Physical distance vs. clustering as influences on contracting complexity for biopharmaceutical alliances

Abstract

We examine whether the presence of alliance firms in the same regional cluster or in close physical proximity influences contracting behaviour of biopharmaceutical companies by enhancing coordination and mitigating the need for control. The literature addressing geographical proximity and alliance contracting fails to make a clear distinction between physical co-location and co-location within a cluster, although the two attributes are conceptually distinct. We find that geographic proximity is not related to contracting behaviour. The impact of co-location within a cluster is more nuanced. Specifically, we find that co-location in the San Francisco Bay Area cluster is associated with less complex contracting; however, co-location in other biotechnology clusters does not seem to be related to contracting behaviour. We believe that the informal business environment characterising the Bay Area cluster, as well as unique roles played by venture capital and law firms located in the Bay Area account for the distinct result.

Keywords:

• Clusters
• alliances
• contractual coordination
• contractual control
• biotechnology

Jel Classifications:

• L24
• L65
• O32

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by the Western Washington University.

Acknowledgement

We are grateful to Tom Roehl, Skylar Powell, two anonymous referees, and the special issue editor for their comments and suggestions on an earlier draft. The authors also thank Trevor Press and Zane Hashmi for their very helpful research assistance. Kim acknowledges the College of Business and Economics at Western Washington University for financial support and to Recombinant Capital (now a part of Clarivate Analytics) for generous access to their data. The usual disclaimer applies.

Notes

¹ Santoro and McGill (2005) consider whether the relative efficiency of hierarchical governance varies when firms in an alliance are from two different countries.

² Bengtsson and Ravid (2009) examine whether the design of private equity contracts between venture capitalists and start-up companies is influenced by the presence of the companies in the same ‘California cluster.’

³ See, for example, Almeida and Kogut (1999), Coyle and Polsky (2013), Powell, Packalen, and Whittington (2012) and Suchman and Cahill (1996).

⁴ In the U.S. biotechnology sector, industrial clusters took root in several regions, most prominently the San Francisco Bay Area, Boston/Cambridge and San Diego. Also prominent are northeastern U.S. regions, including New York/New Jersey, Philadelphia, Washington D.C./Maryland, as well as Seattle, Los Angeles, and the Research Triangle in North Carolina. A few smaller regional clusters also exist (Audretsch 2001).

⁵ Obviously, this risk depends upon the degree to which norms of behaviour are enforced, which, in turn, can depend upon the specific formal and informal, e.g. cultural practices and institutions surrounding an alliance.

⁶ Indeed, contracts in some cases may be entirely ‘boilerplate,’ particularly when some contracting parties have much more bargaining power than their contracting partners do. See, for example, Ben-Shahar and White (2006).

⁷ Booth (2017) notes that while all the biomedical clusters combine a unique blend of biomedical science, venture capital, entrepreneurial talent, risk-taking, geographical density, none have them in the same magnitude as Boston and San Francisco, and the gap has grown over time.

⁸ In the context of this discussion, the Boston Area includes Cambridge, while the Bay Area extends south to Palo Alto, and east to Oakland.

⁹ It should be noted that Bell’s comments may not be appropriate to today’s venture capital environment in Boston as it was in the 1990s and early 2000s. However, the latter period is the one that is covered by our sample.

¹⁰ Bengtsson and Ravid (2009) identify a broader ‘California effect’ in venture capital contracting. Aydogan (2008) also highlights unique aspects of the Silicon Valley region. Almeida and Kogut (1999) specifically highlight a greater localisation of knowledge and greater intra-regional mobility of labour in Silicon Valley compared to other clusters in the context of the semi-conductor industry. Coyle and Polsky (2013) discuss the unique practices of Silicon Valley firms in hiring teams of software engineers from other companies. In a later section of the paper, we examine whether a West Coast effect is largely specific to Silicon Valley or whether it is generalisable to other West Coast clusters, most notably, San Diego.

¹¹ Zhou et al. (2003) find that large firms in China are more likely than small firms to use formal contracts.

¹² Castilla (2003) finds that venture capital firms in Silicon Valley collaborate more closely with each other than venture capital firms in the Boston area.

¹³ In this regards, Iammarino and McCann (2006) argue that differences in cluster types, where they exist, are not necessarily related to industrial sectors.

¹⁴ The sample selection was focused on commercial alliances with substantial R&D components.

¹⁵ We focused on headquarters as the basis for identifying location both because it was a readily available measure, and because alliance partnering activity is likely to be managed from headquarters. Also, according to one of the co-author’s private discussion on this matter with an executive at a high-tech (biotechnology) start-up, the location of the headquarters is more relevant for contracting and other such legal activities than the locations of other facilities, such as separate R&D laboratories or marketing offices (if they exist).

¹⁶ See Appendix 1 for a breakdown of the distribution of alliances across clusters.

¹⁷ In fact, unreported regressions using ordered logit specifications yielded virtually identical results. Poisson specifications also produced similar results.

¹⁸ We also measured distance as a discrete dummy variable, taking a value of ‘1’ if the distance between alliance partners’ headquarters is less than 100 miles and ‘0’ otherwise. Our results did not change significantly.

¹⁹ Our biotech-biotech alliance variable might indirectly account for the influence of differences in the mix of pharma vs. biotech companies across clusters, as well as differences in average firm size.

²⁰ The Bay Area cluster variable is statistically significant at conventional levels in Equations (4) and (5) in Table 5, but it is statistically significant only in Equation (4) in Table 6.