Network Growth and Consolidation: The Effects of Cohesion and Diversity on the Biotechnology Industry Network

The growth regimes of complex networks account for many of their structural features and behavioral effects. Social and economic networks, however, tend to expand along different pathways than their technological or biological counterparts. Complex inter-organizational topologies are characterized by tight-knit clusters of prominent nodes whose dense inter-connections help forge them into an elite that can play gatekeeper and arbiter roles in an expanding network. The characteristics of such emergent elites, however, depend intimately upon the structural locations of the partners that form new ties. Systems where cores deepen their internal connections conserve their position, but may calcify. Those that expand their reach by forming connections to newcomers and to the network’s periphery increase responsiveness at the possible cost of incoherence. We draw on twelve years of dynamic network data from the international biotechnology industry to demonstrate that a mix of expansive and conserving ties account for that industry’s particular combination of stability and responsiveness. This structural view of network growth offers new insights into the distinctive features of social and economic networks, while linking models of network dynamics to debates in organizational theory and innovation studies.

[1]  J. Schumpeter Capitalism, Socialism and Democracy , 1943 .

[2]  Satoru Kawai,et al.  An Algorithm for Drawing General Undirected Graphs , 1989, Inf. Process. Lett..

[3]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[4]  W. Powell,et al.  Interorganizational Collaboration and the Locus of Innovation: Networks of Learning in Biotechnology. , 1996 .

[5]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[6]  Edward M. Reingold,et al.  Graph drawing by force‐directed placement , 1991, Softw. Pract. Exp..

[7]  Walter W. Powell,et al.  Networks, Fields and Organizations: Micro-Dynamics, Scale and Cohesive Embeddings , 2004, Comput. Math. Organ. Theory.

[8]  Steven B. Andrews,et al.  Network Position and Firm Performance: Organizational Returns to Collaboration in the Biotechnology Industry , 1999 .

[9]  David R. Gibson Participation Shifts: Order and Differentiation in Group Conversation , 2003 .

[10]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[11]  Gernot Grabher The embedded firm : on the socioeconomics of industrial networks , 1995 .

[12]  Amy K. Glasmeier,et al.  Technological discontinuities and flexible production networks: The case of Switzerland and the world watch industry * , 1991 .

[13]  D. R. White,et al.  Social Cohesion and Embeddedness : A Hierarchical Conception of Social Groups , 2000 .

[14]  B. Spilker,et al.  Science and Innovation: The US Pharmaceutical Industry During the 1980s , 1996 .

[15]  I. Cockburn,et al.  Scale, scope, and spillovers: the determinants of research productivity in drug discovery. , 1996, The Rand journal of economics.

[16]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[17]  D. R. White,et al.  Structural cohesion and embeddedness: A hierarchical concept of social groups , 2003 .

[18]  J. March Exploration and exploitation in organizational learning , 1991, STUDI ORGANIZZATIVI.

[19]  Franco Malerba,et al.  Technological entry, exit and survival: an empirical analysis of patent data , 1999 .

[20]  P. Bearman,et al.  Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks1 , 2004, American Journal of Sociology.

[21]  F. Harary,et al.  The cohesiveness of blocks in social networks: Node connectivity and conditional density , 2001 .

[22]  Paul A. Gompers,et al.  The venture capital cycle , 1999 .

[23]  M. Newman,et al.  Why social networks are different from other types of networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  W. Powell,et al.  Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1 , 2005, American Journal of Sociology.

[25]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.