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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Research Policy, Volume 33, Issues 6–7, September 2004, Pages 897–920
In the last decade ‘sectoral systems of innovation’ have emerged as a new approach in innovation studies. This article makes four contributions to the approach by addressing some open issues. The first contribution is to explicitly incorporate the user side in the analysis. Hence, the unit of analysis is widened from sectoral systems of innovation to socio-technical systems. The second contribution is to suggest an analytical distinction between systems, actors involved in them, and the institutions which guide actor’s perceptions and activities. Thirdly, the article opens up the black box of institutions, making them an integral part of the analysis. Institutions should not just be used to explain inertia and stability. They can also be used to conceptualise the dynamic interplay between actors and structures. The fourth contribution is to address issues of change from one system to another. The article provides a coherent conceptual multi-level perspective, using insights from sociology, institutional theory and innovation studies. The perspective is particularly useful to analyse long-term dynamics, shifts from one socio-technical system to another and the co-evolution of technology and society.
In the last decade ‘systems of innovation’ has emerged as a new topic on the research agenda of innovation studies. It has opened up a promising strand of study, in which the scope of analysis has been broadened from artefacts to systems, from individual organisations (often firms) to networks of organisations. Systems of innovation can be defined on several levels (e.g. national, sectoral, regional). This paper makes a contribution to the level of sectoral systems. At this level there are several approaches, which describe the systemic nature of innovation, albeit with a slightly different focus, e.g. sectoral systems of innovation (Breschi and Malerba, 1997 and Malerba, 2002), technological systems (Carlsson and Stankiewicz, 1991 and Carlsson, 1997) and large technical systems (Hughes, 1983, Hughes, 1987, Mayntz and Hughes, 1988, La Porte, 1991, Summerton, 1994 and Coutard, 1999). I will briefly describe the thrust of these three approaches. A sectoral system of innovation can be defined as: a system (group) of firms active in developing and making a sector’s products and in generating and utilizing a sector’s technologies; such a system of firms is related in two different ways: through processes of interaction and cooperation in artefact-technology development and through processes of competition and selection in innovative and market activities (Breschi and Malerba, 1997, p. 131). Although this definition includes the selection environment, it does not explicitly look at the user side. Furthermore, the definition mainly looks at firms, neglecting other kinds of organisations. A technological system is defined as: ... networks of agents interacting in a specific technology area under a particular institutional infrastructure to generate, diffuse and utilize technology. Technological systems are defined in terms of knowledge or competence flows rather than flows of ordinary goods and services. They consist of dynamic knowledge and competence networks (Carlsson and Stankiewicz, 1991, p. 111). This definition highlights more explicitly the importance of not only understanding the creation of technology, but also its diffusion and utilisation. On the other hand, technological systems seem to be narrowed down to social systems (‘networks of agents’). Although actors are important, the material aspects of systems could be better conceptualised. The material aspect of systems is central in the Large Technical Systems (LTS) approach. LTS refer to a particular kind of technology involving infrastructures, e.g. electricity networks, railroad networks, telephone systems, videotex, internet. The LTS approach not only has a specific unit of analysis, but also developed a particular mode of analysis, looking at socio-technical ‘seamless webs’ and system builders ( Hughes, 1983, Hughes, 1986 and Hughes, 1987). Among the components of LTS are physical artifacts (such as turbo-generators, transformers, electric transmission lines), but also organisations (e.g. manufacturing firms, investment banks, research and development laboratories), natural resources, scientific elements (e.g. books, articles), legislative artifacts (e.g. laws) and university teaching programs ( Hughes, 1987, p. 51). System builders travel between domains such as economics, politics, technology, applied scientific research and aspects of social change, weaving a seamless web into a functioning whole. New technologies and the user environment are constructed in the same process. These three approaches share an emphasis on interlinkages between elements, and they all see innovation as co-evolutionary process. But there are some differences regarding the kinds of elements involved in systems and their relationships. The aim of this paper is to contribute to the discussion about the kinds of elements and, especially, the dynamic interactions between them. These contributions focus on four points. The first contribution is to include both the supply side (innovations) and the demand side (user environment) in the definition of systems. The sectoral systems of innovation approach has a strong focus on the development of knowledge, and pays less attention to the diffusion and use of technology, impacts and societal transformations. Sometimes, the user side is taken for granted or narrowed down to a ‘selection environment’. Hence I propose a widening from sectoral systems of innovation to socio-technical systems. This means that the fulfilment of societal functions becomes central (e.g. transport, communication, materials supply, housing). This indicates that the focus is not just on innovations, but also on use and functionality. The need to pay more attention to innovation and users has, in fact, already been identified by a range of scholars in innovation studies and evolutionary economics. So the paper aims to link up with an identified ‘open issue’ in the field. Second, with regard to the kinds of elements I will propose to make an analytic distinction between: systems (resources, material aspects), actors involved in maintaining and changing the system, and the rules and institutions which guide actor’s perceptions and activities. I suggest such analytical distinctions are useful because some current literatures group together too many heterogeneous elements. For instance, Malerba (2002), pp. 250–251, wrote that “the basic elements of a sectoral system are: (a) products; (b) agents: firms and non-firm organisations (such as universities, financial institutions, central government, local authorities), as well as organisations at lower (R&D departments) or higher level of aggregation (e.g. firms, consortia); individuals; (c) knowledge and learning processes: the knowledge base of innovative and production activities differ across sectors and greatly affect the innovative activities, the organisation and the behaviour of firms and other agents within a sector; (d) basic technologies, inputs, demands, and the related links and complementarities: links and complementarities at the technology, input and demand levels may be both static and dynamic. They include interdependencies among vertically or horizontally related sectors, the convergence of previously separated products or the emergence of new demand from existing demand. Interdependencies and complementarities define the real boundaries of a sectoral system. They may be at the input, technology or demand level and may concern innovation, production and sale. The (d) mechanisms of interaction both within firms and outside firms: agents are examined as involved in market and non-market interactions; (e) processes of competition and selection; (f) institutions, such as standards, regulations, labour markets, and so on”. Although these elements are all important, it is somewhat unclear how they are linked. This article aims to make progress on this issue. The third contribution links up with another ‘open issue’, which has also been identified in the field, i.e. to pay more attention to institutions. Sometimes institutions are a ‘left-over category’ in analyses. It also happens that institutions are wrongly equated with (non-market) organisations. See, for instance, Reddy et al. (1991), p. 299, “examples of non-market institutions include: professional societies, trade associations, governmental agencies, independent research and coordination organisations, and public-service organisations”. Anyway, there is a recognised need to better conceptualise the role of institutions in innovation. In particular, it is useful to explain how institutions play a role in dynamic developments, rather than explaining inertia and stability. A fourth contribution of the article is to address the change from one system to another. This is relevant, because the main focus in the systems of innovation approach has been on the functioning of systems (e.g. a static or comparative analysis of the innovative performance of countries). If there was attention for dynamics, it was usually focused on the emergence of new systems or industries (e.g. Rosenkopf and Tushman, 1994 and Van de Ven, 1993). Not much attention has been paid to the change from one system to another. In a recent discussion of sectoral systems of innovation Malerba (2002), p. 259, noted that one of the key questions that need to be explored in-depth is: “how do new sectoral systems emerge, and what is the link with the previous sectoral system?” This question is taken up in the article. This means the focus of the article is not on (economic) performance, but on dynamics and change. These four contributions are made by describing a coherent conceptual perspective. This means the paper is mainly conceptual and theoretical, using insights from different literatures. Insights from sociology of technology and institutional theory are combined with innovation studies, science and technology studies, cultural studies and domestication studies. Section 2 proposes to widen the focus from systems of innovation to socio-technical systems. The kinds of elements are described, as well as the different actors and social groups which carry and (re)produce socio-technical systems. Section 2 also describes the basic conceptual framework where systems, actors and institutions/rules are seen as three interrelated dimensions. Section 3 opens up the black box of institutions. To avoid confusion of institutions with (public) organisations, the general concept of rules is proposed. Using sociology and institutional theory, different kinds of rules are distinguished (cognitive, normative and formal/regulative) with different effects on human action. Section 4 returns to the three dimensions of systems, actors and rules, and focuses on dynamic interactions over time. A dynamic sociological conceptualisation is developed which understands human action as structured, but leaves much room for intelligent perception and strategic action. The crucial point is to make the framework dynamic, i.e. indicate how economic activities and processes may influence and transform the sociological structures in which they are embedded. The fourth contribution is made in Section 5, which deals with stability and change of socio-technical systems. To understand stability, literatures on path dependence are mobilised and organised with the three analytic dimensions. To understand transitions from one system to another a multi-level perspective is described, where regimes are the meso-level. To understand regime changes interactions with two other levels are crucial (technological niches and socio-technical landscape). The paper ends with discussion and conclusions in Section 6.
نتیجه گیری انگلیسی
This article has made four contributions to the sectoral systems of innovation approach. The first contribution was to explicitly incorporate the user side in the analysis. Hence, it was suggested to widen the unit of analysis from sectoral systems of innovation to socio-technical systems, encompassing the production, distribution and use of technology. A second contribution was to make an analytical distinction between ST-systems, actors and institutions/rules. Making such analytical distinctions somewhat goes against usual practice in science and technology studies, which tends to emphasise ‘seamless webs’, boundary work and messy empirical reality. Although reality is complex, it is useful to make analytical distinctions, because it allows exploration of interactions between categories. This article explicitly conceptualised dynamic interactions between actors, rules and socio-technical systems in 4 and 5. This way the article went beyond notions that everything is complex and inextricably linked up. A third contribution was to open up the black box of institutions and provide a dynamic sociological conceptualisation which understands human action as structured, but leaves much room for intelligent perception and strategic action. This perspective is particularly useful to analyse long-term dynamics (years, decades), e.g. the co-evolution of technology and society (emergence of new technologies, articulation of new user practices, changes in symbolic meanings). The fourth contribution was to address the issue of change from one system to another. To that end the article described a multi-level perspective, addressing socio-technical change at three different levels. Transitions come about when dynamics at these three levels link up and reinforce each other. This understanding of transitions is not only academically interesting, but also has societal relevance. Modern societies face several structural problems. Examples of these problems can be found in many sectors. The transport sector suffers from problems such as congestion, CO2 emissions, air-pollution (small particles: NOx). The energy sector suffers from problems such as CO2 and NOx emissions and reliability issues (oil). The agricultural and food sectors suffer from problems such as infectious disease (e.g. BSE, chicken plague, foot and mouth), too much manure, too much subsidies. These problems are deeply rooted in societal structures and activities. In order to solve such deep societal problems changes from one system to another may be necessary (Berkhout, 2002). An understanding of the dynamics of transitions may assist policy makers to help bring about these changes. The conceptual perspective in this article is fairly complex. Can it be made operational for empirical research? The proof of the pudding is in the eating, i.e. use the perspective for empirical analyses of dynamics of socio-technical systems. In recent years, the multi-level perspective has been used in several empirical studies. It has been applied to the analysis of the transition from sailing ships to steamships (Geels, 2002a) and the transition from horse-and-carriage to automobiles and from propeller-aircraft to turbojets (Geels, 2002b). Belz (2004) used the perspective to study the ongoing transition in Switzerland (1970–2000) from industrialised agriculture to organic farming and integrated production. Raven and Verbong (2004) used it to analyse the failure of two niches in the Netherlands, manure digestion and heat pumps, because of mis-matches with regime-rules of electricity and agriculture. Van den Ende and Kemp (1999) applied the niche-regime-landscape concepts to analyse the shift from computing regimes (based on punched-cards machines) to computer regimes. Van Driel and Schot (2004) used the multi-level perspective to study a transition in the transshipment of grain in the port of Rotterdam (1880–1910), where elevators replaced manual (un)loading of ships. And Raven (2004) used the perspective to study the niches of manure digestion and co-combustion in the electricity regime. Although the multi-level perspective is complex, these studies show its usefulness for empirical analyses. But these studies also increasingly point to a need to differentiate the multi-level perspective, to accommodate differences between sectors and industries. One way forward is to allow for different routes in systems innovations and transitions ( Geels, 2002b and Berkhout et al., 2004). These routes may consist of different kinds of interaction between the three levels. One route could be rapid breakthrough. Sudden changes in the landscape level (e.g. war) create major changes in the selection environment of the regime. This creates windows of opportunity for an innovation to break out of its niche and surprise incumbent firms ( Christensen, 1997). An example is the breakthrough of jet engines in and after World War II. Another route could be gradual transformation, involving multiple innovations. This route starts with increasing problems in the existing regime. This leads to a search for alternative technologies. The search does not immediately yield a winner, resulting in a prolonged period of uncertainty, experimentation, and co-existence of multiple technical options. Only after some time one option becomes dominant, stabilising into a new socio-technical regime. Yet another route could be a gradual reconfiguration in large technical systems. The new innovation first links up with the old system as an add-on, and gradually becomes more dominant as external circumstance change. An example is the gradual shift in the relationship between steam turbines and gas turbines in electricity production ( Islas, 1997). At this stage these routes are merely an indication of a possible way forward. They indicate that the systems of innovation approaches have a fruitful life ahead of them.