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Innovation Networks in Industries

Malerba, Franco and Vonortas, Nicholas S. (eds.)
Edward Elgar Publishing: Cheltenham, 2009
ISBN 1847203760 (pb)

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Reviewed by Mauro Lombardi
Department of Economics, University of Florence

Cover of book Questions concerning how industries and techno-productive knowledge evolve are acquiring an increasing importance within evolutionary and industrial economics. This book enriches the analysis by providing some very interesting insights, combining network analysis and the study of peculiar aspects of industries and sectoral systems. The entire book is valuable first of all because it gives an integrated and coherent view, while deepening processes at different levels. At the same time it suggests some useful implications in terms of policy at the European level.

Its conceptual "kernel" can be synthesised in this way: to focus on networks viewed as self-organising processes, starting from a sectoral knowledge base above all in uncertain and changing environments. The knowledge base is defined in terms of relevant technologies, institutional factors and norms that forge strategies and behavioural rules for firms. Then interactive relationships between behavioural rules and network structures are basic drivers of industrial and sectoral evolution.

This framework is developed in three parts of the book. Methodological questions are tackled in Part I. The first Chapter (by Vonortas) treats concepts such as network resources and social capital, cognitive benefits for members, relational structural embeddedness, network structure governance. The relationship between the incentives for a firm to participate in a network and the network structure optimality is discussed, particularly on the basis of connections between industry structure and firm strategy. The second contribution (by Zirulia) begins with some stylised facts concerning inter-firm technological agreements: the increasing number of short-term forms of cooperation in high-tech industries during the last decades. Then the analysis is developed at the individual, dyadic and industrial level; subsequently the relationships between technological agreements, firms' performances and technological capabilities are discussed. The role of path-dependence mechanisms and of key actors within networks are at the centre of this essay.

Different forms of networks are analysed in PART II in relation to industries and sectoral systems. The co-authorships of research articles are examined by Tijssen in order to point out the "corporate web of science" within ten European pharmaceutical companies. Significant similarities among these are highlighted that regard the research cooperation propensities, evaluated through highly internationalised collaboration with very specialised R&D Labs scattered across Europe and overseas. The presence of similarities and differences between their research partnership profiles is also indicated: some of these have more international connections than others; others again are more reliant on public research centres; another subset adopts centralised and internationalised collaboration models.

In their chapter, Breschi, Cassi and Malerba estimate the overlapping of knowledge base of different firms, the so-called crowding phenomenon occurring when companies occupy the same search space. The analysis of patent citations concerning 272 companies of the electronics industry allows the authors to highlight a positive relationship between the firms' rate of innovation and "the cumulative exploitation of a firm's own stock of knowledge". However this effect can be dampened by attempts of other competing firms trying to draw upon the same knowledge base of "the focal firm".

Social network analysis is applied by Okamura and Vonortas to the analysis of two types of networks in five sectors (computer, electronics, plastics, instruments): partnership and knowledge networks. The main results of the inquiry are related to the difference between the pharmaceutical firms and the others as far as networking behaviours are concerned. It is worth emphasising that knowledge networks can be characterised as "small worlds" in all five sectors, while partnerships networks appear to be even much smaller and fragmented.

In Chapter 7 Laforgia and Lissoni demonstrate two interesting points, by analysing EPO patent data in bio-technology industry: 1) mobility of inventors is not the basic causal mechanism of multi-applicant inventorship, 2) there is a strong difference between firms' networks generated by job mobility and those related to M&A. The chapter by Wagner and Mohrman concludes PART II by singling out self-organising networks of scientists in the nanoscale science research at an international level.

Part III is devoted to public policies for networking in ICT. In Chapter 9 by Breschi and colleagues, Information Society and Research Technological development (IST-RTD) programmes of Sixth Research Framework Programme (FP6) are discussed in terms of the networks which have been created and their topological properties. One of the most suggestive results of this analysis points out the organizations that play two types of fundamental roles in the IST-RTD: hubs as connectors in a single network, and gatekeepers as hubs in more than one network even at the global level. Their basic function in knowledge transmission and their pivotal role in knowledge generation induce the authors to conceive them as potential levers in exercising fundamental drive within IST-RTD networks. Such organizations can also play a strategic role "in steering the network in the desired socio-economic situation". Finally in Chapter 10 by Cassi and colleagues, the analysis is enriched by considering research and deployment networks, where hub and gatekeeper organizations again play a key function, but a fundamental "catalytic" role should be performed by Institutions. Indeed the latter at the national and regional levels should trigger information flows and strengthen the links between research and deployment of innovations.

That said, a question not tackled by the book is as follows: Should institutions at different levels seek out and count on strategic actors within existing ones? Or should they exercise autonomous key functions in forecasting technological trajectories, in doing so defining priorities and selecting networking dynamics as well? Perhaps this could be an interesting research line for the future. On this, a major attention to the added value of agent-based modelling and social simulation to look at these aspects is recommended


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