The Knowledge Transfer Office of UoC, in
partnership with TIME-MBE, UoC’s joint Master Program and TECHNIS, platform for interdisciplinary innovation and
intellectual property, announce their first seminar for 2022-2023, on Tuesday, 27th September 2022, at 15:00 GMT.

Mr. Zhen Lei, from Penn State University, is the speaker
and the title of his presentation is “Diamond
in the rough: Quantifying failed innovative endeavors”.

Join Zoom Meeting: https://us02web.zoom.us/j/89840336335?pwd=RE1pUE00Z3NybGZGSUpDTldQa2xxZz09

Abstract:  Many innovative pursuits fail, yet little is
known about patterns governing failed innovative endeavors that span scientific
and technological domains. Here we analyze large-scale datasets capturing both
successful and failed innovative endeavors across three distinct domains,
ranging from patent applications to grant proposals to Kickstarter projects.
Prior research shows that hits—the successful and high-impact innovations,
compared with flops—the successful but low-impact, tend to balance novel
combinations of prior knowledge with conventional thinking. Here we propose a
simple measure to quantify similar stratifications within failed innovations,
allowing us to systematically identify diamonds in the rough (DIRs) and lumps
of coal (LOCs). We find that across all three domains, promising but failed
ideas strike a similar balance of novelty and conventionality, with DIRs being
systematically more novel and more conventional than LOCs. Yet, comparing DIRs
with successful innovations, we find that for certain domains, DIRs can be both
more novel and conventional than many of the successful innovations, revealing
a systematically identifiable population of failed innovations that occupy a
similar region as hit innovations on the conceptual space of novelty and
conventionality. We devise a toy model that explores the discrepancy between
evaluation and recognition processes of an innovation, allowing us to not only
explain the hit-DIR proximity, but also identify conditions when such proximity
may emerge. Together, these results not only offer a quantitative framework
that furthers our understanding of the full spectrum of innovative
endeavors—both successful and failed, they may also have implications for
identifying and nurturing promising new ideas and technologies, a relevant
issue for science and innovation policy.