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PurposeThe purpose of this paper is to suggest that the importance of culture on the innovation of technological processes and products has not received sufficient attention from researchers. The paper offers a framework and some categories for investigating the affects of culture on technological innovation.Design/methodology/approachThe data and ideas that inform this paper come primarily from interviews carried out as a part of case studies of the innovation of 13 technology products and processes centered in China and other five countries.FindingsInnovation success in the various technology sectors differs among countries including China in part because of different national cultures – the norms and values that guide and constrain both the individuals in societies and the societies at large.Research limitations/implicationsThe values the paper assigns to eight cultural characteristics for China and other five countries are based on qualitative interviews and more scientific survey is needed.Practical implicationsIncreased understanding of how different national cultures influence innovation will give managers and policy makers improved opportunities to formulate policies and management practices that can overcome cultural barriers and take advantage of cultural assets.Originality/valueThe paper offers a starting point for the investigation of the impact of national cultures on technological innovation in different technology sectors.

AMONG DESIGN PROFESSIONALS, there is certainly a consensus that the US should have a clearer and more aggressive design policy. Taking on the role of devil's advocate, Don Kash explores problems inherent in such well-intended aspirations. In particular, he comments on the difficulties related to defining the multiple roles of design in business activities and, against a background of general policy-making issues, explains how the fragmented nature of design policy goals and constituencies makes for an elusive—and perhaps undefinable—policy target.

The evolution of the fuel injection technology for diesel engines initiated and repeatedly innovated since 1922 by Robert Bosch GmbH of Stuttgart, Germany, is used to illustrate the management and policy adaptations necessary to carry out repeated innovations as technologies move through different innovation patterns — transformation (first-of-a-kind), transition (major redesign) and normal (incremental) — and as they evolve from simple to complex. Special attention is given to the role of cooperative alliances in the innovation, knowledge management and decision-making associated with the development of the diesel injection technology. As the technology has become ever more complex, the Bosch innovation activities have manifested a process of co-evolution between a continuously adapting network of supplier and user organisations and diesel injection technology that has occurred as part of an ever-changing environment (e.g., market, public policy).

This paper investigates India's exceptional development pattern, specifically the major importance of information technology services (ITS), and compares it with China's development pattern. Both countries want to develop capabilities for carrying out the innovation of technologies that compete at the state-of-the-art in the world market. The paper posits that technological/economic success in the contemporary world market requires the ability to innovate complex technologies and complex technology-related services. The share of trade represented by complex technologies is compared with the “high-tech” share. The trading patterns of the two countries are compared using United Nations data. Two case studies of Indian ITS companies are then compared with two case studies of Chinese manufacturing companies. Historical and cultural differences appear to explain some of the differences in the development patterns of the companies located in the two countries.

Technological innovation is increasingly concerned with complex products and processes. The trend toward greater complexity is suggested by the fact that in 1970 complex technologies comprised 43% of the 30 most valuable world goods exports, but by 1996 complex technologies represented 84% of those goods. These technologies are innovated by self-organizing networks. Networks are those linked organizations that create, acquire, and integrate the diverse knowledge and skills required to innovate complex technologies. Accessing tacit knowledge (i.e., experienced-based, unwritten know-how) and integrating it with codified knowledge is a particular strength of many networks. Self-organization refers to the capacity networks have for reordering themselves into more complex structures (e.g., replacing individual managers with management teams), and for using more complex processes (e.g., evolving strategies) without centralized, detailed managerial guidance. Case studies of the innovation pathways traced by six complex technologies indicate that innovations can be grouped into three quite distinct patterns. Transformation: the launching of a new trajectory by a new coevolving network and technology. Normal: the coevolution of an established network and technology along an established trajectory. Transition: the coevolutionary movement to a new trajectory by an established network and technology. Policy makers and managers face the greatest challenge during those periods of movement from one innovation trajectory to another. These are periods of turbulence; they are the embodiment of Schumpeter's “gales of creative destruction.” This paper investigates how, in six case studies, core capabilities, complementary assets, organizational learning, path dependencies, and the selection environment varied among the innovation patterns. The paper builds on work reported in a recent book by the authors entitled: The Complexity Challenge: Technological Innovation for the 21st Century, Pinter, London, 1999.

This article investigates three factors that affect the path dependence of complex technologies and the organizational networks that carry out their innovation: culture and institutions, organizational learning, and technology design. Evidence from the rapidly growing body of literature on path dependence and from six case studies of complex technologies (i.e. turbine blades, cardio-imaging technology, audio compact discs (CD's), radiation therapy technology, micro-floppy disks, and microprocessors) is used to investigate the impact of culture, organizational learning, and technology design on path dependence. Three innovation patterns associated with co-evolution of technologies and organizational networks provide the framework used to structure the investigation.

The changes brought about by the Patent Act of 1952 were needed to adjust the administration of patents to the reality that invention and innovation now primarily result from investment rather than from individual creativity. An unintended result of these changes has been to make it difficult for firms in most non-chemical technologies and especially smaller firms involved in the innovation of complex technologies to obtain the protection they need. Also, denying firms in complex technologies the power to operate patent pools has forced them to multiply their patents as bargaining chips: these large numbers of interlocking patents effectively bar entry by newcomers to complex technologies, thus reducing competition. Reforms are possible and they could enable the patent system to fulfill its proper function in relation to complex technologies and transform the economic climate for small-firm innovation, replacing the patent system's present emphasis on serving large firms in simple technologies. Copyright , Beech Tree Publishing.

Self-organizing networks have become the dominant innovators of complex technologies. This paper presents a framework that offers insight into the three distinctive patterns of innovation that are evident in the evolution of six technologies. It is at those points that networks must change from one pattern to another and that major adaptations in company strategies and public policy are required. Four indicators of pattern changes are discussed. Effective strategies and policy would benefit from the development of a different set of concepts and the science of complexity offers some of those concepts.

Technology leaders need to view uncertainty and instability as the expected condition, failure as essential to learning, and rapid adaptability as the new bottom line. ovERVIEW: Participation in self-organizing networks of firms that exist to carry out the repeated innovation of complex technologies is becoming increasingly important. To achieve and maintain leadership, these networks must achieve a mutually reinforcing fit among organizational core capabilities, complementary assets, learning, and linkages to the external environment. Three distinct patterns have been identified within which these networks operate: transformational, normal and transitional. Each presents its own management opportunities and requirements, but all call for a premium to be placed on exploratory, experimental approaches to decision making. The economic success of companies today increasingly depends on participation in complex self organizing networks that innovate complex technologies. We define complex technologies as those products or processes that cannot be understood in full detail by an individual expert sufficiently to communicate the details across time and space. Aircraft and telecommunications equipment are common examples of complex product technologies; "lean" or "agile" production systems are examples of complex process technologies. Complex networks are those linked organizations (e.g., firms, universities and government agencies) that create, acquire and integrate the diverse knowledge and skills, both tacit and explicit, required to innovate complex technologies. Strategic alliances, joint ventures and other types of more informal collaboration are examples of complex networks. Self organization refers to the capacity these networks have for reordering themselves into more complex structures and for using more complex processes without centralized, detailed management guidance. The trend toward complexity is suggested by the fact that in 1970 complex technologies comprised 43 percent of the 30 most valuable world exports of goods, but by 1996 complex technologies represented 84 percent of those goods. The innovation of complex technologies is often characterized by rapid, highly disruptive, discontinuous change. We described a number of indicators of these disruptions, and provided some preliminary "rules of thumb" for managers confronting them, in a recent issue of Research Technology Management (1 ). Here we want to go a step further by outlining three distinct innovation patterns and characterizing the opportunities and challenges each poses for managers. We begin with two insights from the study of complex technological innovation. First, managers must be deeply immersed in any complex innovation process, but must avoid seeking to control it. The reason for this is that managers operate without sufficient understanding of the diverse knowledge needed to direct successful innovation in detail. Moreover, complex network organizations often react to direction in nonlinear ways-they may generate new adaptations in the form of novel organizational properties or characteristics (e.g., new ways of interaction among work groups) that are "emergent" and thus difficult to predict or guide. Rather, managers must try to affect the context of innovation-to establish and modify the direction and the boundaries within which effective, improvised and self organized solutions can evolve. Instead of trying to directly shape a strategy or decision, managers must shape the organizational environment within which these choices emerge (2). Second, the modification of the context of organizational choices is heavily dependent on the language that managers use. We believe a new terminology is one of the major contributions that the study of complexity makes to the management of complex organizations and their technologies. Terms like "self organization" or "emergence" gives voice and substance to the creative, dynamic, non-linear, and evolutionary work that is already typical of much management and is likely to become the focus of many more managers in the future (3). …

Deep immersion, without micromanagement, in the continuous process of innovation will help you to adapt or lead the inevitable trajectory changes. OVERVIEW: As technologies become more complex, organizational networks become the keys to successful innovation. During those periods when incremental innovation is the route to success, managers need to take a hands-off approach; they need to let the process of network self-organization proceed. The critical role for the manager is to monitor the possibility of major technology changes by looking for such indicators as: technical community disintegration, foreign invaders, new technology waves, and climate changes. When major technology changes are approaching or occurring, managers need to make sure that major organizational adaptations take place. Those adaptations are essential to acquisition and creation of the knowledge needed for successful innovation. The greatest commercial success in the next century will go to those who lead in the repeated innovation of complex technologies such as automobiles, aircraft and telecommunications (1). Successful innovation of complex technologies requires equally complex networks of firms and other organizations, often including universities and government agencies (2). Only complex networks can generate and synthesize knowledge of sufficient diversity to create complex technological processes and products. These complex networks coevolve with their technologies (3). Networks pose unique challenges for managers (4). During the most profitable phases of the evolution of complex technologies, when they are undergoing repeated incremental innovations, successful managers stay out of the way. The manager's primary role during these phases is to monitor the process of network self-organization that takes place as incremental innovations are developed. Self-organization refers to the capacity of networks to reorder themselves and their knowledge into more complicated structures and processes without centralized managerial guidance (5). Constant monitoring of the process of self-organization is necessary for detecting disruptions in the "normal" process of incremental innovation. These disruptions or discontinuities demand greater managerial participation. But what aspects of the self-organization process should managers monitor? What are the indicators of emerging discontinuities? Providing preliminary answers to these questions is the purpose of this article. In searching for insight into the management of complex networks, we utilized two bodies of literature-- complexity science and evolutionary economics (6), and we carried out detailed case studies of the innovation of six complex technologies (7). The innovation patterns evident in the cases involved the incremental movement of networks of diverse organizations toward increased complexity and away from detailed understanding and management by individuals. In every case, however, this evolution was characterized by periods of discontinuous and highly disruptive change. The innovation of the Varian Corporation's "Clinac" radiation therapy cancer treatment technology is typical (see next page). For almost two decades, an established network structured around Varian's core capabilities in radiation technology carried out incremental hardware innovations (points 3 through 6 on the trajectory, next page) that provided medical practitioners ever-more precise control of the energy beam used to treat cancer. However, in the 1980s, the Clinac network required a major restructuring because of the saturation of the existing market and the opportunities provided by computer capabilities. Restructuring the network involved a trial-and-error process that produced great stress for those involved. The integration of a new computer-based software core capability into the physics-based network required an organizational synthesis of very different cultures (e. …

Technology is becoming ever more complex and this has important implications for national technology policies. A major US policy challenge is how to formulate and implement policies effectively when innovation cannot be understood. Using a review of the complexity-science and evolutionary-economics literature, and six case studies of evolving complex technologies, this paper concludes that there are five common patterns which policy must recognize: seamlessness, diversity continuous change, lack of understanding, and the predictability of incremental innovation steps. The self-conscious development of a US national innovation system as a policy priority is important, because technology policies must cover all elements of the innovation process holistically. Copyright , Beech Tree Publishing.

There has been a growing divergence between the reality of U.S. society and the nation's conceptual model of governance and this pattern will likely continue into the 21st century. The divergence is being driven by a rapidly changing reality which has at its core the continuous innovation of complex technologies through a process of synthesis. The nation's analytic model of governance is increasingly unresponsive to the synthetic reality with one result being increased social stress. This article investigates the reasons for the divergence and future governance needs.

A new technological imperative which punishes individualism and conflict and rewards community and cooperation is impacting the world. Lack of a conceptual framework which allows understanding of that imperative is a barrier to technology based economic policy in the US. A key component of the needed conceptual framework will be the role of community in the continuous innovation of complex technologies. Three characteristics of complex innovation are integral to the conceptual framework needed to inform technologically based economic policy: complexity, networks, and collaboration. These characteristics both require and contribute to community

We have crossed an historical Rubicon into an era in which the capacity to innovate increasingly complex technologies has created a set of opportunities and problems that make our reductionist and simplistic linear models of policy and governance obsolete. America must base its technology policy on a synthesis of both international experience and new conceptualizations. The most important recent experience with successful technological innovation has taken place in Asia, whereas the most rapid conceptual advances appear to be occurring in Europe and the U.S. Complexity is the key factor in both.

President Clinton has given commercial technology policy a priority position amid signs that there is growing consensus in America that such policy is needed. However, while there is growing consensus on the need, there is widespread disagreement about exactly what initiatives we should undertake. Insight into the choice of policy options is provided by the new science of complexity. Four concepts are developed to guide technology policy: self- organization, learning, positive feedback, and emergence.

Before the United States can create the capability to compete in the international market place, it must address the need for organizational systems that are composed of components from both the public and private sectors. This article investigates the constraints on effective policy resulting from: (1) ideology and economic theory, (2) an inaccurate reading of history, and (3) an outdated interpretation of technological innovation. The article concludes that one cannot have a technology policy if one does not create systems that can pick winners.

This chapter investigates the role of information and knowledge management in innovation of complex technologies. A conceptual framework for three patterns of technological innovation (normal, transitional, and transformational) is presented, and the process of information and knowledge management in accessing and using knowledge is analyzed. Particularly, emphasis is put on the cultural impact on the information and knowledge management processes. Five case studies of evolving technologies carried out in the United States, Japan, Germany, India, and China are used to elaborate the conceptual framework and key points presented in this chapter. Lessons for managers and public policymakers concerned with facilitating the innovation of technologies are discussed.

Networks, alliances, and partnerships are essential to the innovation of complex technologies.As used here, networks refer to organizational systems that exist to carry out the innovation of technologies. Networks are composed of multiple organizations that, at a minimum, range from the holders of core capabilities, to the suppliers of complimentary assets, to user organizations (see Figure 1). Alliances and partnerships are organizational relationships (of varying structure) commonly used to establish critical linkages in the networks that carry out the innovation of complex technologies.

The innovation of complex technologies is now widely regarded as the major “engine” of modern economies. Complex technologies are those that cannot be understood in full detail by an individual expert sufficiently to communicate all the details across time and distance to other experts. The trend toward complexity is suggested by Figure 1, which shows that in 1970 complex technologies comprised 53% of the thirty most valuable world manufactures exports. By 1996, that number had grown to 76%.

Critics of this nation's research and development priorities decry the lack of a consistent, over-all policy. Professor Kash, director of the Program in Science and Public Policy at Purdue University, suggests that the R&D system in the United States has been undergoing a reappraisal. This portends more critical evaluation in the future of such projects as the anti-ballistic missile, the supersonic transport and the Weston accelerator. This paper was presented at a conference on the Impact of Aerospace Science and Technology on Law and Government, sponsored by the American Institute of Aeronautics and Astronautics and the American Bar Association, August 30, 1968 in Washington, D.C.

The purposes of this essay are to describe how federal research and development policy has altered authority relationships and to suggest a new concept of legitimacy in accord with the changed conditions. Research and development (R and D) creates an indeterminate future. Thus, the politics of research and development incorporates an apparent contradiction : political leadership demands that jobs be done which require creative and unpredictable actions on the part of private organizations, while it also demands that contractors be held responsible for fulfilling goals efficiently, avoiding deleterious secondary consequences, and refraining from abuses of power. The paradox can be resolved by creating norms of responsibility that allow for judgments on how a job is done rather than what is to be done. New institutions for technological assessment to check on unintended consequences of projects and citizen review boards to estimate the quality of life engendered by projects may provide such norms of responsibility.

The present program of cooperation in space research “clearly rejects the notion that cooperation can be used effectively to bring about fundamental change,” writes Don E. Kash in the article that follows. In space cooperation, as in arms control, the “genuinely dramatic” has been blocked.Don E. Kash is associate professor of political science and director of the Program in Science and Public Policy, Purdue University. He is presently preparing a book, from which this article is taken, to be entitled International Scientific Cooperation: The Space Program.

N THE UNITED STATES the mention of Quemoy and Matsu usually evokes one of two extreme reactions. On the one hand the reaction is that this policy is an illustration of United States foreign policy at its best. In figurative terms this is best illustrated by the notion that we are not going to give up one more square inch of free territory to the Communists. On the other hand, the reaction is that we have committed ourselves to a policy to which rational men would never commit themselves.

The light in which cooperation in science appears to some political scientists is illustrated by the following article. Professor Kash argues that scientists should not make political decisions, and, furthermore, that international enterprise in science is not necessarily good politics even if it is good science. Has politics become an instrument of science?

The objective of this study was to survey both energy technologies and crosscutting areas of science and technology in order to identify important R and D needs and opportunities in the context of the US and world energy situations. The imperative for R and D was judged against its potential for fixing current energy system problems; for providing a robust set of options for coping with, taking advantage of, or encouraging future energy circumstances; and for creating unanticipated opportunities. 103 refs., 36 figs., 22 tabs.

In summary then, the growing call from government for the universities to do applied research in the civilian sector has many disturbing elements. It asks the university to provide more policy advice. In addition, it calls upon the university to become an advocate for that policy research. One can hardly be a part of the university tradition in this country without being initially appalled. Yet the demand is clearly there and it is hard to disagree with Perkins when he says, "The University-as the most sophisticated and, let us hope, independent agency now at work advancing, transmitting and applying knowledge-has come too far to retreat before what may be its finest hour" (8, p. 24).

Presentation des grands axes de recherche et developpement en energies, aux Etats Unis, dans le cadre d'une politique qui vise a satisfaire la demande croissante en energie et qui cherche a tenir compte des problemes ecologiques (effet de serre). Ces grands axes sont l'utilisation rationnelle de l'energie, la conservation de l'energie, l'amelioration de l'utilisation de l'energie nucleaire (surete), le developpement de la fusion nucleaire, des energies solaires ou renouvelables, le developpement de nouvelles technologies ou l'adaptation de celles qui existent aux pays en voie de developpement