"The art of tuning time and technology" knowledge cycles and innovation in networks

Abstract

We have developed the TAO model/sup /spl copy// (technology and application organization) as an innovation roadmap from the perspective of individual companies. However, what is a product for one company may be a production means for the next. We have found that, to fully understand innovative business clusters, stacks and chains of TAOs are a more useful presentation than capturing the whole organizational cluster of a corporation or chain in just one business representation. Studying the dynamics of individual TAOs within these networks, it became clear that also dynamic knowledge streams play an important role between individual organizations. These knowledge loops have their own cycle time. Differences in cycle time may limit exchange of information so that therefore not all TAO functions can be performed by just any company, limiting innovation. Especially universities, government funded laboratories and government funded-research programs, with their long cycle times play an important role in potential mismatching these differences in dynamics. From the insights from the stacks and chains of TAOs and their dynamics behavior guidelines may be derived for setting up more effective innovation programs for universities, commercial and public research institutes and public funded research programs. The methodology presented in the paper has been successfully applied to 'anchoring' the results and the relation network of a government funded innovative research program on computer-vision and image processing in the Netherlands.