A decision support model to assess technological paradigms

Envisioning the emergence of a new technological paradigm involves several issues, spanning from strategic assessments and managerial actions to design decisions and technology related choices. The present study focuses on this latter perspective, by proposing a model that estimates the success probability of innovative products as a function of design actions. This focus on the design decisions that underlie radical shifts is not conflicting, but complementary to the more traditional perspectives of forecasting that consider environmental variables or process management factors. The model is based on a database of past successful and unsuccessful innovations, which are used to build a logistic regression model, whose evidences can assist both designers and managers. The former get advice on how specific design choices affect product perception and innovation adoption, while the latter are supported in identifying the most promising projects. The model is illustrated through two cases of digital products.