This article presents the results of a survey of competitive intelligence (CI) practices in European firms. In comparing the results to a similar 2006 global study and a 2006 European CI study, it appears that the breadth of applications for CI has grown well beyond competitors to include customer related intelligence, technology, market, etc. Innovation is driving much intelligence activity, in particular research and development (R&D) and new product development decisions. CI is more formalised now in European firms than it was in 2006. The study also found similarities between corporate foresight and CI in terms of objectives (development and maintenance of competitive advantage, help with decision making) and analytical techniques with scenarios being among the more frequently used analytical techniques along with STEEP and other environmental analysis in both corporate foresight studies and the CI study.
This paper reports a Foresight exercise, which was carried out to develop a research strategy and a business model for the science park of Ankara University (AU). Science parks have been crucial elements of innovation systems both in developed and developing countries due to their role in bridging the gap between academia and business through knowledge spill-overs and spin-offs. Although there is a widespread consensus about the usefulness of the science park concept, the actual performance of science parks and how well they meet expectations have been controversial. This paper discusses the success factors for science parks. A three dimensional policy framework, which includes ‘complementarity’, ‘networking’ and ‘strategic scalar positioning’ is suggested to be taken into account during the design and operation of science parks. The paper describes the Foresight process and the policies and strategies developed by using the three dimensional policy framework proposed for the newly established science park at Ankara University.
Future-oriented Technology Analysis (FTA) deals in phenomenological ignorance of three kinds (known unknowns, unknown knowns and unknown unknowns) that give rise to its basis in subjective opinion. These invade both the qualitative and quantitative information co-joined to create outcomes for policy and management in all the STEEPV (Social, Technological, Economic, Ecology, Politics and Values and Norms) themes. FTA then becomes an imaginative projection of current knowledge in which formal methods/techniques play a subsidiary role following Wittgenstein’s dictum that ‘methods pass the problem by’. These contentious matters form a platform for discussion, concluding that FTA’s practical outcomes are underlain by human behaviour, subsumed under subjective opinion in many dimensions and will be more so as FTA becomes involved with technologies of great social and commercial complexity.
The article identifies how the combination of concepts drawn from foresight and foresight networks can be used to help open innovation. We found that foresight can support open innovation by providing analysis that looks at key open innovation questions such as those around technology selection, identifying future customer needs and scanning for disruptions. Foresight can also help open innovation address some of the challenges that have been identified in the open innovation literature as barriers to effective open innovation. Foresight has experience around obtaining access to appropriate external experts and their knowledge; making sense of the mass of information that can emerge through a more open process, both areas that the open innovation literature has identified as being challenges to effective open innovation. Finally, a concept explored in this paper, foresight networks offer’s open innovation new ideas in innovative collaboration forms and how they can be pivotal in innovation and in assisting open innovation.
The system of food production is facing grand challenges, such as a rising population, climate change, degrading bio-productivity of agricultural land and over-fishing. Agriculture and food production are becoming more innovative and implement new infrastructure, IT-platforms or biotechnologies, like gene editing or synthetic food production. A more advanced knowledge base about food innovations helps customers to build informed opinions of new technologies and provides policy makers and industry actors with better information for strategic decision-making. As the amount of available information exceeds expert knowledge or manual filtering of data outputs, this paper presents a text mining study on science and technology in food production based on more than 30 million documents. The proposed methodology which we demonstrate on the example of the future of food production can be applied each time new data becomes available and can serve as an early warning system for a changing technology landscape.