Biotechnology Abstracts and links in PDF and html
Movie Visualizations: The Evolution of Inter-Organizational Collaboration In the Life Sciences2005 Walter W. Powell, Douglas R.
White, Kenneth W. Koput and Jason Owen-Smith. Network
Dynamics and Field Evolution: The Growth of Interorganizational
Collaboration in the Life Sciences.
American Journal of Sociology 110(4):1132-1205 (has full text in pdf
as well as html
with enhancements)
electronic edition
Available at a library near you
Download: 
SFI-WP2003d.pdf See link to movies at
Barabasi site
Santa Fe Institute Working Paper
This paper received the 2007 Viviana Zelizer Distinguished Scholarship Award given every two years by the
American Sociological Association's Economic Sociology Section. The award recognizes an outstanding article published
in the field of economic sociology in the previous two years.
The award letter states that the paper "advances several questions central to economic sociology," and
the award committee letter of congratulations states: "We see this piece as groundbreaking; we expect it will continue
to be highly useful and frequently cited over the long run in our subfield." .
Abstract: We develop and test, using McFadden's discrete choice statistical modeling applied to network dynamics, four alternative logics of attachment - - accumulative advantage, homophily, follow-the-trend, and multiconnectivity - - to account for the development of interorganizational collaboration in the field of biotechnology. The commercial field of the life sciences is characterized by wide dispersion in the sources of basic knowledge and rapid development of the underlying science, fostering collaboration among a broad range of institutionally diverse actors. We map the network dynamics of the field over the period 1988-99. Using multiple novel methods, including analysis of network degree distributions, network visualizations, and multi-probability models to estimate dyadic attachments, we demonstrate how a preference for diversity shapes network evolution. Collaborative strategies pursued by early commercial entrants are supplanted by strategies influenced more by universities, research institutes, venture capital, and small firms. As organizations increase both the number of activities around which they collaborate and the diversity of organizations with which they are linked, cohesive subnetworks form that are characterized by multiple, independent pathways. These structural components, in turn, condition the choices and opportunities available to members of a field, thereby reinforcing an attachment logic based on connection to partners that are diversely and differently linked. The dual analysis of network and institutional evolution offers a compelling explanation for the decentralized structure of this science-based field.
2004 Douglas R. White, Jason Owen-Smith, James Moody, and Walter W. Powell
Networks, Fields and Organizations: Micro-Dynamics, Scale and Cohesive Embeddings.
Computational and Mathematical Organization Theory 10(1):95-117.
Special issue on Mathematical Representations and Models for the Analysis of Social
Networks within and between Organizations, Guest Editors Alessandro Lomi and
Phillipa Pattison.
Download:
SFI-WP2004-03-09
CMOT site
Keywords: Graph theory, social networks, algorithmic detection, cohesive network topologies, fields, organizations, micro-macro linkages.
Abstract: Social action is situated in fields that are simultaneously composed of interpersonal ties and relations among organizations, which are both usefully characterized as social networks. We introduce a novel approach to distinguishing different network macro-structures in terms of cohesive subsets and their overlaps. We develop a vocabulary that relates different forms of network cohesion to field properties as opposed to organizational constraints on ties and structures. We illustrate differences in probabilistic attachment processes in network evolution that link on the one hand to organizational constraints versus field properties and to cohesive network topologies on the other. This allows us to identify a set of important new micro-macro linkages between local behavior in networks and global network properties. The analytic strategy thus puts in place a methodology for Predictive Social Cohesion theory to be developed and tested in the context of informal and formal organizations and organizational fields. We also show how organizations and fields combine at different scales of cohesive depth and cohesive breadth. Operational measures and results are illustrated for three organizational examples, and analysis of these cases suggests that different structures of cohesive subsets and overlaps may be predictive in organizational contexts and similarly for the larger fields in which they are embedded. Useful predictions may also be based on feedback from level of cohesion in the larger field back to organizations, conditioned on the level of multiconnectivity to the field.
Reprinted: Virtual Journal of Biological Physics Research
February 1, 2006 issue. The Virtual Journal, which is published by
the American Physical Society and the American Institute of Physics in
cooperation with numerous other societies and publishers, is an edited
compilation of links to articles from participating publishers, covering
a focused area of frontier research.
reviewed 2005 in
Europhysicsnews 36(6):218-220
by Stefan Thurner:
2006 Douglas R. White, Natasa Kejzar, Constantino Tsallis, Doyne Farmer, and Scott White.
Download:
A Generative Model for Feedback Networks (including trade, biotech, kinship)
Physical Review E 73, 016119 abstract doi:10.1103/PhysRevE.73.016119
http://arxiv.org/abs/cond-mat/0508028
Santa Fe Institute Working Paper 2005
Abstract. We investigate a simple generative model for network formation. The model is designed to describe the growth of networks of kinship, trading, corporate alliances, or autocatalytic chemical reactions, where feedback is an essential element of network growth. The underlying graphs in these situations grow via a competition between cycle formation and node addition. After choosing a given node, a search is made for another node at a suitable distance. If such a node is found, a link is added connecting this to the original node, and increasing the number of cycles in the graph; if such a node cannot be found, a new node is added, which is linked to the original node. We simulate this algorithm and find that we cannot reject the hypothesis that the empirical degree distribution is a q-exponential function, which has been used to model long-range processes in nonequilibrium statistical mechanics.
Unpublished Manuscripts
2005 Jason Owen-Smith, Walter W. Powell, and Douglas R. White.
Network Growth and Consolidation: The Effects of Cohesion and Diversity on the Biotechnology Industry Network.
Submitted to Management Science, Special issue on Complex Systems Across Disciplines.
Download:
Growth_andConsolidation.pdf