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Information systems (IS) are technology‐based innovations. Argues for the need to develop an approach to IS research based on studies of technological innovation in the social sciences. While research on the adoption and diffusion of innovations has become a popular approach to implementation and use issues in IS research, IS research projects should be aware of both the strengths and limitations of traditional approaches to technological innovation, and should consider building upon newer approaches that address these limitations. Identifies alternative assumptions about the innovation process that are developing across a range of technological innovation studies, and offers examples of how these ideas can be used in IS research.

Non-technological innovation is an important element of firms' innovation activities that both supplement and complement technological innovation, i.e. the introduction of new products and new processes. We analyse the spread of nontechnological innovation in firms, their relation to technological innovation, and their effects to firm performance and success with product and process innovation, using data from the German Community Innovation Survey conducted in 2005 (German CIS 4). Non-technological innovation is defined as the introduction of new organisational methods or the introduction of new marketing methods. We find that the determinants of a firm's propensity to introduce technological and non-technological innovations are very similar and that both types are closely related. There are only small effects of non-technological innovation on a firm's profit margin, which contrasts the strong effects to be found from technological innovation. However, non-technological innovation spurs success with product and process innovation terms of sales with market novelties and cost reductions from new processes.

The use of simulation modelling techniques in studies of technological innovation dates back to Nelson and Winter's 1982 book, An Evolutionary Theory of Economic Change. Four main issues are identified in reviewing the key contributions in this burgeoning literature. First, a key driver in the construction of computer simulations has been the desire to develop theoretical models capable of dealing with the complex phenomena characteristic of technological innovation. Second, no single model captures all of the dimensions and stylized facts of innovative learning. The article develops a taxonomy that distinguishes between these dimensions and clarifies the different perspectives underpinning the contributions made by mainstream economists and nonmainstream, neo-Schumpeterian economists. Third, the simulation models are heavily influenced by the research questions of these different schools of thought. Finally, attention is drawn to the difference between learning and adaptation within a static environment and within a dynamic environment in which the introduction of new artifacts and patterns of behavior changes the selective pressure faced by agents.

The intimate, though as yet imperfectly understood, causal relation-ship between scientific and technological development and the economic growth in industrially advanced countries over the past 30 years has been investigated and refined over a number of years, and attempts have been made to quantify the relationship. Although a strong scientific and technological (S & T) base does not by itself guarantee rapid economic growth, most observers consider it to be a necessary prerequisite, after a certain level of development has been reached. One of the main ways that S & T act on the economic system is by the generation of new knowledge through research activities and the application of this in production. Such application often results in new products and processes which are grouped under the term "technological innovations." The innovation process is usually defined as "the technical, industrial and commercial steps which lead to the successful marketing of new manufactured products and/or to the commercial use of technically new processes or equipment."

The purpose of this paper is to consider the implications of the fragmented, multidisciplinary technological innovation literature for possible national strate gies for innovation. After a review and synthesis of theories and research on innovation, some highly generalized strategies for promoting innovation are outlined for nations at various levels of technological development. In a final section some consideration is given to the "systemic costs" of innovation, particularly the possibility that high rates of innovation may not be sustainable and that innovation dependency may prove to be an "excelsior trap" with dire economic consequences.

California has achieved considerable economic success through technological innovation and the formation of businesses based upon those technologies. This paper addresses some of the roles of universities in that success story. It starts with some measures of the contributions of innovation and a robust university structure to the California economy, drawn from the biotechnology and wine industries. This is followed by an exploration of some recent partnership structures involving universities with industry and/or the state government. Emphasis is on the University of California, since that is where the experience of the author lies. This is followed by considerations of how such partnerships can be most successful and at the same time meet concerns about potential undesirable consequences stemming from them.

In the past few years, Chinese researchers on domestic S & T (science and technology) policy have identified a number of factors responsible for the past inability of the indigenous S & T system to produce the type of R & D results which whould have stimulated rapid economic development and factors leading to the under-utilization of those results that had the potential to do so. Present strategy accordingly is focussed on both solving organizational, managerial and linkage problems involving the actors in the innovation process and on improving the environment in which each stage of the process takes place. China moving away from an ineffectual innovation system. (DÜI-Sen)