ABSTRACT
Innovation as one solution to the challenge In line with Schumpeter’s bequest to economic strategy and policy, we today view innovation as key to a knowledge-based society and its economic growth (Schumpeter, 1934). Indeed, innovation in its various forms – technological, market-related, organizational, etc. – is often what outlines the competitive edge for firms as well as for countries. In addition to the economic rationale, innovation is also seen as a key to achieving more sustainable development worldwide (Norberg-Bohn, 1999; Pearson et al., 2004). Indeed, achieving sustainable development depends on technological and social innovations coupled with organizational and institutional change geared towards environmental sustainability. One salient example is the climate change issue, in particular in relation to ‘post2012’ discussions, where in the light of global difficulties in reaching political agreement, technology is nowadays widely considered the key solution to the dilemma of getting national governments to agree to ambitious carbon reductions while at the same time safeguarding economic development and welfare. Great hopes are also attached to the promise of sustainable technology innovation in other fields of resource use and environmental impact, such as, for instance, non-renewable and renewable resource use, energy conversion and chemicals. Indeed, some of that promise has also been delivered in certain domains. Any innovation process involves a multitude of activities necessary to bring products and services to the market, where an underlying invention is only a partial aspect of the process. Important activities may comprise scientific work, technology and product development, design, market development, changes in organization, social practices, regulations, building industrial networks, infrastructure and culture (Ashford, 2004). This implies that innovation processes involve the creation, absorption and transmission of knowledge and are highly interactive in character in that they involve continuous learning cycles. The previous view of linearity and the focus on a presumed static event of novelty
creation are no longer valid. A departure point in modern innovation studies is that the technological, sectoral, spatial, institutional, organizational, social and economic domains of innovation are highly related and cannot be meaningfully separated in the real world (Ashford, 2004). Sometimes, learning loops can be concentrated within an individual or a limited number of people, but the rule is more often that a multitude of individuals and organizations are involved, holding various resources and tasks. The complex and multidisciplinary character of most innovation processes implies that resources, skills and competencies can seldom reside within an individual, or even within a single organization. Cooperation, knowledge exchange and learning become key. It is the combination of complementary resources and competencies – be it knowledge, capital, facilities, etc. – that may bring the creation of new things: innovation. For any specific organization, such as a firm, recombination of resources and knowledge may take place within the borders of the company in a vertically integrated organizational manner. More often, innovation requires not transactions with external partners, but rather intertwining of organizational processes for innovation to come about. Partners include other firms, customers, suppliers, competitors, research organizations, financiers, policy organizations, bridging actors, etc., locally, nationally or in other countries. Such exchange gives access to resources of various kinds, including equipment, proven laboratory methods, blueprints, development tools, etc. Also, discussions may lead to novel ideas, solutions to technical problems or organizational changes such as suggestions for product or process improvement. Often, interaction is direct and facilitated by face-to-face meetings, being set up as bilateral or multi-partner collaboration on scientific development and copublication, shared platforms for prototype testing, common market efforts, and so on. Sometimes, learning from others comes about through observation rather than by interaction, including, for example, reverse engineering, studying publications, patents or prototype releases at market fairs. In addition, the mobility of people is a main mechanism of knowledge transfer. To underline this inherently social, interactive learning process of creating innovations, a systems approach to innovation has been put forward under the terminology of ‘innovation systems’ (ISs) (Lundvall, 1992; Nelson, 1993; Edquist, 1997). Such studying of innovation helps us understand both how and why new patterns of organization, technology, production and consumption come about, and provides guidance on how these patterns can be induced or accelerated. An IS may be defined as ‘the groups of organizations and individuals involved in the generation, diffusion and adaptation, and use of knowledge of socio-economic significance, and the institutional context that governs the way these interactions and processes take place’ (Hall et al., 2003: 3). Thus, in this school of thought a set of structural elements and their interconnections are the focus – a set of knowledge areas and artefacts (e.g. technology, intellectual property, products), innovating and innovation-related actors and the inherent knowledge flows and networks between these, as well as the underlying institutional framework (Carlsson and Stankiewicz, 1991). Firms in various parts
of the value chain are often the main innovating actors. Research and educational organizations, including universities, are important providers of new knowledge, human capital, etc., but are also intensively engaged in several other activities throughout the innovation process. In addition, there are organizations giving innovation support of various kinds: public organizations and authorities setting conducive policies and institutional arrangements, trade associations, incubators and venture capitalists. An important feature of any innovation system is thus the institutional features setting the rules of the game for the actors and artefacts. The institutions – laws, rules, norms and routines – function as key ordering devices shaping behavioural patterns, and therefore ISs within differing institutions display different patterns of interaction, prevalence of corporate spin-outs, propensity to share knowledge between universities and firms, etc. Innovation processes often include development of a shared vision by dominant actors in a network and evolutions of the institutional landscape in ways that make it open for change (Kaijser, 2001; Kemp et al., 1998). As highlighted above, ISs are networks of organizations and individuals, working under a common institutional set-up (laws, practice, etc.), within which the creation, dissemination and exploitation of new knowledge and innovations occur (Cooke et al., 2004). While it is acknowledged that innovation processes are often global, where the connected knowledge formation, resource accumulation and diffusion processes span regions and nations, there are also spatially delimited aspects of innovation. In fact, one of the ways by which the IS approach helps us to understand such dynamics is by focusing on the institutional specificities of various ISs. Clearly, institutions differ between countries – and even within countries – and they differ between knowledge areas (e.g. between various technological settings) or sectors. Therefore, in the analysis of ISs, one draws a border around the specific system, thereby including or excluding actors, artefacts, networks and institutions as being central to the system or not. To some extent all such delineation is by necessity arbitrary, but nevertheless necessary to do a useful analysis. The literature is thus divided into various IS approaches, focusing on different rules for the delineation: national (Nelson, 1993; Edquist, 2004), regional (Cooke, 2001; Asheim and Coenen, 2006), sectoral (Breschi and Malerba, 1997) or technology based (Carlsson et al., 2002). In essence, the approaches share many common elements, and the structural components included are similar, but the system analysed will look somewhat different depending on which approach is chosen. Importantly, this underscores that the IS approaches are analytical constructs helping us to better understand innovation dynamics, but tells us that the systems may be portrayed in several equally accurate ways. This volume departs from one such IS perspective: the technological innovation system (TIS) approach (Carlsson and Stankiewicz, 1991), emphasizing that we are interested in the emergence and growth of technological areas into specific sectors. Taking technology as the starting point for delineation of a system does not imply technological determinism or underplay, for example, marketbased determinants, but rather we set the borders of the system to those actors,
artefacts and institutions that relate to specific sets of knowledge areas. In our case these areas relate to sustainable technologies for road transport. What is particularly appealing about the TIS approach is its conceptualization of system dynamics through its focus on functions, or key processes, as is discussed below (Bergek et al., 2008).
