The study of innovation in industry draws on insights from several social science disciplines: economics, sociology, economic geography, political science and management. The economics of innovation developed as a subdiscipline based on the work of pioneers such as Schumpeter (1942/1975), who coined the term “creative destruction” to describe the transformation that accompanies radical innovation under capitalism. He was followed by the economists Arrow (1962), Nelson and Winter (1982), Freeman (1982), Lundvall (1992) and Metcalfe (1998).
“Innovation” in the productive sector, whether in manufacturing or services, is usually defined as the creation of novelty of economic value. This translates into viewing innovation as the creation of new products and services, as change in the processes of producing these products and services and as organisational change, including new work practices. Innovation in industry may also mean using new methods to produce services and the creation of “product-service packages”, either as “generics” for a market or to solve particular client needs (Marceau, Cook and Dalton 2002). An example of a new “product-service” package is the set of services provided as part of the “deal” or “bundle” when purchasing a mobile phone.
Both creativity and invention can be found in innovation. Here I define “creativity” as the creation of new ideas or a recombination of existing knowledge that has no immediate or particular market drivers. Invention is a new product (usually) or service whose economic value has not been tested in the market or whose value has been tested but has been found deficient and the new product remains unused. In this sense, creativity is similar to invention. Creative people are viewed as drawing on their thinking and research to find solutions to “problems”, with an emphasis on thinking “outside the box”, “playing” with existing products or services (cf. Dodgson, this volume) to find new ideas for product or services and new understandings of how “things work”. Creative people are also those who can recognize new knowledge and apply it to address both scientific and product-related problems. Creativity is difficult to define in relation to innovation. It is clear that successful innovation depends on creative people as new products and processes require people to think outside the box. This is especially true for radical innovation where new products, processes or services combine new and older knowledge in particularly novel ways. The creative spark is also involved in designing the organisational forms to improve production and sales. The creative leap involved in thinking of and about new knowledge combinations is seldom examined by innovation theorists. Accordingly, even in the management literature, creativity and innovation tend to occupy different conceptual spaces, as argued by Mark Dodgson in this volume.
Innovations may be “radical” or incremental. Some innovations change fundamentally the kinds of products produced, for example, computers and automobiles, while some are small improvements on existing products or manufacturing processes. Incremental innovations are far more common than radical innovations as most fi rms prefer to stay on familiar ground and make only small changes to minimise risk. Radical innovations, such as those in the information and communications technology, which begin life as products, may lead to major process changes; examples are computer- aided design and computers in manufacturing. Some new technologies begin as scientific breakthroughs—examples are biotechnology and nanotechnology—and take considerable time to become the platform for new products.
Modern economies tend to comprise a mix of firms making radical and incremental innovations. Firms may move between radical and incremental innovation as the platform technologies mature and the business environment changes. Radical innovation is more likely to stem from R&D, while incremental innovation, including process innovation, is more likely to stem from customer suggestions and feedback or by experience with the product. The different kinds of innovation all necessitate “creativity” as they involve doing things differently. The new business models essential for commercial breakthroughs also require creative thinking (an example is the Just-in-time operations management system), but often take time to emerge in the marketplace.
The so-called “high-tech” industries are considered significantly more innovation-intensive than their “low-tech” counterparts, but recent studies have shown that the so-called low-tech sectors often use leading-edge technology for product and process innovation (von Tunzelman and Acha 2005). “Old” industries, such as mining and agriculture, are in fact highly knowledge- and R&D-intensive, and have become constant innovators through the application of new science and new business models, including the outsourcing of key activities. The leading mining fi rms, for example, often outsource mine tunneling operations to engineering and construction firms with “cutting- edge” expertise in tunneling. This is an example of how links between different industries can transform operations in another. There are many models of the innovation process.
The linear model (knowledge–push) suggests that new knowledge moves directly from its creators in public-sector research organisations into commercial hands. Over time the linear model has been modifi ed to include factors such as market pull, feedback loops, organisation of the fi rm, knowledge management and links with outside organisations. The new generation models point to distributed or “open” forms of innovation and establishment of networks to share knowledge and capabilities of several organizations (global and local), permanent and transient (Chesborough, Vanhaverbeke and West 2006; Bessant and Venables 2008). In the new generation innovation model, new IT-based “innovation technologies” enable new product and process simulation, rapid prototyping, team design and rapid steps to manufacturing through a process Dodgson, Gann and Salter (2005) refer to as “think, play, do” (see Dodgson, this volume).Creativity plays its clearest role in the new generation models. The opportunity for highly creative ideas based on multiple sources of knowledge and perspectives to become an innovation grows as innovation becomes a more open, distributed and networked activity. As the new models of innovation take hold, creativity may attract greater attention among writers on innovation. With changes in the organisation of innovation we may see a deeper examination of creativity in firms and organisations.
COMPONENTS OF INNOVATION SYSTEMS
Innovation in an industry is dependent on the context (e.g. nation, region and city) in which industrial firms and related institutions function. Here I describe the components frequently identified as critical for innovative capability and performance and how they can be understood as elements of an integrated system.
- human capital
- science system
- research and development
- business system
- venture capital
- technology change
INNOVATION IN INDUSTRY: LARGE FIRMS, SMALL FIRMS, HIGH TECH AND LOW TECH
What determines the level of innovation across different industries? International surveys (OECD 2002, 2003) have measured the levels of innovation activity undertaken by companies and suggest that expenditure on R&D is a critical differentiator for success. The surveys show significant differences in levels of innovation-related expenditure between nations, industry sectors (high versus low tech) and between firms of different sizes. High-technology firms, such as biotechnology, are innovation-intensive and spend up to 10 per cent or more of turnover per annum on R&D; science-based start-up firms may spend considerably more.
Many firms obtain their innovation ideas externally. Studies have shown that customers are the single most important source of innovation knowledge, followed by suppliers and competitors (see e.g. von Hippel 1988; Marceau 1999). Maintaining close links with customers as end-users reduces innovation risk and smoothes the innovation process, especially in regard to product design. Some observers suggest that the most successful firms rely on multiple sources of innovation ideas and seldom a single source (Hyland, Marceau and Sloan 2006), especially, of course, if their markets are differentiated and consist of more than a few large clients. The size of a firm, however, does not alone determine the degree and direction of innovation activity. The type of technology central to the firm, the stage of development of that technology and the type of market in which
a company operates also shape decisions about innovation and investment in new products (Whitley 2000). Some recent studies attempt to identify the different sources and “packages” of influence (Hollenstein 2003). There is likely to be considerable industry variation as, for example, biotechnology firms may behave very differently from, say, metals manufacturers, at least in the early stages of development. The information exchange relationships between four key players (customers/users, producers, regulators, etc.) in a product system. This is a “perfect” map of information and knowledge exchange. All four players are linked equally in information and knowledge exchange across all combinations. We would predict much innovation, unless of course the four players spend all their time informing and not implementing! Few real-life situations approximate equality of information flows and influence. However, under some conditions, such as rapid technological change or a dramatic shift in the regulatory environment (e.g. removal of tariff protection), the industry may rely on powerful dominant players to shift the organisational and operational arrangements and push suppliers into compliance in order to survive. Under other conditions, the major players may be the only ones able to negotiate and coordinate the necessary but complex changes in relationships between all the players in the industry (e.g. with the regulators and the training institutions). Tensions may arise between the “creative” elements of the industry (who value their autonomy and independence) and their “innovative” counterparts who place a premium on business results and industry survival. In practice at any time some players dominate the activities of the industry. The case examples have been selected to focus on industries with significant creative elements—architecture and engineering in the building industry and fashion design in the clothing industry.
Our mapping of an industry product system has implications for policy. For example, the map might reveal perceptions and evidence of too little input from customers or from R&D organisations (information dimension) or too heavy-handed a policy and regulatory compliance framework from government (power relations). In each case this pinpoints the location of an obstacle to innovation. In interviews we look at information
flow and degree of influence from the player’s point of view. Thus, one player (producers) might claim there is little input from research technology organisations, and another reports there is too much interference by powerful regulators. The “maps” thus generated are slices of subjective reality designed to highlight issues and dynamics which industry and policymakers may wish to address for improving innovation.
- research and development
- training institution