Inter-organizational mobility, social networks and innovative performance
Goossen M. C.
Building on the argument that inter-organizational mobility triggers a “learning by hiring” mechanism, a thriving stream of research emerged in the past few years on the relation between inventor mobility and innovation (e.g., Agrawal et al. 2006, Singh 2007, Oettl and Agrawal 2008, Agarwal et al. 2009, Corredoira and Rosenkopf 2010). By analyzing knowledge-intensive industries such as the pharmaceutical and semiconductor sectors, this literature brought compelling evidence that the mobility of inventors across organizations has far-reaching implications for the innovative performance of both the “source” and the “recipient” firm1 (e.g., Corredoira and Rosenkopf 2010).
Despite the many insights generated by these studies, a few fundamental questions have remained unaddressed. In particular, two aspects have recently been recognized as critically important but understudied. First, received research has almost exclusively focused on the link between inventor mobility and firm-level innovative performance, while much less attention has been paid to understanding how inter-organizational mobility impacts the innovative performance of the inventor him/herself. Arguably, however, a deeper understanding of the mobility-innovation link would require us to more closely look into the inventor-level consequences of mobility events, given that the innovative performance of the firm is largely a reflection of the innovativeness of its individual employees (Felin and Hesterly, 2007). Second, despite increasing awareness that the social network developed by an inventor within the workplace may moderate the performance impact of inter-organizational mobility (e.g., Groysberg et al., 2008), no studies have thus far examined whether such moderating effect exists and how exactly it operates.
In light of these considerations, the objective of the present project is to develop an articulated research design aimed at addressing the following research question: Does inter-organizational mobility differentially impact inventors’ innovative performance depending on the network structure in which the moving inventor is embedded? To address this question, we will integrate two well-established but thus far largely unrelated theoretical perspectives on the determinants of inventors’ innovativeness. One looks at inter-organizational labor mobility as a source of learning and knowledge recombination (e.g., Song et al., 2003); the other examines how the social network around an inventor affects his/her innovative capabilities (e.g., Fleming et al., 2007). By combining insights from both perspectives, we will address four specific research questions:
1) Does the impact of inter-organizational mobility on inventors’ innovative performance change depending on the inventor’s network position within the source firm (i.e., prior to the move)?
2) Does the impact of inter-organizational mobility on inventors’ innovative performance change depending on the inventor’s network position within the recipient firm (i.e., after the move)?
3) Under which (network) conditions are mobile inventors more likely to “explore” new knowledge areas outside their current expertise, as a result of inter-organizational mobility?
4) Under which (network) conditions is a recipient firm more likely to “explore” new knowledge areas outside its current expertise, as a result of inter-organizational mobility?
The empirical setting in which the research will be carried out is the global pharmaceutical industry in the period 1975-2008. In particular, we will extend a data set collected by Dr. Francesco Di Lorenzo2 as part of his PhD, which describes the five most important publicly traded pharmaceutical firms: Pfizer Inc., GlaxoSmithKline Plc., Merck & Co. Inc., Bristol-Myers Squibb, Novartis AG. Our aim is to extend this data set in two main ways. First, we will include the top 25 pharmaceutical firms, as this would greatly enhance the representativeness of the industry as well as provide us with significantly more variance in mobility patterns. Second, we will gather more detailed data on each of those 25 firms, particularly with regard to their internal collaboration network. We will collect patent data from the Dataverse Network (Lai et al., 2009); this data will allow us to identify mobility events (e.g. Singh and Agrawal, 2011), network ties (e.g., Paruchuri, 2010), and innovative performance. Financial and organizational data will be collected from Compustat Global Fundamental Annual dataset, CorpTech, and SDC Platinum Database.
By theoretically and empirically elucidating the role of inventors’ networks in mobility events, the results of the study promise to significantly improve our understanding of the mobility-innovation link.