TY  - JOUR
PB  - Springer
JF  - Journal of Evolutionary Economics
IS  - 2
SN  - 0936-9937
N2  - In this paper, we build a cumulative innovation model to understand the role of both success and failure in the learning dynamics that characterize pharmaceutical R&D. We test the prediction of our model by means of a unique dataset that combines patent information with R&D projects, thus distinguishing patents related to successfully marketed products from those covering candidate drugs that failed in clinical trials. Results confirm model predictions showing that patents associated with successfully completed projects receive more citations than those associated with failed projects. However, we also show that failed projects can be in turn cited more often than patents lacking clinical or preclinical information. We further explore the `black box' of innovation, providing evidence that both successes and failures contribute to R&D investment decisions and knowledge dynamics in science-driven sectors.
ID  - eprints3572
EP  - 290
VL  - 26
UR  - http://dx.doi.org/10.1007/s00191-015-0439-z
A1  - Chiou, Jing-Yuan
A1  - Magazzini, Laura
A1  - Pammolli, Fabio
A1  - Riccaboni, Massimo
Y1  - 2016///
AV  - none
N1  - SCOPUS ID: 2-s2.0-84953209929; WOS Accession Number: WOS:000374576900002
SP  - 271
TI  - Learning from successes and failures in pharmaceutical R&D
ER  -