Institute for Technology and Innovation Management at RWTH Aachen, Germany
Enabling technologies are emerging general-purpose technologies with broad potential and unique properties. Their development and diffusion are associated with significant uncertainties, especially on the demand side—ranging from user adoption and business models to evaluating future application domains. These uncertainties, in turn, influence the technology side, as innovations must adapt to evolving demand. Relational forecasting methods for viable future application domains are essential to forecast future developments for enabling technologies and alleviate uncertainties effectively. Established forecasting approaches are limited in this regard as they focus on a single application domain and gather experts solely related to that domain. This limitation is evident in the case of Bio-functional Building Blocks, a versatile protein-based technology capable of functionalizing various materials to create new product characteristics. In our manuscript, we develop and test a Cross-Domain Delphi method for enabling technologies that connect technology- and application-side experts to collaboratively develop and assess projections and scenarios for future application domains. We validate and illustrate this method using the case of Biofunctional Building Blocks as a particularly promising enabling technology.
