Asset profiles for technological innovation

research policy ELSEVIER

Research Policy 24 (1995) 727-745

Asset profiles for technological innovation Jens F r o s l e v C h r i s t e n s e n * Institute of Industrial Economics and Strategy, Copenhagen Business School, Nansensgade 19, 6, DK 1366 Copenhagen, Denmark

Final version received March 1994

Abstract This paper proposes a conceptual distinction between four generic categories of assets for technological innovation: 1) scientific research assets, 2) process innovative assets, 3) product innovative application assets, and 4) aesthetic design assets. Technological innovation may sometimes require the activation of only one asset type, but more often a specific constellation of more asset types has to be mobilized. The asset categories differ profoundly with respect not only to their respective competence bases but also with respect to their "functional" contribution to industrial innovation and mostly also to their organizational attachment. This way of conceiving technological innovation is opposed to the one-dimensional R & D conception that tends to view R & D as one functional asset along with others like manufacturing or marketing. It is argued that the different innovative assets are often located in different organizational settings within the corporation. The coupling between assets is discussed in terms of inter-asset specificity. We illustrate the great variation of innovative asset profiles across a wide spectrum of product categories. The concept of technological trajectories is reinterpreted in terms of asset profile oscillations and regroupings. Finally, the framework is related to recent efforts to formulate a resource-based theory of the firm, and the implications for innovation strategy is discussed.

I. Introduction This p a p e r p r o p o s e s a f r a m e w o r k for analyzing assets for t e c h n o l o g i c a l innovation. T h e f r a m e w o r k is b a s e d on a r e s o u r c e a n d c a p a b i l i t y conc e p t i o n o f t h e firm. Thus, t h e firm m a y b e de-

* Jens Fr~slev Christensen, Institute of Industrial Economics and Strategy, Copenhagen Business School, Nansensgade 19, 6., DK-1366 Copenhagen K Denmark. *Tel. + 45 38152535; Fax + 45 38152540. I am grateful to L. Davis, N.J. Foss, P. Lotz and F. Valentin from Copenhagen Business School and two anonymous referees for their helpful comments on an earlier draft.

fined in t e r m s o f its c o n s t i t u e n t assets ( r e s o u r c e s a n d c a p a b i l i t i e s ) l i n k e d to f u n c t i o n a l a r e a s o f t h e value chain a n d to i n t e r - f u n c t i o n a l a n d g e n e r a l m a n a g e m e n t assets. T h e ability to p r o d u c e technological i n n o v a t i o n is g e n e r a l l y r e c o g n i z e d to be b a s e d on the R & D assets o f the firm. U n d e r such h e a d i n g s as R & D policy or m a n a g e m e n t of t e c h n o l o g y a large l i t e r a t u r e has e x p l o r e d the m a n a g e m e n t o f R & D resources, t h e i n t e r a c t i o n b e t w e e n R & D a n d f u n c t i o n a l assets such as m a n u f a c t u r i n g a n d m a r k e t i n g assets, a n d t h e int e g r a t i o n o f R & D into t h e overall strategy o f the firm. T e e c e (1986) has convincingly a r g u e d that t e c h n o l o g i c a l innovation, once p r o d u c e d , has to

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be aligned with functional "complementary assets" such as marketing or after-sales service in order to appropriate the rents from innovation. In this paper we shall attempt to "transfer" the idea of complementary assets from Teece's ex post perspective to an a priori perspective on technological innovation. In doing this we reject the general tendency to view R & D as a unified functional asset along with other functional assets in the firm and suggest a decomposition of R & D assets into more sub-categories. In other words, we shall focus attention on the various assets required to bring about technological innovation rather than on the assets required to commercially exploit innovation. Mostly, R & D capacity has been identified as the asset the function of which is to produce technological innovation. However, the R & D conception does not grasp the full spectrum of relevant assets for technological innovation. First, R & D, in its narrow statistical meaning, grossly underestimates or even neglects important parts of technological development efforts, especially those related to process development, product application and design (Freeman, 1992; Pavitt, 1986). Secondly, the widespread use of R & D as an indicator of the "functional" asset for producing technological innovation has promoted a stereotyped and often misleading comprehension of innovative activity as being based on one homogeneous category of resources and capabilities. Of course, formally R& D consists of R and D, but mostly the two are fused into one category, and while R & D is often taken to be synonymous with science-based research, generally more than two-thirds of all industrial R & D is D which cannot be further differentiated in current R & D statistics. We propose a differentiation of the D-component into three asset categories: 1) process innovative assets, 2) product innovative application assets, and 3) aesthetic design assets. These categories, together with scientific research assets, comprise a more adequate representation of assets for technological innovation than does the R & D rubric. Our argument is based on three premises: First, there are not one but several generic categories of innovative assets that differ

with respect to "functional" orientation, distinctive skills and strategic importance in a given context. Secondly, these assets may be complementary in the sense that most technological innovations may require the activation and coupling of different types of innovative assets, not just the mobilization of R & D resources in general. Thirdly, these innovative assets do not translate easily into the conventional functional categories of the firm. The technology base of innovative industrial firms consists of a unique profile of innovative assets. Different firms in the same industry may operate at the same absolute or relative level of R & D but still vary greatly with respect to innovative asset profiles. Even if the asset profile of firms within the same industry (or product market) may look very much alike, not two firms possess identic asset profiles, and even minor differences may provide firms with major competitive advantages or disadvantages. We shall argue that industrial innovation can generally be better understood in terms of asset profiles associated with product-market challenges than in terms of R&D-intensity or ideal types of firms. Within this framework we may reformulate the theory of technological trajectories in terms of evolutionary dynamics of asset profiles linked to specific product-market challenges. Section 2 explains the content of the suggested categories of innovative assets. Section 3 discusses from a firm perspective the complex organizational differentiation and integration of the different innovative assets and patterns of couplings between them. In section 4 we indicate the great variation of innovative asset profiles across different product categories, and in section 5 we discuss the evolutionary dynamics of innovation profiles. Section 6 draws some general implications of this analytical approach for the innovation strategy of the firm.

2. Generic categories of innovative assets

Based on analyses of the SPRU Innovation Databank containing more than 4000 significant

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innovations Pavitt (1984, 1986) identifies four types of firm-based technological trajectories: The science-based, the scale-intensive, the specialized supplier, and the supplier-dominated trajectory. They represent different specifications of three basic parameters: 1) Sources of technical change (internal or external to the firm), 2) customer needs (price and volume versus performance characteristics), and 3) appropriability conditions (e.g. the effectiveness of patents, lead time, the experience curve or secrecy). The science-based trajectory is linked to strong internal R& D resources; customer needs may be either cost or differentiation oriented, and the means of appropriability tends to be based on technological strength. This trajectory is especially prevalent within the chemical and electronic industries. The scale-intensive trajectory is linked to strong internal process technological capabilities interacting with suppliers of process equipment; customer needs primarily focus on cost, and means of appropriability are related to process technology (especially experience curve and secrecy). This trajectory is particularly important in large firms in process industries like the foodstuff, glass and steel industries. The specialized supplier trajectory involves internal product application capabilities often in close interaction with customers whose needs are performance oriented. Means of appropriability relate to product technology, marketing and switching costs. This trajectory is typically seen in machinery and instrument industries where small firms play a significant role in innovation. Finally, the supplier-dominated pattern of technological change is based on investment in process equipment produced by suppliers. Customer needs tend to be cost dominated, and the appropriability regime is weak and primarily based on marketing assets. This trajectory is mostly seen in relatively small firms in traditional industries, e.g. textile, leather and shoe industries. This typology has provided a much more differentiated perspective on technological innovation than that accounted for by formal R & D and simple dichotomies like high-tech versus low-tech

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firms. However, the typology is based on empirical data on innovations rather than firms, and since technological change in firms and industries perhaps more often than not incorporates elements from more than one of the categories, we should be cautious about using the typology as an "ideal type" of firms. In this respect we agree with Coombs and Richards that the categories should be considered as innovative and technological "attributes" rather than categories of firms. They propose that firms may be moving within the "Pavitt-space" defined by three axes corresponding to the three of Pavitt's four categories (specialized supplier, scale-intensive, and science-intensive attributes). Moreover, Coombs and Richards pioneer the promising attempt to make use of these categories as a strategic variable on which the firm managers might operate. We shall argue, though, that the analytical (and normative) potential of the three Pavitt-categories is more fully exploited when interpreted and specified as generic types of innovative assets rather than as either types of firms and industries or "attributes" of technological change. When interpreted in terms of innovative assets, it becomes obvious that firms can possess more types of assets, in different constellations, and with changing constellations over time. Thus, the science-based trajectory reflects the science-based part of R& D assets which may also play a significant if not dominant role in other industries than chemical and electronic industries. The scale-intensive trajectory signifies process-innovative assets which dominate innovation profiles in some bulk oriented process industries but which are also important in most other industries. The specialized supplier trajectory reflects assets for product innovative application that are vital to competitive performance in most industries and not only within specialized capital goods industries. Thus, Pavitt's taxonomy can be translated into three distinct categories of innovative assets: Scientific research assets, process innovative assets, and product innovative application assets. The fourth category in Pavitt's scheme, the supplier-dominated trajectory is not ascribed any substantial innovative contribution, neither with

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respect to process technology which is largely bought from outside, nor with respect to the products which tend to be traditional standard products or minor variants. This may seem somewhat peculiar since the category is extracted from data on industrial innovations. Even if the innovations produced by supplier-dominated firms may be described in terms of the three innovative categories we suspect that at least product innovation is often better described in terms of a fourth category, aesthetic design. We believe that aesthetic design should be recognized as an innovative asset category on equal terms with the other categories. First of all because aesthetic design, like the more "classic" categories of technological assets, is often vital to the creation of competitive products. Secondly, aesthetic design is based on skills that are distinctly different from the skills contained in any of the other categories of innovative assets. In fact, many supplierdominated firms, though otherwise not technologically innovative, possess unique capabilities with respect to aesthetic design. Therefore we should not a priori put the label of non-innovativeness on all supplier-dominated firms 1. We suggest that the technological assets of firms are often more adequately characterized in terms of specific combinations of different asset types rather than in terms of R & D level or only one of the asset types. Moreover, we argue that technological trajectories are often better analyzed in terms of evolutionary dynamics of asset profiles in firms and industries than in terms either of one asset type (e.g. R or D, or one of Pavitt's firm-based trajectories) or a gradual change of innovative emphasis from product innovation to process innovation (cf. Abernathy and Utterback's model).

i This modification may apply to the process side as well: Even if all machinery and equipment are bought from external suppliers there may still be room for process-related innovative activities e.g. in relation to the specification of the equipment, the design of the production system, the h u m a n resource approach, and the role of quality control.

The asset types are analytical in nature, and in the practical world of technological innovation there are often no unambiguous borderlines between them. While the traditional functional conception of the firm considers the broad functional activity areas (i.e. general management, finance, manufacturing or marketing) that is generally required for productive operation, the innovative asset categories reflect the different functional activity areas that are potentially required to carry out the innovation process. In his "complementary asset" approach Teece (1986) points to the importance for the firm to have access to functional assets in order to secure commercial benefits from the innovation. In our "innovative asset" approach we point to the importance of having access to relevant innovative assets in order to secure the very production of technological innovation. Thus, there is a dynamic complementarity between our a priori pespective and Teece's ex post perspective on technological innovation. We use the term asset to signify both resources and capabilities. Resources are the "factors" which constitute the inputs into the productive services or value activities of the firm. Resources may be physical (i.e. technical equipment) or intangible (i.e. human resources with specific skills, patents or brands) or financial. Capabilities are capacities to set resources in motion and direct activities towards given strategic objectives. While resources may be accessed in the market-place (Barney), capabilities generally have to be accumulated within the firm (Dierickx and Cool). Capabilities for technological innovation do not exclusively comprise purely technical skills (knowledge, information) as stored in the heads of particular individuals, and technical recipes written down in documents, articles, and patents. As Nelson and Winter have argued, and more recently further developed, innovative capabilities are just as much based on experienced tacit knowledge as on articulable knowledge and recipes. Moreover, since teamwork characterizes technological efforts, managerial and organizational skills are at least as important to technological capabilities as are purely technical skills. Let us roughly characterize the innovative asset categories one by one.

J.F. Christensen/ Research Policy 24 (1995) 727-745 Scientific research assets. Following Kline and Rosenberg, there are two components of science that affect technological innovation: first, the stock of stored scientific knowledge, and second, new research, the results of which add to the total stock of knowledge. Scientific research can be divided into two sub-categories (Valentin): "pure" scientific research may be more or less specifically targeted but generally has to be undertaken by scientific (or scientifically trained) personnel within scientific communities. This end of scientific research represents either basic science or the link between basic and applied science. As many scholars have noted (e.g. Freeman, 1982; Kline and Rosenberg) technological innovation is rarely based exclusively on new research. The other sub-category comprises the processing and exploiting of existing scientific knowledge for specific technical tasks within the innovation process, and this activity mostly involves various types of interfaces between technologists and scientists (Gibbons and Johnston). This end of scientific research which Kline and Rosenberg term industrial research constitutes the bridge to process development and new product application and has to integrate scientific and technological competence. While most "pure" scientific research within industrial corporations is of a pre-competitive nature and located in central research labs, industrial research is mostly directly linked to product or process development projects. Process innovative assets. We conceive process technology in a broad sense referring to capabilities associated with both manufacturing technology (production equipment, its integration in a production system and the related work organization and management structures), inbound and outbound logistics, quality control, and plant layout. Thus, assets for innovative process development should not be restricted exclusively to capabilities for "hardware" process innovation, but also include the sometimes extremely important "systemic", organizational and managerial assets involved in developing the production system (e.g. just-in-time, lean production, total quality control). Especially in relatively labour-intensive production fields innovation in work organization

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and the broader plant governance may be more critical to quality performance, productivity and learning economies than innovation in process equipment (Adler and Cole). While the "hardware" and organizational assets in some cases are highly integrated, they may in others be de-coupled and associated with very different types of skills embodied in different teams. Likewise, the capabilities for process innovation may be more or less closely connected to the operating process capabilities. Thus, while the same personnel to varying degrees may be involved both in operations management and process innovation, the functions are distinctly different and in the short term strength in operating efficiency may not necessarily translate into capabilities for future process innovation. The two remaining categories of innovative assets are defined in terms of product development activities. Product innovative application assets are the resources and capabilities required to deal with product development activities (apart from possibly scientific research and aesthetic design): Product engineering, instrumentation and software development. This implies innovative application of "technological opportunities": searching, evaluating, selecting and synthesizing a plurality of artifacts (materials, semi-manufactures, components etc.) and bodies of knowledge (technical principles and heuristics) often linked to different technical fields. Such activities accumulate experience-based, firm-specific knowledge of product technology. Innovative application should not be considered synonymous with application of scientific accomplishments where application represents the routine (and subordinate) part of technological innovation. Innovative application constitutes a distinct innovative activity that may be more or less linked to other innovative as well as operating activities. In some areas product innovation may be exclusively based on either scientific research (e.g. in pharmaceuticals), or application engineering (e.g. in machinery), but often the one is dominant while the other (outside chemicals typically scientific research) has a supplementary role to play. Adding to this general outline of innovative

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product application, we propose an analytical distinction between technical and functional application. Technical application deals with "purely" technical issues in order to reduce technical uncertainty, which, to quote Freeman (1982, p. 149) "lies in the extent to which the innovation will satisfy a variety of technical criteria without increased cost of development, production or operation". Functional application is directed towards reducing functional uncertainty with respect to the user-interface (cf. Lotz) and involves development of knowledge concerning design and service characteristics that can match user-needs. Thus, while technical application deals with the technical features of the innovation from the engineering and economic perspective of the firm, functional application deals with the functionality from a user-perspective. This distinction corresponds to Rosenberg's (1992) distinction between learning by doing (technical application) and learning by using (functional application). The widespread user-producer interaction in product innovation that von Hippel has called attention to, seems especially prevalent where functional application has an important share of the total innovation process. Moreover, the cases of very strong lead-user involvement that von Hippel has both registered in his empirical studies and recommended as a vehicle for successful innovation is probably especially frequent where functional uncertainty combines with users with a strong professional interest in and competence with respect to the prospective product in question. The original Sony Walkman is an example of an innovation purely based on functional application since there was no technical uncertainty related to the innovation, only functional uncertainty and uncertainty regarding the size of the potential market (Morita). In many cases, however, the distinction between technical and functional application may in practice be difficult or impossible to operationalize with respect to specific work processes and the qualifications required, and primarily a question of degree of orientation. In the emerging wind turbine industry's search for a "best possible" systems design, functional and technical application fused into a combination of learning by doing and learning by

using (KarnCe). On the other hand, in cases where technical application is more easily distinguished from functional design, the former may be more closely related to industrial research, while the latter may be hard to separate from aesthetic design (see below). For example, the competitive niche position of the Bang & Olufsen TV and audio systems is to a large extent based on highpriority focus on industrial design which explicitly integrates functional and aesthetic parameters. In the innovative part of the furniture industry, some firms concentrate innovative efforts primarily on functional application, others on aesthetic design, and still others on design for manufacturability (technical product application strongly linked to process dynamics). Aesthetic design assets are generally ignored within the technological innovation literature, including the product innovation literature and is primarily studied within marketing oriented literature on consumer product development (e.g. (Alexander; Urban and Hauser; White). Aesthetic design of both product and packaging is mostly considered part of the marketing promotion as the possible brand name of the product. However, in addition to its marketing attributes, aesthetic design is also part of or has a close physical relationship to the product which makes it a bridge between technical and functional features of the product and the marketing strategy: "The surface design is the key link between the product and the idea of the product as expressed in the advertising and promotion" (White, p. 99). By trying to reflect market trends in taste and fashion, aesthetic design mostly involves interaction with marketing rather than direct interaction with users/customers. This may involve an exclusive focus on style, fashion, gimmicks (in toys and clothes) or even artistic expression (in artwares and handicraft products). But it may also involve an integrated industrial design approach where functional concerns (e.g. ergonomics and userfriendliness) and aesthetic concerns are sought harmonized (e.g. in industrial and household machinery, medico-technical equipment, or in furnitures and many other consumer durables). The recent work by Walsh and her colleagues has provided a strong argument for the increasing

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and often crucial role of both functional and aesthetic design in industrial innovation. While scientific research and aesthetic design are the two innovative assets that are the easiest to distinguish, they share one peculiar characteristic. Both tend to contain stronger elements of footloose or unbound creativity which gives rise to greater uncertainty and surprising outcomes than is mostly observed in process development and product application.

3. The organizational differentiation and integration of innovative assets Even if technological development is sometimes adequately described in terms of one of the categories, very often it is more adequately characterized as some form of a "hybrid" integrating two or more of the categories. This section discusses from the perspective of the firm the organizational differentiation and integration of the innovative assets and patterns of couplings between them. The accumulation of innovative assets as well as decisions concerning their funding, strategic orientation and management may take place at different organizational levels or in different functional or hierarchical interfaces. In large innovative corporations the generic assets have generally been subject to increasing division of labour, professionalization, cultural segregation and rivalry. This "balkanization" has underlined differences not only with respect to the professional functions and skills involved but also with respect to organizational culture, management traditions and relative prestige and power allocated within the company. The traditional central labs take care of long-term more or less sciencebased R & D and tend to be situated close to corporate headquarters. Process development takes place in the manufacturing department and may be located close to the relevant factor markets which may be far away from corporate center. Product development (innovative application) may be situated in separate departments within each division or strategic business unit of the company. Aesthetic design may be either ignored

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altogether, internalized as a distinct visible function or as a "silent" unconscious activity (Gorb and Dumas), or sub-contracted out to professional industrial designers or design bureaus. There is a tendency for large high-technology companies to attribute the highest level of recognition and prestige to the science-based innovative activities, much lower status to the technological and engineering accomplishments (Rosenberg, 1992, in Technology and the Enterprise in a historical perspective, p. 63), and the lowest status to aesthetic design, (Walsh et al., p.22 and chapter 4). Moreover, while corporate scientific research and product development are generally recognized as "innovative functions", the manufacturing side is often perceived as a domain for primarily routine-based process engineering, capital investment and production management rather than a domain for innovation. Likewise, aesthetic design is often considered to be more a marketing asset than a "real" innovative asset. Especially in large diversified corporations technology strategy has become highly complex especially concerning the responsibility between the corporate level and the business unit level for the accumulation of technological assets and the ability to exploit synergies (and avoid duplication of efforts) between decentralized R & D facilities (Ayal and Rothberg; Coombs and Richards, 1993; Pavitt, 1991; Rubenstein). In small manufacturing firms the division of labour is sometimes less developed. Thus, in small specialized engineering firms product development is often situated at the production facility and carried out by skilled production workers and engineers. Compared to large firms innovative small firms tend to focus innovative efforts on product application and aesthetic design. To the extent scientific research is required, it is more often of the "industrial research" category rather than the "pure research" category, and more frequently acquired from external R & D institutions than accumulated in-house. Finally, process development tends to be less innovative and more supplier-dominated. Innovation may of course be based exclusively on one type of innovative asset, for example "pure" process or product application innova-

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tion, but we suggest that most industrial innovation requires the combination of two or more asset types. The different innovative assets should therefore be considered potentially complementary and more or less interconnected. In terms of transaction cost economics we may speak of inter-asset specificity, that is, the degree to which innovative activities based on one asset category implies idiosyncratic activities based on other asset categories. We have already mentioned the complementary and often interactive relation between technical and functional application, and between functional application and aesthetic design. Other axes of complementarities that have attracted a great deal of strategic as well as academic attention are the product-process relation and the relationship between scientific research and product or process development. Product and process technology may be more or less interconnected. At the one extreme interasset specificity is low when 1) process and product can be dealt with independently by separate departments or even separate firms, or 2) a range of different products within the firm can be manufactured by the same production system without major adjustment. This means that product innovation has no necessary repercussion on the process technology or only require marginal adjustment which can be handled in a routine manner, or reversely, that process innovation takes place without major change in product characteristics. At the other extreme, product and process technology may be so strongly interdependent that any product innovative activities imply process innovative activities or reversely that process innovation is a precondition for the ability to produce competitive new products. We may distinguish between three variants: A processdominated variant where process activities constitute the fundamental prerequisite for product innovation, or even the all-dominating innovative activity within the product-market in question (e.g. in many industrial raw materials, or in traditional animal and vegetable production). A product-dominated variant occurs when radical product innovation necessitates the innovative buildup of a new manufacturing system that exclusively fits the new product. The most typical

variant, however, involves a more "balanced" type of interdependency, in which non-routine process-development (including investments in new equipment) is interlinked with product innovation activities in either a parallel or sequential process. Whether product and process innovation is strongly interlinked or not is, however, only to some extent a question of "objective" technical criteria. It is also a question of deliberate strategic choice. Thus, Mansfield has shown that US firms tend to be more oriented towards product innovation, while their Japanese counterparts have taken a much more process-oriented approach. Imai has recently suggested that Japanese firms have managed increasingly to "fuse" process improvement and product innovation into a "systemic innovation" approach. Such an approach does not, however, transcend the tensions and trade-offs between product and process development considerations; rather, it seeks to mediate these tensions from a systemic inter-asset perspective (Rosenberg, 1992 in Technology and the enterprise in a historical perspective). The same line of argument holds for the interface between scientific research and product or process development. Inter-asset specificity is low when the two activities can be carried out autonomously by different organizational units (departments, firms or research institutions). If the interface involves transfer of scientific knowledge from a research institution to a firm that does not posses scientific research capabilities, the transfer may only succeed if the science-input has the form of a well-specified blueprint (i.e. a patent) which can easily be transformed into the technological application process. When the science-input is less codified and its application highly complex the interface must involve intensive interaction and teamworking between the research institution and the firm, and such interaction is generally difficult when the firm-side does not possess at least some competence in scientific research. The organizational governance structure should reflect these inter-asset relations. Thus, the room for "balkanization" and externalization is greater when inter-asset specificity is low, while

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some kind of integrative organizational structure is needed when inter-asset specificity is high. However, to some extent inter-asset specificity may be the result of strategic choice rather than objective criteria.

4. Product-market

based

innovation

profiles

Having discussed the different asset categories and their organizational setting, we now turn to the question of how firms in their technological innovation efforts may integrate more asset categories into different asset constellations or innovation profiles. We shall only focus on technological innovation efforts that is directly linked to particular product markets and primarily carried out by

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strategic business units or product divisions. Thus, we do not take into consideration the development of generic technologies with broad application potentials across industries and product markets. Such development efforts primarily involve scientific research and technical application engineering and tend to be located in corporate R & D laboratories in large diversified high-technology corporations. Fig. 1 attempts to map typical innovation profiles across a wide spectrum of product categories. Four broadly defined categories are distinguished: materials, components, complex systems and consumer products, and each of these are illustrated by two or three subcategories. The map is intended to illustrate that the focal attention of innovative activities differs substantially

Genenc types o f innovative assets Product c~legone~ chemicals ~

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product application Techmcal Functional

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Components

motor

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i Intermediate chemicals such as agricultural chemicals, industrial commodity chemicals, pharmaceuticals, biotechnology based products (enzymes, growth hormones etc.) etc. z E.g. steel, aluminium, paper and pulp, glass, cement, and foodstuffs. 3 Basic semiconductor components such as integrated circuits and high-capacity memory chips. 4 Standardized components and devices such as pumps, compressors, filters, thermostats, valves, and gears. 5 Measurement instruments, specialized industrial machinery and medical equipment, application software, software services and integrated information technology systems. 6 E.g. shavers, refrigerators, televisions, video cassete recorders, compact disques. 7 Furnitures, shoes, clothes etc. Fig. 1. Profiles of innovative assets across product categories.

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across product-markets and that technological innovation more often than not involve a combination of generic activities. The map does not, however, pretend to be all-embracing with respect to product categories. Neither does it pretend to give a precise representation of all innovative activities within the particular product categories mentioned. In principle that can only be done at the level of the firm or the individual product family within a rather limited time frame. Still there tend to be quite robust patterns that dominate at more aggregate levels of industries and product categories. As we move down across the product categories the center of gravity tends to change from scientific research and process development towards product application and aesthetic design. In materials scientific research and process development tend to dominate technological innovation. In components and complex systems process development and product application (both technical and functional) usually play much more dominant roles in innovation than scientific research. In consumer products innovative efforts tend to center around product application and aesthetic design. However, we should be cautious about overgeneralization; the innovation profiles vary greatly, not only across but also within the product categories. In some product areas, like basic semiconductor devices or motor cars, innovative capabilities covering a broad range of the asset spectrum are required to stay in business over the longer run. In other areas, like specialized machinery or arts and craft, a more narrow profile may be sufficient. In some areas there are high levels of inter-asset specificity (or strong coupling), in others there are not. In some areas there are significant scale economies linked to innovative assets, while in others there are not. Generally it can be assumed that large firms dominate technological innovation in product areas where a broad range of assets are needed, where the coupling between assets is strong, complex and highly specific, and where one or more of these assets involve significant economies of scale. In contrast, small firms may gain strong positions in product areas where technological

innovation involves only one innovative asset or a narrow range of assets with low levels of inter-asset specificity, and while there are no significant economies of scale, learning economies may be strong. Let us briefly comment on the product categories in the figure to demonstrate the wide span of possible innovation profiles. Materials. Innovative efforts in chemicals tend to be dominated by science-based R & D and process development (Landau and Rosenberg). This is particularly true with respect to bulk chemicals, while other chemical products may show somewhat different patterns: in pharmaceuticals innovation is primarily science-based, and outside the biotechnology domain production processes tend to be comparatively simple. Innovation in cosmetics may combine science-based R & D or process development with aesthetic design related to packaging. Compared to bulk chemicals, innovation in other industrial bulk markets like steel, glass, paper, pulp or cement is overwhelmingly process-based, while science plays a limited role. Components. To be competitive within the basic end of the semiconductor industry requires huge investments in both scientific research, process development and application design, and only a small and declining group of very large companies have managed to keep in touch with the cutting edge of world technology (Hobday 1991; Malerba; Okimoto et al.). In short, technological innovation is characterized by both scale economies and inter-asset specificity. Other types of standardized industrial components and devices such as pumps, compressors, thermostats etc. are less (or not at all) sciencebased; they primarily require particular capabilities in process development, product application and the integration of both. Complex systems. Complex systemic innovations always require strong emphasis on application, but within some product areas like the motor car industry long-term competitive power also requires major process capabilities (both with respect to the technical system, the work organization, and the broader plant governance), aesthetic (industrial) design capabilities, and substantial managerial skills to assure an integrative ap-

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proach to product and process development (Adler and Cole; Bhaskar; Graves; Womack et al.). In specialized capital equipment (instruments and machinery) innovation tends for long periods to be dominated by incremental product innovation based on technical and functional application, while scientific research, internal process innovation and aesthetic design mostly play minor roles. Scientific instruments may have a somewhat deviating profile that combine technical application and scientific research. This may involve intensive user-producer interaction in which the user provides the scientific capability and the producer provides the application (instrumentation) capability (Lotz; Rosenberg, 1992, Research Policy). Consumer products. Innovation in consumer product areas mostly require functional application and aesthetic design capabilities. This is strongly the case in furnitures, shoes, toys, clothes, arts and crafts. In many of these areas product design and manufacturing have become more or less decoupled, and frequently innovative activities exclusively relate to the former, while the latter may be sub-contracted or dealt with internally as a non-innovative, supplier-dominated function. The scale-intensive food industry tends, however, to be comparatively more concerned with the manufacturing side than with the product side, which sometimes is reduced to packaging design activities. Some parts of the food industry have innovative profiles similar to industrial bulk materials (strongly focused on process oriented assets), whereas others are more akin to sciencebased chemical or biotechnology products. In the modern consumer durables industry mass production prevails, and scale-intensive process development tend to be at least as important as product innovative activities. While U.S. firms in many areas pioneered in basic product innovation during the 1950's and 1960's, Japanese firms later came to be world-dominating within these markets through their strong focus on and innovative approach to the manufacturing processes combined with an incremental approach to product innovation (Rosenbloom and Abernathy). As many of these product groups have matured (e.g.

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colour televisions, audio products and video cassette recorders) several innovative features have become similar to those seen in the automobile industry: Increasing attention to the manufacturing side and rapid introduction of new models primarily based on aesthetic design parameters and marginal functional improvement. But the "mature" consumer electronic products have, compared to automobiles, been subject to quite radical technical change through the application of integrated circuits, signal processing and optical recording technologies (Cawson and Holmes). Furthermore, these new technologies form the basis of still new categories of consumer electronic products like the digital audio tape. This tour de force through different product market areas has shown that innovation varies greatly with respect to assets involved. Technological innovation should not primarily be identified with the "traditional" R&D-intensive innovations based on scientific research and technical application. Admittedly, such innovative efforts constitute the critical elements in promoting new generic technologies, but the R & D-conception of technological innovation tends to ignore or grossly underestimate innovative dynamics that are primarily based on process development 2, functional product application and aesthetic design. This furthermore tends to promote the misconception that "low technology" industries (as defined in terms of R&D-ratios) are necessarily also "low innovation" industries.

5. The dynamics of innovation profiles Most product markets are subject to long periods of incremental technological development succeeded by phases of turbulence and discontinuity (Anderson and Tushman; Foster; Olleros). In this section we shall interpret the models of technological trajectories in terms of dynamic

2While process developmentactivitiesare generallyrather poorly reflected in the R&D accounts, this may especiallybe so with respect to the more organizationalelementsin process development.

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"oscillation" of the asset profiles within particular product-markets at different stages of their life cycles. Changes in asset profiles come about due to new technological opportunities, contingencies specific to the product market or industry and the "creative destruction" of pioneering firms. Technological trajectories tend to be strongly path-dependent and cumulative in nature, but that does not necessarily imply that innovation profiles do not (or should not) change. But changes are more "creeping" in incremental phases than in turbulent phases where more radical regroupings in asset profiles might occur. Moreover, incremental change concerning the "core technologies" based on science and technical application may sometimes be combined with, or rather give room for, more radical changes with respect to work organization, plant governance, functional application and aesthetic design. Two models have dominated reflections on the pattern of technological evolution: The linear science-push conception and Abernathy and Utterback's product-process cycle.

5.1. Science-technology transformation dynamics The linear science-push model is linked to the neo-Schumpeterian hypothesis that science-based breakthrough inventions/innovations may lead to the emergence of new industries, but gradually, as the industries mature, a more technology-based body of knowledge become the central lever for further process and product innovation. The early development of the radio industry represents a classic case of such a "science-push" development (Maclaurin). A contemporary case is the semiconductor industry which is at the core of the ongoing microelectronic revolution and which has been among the fastest growing industries during the last decades. It has been moving from an initially strongly science-based position into a much stronger dependency on technology-based activities directed towards both process and product application (Dosi; Malerba), without, though, losing its links to science. Eventually, the industry

has become divided into two segments: The one is the hard-core segment of basic components and systems marked by large and increasing investments in both science-based and application oriented R& D and manufacturing capabilities; the other is the "softer" segment of systems applications marked by technical and functional application based on interactive relations with customers (Malerba). Hobday (1990) has specified how the semiconductor industry - after having undergone the initial science-technology transformation - has proliferated into two different trajectories, the "standard commodity chip" trajectory (e.g. dynamic and static random access memories, DRAMs and SRAMs) and the later coming "design intensive" (or ASIC) trajectory. In the former integrated circuit design and fabrication technology are closely interlinked, and the user sphere is dislocated from both design and fabrication. "Prospective new manufacturers and designers of semiconductors face crippling financial and technological barriers to entry. With each successive generation of chips, from small scale integration (SSI) through to very large scale integration (VLSI), entry barriers became more formidable" (Hobday, 1990, p.575). In the new "design-intensive" trajectory progress in design technology is enabling a gradual decoupling of chip design from fabrication technology, and the increasing design market has given rise to a wave of new firms specializing in chip design, training, consultancy, etc. Not all initially science-based industries undergo such a transformation into a more technology-based development pattern. Within the chemical industry somewhat deviating patterns can be found. Product innovation has remained strongly science-based, while the gradual development of a chemical engineering competence has provided an increasingly technology-based complementary capacity for process development and innovation (Freeman, 1982; Landau and Rosenberg). To this asset profile is sometimes added supplementary asset types. In parts of the pharmaceutical industry, for instance, scientific research is generally dominating innovative efforts, but in many product lines scientific re-

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search has increasingly become supplemented with product application activities otherwise alien to chemical industries. This development has been explained by the increasing focus on alternative delivery systems of the drugs in question. For example, within insulin for diabetes care, the globally leading companies (Novo-Nordisk, Eli Lilly and Hoechst) all possess the science-base and manufacturing capability for competitive production of high-quality human insulin. During the last years the NOVO-pen for insulin delivery has given Novo-Nordisk a competitive advantage on world markets. Thus we see a science-based company in a predominantly science-based product market capturing a competitive edge by introducing a superior application (as well as aesthetic) design more similar to product innovation in components or plastic products.

5.2. Product-process cycle dynamics The Abernathy/Utterback cycle implies a gradual change from diverse product innovation to scale-intensive process innovation as the industry moves into its mature phase, and eventually an overall decline in innovative activities. Even within the proto-cases of the Abernathy/Utterback cycle, automobiles and electronic consumer durables, the actual innovative development has shown a more complex pattern especially in the mature phase, allowing for "a multiplicity of design changes, fashions, styles, redesigns and variations in the designs within a product range aimed at different market segments, rather than "undifferentiated standard products .... (Walsh et al., p.28). This has been made possible by the flexibilization of the manufacturing systems during the last decades. Thus, it seems to be a more general tendency for consumer products marked by dominant design and stabilized product technology that the innovative focus change not only in the direction - - as asserted by Abernathy and Utterback - - of process development, but also aesthetic design and functional application design associated with market segmentation come to play an increasingly important role. In the 1970s Japanese automobile producers initiated a virtual innovative renaissance. The so-

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called "lean production system" based on a new combination of technology, work organization and management structures outperformed the traditional Fordist mass-production system in America and Europe in terms of both productivity and quality (Womack et al.). The Japanese producers, however, did not stop at process innovation. As American and European firms tried to catch up in productivity and quality, Japanese firms invested heavily in product innovation (Graves). Lead times for the development of new models were drastically reduced and a wider range of models were launched to create new market niches. Functional and aesthetic design grew in importance as the duration of competitive advantage from hard-core technological innovation were reduced. "For example, radical innovations such as turbo-charges, anti-locking brakes and four-wheel drive systems brought relatively short-lived monopoly rents. Even where patents are taken out, competitors are increasingly quick to adopt new technological advances. This means that styling and design capabilities are major factors stimulating product differentiation and maintaining competitive advantage" (Graves, p. 271). But design activities are strongly interwoven with technological changes of a more basic nature. The rapid model replacement cycles have made it possible for the Japanese producers incrementally to develop and introduce new technologies that eventually turn out to be quite radical, for example the increasing use of plastics and composite materials (Graves). While the simple science-push and Abernathy-Utterback models provide basic insights in the course of technological evolution in certain industries, they do not grasp the whole truth. In fact, a rigid use of the models may imply that analysts or managers fail to see important proliferation and supplementary mechanisms. These tend to become critical after the "great transformation" processes have taken place, that is, the transformation from a science-dominated to a technology-dominated type of dynamics in the science-push model, and the transformation from product-dominated to process-dominated innovative efforts in the Abernathy-Utterback model.

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5.3. Other innovation profile dynamics In addition, the technological evolution of many other product areas cannot be conceived in terms of either science-technology or productprocess transformation dynamics, but tend to keep a quasi-permanent innovative focus on product application (e.g. many specialized capital goods areas), on process development (e.g. many industrial raw materials) or on aesthetic design (e.g. clothing, furnitures, arts and crafts), possibly with rare digressions into supplementary asset areas due to specific problem-solving tasks. In a recent study on industrial innovation in small-scale Danish manufacturing industry that was conducted by Finn Valentin and the present author (Christensen; Christensen et al.; Valentin) we found that the majority of firms, especially within capital goods, continuously focused their innovative attention on product application. Across product generations there was often some oscillation between technical application and functional application, sometimes supplemented by externally contracted science-based analyses and tests, and aesthetic design. Long periods of incremental product innovation may be broken by more radical product changes (perhaps but not necessarily science-based). The life cycle of the product (or product generation) may or may not follow the normal S-curve. Only rarely, however, we saw that the "growth phase" implied a more radical transformation within the firm from small scale production and primary focus on product application to mass production and primary focus on process development. Generally problems and bottlenecks associated with existing technological designs and procedures constitute what Rosenberg (1969) terms "focusing devices" or "technological imperatives" that focus the direction of the innovative search process. From an asset profile perspective we may argue that there exists an inherent tendency at the firm level to favour innovative search within the previously dominating generic asset(s), and thus for focusing devices to be biased towards intra-asset problem solving. This can especially be assumed to be the case where small companies with "narrow" innovative profiles prevail, or where inter-asset linkages are technically complex

and not easily institutionalized. In his earlier work Rosenberg (1963, 1969) analyzed how such focusing dynamics operated with reference to mechanical engineering technologies (especially product application) in the early history of the American machine tool industry. There are remarkable similarities between the technological dynamics of the nineteenth century American machine tool industry, and the dynamics characterizing Danish small-scale capital goods industry at the end of the twentieth century: The continuous strong focus on innovative product application and the way focusing devices are often mediated by userproducer interaction. However, focusing devices also operate across generic assets. We have already referred to the science-technology and the product-process transformation mechanisms in which the maturing of the accomplishments in one asset area sets the agenda for development in another asset area. Rosenberg has in several works and especially in a seminal paper co-written with Kline criticized the widespread tendency to over-generalize the validity of the linear science-push conception of technological innovation and argued that a "reverse science-push" mechanism is probably the more common form of science-technology interplay. This means that application activities, as the room for improvements are exhausted, may become focusing device for science-based searching that may lead to new techniques to circumvent the limits to progress. "The natural trajectory of certain specific technological improvements serves to identify and to define the limits to further improvement which, in turn, serves as a focusing device for subsequent scientific research" (Rosenberg, 1992, in Technology and the enterprise in a historical perspective, p. 82). To this may be added that the relevant science base must possess a certain capacity for empirical analysis and prediction in order to be able to respond innovatively to demands from the technology side. 6. Implications for innovation strategy The asset profile framework presented in this paper is intended to contribute to strengthen the analytical coherence of the extremely heteroge-

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neous empirical research on technological change and to create a more differentiated and adequate conception of assets for technological innovation than the one provided by the formal R & D rubric. In addition, the framework may contribute to create a bridge between the analysis of technological innovation and the recent efforts to formulate a research platform for a resource-based theory of the firm (Barney; Conner; Dierickx and Cool; Grant; Rumelt, 1984 and 1991; Teece, 1986; Wernerfelt; Winter). These efforts, originally pioneered by Edith Penrose have explicitly addressed what has remained the "black box" of the conventional economic "theory of the firm", namely the resources and capabilities that constitute the quasi-stable basis of the firm's economic performance and direction of change. This resource-based research perspective has become a "focusing device" for some of the more strategy oriented industrial economists to change the primary focus of research from the contextualities of the firm, i.e. the structural features at the industry level, to the internal resources and capabilities of the firm. For the student of technological change this means that a more richly faceted conceptual framework has to replace the one-dimensional R & D accounts which is better fit for administrative and statistical convenience than for its capacity to grasp the multi-dimensional resource and capability base for technological innovation. A differentiated asset taxonomy can be a step towards both more coherent and empirically rich descriptions and analyses of capabilities for technological innovation. This may again provide new perspectives and insights to the innovation or technology strategy of the firm. During the last decade the literature on innovation strategy has exploded and several approaches have been proposed: The "posture-approach" focuses on the timing and positioning of product innovation in the market place, and firms may pursue a spectrum of strategies from a first-to-the-market or offensive strategy at the one end, to an imitative strategy at the other (see for example Ansoff and Stewart; Freeman, 1982, chapter 8; Maidique and Patch). However, this approach tends to use the one-dimensional R & D yardstick to discriminate be-

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tween the different strategies, sometimes though differentiating loosely between R-dominated (offensive) and D-dominated (defensive) R & D efforts. Thus, firms are positioned as technological leaders if they pursue "aggressive" and highvolume R&D-investments (possibly with some R-bias), or as followers or imitators due to no or limited R& D resources (possibly with some D bias) plus cost advantages based on complementary assets. But there is rarely one single technological road that all firms within a given product market have to follow and that is exclusively build on abundant R & D resources in general terms. The asset profile framework can provide a more differentiated perspective allowing firms to be pioneers within one or two asset areas, and followers in other areas. Or competing firms may pioneer different technological paths within the same asset area or constellation of assets. This has two important implications. First, the question of first-mover advantages becomes more complex and therefore more difficult to identify in an unambiguous way. Secondly, the scope for innovation strategy becomes richer than suggested in the R & D - f o c u s e d posture framework, since innovation strategy becomes a question of positioning with respect not to R & D efforts in general but to the various generic innovative assets (and sub-assets) and the linkages between them. Within the broader framework of the "competitive strategy" approach Michael Porter has also elaborated on the specific role of technology strategy (chapter 5). His general position seems to be that technology strategy should be subordinated higher-level competitive strategy within given product markets or industries. Technology strategy is then primarily discussed with respect to two problematiques: a first- versus late-mover problematique and a product versus process technology problematique. While his discussion of the former is in line with the "posture-approach", Porter transcends the traditional R & Dreductionist perspective by distinguishing between product and process technology and the roles each of them can play in supporting the general competitive strategy of the firm. This is a

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step towards applying an asset profile perspective on technology strategy, but while Porter primarily discusses the various potential functions of product and process technology, he does not distinguish between innovative and routine or operating assets, and he misses the analysis of the resource and capability dimension of the technologies. Moreover, he leaves other assets than product and process oriented assets, i.e. sciencebased and aesthetic design assets unregarded. A third approach to technology strategy may be termed the "technology base" approach. It focuses on the internal building and commercial exploitation of technological capabilities defined in terms of "strategic technological areas", "core skills" or "technology-product-portfolios" (Ergas; Frohman; Grant; Link and Tassey; Mitchell; Prahalad and Hameb; Winter). Core skills constitute the basis of competitive power, but the building of competitive core skills is a long-term and mostly cumulative and consistent process, the course of which cannot easily be changed. The productmarket orientation of the firm is perceived at least partly as springing from the technology base of the firm rather than vice versa (see especially (Link and Tassey; Prahalad and Hamel), that is, technology-related diversification is ascribed a decisive form of strategic renewal and a test of the long-term viability of the technology base. This approach to technology strategy may be seen as the technology oriented part of the general resource-based research programme that has emerged during the last decade or so. Mostly, however, the "technology base" or the "core skills" of the firm is only discussed at a principal level, perhaps added some loosely sketched examples that are vaguely specified in terms of technical disciplines. The innovative asset framework suggested in this paper maintains that there are generic categories of innovative assets that differ with respect to type of knowledge and competence, functional orientation and organizational locus, and that cannot be reduced to a common denominator called "technical disciplines". Sometimes the scientific research asset, the process innovative asset and the product application asset of a firm may be quite precisely specified in terms of the techni-

cal disciplines that they comprise, but probably more often than not the pattern is highly complex and characterized more by idiosyncratic inter-disciplinary constellations than by an additive constellation of separate disciplines. Moreover, the taxonomy of technical disciplines is rarely stable and unambiguously defined but is constantly on the move especially with respect to the forefronts of technological searching which often reflect efforts of cross-fertilizing between so far separated technologies or research disciplines (Kodama; Rosenberg, 1992). One way to come around this problem of conceptual flux is to link the technical categories to their strategic relevance. Mitchell proposes the concept of "strategic technical areas" that are not only defined in technical terms, but also specified according to their functions, product applications and market orientation, in order for their strategic relevance to be properly addressed by corporate management. From the perspective of asset profiles and innovation strategy, we may argue that technical capabilities should be related not only to products and markets but to the relevant innovative asset or asset constellation to which they may contribute. This makes it possible to uncover the broader innovative scope of technological capabilities. In general, the asset profile perspective implies that innovation strategy should recognize the potential importance of all the innovative asset types and different options for their integration into activity profiles. This raises several important questions that require further investigation. One central issue relates to the distribution of the total firm-resources for technological development between shorter term product or process development projects as compared to the development of a broader base of technological competence that may be decisive both for assuring long-term competitive advantages within existing product families and for successful entry into related product markets (Ergas; Link and Tassey; Teece, 1982). While the short-term projects are normally based primarily on a specific constellation of process development, technical and functional application, and aesthetic design, possibly

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added some narrowly focused scientific research tasks, the long-term build-up and maintaining of a broader technology base generally involve a science-based R & D involvement for which mostly large firms possess the required resources. Other relevant questions that require investigation from an asset profile perspective relate to the sourcing of assets, the appropriability conditions of innovative assets, and the organization of interaction between different asset types. Moreover, the analysis of innovative assets has to be linked to the analysis of complementary assets as proposed by Teece (1986) to constitute a more comprehensive framework for analyzing innovation strategies. Even if the precise character of successful technological trajectories can only be outlined in the hindsight, innovative firms have to act as if they knew the course to come. This necessarily involves a continuous recognition of and preparedness for possible "profile oscillations" or even more radical profile changes as product markets move into new phases and new technological opportunities show up. However, technological innovation always involves a substantial risk of failing due to missing the "profile-fit": By missing the right focus and configuration of internal capabilities, for example underestimating the need for a good aesthetic design, or for functional application in a dialogue with lead-users, or for dealing with the tensions between product application and process development. By focusing all attention on internal activities and ignoring the potential benefits from external sources. By focusing exclusively on the innovation process and neglecting the complementary assets required to commercially exploit the innovation. By sticking to the "same procedure as last year", that is, resting on the laurels of previous successes (Maidique and Zirger) and not recognizing that technological opportunities and market requirements change and make reconfiguration of asset profiles necessary.

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