interaction, but

on the contributions regarding learning, the dynamics of technology and market structure and

industry evolution. I will place a specific emphasis on a longitudinal perspective, in that it allows to

focus on sequences of events, changes and feedbacks in industrial dynamics. This perspective is

very important not only for understanding industrial dynamics, but also for the analysis of the

broader evolution of markets, as clearly pointed out by the discussion and papers in Geroski-Mata

(2001).

2. Industrial dynamics and innovation

Since the late 1970s, industrial dynamics has emerged as a major research area for industrial

economists. Pioneering work by Paul Geroski and David Audretsch at the empirical level and by

Bojan Jovanovic, Richard Nelson and Sidney Winter at the theoretical level have focussed the

attention of researchers on the way industries change over time and on the dynamics processes of

entry, selection and growth of firms within industries.

Within the growing interest in industrial dynamics, innovation has been recognized as a key

element affecting the dynamics of industries and the rate of entry, survival and growth of firms.

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Looking back at the last 25 years, one has to recognise that on this front progress has been indeed

impressive at both the empirical and the theoretical levels.

2.1 The empirical contributions

At the empirical level, since the late 1970s the so-called SPRU tradition has greatly contributed

to our appreciative understanding of the role of innovation in the evolution of industries, and it has

shown that the relationship between innovation and industrial change is multidimensional, involves

several actors and differs greatly across industries (Pavitt,1984, Freeman-Soete,1997, Dosi,1988).

Innovation in industries has been found to be the result of the interaction of different actors (firms,

universities, public agencies, financial organizations) which are related both formally as well

informally and have actions strongly influenced by their competences, learning processes, the

knowledge base of sectors and institutions. In this frame, the notion of sectoral systems of

innovation (Malerba,2004) has provided to be a useful tool for examining innovation in a sector.

Industries have been shown to follow life cycles of innovation, firms entry and growth and changes

in market structure (Abernathy-Utterback,1978; Utterback,1994). It has also been convincingly

found that that these dynamic sequences are different from one industry to another (Klepper,1997,

Geroski,2003).

In addition, with the availability of advanced computer technology and new firm level data,

econometric analyses have moved from cross sections work during the 1960s and 1970s to

longitudinal analyses of industrial dynamics and innovation since the early 1990s. In general, great

progress has been obtained in identifying, measuring and understanding stylized facts and statistical

regularities and the factors explaining them: intersectoral diversity in firm size distribution; fat-

tailedness of corporate growth rates across industries; heterogeneous firm-specific autocorrelation

profiles with each industry; persistence of profitability, labor productivity and TFP differences

across firms and across plants within industries at all level of disaggregation. It has been shown

that market selection does not seem to work effectively particularly in the short and medium-run,

the time span of the available statistics. Concerning then innovation more specifically, some other

robust stylized facts and regularities have been identified:

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-High within- industry heterogeneity in innovativeness

Heterogeneity of firms innovativeness has been shown to be quite pervasive and persistent over

time in spite of competition and selection processes. There is now a very broad set of contributions

in the industrial dynamics literature that forcefully point to the role of heterogeneity. In most

industries there are few firms which are responsible for a large number of innovation, and there is a

core and a fringe of innovators. But there is more than that: heterogeneity concerns also the core

and the fringe of innovators. This is not just a question of aggregation. As Griliches and Mairesse

(1997) have clearly stated: The observed variability-heterogeneity does not really decline as we cut

our data finer and finer. Heterogeneity across firms in innovation means the presence of

idiosyncratic capabilities (absorptive, technological, etc.) and implies that firms not only do

different things but, and most importantly, when they do the same thing, they know how to do it in

different ways.

This heterogeneity is closely associated to persistence in innovative activity, which is a key

phenomenon that affect the patterns of innovative activities in a sector (Malerba-Orsenigo-

Peretto,1997, Cefis,2003). Some of this heterogeneity is related to entry. It has been found that

the entry process is driven by several factors (Geroski,1995, Bartelsman et al., 2005) and that there

is a high rate of entry after a technological discontinuity. In particular, new entrants are the vehicles

for the introduction of new technologies, as Geroski (1995), Audretsch (1995) and Baldwin (1995)

among others have shown. In any case, entry differs very much also with respect to the type of

innovation and speed of technological change.

Heterogeneity in innovativeness is then translated into differential profitability, as documented by

Geroski-Machin-Van Reenen (1993), while the impact of innovation on corporate growth is still a

matter for deep empirical scrutiny, with a less straightforward relationship for firm level data than

for plant level data (Baldwin,1995). Actually in some specific industries, such the international

pharmaceutical industry, econometric evidence shows that dynamics is driven by the introduction

of few major innovations, which create new markets, and by imitation. In this industry innovative

firms do not grow more than the other firms. Rather there is a coexistence of quite heterogeneous

innovators (Bottazzi et al.,2001)

- Major inter-sectoral differences in the rate of technical change, market structure and organization

of innovative activity

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It has been shown that sectors differ greatly not only in terms of rate of innovation, but also of

market structure and organization of innovative activities. Work at the patent level has found

stylized and robust differences across sectors. In some in sectors innovative activities are

concentrated in a few firms, stability of innovators is relevant and new innovators are rare. In other

sectors patterns of innovation are distributed across a wide population of firms, with a high

turbulence in innovative activity, and new innovators coming from every quarter. These two

different models of organization of innovative activities, which could be labelled Schumpeter Mark

II and Schumpeter Mark I, have been found in several industries and are quite robust for the same

industry across countries (Malerba-Orsenigo,1995, 1997). These findings can be related to the old

stylized fact concerning major inter-industry differences in concentration (see Schmalensee,1989)