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Innovation and Entrepreneurship
Published in Klaus D. Sattler, st Century Nanoscience – A Handbook, 2020
Coming to the paths followed by innovative activities, these have been traditionally sketched with the so-called “linear model of innovation”, described synthetically in Figure 1.1. In this model innovation process starts from basic research (or, better, “target-free research”, or “research without immediate practical purpose”). The object of this activity is to discover the fundamental behavior of nature. Then “applied research” should be able to exploit fundaments of nature for practical purposes, that is, the results of basic research are transferred to applied research, then to development, and finally to production and diffusion. The transfer passages between the different steps are linear; there is no interconnection, and the flow of innovation moves in one direction – from the laboratory to the market.
The Innovation Process Model
Published in Frank Voehl, H. James Harrington, Rick Fernandez, Brett Trusko, The Framework for Innovation, 2018
Frank Voehl, H. James Harrington, Rick Fernandez, Brett Trusko
The development of representations about the innovation process in science led to the identification of two main approaches: linear and nonlinear, which for the past several decades are being refined in parallel. The author highlights the strengths and weaknesses of each approach in Table 8.2. Thus, there is no replacement of one approach by another. The large variety of models proposed in the framework of each approach points to a failure to develop a universal model of the innovation process that meets all the requirements of a particular company and time. However, nonlinear models are closer to the real innovation process at the present stage and are therefore better able to transmit qualitative changes that occur in the economy. So the idea of a rooted innovation process is reflected, in particular, in the nonlinear models. The main features of nonlinear models regarding the localization of the innovation process are that they (1) take into account the nature of the networked relations between regional actors; (2) reflect models of triple, quadruple, and quintuple helices in the structure of the innovation network; (3) reflect the multiple changes of types of knowledge in the innovation process; and (4) reflect the ambiguity and variability of the source of innovation.3 Over the past 50 years or so, the effect of trends in the localization of the innovation process in the current models has been studied, but the outcomes have been mixed and confusing, at best. The modeling of the innovation process at the present stage is considered a complex, interactive, nonlinear, localized learning process. The traditional model of the innovation process is a linear model of innovation, which has proliferated since the era of Henry Ford. It assumes great significance of codified scientific knowledge, the dominance of basic research as a source of innovation, consistency in the innovation process, and the technocratic nature of innovation.
What Is Science For?
Published in Yongyuth Yuthavong, Sparks from the Spirit, 2018
These examples give clear recognition to the importance of scientific discoveries in the generation of technology and innovations, which fulfils social needs and industrial demands. They appear to follow the linear model of innovation, which basically states that innovation results from a linear process, from scientific discoveries to applied research, technology development, and launch of products and processes in the market or to the society at large. The linear model of innovation is sometimes called the science-push or technology-push model. However, in the past few decades it has been argued that most innovations result from demand pull, namely that it is the demand from industry or society at large that drives the development of products and processes. Closely related to the demand-pull model is the need-based model of innovation, which states that innovations occur as consequences of need felt by society. Examples of mostly demand-pull innovations can be seen everywhere, including in the computer and cell phone industries, alternative energy, and environmental applications such as recycling technologies. Examples of need-based innovations can be found, for example, in vaccines against emerging virulent diseases. Simply put, they are the results of stimulation from outside the sphere of science—namely the society at large—so as to have innovations that are based on demands of the market or needs of society and do not stem mainly just from advances in scientific knowledge in itself. Yet, just like the science- or the technology-push model, the demand-pull model has been criticized for its oversimplification of the complex situation in the real world. Interactive models of innovation have been proposed [29, 30], with interaction between suppliers and users of innovation. Such models should give better representations of science as a source of technology and innovations. In some cases, scientific advances give rise to opportunities that are taken up by industry or the public sector. In other cases demands from the market or needs of society stimulate relevant sectors of the scientific community to focus on the specific problems and come up with new scientific and technological advances.
The role of CDIO in engineering education research: Combining usefulness and scholarliness
Published in European Journal of Engineering Education, 2020
Also in Edison’s quadrant, the focus is on solving specific problems, but Stokes points out ‘how strictly Edison kept his co-workers from pursuing the deeper scientific implications of what they were discovering in their rush toward commercially profitable electric lighting’. Söderberg (1967) characterised both Edison and Ford by ‘a core of anti-intellectualism along with impatience toward scientific sophistication’. Bohr’s quadrant is the pure basic science, or knowledge for its own sake. The ideal here is a ‘disinterested’ researcher, i.e. seeking only fundamental understanding, without allowing practical concerns to hinder the inquiry. This is not to say that such research cannot be – or become – useful, but the premise is that someone else can figure out later whether and how the new knowledge can be used. The justification for this is the linear model of innovation, which assumes that basic research will be followed by applied research and development, then leading to production and diffusion. The linear model has been largely refuted empirically but is still much used in arguments for funding basic science (Godin 2006). To help reconcile the basic/practical tension, Stokes suggested a separation between the aims of the researchers and those who support it. He meant that strategic research, i.e. basic research related to practical problems, could fit into Pasteur’s quadrant. While the motive of researchers can be to make a contribution to the discipline, the funding agency has an area of application in mind when selecting which project proposals to support (Stokes 1997, 61–62).