Robert W. Rycroft

Definitions of conflict and the legitimation of resources: The case of environmental risk

This paper examines the social construction of conflict over environmental health and safety issues (i.e., environmental risk). Four explanations for such conflict are commonly offered in the environmental policy literature. We examine the interests served by each. We hypothesize that environmental policy professionals hold definitions of conflict consistent with the values and interests of the organizations for which they work and the professions of which they are members. These definitions enhance the legitimacy of the resources those groups possess in relative abundance. Data from a survey of risk professionals are generally consistent with these hypotheses. We conclude by generalizing beyond environmental conflict to identify ways in which disputes about the nature of a social problem or conflict are often at the same time struggles to determine the value of the resources available to social movements and their opponents.

Self-organizing innovation networks: implications for globalization

Abstract The most valuable and complex technologies are increasingly innovated by networks that self-organize. Networks are those linked organizations (e.g., firms, universities, government agencies) that create, acquire, and integrate the diverse knowledge and skills required to create and bring to the market complex technologies (e.g., aircraft, telecommunications equipment). In other words, innovation networks are organized around constant learning. Self-organization refers to the capacity these networks have for combining and recombining these learning capabilities without centralized, detailed managerial guidance. The proliferation of self-organizing innovation networks may be linked to many factors, but a key one seems to be increasing globalization. Indeed, globalization and self-organizing innovation networks may be coevolving. Changes in the organization of the innovation process appear to have facilitated the broadening geographical linkages of products, processes, and markets. At the same time, globalization seems to induce cooperation among innovative organizations. Research on innovation networks is used to illustrate these ideas. The evolution of the automotive industry provides a test case.

Emerging patterns of complex technological innovation

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 Schumpeters “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.

Path Dependence in the Innovation of Complex Technologies

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 (CDs), 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.

Technology-based globalization indicators: the centrality of innovation network data

Abstract Useful technology-based indicators are central to efforts to gain insights into the causes and consequences of globalization. But traditional technology-based globalization indicators are of limited use because they are based exclusively on innovation inputs (e.g. R&D spending) or outputs (e.g. patenting). Coming to grips with the globalization phenomenon requires more attention to events taking place in the innovation process itself. Indicators of technological collaboration (e.g. strategic alliances, joint ventures, intimate supplier-producer linkages) help fill this gap. Focusing on these cooperative arrangements places the emphasis where it should be—on the key organizational actors (e.g. firms, universities, government agencies) in the process of globalization. Indicators based on the dynamics of these innovation networks hold great promise for integrating input and output indicators. An example is the development of indicators of social capital—a stock of collective learning. Viewing globalization through the lens of the emergence and evolution of social capital points out that even in the most powerful technological innovation process, success depends as much on social factors (e.g. the key roles of trust, shared values, and community) as on economic, scientific, or engineering variables.

Complex technology and community: implications for policy and social science

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

Risk assessment in the policy-making process: environmental health and safety protection.

This article examines the extent to which differences exist in the relative degree of discretion permitted by the statutory mandates under which health risk assessments are conducted as a basis for regulatory action. Attention is focused on the Environmental Protection Agency and the Food and Drug Administration, because they are the lead federal regulatory agencies on most environmental health matters. The statutes are found to define risk, consider effects, identify target populations, and use benefit-cost analysis in a flexible way. But the burden of proof of risk typically is assigned in a more direct and stringent fashion. Overall, however, agencies are found to have substantial discretion in the manner in which risk assessments are incorporated into the policy process. A number of examples of efforts to reduce this flexibility are outlined and their implications for the future of the analysis of risks are delineated.

To manage complex innovation, ask the right questions

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.

Technology policy: Fitting concept with reality

Abstract 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.

Technology policy in a complex world

Abstract 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.