Chapter 6 Section 1 Guided Reading and Review a Technological Revolution

Innovation: A Guide to the Literature

Abstract and Keywords

Innovation is not a new phenomenon. Arguably, information technology is as old as flesh itself. There seems to be something inherently "human" about the trend to think near new and amend means of doing things and to attempt them out in practise. In spite of its obvious importance, innovation has non always received the scholarly attending it deserves. For instance, students of long-run economical change used to focus on factors such every bit capital accumulation or the working of markets, rather than on innovation. This is now changing. Research on the role of innovation in economical and social change has proliferated in recent years, particularly inside the social sciences, and with a bent towards cross-disciplinarity. In fact, equally illustrated in this commodity, in recent years the number of social-science publications focusing on innovation has increased much faster than the full number of such publications.

Keywords: innovation, economic alter, capital aggregating, social alter, social sciences

1.i Introduction ¹

Innovation is non a new phenomenon. Arguably, information technology is as old as flesh itself. There seems to exist something inherently "human" about the trend to think most new and amend ways of doing things and to try them out in exercise. Without it, the globe in which nosotros live would look very, very different. Try for a moment to think of a world without airplanes, automobiles, telecommunications, and refrigerators, just to mention a few of the more of import innovations from the not-likewise-distant past. Or—from an even longer perspective—where would nosotros be without such fundamental innovations as agronomics, the bike, the alphabet, or printing?

Fig. 1.ane Scholarly Manufactures with "Innovation" in the title, 1955–2004 (per 10,000 social scientific discipline manufactures)

Notation: The source is the ISI Web of Knowledge, Social Sciences Commendation Alphabetize (SSCI).

In spite of its obvious importance, innovation has not e'er received the scholarly attention it deserves. For instance, students of long-run economical change used to focus on factors such every bit capital letter accumulation or the working of markets, rather than on innovation. This is now changing. Research on the role of innovation in economic and social change has proliferated in recent years, particularly within the social sciences, and with a aptitude towards cross-disciplinarity. In fact, as illustrated in Figure i.i, in recent years the number of social-science publications focusing on innovation has increased much faster than the full number of such publications. (p. 2) Every bit a result, our knowledge about innovation processes, their determinants and social and economical impact has been greatly enhanced.

When innovation studies started to emerge equally a separate field of enquiry in the 1960s, information technology did and so mostly exterior the existing disciplines and the most prestigious universities. An important effect in this process was the germination in 1965 of the Science Policy Research Unit (SPRU) at the Academy of Sussex (see Box 1.1). The proper noun of the center illustrates the tendency for innovation studies to develop unde other (at the time more adequate?) terms, such as, for instance, "science studies" or "scientific discipline policy studies." But equally we shall see in the following, 1 of the main lessons from the enquiry that came to be carried out is that science is merely i among several ingredients in successful innovation. Every bit a consequence of these findings, non only the focus of research in this expanse merely also the notions used to characterize it inverse. During the belatedly twentieth/early xx-commencement century, a number of new research centers and departments take been founded, focusing on the part of innovation in (p. iii) economic and social change. Many of these accept a cross-disciplinary orientation, illustrating the need for innovation to be studied from different perspectives. Several journals and professional person associations have also been founded.

The leaning towards cross-disciplinarity that characterizes much scholarly work in this area reflects the fact that no single subject deals with all aspects of innovation. Hence, to get a comprehensive overview, it is necessary to combine insights from several disciplines. Traditionally, for instance, economics has dealt primarily with the allocation of resources to innovation (in competition with other ends) and its economic effects, while the innovation process itself has been more than or less treated as a "black box." What happens within this "box" has been left to scholars from other disciplines. A lot of what happens obviously has to do with learning, a central topic in cognitive science. Such learning occurs in organized settings (east.1000. groups, teams, firms, (p. four) and networks), the working of which is studied inside disciplines such as sociology, organizational science, management, and business studies. Moreover, equally economic geographers point out, learning processes tend to be linked to specific contexts or locations. The way innovation is organized and its localization too undergo important changes through time, as underscored past the piece of work within the field of economic history. There is as well, as historians of technology have pointed out, a specific technological dimension to this; the manner innovation is organized, as well as its economic and social effects, depends critically on the specific nature of the technology in question.

Two decades ago, information technology was still possible for a difficult-working educatee to go a fairly good overview of the scholarly piece of work on innovation past devoting a few years of intensive study to the subject. Not whatsoever more. Today, the literature on innovation is so large and diverse that even keeping up-to-date with one specific field of research is very challenging. The purpose of this book is to provide the reader with a guide to this rapidly expanding literature. We exercise this nether the following wide headings:

Part One focuses on the process through which innovations occur and the actors that accept function: individuals, firms, organizations, and networks. Every bit we volition discuss in more than detail below, innovation is by its very nature a systemic phenomenon, since it results from continuing interaction between different actors and organizations. Function Two outlines the systems perspective on innovation studies and discusses the roles of institutions, organizations, and actors in this process at the national and regional level. Part Iii explores the diverseness in the manner in which such systems work over time and beyond different sectors or industries. Finally, Office Four examines the broader social and economic consequences of innovation and the associated policy issues. The remainder of this chapter sets the stage for the discussion that follows by giving a wide overview of some of the primal topics in innovation studies (including conceptual issues).

1.2 What is Innovation?

An important distinction is unremarkably made betwixt invention and innovation. ² Invention is the start occurrence of an idea for a new production or procedure, while innovation is the first try to carry it out into practise. Sometimes, invention and innovation are closely linked, to the extent that information technology is difficult to distinguish 1 from (p. 5) another (biotechnology for instance). In many cases, however, there is a considerable time lag between the two. In fact, a lag of several decades or more is non uncommon (Rogers 1995). Such lags reflect the different requirements for working out ideas and implementing them. While inventions may be carried out anywhere, for example in universities, innovations occur mostly in firms, though they may also occur in other types of organizations, such equally public hospitals. To be able to turn an invention into an innovation, a house normally needs to combine several dissimilar types of knowledge, capabilities, skills, and resources. For instance, the business firm may require production noesis, skills and facilities, market cognition, a well-functioning distribution system, sufficient financial resources, and so on. It follows that the role of the innovator, ³ i.e. the person or organizational unit responsible for combining the factors necessary (what the innovation theorist Joseph Schumpeter (see Box 1.2) called the "entrepreneur"), may be quite different from that of the inventor. Indeed, history is replete with cases in which the inventor of major technological advances fails to reap the profits from his breakthroughs.

Long lags between invention and innovation may have to do with the fact that, in many cases, some or all of the conditions for commercialization may be defective. There may not be a sufficient demand (yet!) or it may be impossible to produce and/or market because some vital inputs or complementary factors are not (yet!) available. Thus, although Leonardo da Vinci is reported to accept had some quite advanced ideas for a flight machine, these were impossible to comport out in practise due to a lack of adequate materials, production skills, and—above all—a ability source. In fact, the realization of these ideas had to wait for the invention and subsequent commercialization (and improvement) of the internal combustion engine. ⁴ Hence, as this case shows, many inventions require complementary inventions and innovations to succeed at the innovation stage.

Another complicating factor is that invention and innovation is a continuous process. For instance, the car, as we know it today, is radically improved compared to the first commercial models, due to the incorporation of a very large number of dissimilar inventions/innovations. In fact, the first versions of virtually all significant innovations, from the steam engine to the airplane, were crude, unreliable versions of the devices that eventually diffused widely. Kline and Rosenberg (1986), in an influential paper, point out:

it is a serious mistake to treat an innovation as if it were a well-defined, homogenous thing that could be identified as entering the economic system at a precise date—or becoming bachelor at a precise point in fourth dimension…. The fact is that most of import innovations go through desperate changes in their lifetimes—changes that may, and often do, totally transform their economic significance. The subsequent improvements in an invention later on its first introduction maybe vastly more than of import, economically, than the initial availability of the invention in its original course. (Kline and Rosenberg 1986: 283)

Thus, what we think of every bit a single innovation is often the result of a lengthy process involving many interrelated innovations. This is one of the reasons why (p. vi) many students of applied science and innovation discover it natural to apply a systems perspective rather than to focus exclusively on individual inventions/innovations.

Innovations may also be classified according to "type." Schumpeter (run into Box 1.2) distinguished between v different types: new products, new methods of product, new sources of supply, the exploitation of new markets, and new ways to (p. 7) organize business organisation. However, in economics, near of the focus has been on the two first of these. Schmookler (1966), for instance, in his classic work on "Invention and Economical Growth," argued that the distinction between "product technology" and "production applied science" was "disquisitional" for our understanding of this miracle (ibid. 166). He divers the former type equally knowledge virtually how to create or improve products, and the latter every bit knowledge about how to produce them. Similarly, the terms "product innovation" and "procedure innovation" accept been used to characterize the occurrence of new or improved appurtenances and services, and improvements in the ways to produce these good and services, respectively. ⁵ The argument for focusing particularly on the distinction betwixt product and process innovation often rests on the assumption that their economic and social impact may differ. For case, while the introduction of new products is commonly assumed to have a clear, positive effect on growth of income and employment, it has been argued that process innovation, due to its cost-cutting nature, may have a more ambiguous effect (Edquist et al. 2001; Pianta in this volume). Withal, while clearly distinguishable at the level of the private house or industry, such differences tend to become blurred at the level of the overall economy, because the product of one business firm (or industry) may end upwards as existence used to produce goods or services in another. ^vi

The focus on production and process innovations, while useful for the analysis of some bug, should non atomic number 82 u.s.a. ignore other important aspects of innovation. For instance, during the first half of the twentieth century, many of the innovations that made information technology possible for the United states to "forge ahead" of other capitalist economies were of the organizational kind, involving entirely new ways to organize production and distribution (run across Bruland and Mowery in this volume, while Lam provides an overview of organizational innovation). Edquist et al. (2001) have suggested dividing the category of process innovation into "technological process innovations" and "organizational process innovations," the quondam related to new types of mechanism, and the latter to new ways to organize work. However, organizational innovations are not express to new ways to organize the process of production within a given firm. Organizational innovation, in the sense used by Schumpeter, ^seven also includes arrangements across firms such as the reorganization of entire industries. Moreover, equally exemplified by the example of the USA in the first half of the previous century, many of the virtually important organizational innovations have occurred in distribution, with great consequences for a whole range of industries (Chandler 1990).

Another arroyo, also based on Schumpeter'south work, has been to classify innovations according to how radical they are compared to current engineering science (Freeman and Soete 1997). From this perspective, continuous improvements of the type referred to above are often characterized as "incremental" or "marginal" innovations, ⁸ as opposed to "radical" innovations (such as the introduction of a totally new type of machinery) or "technological revolutions" (consisting of a cluster of innovations that together may take a very far-reaching impact). Schumpeter focused in particular on the latter two categories, which he believed to be of greater (p. 8) importance. It is a widely held view, however, that the cumulative impact of incremental innovations is just as bully (if not greater), and that to ignore these leads to a biased view of long run economical and social change (Lundvall et al. 1992). Moreover, the realization of the economic benefits from "radical" innovations in most cases (including those of the plane and the automobile, discussed before) requires a series of incremental improvements. Arguably, the bulk of economic benefits come from incremental innovations and improvements.

There is besides the question of how to accept unlike contexts into account. If A for the commencement time introduces a particular innovation in 1 context, while B later introduces the same innovation in another, would we characterize both as innovators? This is a matter of convention. A widely used practice, based on Schumpeter's work, is to reserve the term innovator for A and characterize B as an imitator. Merely one might contend that, following Schumpeter'due south own definition, it would be equally consequent to call B an innovator equally well, since B is introducing the innovation for the first time in a new context. This is, for example, the position taken by Hobday (2000) in a discussion of innovation in the so-called "newly industrializing countries" in Asia. ^nine One might object, though, that there is a qualitative departure between (a) commercializing something for the first time and (b) copying information technology and introducing it in a different context. The latter arguably includes a larger dose of imitative behavior (false), or what is sometimes called "technology transfer." This does not exclude the possibility that fake may pb to new innovation(s). In fact, as pointed out by Kline and Rosenberg (1986, meet Box 1.3), many economically pregnant innovations occur while a product or process is diffusing (see as well Hall in this book). Introducing something in a new context ofttimes implies considerable adaptation (and, hence, incremental innovation) and, every bit history has shown, organizational changes (or innovations) that may significantly increment productivity and competitiveness (come across Godinho and Fagerberg in this book). ^ten

(p. 9)

1.three Innovation in the Making

Leaving definitions aside, the primal question for innovation research is of course to explicate how innovations occur. One of the reasons innovation was ignored in mainstream social science for so long was that this was seen equally impossible to do. The best one could exercise, information technology was commonly assumed, was to await at innovation as a random phenomenon (or "manna from heaven," as some scholars used to phrase it). Schumpeter, in his early on works, was one of the kickoff to object to this exercise. His own account of these processes emphasized three main aspects. The first was the fundamental uncertainty inherent in all innovation projects; the 2nd was the demand to motility apace before somebody else did (and reap the potential economic advantage). In exercise, Schumpeter argued, these ii aspects meant that the standard behavioral rules, due east.chiliad., surveying all data, assessing information technology, and finding the "optimal" choice, would not work. Other, quicker ways had to be plant. This in his view involved leadership and vision, two qualities he associated with entrepreneurship. The 3rd aspect of the innovation process was the prevalence of "resistance to new ways"—or inertia—at all levels of society, which threatened to destroy all novel initiatives, and forced entrepreneurs to fight hard to succeed in their projects. Or as he put it: "In the breast of i who wishes to do something new, the forces of habit raise up and carry witness confronting the embryonic projection" (Schumpeter 1934: 86). Such inertia, in Schumpeter's view, was to some extent endogenous, since information technology reflected the embedded character of existing knowledge and habit, which, though "energy-saving," tended to bias decision-making confronting new ways of doing things.

Hence, in Schumpeter'south early on work (sometimes chosen "Schumpeter Mark I") innovation is the outcome of continuous struggle in historical time betwixt individual entrepreneurs, advocating novel solutions to particular problems, and social (p. ten) inertia, with the latter seen as (partly) endogenous. This may, to some extent, have been an adequate interpretation of events in Europe effectually the turn of the nineteenth century. Simply during the showtime decades of the twentieth century, it became clear to observers that innovations increasingly involve teamwork and take place within larger organizations (run into Bruland and Mowery (Ch. 13), Lam (Ch. v), and Lazonick (Ch. 2) in this volume). In later work, Schumpeter best-selling this and emphasized the need for systematic study of "cooperative" entrepreneurship in large firms (and then-called "Schumpeter Mark 2"). However, he did not analyze the phenomenon in much particular (although he strongly brash others to). ¹¹

Systematic theoretical and empirical piece of work on innovation-projects in firms (and the management of such projects) was tedious to evolve, but during the last decades a quite substantial literature has emerged (see capacity by Pavitt and Lam in this book). In general, research in this surface area coincides with Schumpeter's emphasis on uncertainty (Nelson and Winter 1982; Nonaka and Takeuchi 1995; Van de Ven et al. 1999). In particular, for potentially rewarding innovations, it is argued, i may simply non know what are the most relevant sources or the best options to pursue (however less how great the chance is of success). ¹² Information technology has also been emphasized that innovative firms need to consider the potential problems that "path dependency" may create (Arthur 1994). For instance, if a firm selects a specific innovation path very early, it may (if information technology is lucky) enjoy "first mover" advantages. Merely it likewise risks being "locked in" to this specific path through various self-reinforcing effects. If in the end it turns out that there actually existed a superior path, which some other house equipped with more patience (or luck) happened to find, the early mover may be in big trouble because and so, information technology is argued, information technology may simply be too costly or as well belatedly to switch paths. Information technology has been suggested, therefore, that in the early on phase of an innovation project, before sufficient noesis of the alternatives is generated, the best strategy may simply be to avoid being "stuck" to a particular path, and remain open up to different (and competing) ideas/solutions. At the level of the firm, this requires a "pluralistic leadership" that allows for a multifariousness of competing perspectives (Van de Ven et al. 1999), in contrast to the homogenous, unitary leader style that, in the direction literature, is sometimes considered as the most advantageous. ^thirteen

"Openness" to new ideas and solutions? is considered essential for innovation projects, particularly in the early phases. The master reason for this has to exercise with a fundamental characteristic of innovation: that every new innovation consists of a new combination of existing ideas, capabilities, skills, resources, etc. It follows logically from this that the greater the variety of these factors within a given system, the greater the scope for them to be combined in different ways, producing new innovations which volition exist both more complex and more sophisticated. This evolutionary logic has been used to explain why, in ancient times, the inhabitants of the large Eurasian landmass came to exist more than innovative, and technologically sophisticated, than small, isolated populations elsewhere around the globe (Diamond 1998). Practical mechanically on a population of firms, this logic might perhaps exist taken to (p. 11) imply that large firms should be expected to be more innovative than small-scale firms. ^fourteen All the same, modern firms are not closed systems comparable to isolated populations of ancient times. Firms accept learnt, by necessity, to monitor closely each other's steps, and search widely for new ideas, inputs, and sources of inspiration. The more firms on boilerplate are able to acquire from interacting with external sources, the greater the pressure on others to follow suit. This greatly enhances the innovativeness of both private firms and the economical systems to which they vest (regions or countries, for instance). Arguably, this is of detail importance for smaller firms, which have to recoup for small internal resource by beingness practiced at interacting with the outside earth. However, the growing complexity of the noesis bases necessary for innovation means that fifty-fifty large firms increasingly depend on external sources in their innovative action (Granstrand, Patel, and Pavitt, 1997; and in this volume: Pavitt; Powell and Grodal; Narula and Zanfei).

Hence, cultivating the capacity for absorbing (exterior) knowledge, and then-called "absorbent chapters" (Cohen and Levinthal 1990), is a must for innovative firms, large or modest. It is, nevertheless, something that firms frequently find very challenging; the "non invented here" syndrome is a well-known characteristic in firms of all sizes. This arguably reflects the cumulative and embedded character of firm-specific knowledge. In most cases, firms develop their knowledge of how to do things incrementally. Such noesis, then, consists of "routines" that are reproduced through practice ("organizational memory": Nelson and Wintertime 1982). Over fourth dimension, the organizational structure of the business firm and its knowledge base typically co-evolve into a prepare-up that is beneficial for the day-to-day operations of the house. It has been argued, nevertheless, that such a set-up, while facilitating the daily internal advice/interaction of the firm, may in fact constrain the house's capacity for absorbing new knowledge created elsewhere, especially if the new external noesis significantly challenges the existing set up-upwardly/knowledge of the firm (so-chosen "competence destroying technical change": Tushman and Anderson 1986). In fact, such issues may occur even for innovations that are created internally. Xerox, for instance, adult both the PC and the mouse, but failed to exploit commercially these innovations, primarily because they did non seem to exist of much value to the firm's existing photograph-copier business organisation (Rogers 1995).

Thus organizing for innovation is a delicate task. Research in this area has, amidst other things, pointed to the need for innovative firms to permit groups of people within the organization sufficient freedom in experimenting with new solutions (Van deVen 1999), and establishing patterns of interaction within the firm that allow it to mobilize its entire cognition base when confronting new challenges (Nonaka and Takeuchi 1995; Lam, Ch. five in this book). Such organizing does non terminate at the gate of the firm, simply extends to relations with external partners. Ties to partners with whom communication is frequent are often called "strong ties," while those that are more occasional are denoted as "weak ties" (Granovetter 1973; see Powell and Grodal, Ch. three in this volume). Partners linked together with strong ties, either (p. 12) directly, or indirectly via a common partner, may self-organize into (relatively stable) networks. Such networks may be very useful for managing and maintaining openness. But merely as firms can display symptoms of path-dependency, the same can happen to established networks, equally the participants converge to a common perception of reality (and then-chosen "grouping-think"). Innovative firms therefore often discover information technology useful to as well cultivate so-called "weak ties" in order to maintain a capacity for irresolute its orientation (should information technology prove necessary).

1.iv The Systemic Nature of Innovation

As is axiomatic from the preceding word, a central finding in the literature is that, in most cases, innovation activities in firms depend heavily on external sources. One contempo study sums it upwardly well: "Pop folklore notwithstanding, the innovation journey is a collective achievement that requires primal roles from numerous entrepreneurs in both the public and private sectors" (Van de Ven et al. 1999: 149). In that item study, the term "social system for innovation evolution" was used to characterize this "collective achievement." All the same, this is just i among several examples from the last decades of how arrangement concepts are applied to the analysis of the relationship between innovation activities in firms and the wider framework in which these activities are embedded (see Edquist, Ch. 7 in this volume).

One main approach has been to delineate systems on the basis of technological, industrial, or sectoral characteristics (Freeman et al. 1982; Hughes 1983; Carlsson and Stankiewicz 1991; Malerba, Ch. fourteen in this volume) just, to a varying degree, to include other relevant factors such equally, for instance, institutions (laws, regulations, rules, habits, etc.), the political procedure, the public enquiry infrastructure (universities, research institutes, back up from public sources, etc.), fiscal institutions, skills (labor force), and and then on. To explore the technological dynamics of innovation, its various phases, and how this influences and is influenced past the wider social, institutional, and economic frameworks has been the main focus of this type of assay. Another of import approach in the innovation-systems literature has focused on the spatial level, and used national or regional borders to distinguish between different systems. For instance, Lundvall (1992) and Nelson et al. (1993) have used the term "national arrangement of innovation" to characterize the systemic interdependencies within a given land (come across Edquist in this volume), while Braczyk et al. (1997) similarly have offered the notion of "regional innovation systems" (come across Asheim and Gertler, Ch. 11 in this book). Since the spatial systems are delineated on the basis of political and administrative borders, such factors (p. 13) naturally tend to play an important role in analyses based on this approach, which has proven to exist influential among policy makers in this surface area, peculiarly in Europe (see Lundvall and Borrás, Ch. 22 in this volume). (Part Ii of this volume analyzes some of the elective elements of such systems in more detail. ¹⁵ )

What are the implications of applying a system perspective to the study of innovation? Systems are—equally networks—a set of activities (or actors) that are interlinked, and this leads naturally to a focus on the working of the linkages of the system. ¹⁶ Is the potential for communication and interaction through existing linkages sufficiently exploited? Are at that place potential linkages within the system that might profitably be established? Such questions use of course to networks equally well equally systems. Even so, in the normal usage of the term, a system will typically have more "structure" than a network, and be of a more enduring graphic symbol. The structure of a arrangement volition facilitate certain patterns of interaction and outcomes (and constrain others), and in this sense there is a parallel to the function of "inertia" in firms. A dynamic system also has feedbacks, which may serve to reinforce—or weaken—the existing structure/functioning of the system, leading to "lock in "(a stable configuration), or a change in orientation, or—eventually—the dissolution of the system. Hence, systems may—merely every bit firms—be locked into a specific path of evolution that supports certain types of activities and constrains others. This may be seen as an advantage, as it pushes the participating firms and other actors in the system in a direction that is deemed to be benign. But it may also be a disadvantage, if the configuration of the arrangement leads firms to ignore potentially fruitful avenues of exploration. The character of such processes will be affected by the extent to which the organisation exchanges impulses with its environment. The more open a system is for impulses from exterior, the less the risk of existence "locked out" from promising new paths of development that emerge exterior the system. It is, therefore, important for "organization managers"—such as policy makers—to keep an center on the openness of the system, to avert the possibility of innovation activities becoming unduly constrained by cocky-reinforcing path-dependency.

Some other important feature of systems that has come into focus is the stiff complementarities that normally exist betwixt the components of a system. If, in a dynamic arrangement, ane critical, complementary component is lacking, or fails to progress or develop, this may block or slow down the growth of the entire system. This is, as pointed out earlier, one of the main reasons why in that location is often a very considerable fourth dimension lag between invention and innovation. Economic historians have normally used concepts such as "reverse salients" and "bottlenecks" to characterize such phenomena (Hughes 1983; Rosenberg 1982). All the same, such constraints need not be of a purely technical graphic symbol (such as, for instance, the failure to invent a decent battery, which has severely constrained the diffusion of electric cars for more than century), but may have to practise with lack of proper infrastructure, finance, skills, etc. Some of the virtually important innovations of this century, such as electricity and automobiles (Mowery and Rosenberg 1998), were dependent on very extensive (p. 14) infrastructural investments (wiring and roads/distribution-systems for fuel, respectively). Moreover, to fulfil the potential of the new innovation, such investments often demand to be accompanied by radical changes in the arrangement of production and distribution (and, more than by and large, attitudes: come across Perez 1983, 1985; Freeman and Louçâ 2001). There are important lessons here for firms and policy makers. Firms may need to take into account the wider social and economic implications of an innovation project. The more radical an innovation is, the greater the possibility that it may require extensive infrastructural investments and/or organizational and social change to succeed. If so, the firm needs to think through the style in which it may join upwards with other agents of modify in the individual or public sector. Policy makers, for their office, need to consider what different levels of regime tin can do to forbid "bottlenecks" to occur at the organization level in areas such equally skills, the inquiry infrastructure, and the broader economic infrastructure.

1.5 How Innovation Differs

One of the hitting facts well-nigh innovation is its variability over time and space. It seems, every bit Schumpeter (see Box 1.ii) pointed out, to "cluster," not only in sure sectors but too in certain areas and time periods. Over time the centers of innovation have shifted from one sector, region, and country to another. For instance, for a long period the worldwide center of innovation was in the UK, and the productivity and income of its population increased relative to its neighboring countries, so that past the mid-nineteenth century its productivity (and income) level was 50 per cent college than elsewhere; at nearly the beginning of the twentieth century the middle of innovation, at to the lowest degree for the modern chemical and electrical technologies of the day, shifted to Federal republic of germany; and now, for a long time, the worldwide centre of innovation has been in the United states, which during well-nigh of the twentieth century enjoyed the highest productivity and living standards in the world. Equally explained past Bruland and Mowery in this volume, the rise of the US to world technological leadership was associated with the growth of new industries, based on the exploitation of economies of scale and scope (Chandler 1962, 1990) and mass product and distribution.

How is this dynamic to be explained? Schumpeter, extending an earlier line of argument dating back to Karl Marx, ¹⁷ held technological competition (contest through innovation) to exist the driving strength of economical development. If i business firm in a given industry or sector successfully introduces an important innovation, the argument goes, it will be amply rewarded by a higher rate of profit. This functions (p. 15) equally a signal to other firms (the imitators), which, if entry conditions permit, volition "swarm" the industry or sector with the hope of sharing the benefits (with the issue that the initial innovator's first mover advantages may be quickly eroded). This "swarming" of imitators implies that the growth of the sector or industry in which the innovation occurs will exist quite loftier for a while. Sooner or later on, however, the effects on growth (created by an innovation) volition be depleted and growth will slow down.

To this substantially Marxian story Schumpeter added an important modification. Imitators, he argued, are much more likely to succeed in their aims if they meliorate on the original innovation, i.due east., become innovators themselves. This is all the more than natural, he continued, because 1 (of import) innovation tends to facilitate (induce) other innovations in the same or related fields. In this way, innovation– improvidence becomes a artistic process—in which one important innovation sets the stage for a whole series of subsequent innovations—and not the passive, adaptive procedure oft assumed in much diffusion research (meet Hall in this volume). The systemic interdependencies between the initial and induced innovations also imply that innovations (and growth) "tend to concentrate in sure sectors and their surroundings" or "clusters" (Schumpeter 1939: 100–ane). Schumpeter, as is well known, looked at this dynamic every bit a possible explanatory factor backside business cycles of various lengths (Freeman and Louçâ 2001).

This uncomplicated scheme has been remarkably successful in inspiring applications in different areas. For instance, there is a large amount of research that has adapted the Marx–Schumpeter model of technological competition to the study of industrial growth, international trade, and competitiveness, ¹⁸ although sometimes, it must be said, without acknowledging the source for these ideas. An early and very influential contribution was the so-called "product-life-wheel theory" suggested by Vernon (1966), in which industrial growth following an of import product innovation was seen as composed of stages, characterized by changing conditions of and location of production. ¹⁹ Basically what was assumed was that the ability to do production innovation mattered almost at the early stage, in which there were many dissimilar and competing versions of the product on the market. However, with time, the product was assumed to standardize, and this was assumed to be accompanied by a greater emphasis on process innovation, scale economics, and cost-contest. It was argued that these changes in competitive conditions might initiate transfer of the technology from the innovator country (high income) to countries with large markets and/or low costs. Such transfers might also be associated with international majuscule flows in the form of so-called foreign straight investments (FDIs), and the theory has therefore also go known as a framework for explaining such flows (see Narula and Zanfei in this volume).

The "product-life-cycle theory," attractive as information technology was in its simplicity, was not always corroborated by subsequent enquiry. While it got some of the general conjectures (borrowed from Schumpeter) correct, the rigorous scheme information technology added, (p. xvi) with well-defined stages, standardization, and irresolute competitive requirements, was shown to fit merely a minority of industries (Walker 1979; Cohen 1995). Although good data are hard to come up by, what emerges from empirical research is a much more circuitous picture, ²⁰ with considerable differences across industrial sectors in the way this dynamic is shaped. As exemplified by the taxonomy suggested past Pavitt (run into Box ane.four), exploration of such differences ("industrial dynamics") has evolved into i of the main areas of research inside innovation studies (see in this volume: (p. 17) Ch. 14 by Malerba; Ch. xv by Von Tunzelmann and Acha; Ch. 16 by Miles). Inspired, to a large extent, by the seminal work by Nelson and Winter (see Box 1.5), research in this area has explored the fashion in which industries and sectors differ in terms of their internal dynamics (or "technological regimes": see Malerba and Orsenigo 1997), focusing, in particular, on the differences across sectors in knowledge bases, actors, networks, and institutions (so chosen "sectoral systems": see Malerba, Ch. fourteen in this volume). An important result from this enquiry is that, since the factors that influence innovation differ across industries, policy makers take to take such differences into account when designing policies. The same policy (and policy instruments) will not piece of work equally well everywhere.

(p. 18) 1.6 Innovation and Economic Performance

The Marx–Schumpeter model was non intended every bit a model of industrial dynamics; its master purpose was to explain long run economical change, what Schumpeter called "development." The core of the argument was (1) that technological contest is the major course of contest under capitalism (and firms not responding to these demands fail), and (two) that innovations, eastward.k. "new combinations" of existing knowledge and resources, open up possibilities for new business opportunities and future innovations, and in this style set the stage for standing alter. This perspective, while convincing, had little influence on the economic science discipline at the time of its publication, perhaps because it did not lend itself easily to formal, mathematical modeling of the type that had become popular in that field. More than recently, however, economists (Romer 1990), cartoon on new tools for mathematical modeling of economic phenomena, have attempted to innovate some of the above ideas into formal growth models (so-called "new growth theory" or "endogenous growth theory"). ²¹

In developing this perspective, Schumpeter (1939) was, as noted, particularly concerned with the tendency of innovations to "cluster" in certain contexts, and the resulting structural changes in production, organization, need, etc. Although these ideas were not well received past the economic customs at the time, the big slump in economical activity worldwide during the 1970s led to renewed attention, and several contributions emerged viewing long run economical and social modify from this perspective. Both Mensch (1979) and Perez (1983, 1985), to take just two examples, argued that major technological changes, such every bit, for instance, the ICT revolution today, or electricity a century ago, crave extensive organizational and institutional change to run their course. Such change, nevertheless, is hard considering of the continuing influence of existing organizational and institutional patterns. They saw this inertia every bit a major growth-impeding factor in periods of rapid technological change, possibly explaining some of the variation of growth over time (eastward.g. booms and slumps) in capitalist economies. While the latter proposition remains controversial, the relationship between technological, organizational, and institutional change continues to be an important research issue (Freeman and Louçã 2001), with important implications both for the analysis of the diffusion of new technologies (come across Hall in this volume) and the policy discourse (meet Lundvall and Borras in this volume).

Although neither Marx nor Schumpeter practical their dynamic perspective to the analysis of cross-national differences in growth operation, from the early 1960s onwards several contributions emerged that explore the potential of this perspective for explaining differences in cantankerous-country growth. In what came to exist a very influential contribution, Posner (1961) explained the departure in economical growth (p. 19) betwixt two countries, at unlike levels of economic and technological development, as resulting from two sources: innovation, which enhanced the difference, and fake, which tended to reduce it. This set the phase for a long serial of contributions, often labeled "technology gap" or "north–south" models (or approaches), focusing on explaining such differences in economical growth across countries at different levels of evolution (see Fagerberg 1994, 1996 for details). As for the lessons, one of the theoretical contributors in this area summed information technology up well when he concluded that: "Like Alice and the Red Queen, the developed region has to go along running to stay in the same place" (Krugman 1979: 262).

A weakness of much of this work was that it was based on a very stylized representation of the global distribution of innovation, in which innovation was causeless to be concentrated in the developed world, mainly in the U.s.. In fact, as argued by Fagerberg and Godinho in this volume, the successful catch-upward in applied science and income is normally non based simply on imitation, but likewise involves innovation to a significant extent. Arguably, this is also what one should expect from the Schumpeterian perspective, in which innovation is causeless to be a pervasive miracle. Fagerberg (1987, 1988) identified iii factors affecting differential growth rates across countries: innovation, imitation, and other efforts related to the commercial exploitation of engineering. The analysis suggested that superior innovative activeness was the prime number factor behind the huge difference in performance between Asian and Latin American NIC countries in the 1970s and early on 1980s. Fagerberg and Verspagen (2002) likewise plant that the continuing rapid growth of the Asian NICs relative to other land groupings in the decade that followed was primarily caused by the rapid growth in the innovative performance of this region. Moreover, information technology has been shown (Fagerberg 1987; Fagerberg and Verspagen 2002) that, while simulated has go more than demanding over fourth dimension (and hence more hard and/or costly to undertake), innovation has gradually become a more than powerful cistron in explaining differences beyond countries in economic growth.

i.vii What do we Know almost Innovation? And what do nosotros Need to Larn more about?

Arguably, we accept a proficient understanding of the role played by innovation in long run economical and social change, and many of its consequences: (p. xx)

Because of these desirable consequences, policy makers and concern leaders akin are concerned with ways in which to foster innovation. Nevertheless, in spite of the large amount of inquiry in this surface area during the by fifty years, nosotros know much less about why and how innovation occurs than what information technology leads to. Although it is by now well established that innovation is an organizational miracle, nearly theorizing near innovation has traditionally looked at it from an individualistic perspective, as exemplified by Schumpeter'due south "psychological" theory of entrepreneurial behavior (Fagerberg 2003). Similarly, most work on noesis and knowledge focuses on individuals, not organizations. An important exception was, of course, Nelson and Winter (1982), whose focus on "organizational memory" and its links to do paved the way for much subsequent piece of work in this area. ²² But our understanding of how knowledge—and innovation—operates at the organizational level remains fragmentary and further conceptual and applied enquiry is needed.

A key finding in the innovation literature is that a firm does not innovate in isolation, but depends on extensive interaction with its environment. Various concepts have been introduced to heighten our understanding of this phenomenon, most of them including the terms "arrangement" or (somewhat less ambitious) "network." Some of these, such as the concept of a "national system of innovation," have become popular among policy makers, who accept been constrained in their ability to act by lack of a sufficiently developed framework for the blueprint and evaluation of policy. All the same, it is a long way from pointing to the systemic character of innovation processes (at different levels of analysis), to having an approach that is sufficiently developed to allow for systematic analysis and assessment of policy issues. Arguably, to be really helpful in that regard, these organization approaches are in need of substantial elaboration and refinement (come across the chapter by Edquist in this volume).

(p. 21)

One obstacle to improving our understanding is that innovation has been studied past different communities of researchers with different backgrounds, and the failure of these communities to communicate more than effectively with ane another has impeded progress in this field. Ane consequence of these communication difficulties has been a certain degree of "fuzziness" with respect to basic concepts, which can just be improved past bringing these different communities together in a constructive dialogue, and the present volume should exist seen every bit a contribution towards this aim. Different, and to some extent competing, perspectives should not always be seen as a trouble: many social phenomena are too complex to exist analyzed properly from a single disciplinary perspective. Arguably, innovation is a prime example of this.

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Notes:

(*) Asterisked items are suggestions for farther reading.

(i.) Iwish to give thanks my fellow editors and contributors for helpful comments and suggestions. Thanks also to Ovar Andreas Johansson for assistance in the enquiry, Sandro Mendonça for his many creative inputs (which I unfortunately have not take been able to follow to the extent that he deserves), and Louise Earl for good advice. The responsibility for remaining errors and omissions is mine.

(two.) A consistent use of the terms invention and innovation might be to reserve these for the beginning fourth dimension occurrence of the thought/concept and commercialization, respectively. In do it may not always be so simple. For instance, people may very well conceive the same thought independently of one some other. Historically, there are many examples of this; writing, for instance, was conspicuously invented several times (and in different cultural settings) throughout history (Diamond 1998). Arguably, this phenomenon may accept been reduced in importance over time, as communication around the earth has progressed.

(3.) In the sociological literature on improvidence (i.e. spread of innovations), information technology is common to characterize any adopter of a new technology, product, or service an innovator. This then leads to a stardom between different types of innovators, depending on how quick they are in adopting the innovation, and a discussion of which factors might peradventure explain such differences (Rogers 1995). While this apply of the terminology may be a useful one in the chosen context, information technology clearly differs from the one adopted elsewhere. Information technology might be preferable to use terms such every bit "imitator" or "adopter" for such cases.

(four.) Similarly for automobiles: while the idea of a ability-driven vehicle had been around for a long time, and several early attempts to commercialize cars driven by steam, electricity, and other sources had been fabricated, it was the incorporation of an internal combustion engine driven past depression-cost, easily available petrol that made the product a existent hit in the market (Mowery and Rosenberg 1998).

(5.) A somewhat similar stardom has been suggested past Henderson and Clark (1990). They distinguish between the components (or modules) of a product or service and theway these components are combined, e.g. the product "blueprint" or "architecture." A change but in the sometime is dubbed "modular innovation," change simply in the latter "architectural innovation." They contend that these two types of innovation rely on different types of knowledge (and, hence, create unlike challenges for the firm).

(vi.) In fact, many economists get so far as to contend that the savings in costs, following a process innovation in a unmarried firm or manufacture, past necessity will generate boosted income and need in the economy at large, which volition "recoup" for whatever initial negative effects of a process innovation on overall employment. For a rebuttal, run across Edquist 2001 and Pianta, Ch. 21 in this book.

(seven.) Schumpeter 1934: 66.

(8.) In the sociological literature on innovation, the term "reinvention" is often used to characterize improvements that occur to a product or service, while it is spreading in a population of adopters (Rogers 1995).

(ix.) In the Customs Innovation Survey (CIS) firms are asked to qualify novelty with respect to the context (new to the business firm, industry or the world at large). Meet Smith in this book for more than information nearly these surveys.

(10.) Kim and Nelson (2000a) propose the term "active imitation" for producers who, by imitating already existing products, modify and better them.

(11.) For instance, in 1 of his last papers, he pointed out: "To let the murder out and startmy terminal thesis, what is actually required is a large collection of industrial and locational monographs all drawn upward co-ordinate to the same plan and giving proper attention on the ane paw to the incessant historical change in production and consumption functions and on the other paw to the quality and behaviour of leading personnel" (Schumpeter 1949/1989: 328).

(12.) Even in cases where the project ultimately is successful in aims, entrepreneurs confront the challenge of disarming the leadership of the firm to launch it commercially (which may be much more plush than developing information technology). This may fail if the leadership of the house has doubts almost its commercial viability. It may exist very hard for direction to foresee the economical potential of a project, even if it is "technically" successful. Remember, for instance, IBM manager Thomas Watson's dictum in 1948 that "there is a world market for about five computers" (Tidd et al. 1997: 60)!

(13.) "A unified homogenous leadership structure is constructive for routine trial-and-error learning past making convergent, incremental improvements in relatively stable and unambiguous situations. Nevertheless, this kind of learning is a conservative process that maintains and converges organizational routines and relationships towards the existing strategic vision … although such learning is viewed as wisdom in stable environments, it produces inflexibility and competence traps in changing worlds" (Van de Ven et al. 1999: 117).

(14.) It would also imply that large countries should be expected to be more innovative than smaller ones, consistent with, for case, the prediction of so-called "new growth" theory (Romer 1990). See Verspagen in this volume.

(fifteen.) Come across, in particular, Ch. 10 by Granstrand (intellectual property rights), Ch. viii by Mowery and Sampat (universities and public enquiry infrastructure), and Ch. 9 by O'Sullivan (finance).

(16.) This is essentially what was suggested by Porter (1990).

(17.) Meet Fagerberg 2002, 2003 for a discussion of this "Marx–Schumpeter" model.

(18.) See Fagerberg (1996), Wakelin (1997), and Cantwell, Ch. 20 in this book for overviews of some of this literature.

(19.) For a more recent analysis in this spirit, with a lot of empirical case-studies, see Utterback (1994).

(20.) Bachelor econometric evidence suggests that innovation, measured in various ways (see Smith in this volume), matters in many industries, not only those which could be classified as being in the early stage of the production-cycle (Soete 1987; Fagerberg 1995).

(21.) For an overview, run into Aghion and Howitt (1998). Run into too the word in Fagerberg (2002, 2003), and Ch. eighteen by Verspagen in this volume.

(22.) For a give-and-take of the office of different types of noesis in economics, including the organizational dimension, see Cowan et al. (2000) and Ancori et al. (2000).

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