Review of innovation theories in the perspective of Bayesian decision analysis

Abstract

Innovation requires novel technologies or its novel application and will only impact if it creates industrial and societal benefits on large scale. Thus, the industrial and societal benefits should be quantified prior and during the development of the technological readiness by comprehensive technological performance and utility modelling and forecasting. This will facilitate to guide the technological development in a very early stage and in later stages to optimise the performance of the technology for industrial and societal benefit generation, i.e. an innovation scaling. This paper contains approaches on how (1) innovation and technology development can be aligned with decision value analyses and (2) guided towards a high industrial and societal value building upon [1]. The approach is exemplified with examples of actual and novel digital inspection and monitoring technology developments.

References

[1] S. Th�ns, A. A. Irman, and M. P. Limongelli, "On Uncertainty, Decision Values and Innovation," presented at the International Conference on Uncertainty in Mechanical Engineering (ICUME), Darmstadt, Germany, June 7 to 8, 2021, 2021.