Deals of a feather… Modelling latent classes in R&D collaboration data using finite mixture analysis
Troy Neilson, Joshua Byrnes, Nicholas Rohde
TL;DR
This paper shows that public sentiment affects R&D collaboration deal values, especially for preclinical stage projects where uncertainty is high.
Contribution
The study identifies latent classes in RDC data and shows how market behavior impacts deal valuation under knowledge asymmetry.
Findings
Public sentiment significantly predicts deal value for 15% of the dataset.
This effect is limited to Preclinical stage deals, indicating higher market sensitivity.
Latent class analysis reveals behavior's influence on pricing in uncertain R&D contexts.
Abstract
This work explores if behaviour-based asymmetries are likely to impact deal valuation in the life sciences by examining positive public sentiment as a proxy for market behaviour when negotiating under asymmetric conditions to examine heterogeneity in research & development collaboration (RDC) deal data. We use public sentiment as a proxy for behaviour along with stage of development-based RDC deal data to search for latent classes in the deal data using finite mixture modelling. The analysis reveals a nuanced picture: public sentiment emerges as a significant predictor of deal value, but only for approximately 15% of the data set. This subset exclusively includes firms in the Preclinical stage, where projects have moved past discovery but are yet to commence human studies. Interestingly, the research finds that sentiment’s impact on deal valuation is particularly pronounced in this…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInnovation Diffusion and Forecasting · Innovation and Knowledge Management · Firm Innovation and Growth