TY - JOUR
T1 - Spontaneous vs. policy-driven
T2 - The origin and evolution of the biotechnology cluster
AU - Su, Yu Shan
AU - Hung, Ling Chun
N1 - Funding Information:
The Bay Area enjoys tremendous financial support from both public and private sources. On the federal government level, the National Institute of Health and the National Science Foundation (NSF) are main financial supporters for basic research in biotech. The local leading universities receive immense amounts of R&D funding from these two government departments. For instance, according to the NSF, the top universities located in the North California received a record $2.8 billion in R&D funding in 2007. 6 6 This generous research funding accelerated these universities' research progress, and indirectly facilitated technology transfer and the creation of academic spin-offs.
Funding Information:
The two authors contribute equally. We thank Fred Phillips and Klaus Meyer for helpful comments. This work was initiated at the time Dr. Yu-Shan Su was a Fulbright scholar at University of Texas at Dallas, while Dr. Ling-Chun Hung was a PhD student there in 2007. This paper was presented at the Academy of Management (Anaheim, United States, 2008), Association for Chinese Management Educators (Toronto, Canada, 2008) and Chinese Economic Association (Cambridge University, United Kingdom, 2008). This research is supported in part by the Fulbright Association and the Taiwan Ministry of Education. All views expressed are those of the authors and do not represent those of the sponsoring organizations.
Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - The biotechnology industry is at the heart of the fast-growing knowledge-based economy. One of the distinguishing characteristics of this industry is clustering. A cluster, like an organism, experiences origin, growth, and decline/reorientation. Our study constructs a framework to analyze biotechnology clusters with different origins, "spontaneous" and "policy-driven", through their life cycles. We use the Bay Area in the United States and Shanghai Zhangjiang Hi-Tech Park in China as two cases to represent spontaneous and policy-driven biotechnology clusters. This study fills the gap in the literature by comparing these two types of biotechnology clusters in an evolutionary perspective. The key success factors of both biotechnology clusters are their own human and financial capital, but they differ in their underlying processes for creating and sharing these resources. The most fundamental differences arise from the impact of entrepreneurship, social capital and network patterns on the cluster's configuration.
AB - The biotechnology industry is at the heart of the fast-growing knowledge-based economy. One of the distinguishing characteristics of this industry is clustering. A cluster, like an organism, experiences origin, growth, and decline/reorientation. Our study constructs a framework to analyze biotechnology clusters with different origins, "spontaneous" and "policy-driven", through their life cycles. We use the Bay Area in the United States and Shanghai Zhangjiang Hi-Tech Park in China as two cases to represent spontaneous and policy-driven biotechnology clusters. This study fills the gap in the literature by comparing these two types of biotechnology clusters in an evolutionary perspective. The key success factors of both biotechnology clusters are their own human and financial capital, but they differ in their underlying processes for creating and sharing these resources. The most fundamental differences arise from the impact of entrepreneurship, social capital and network patterns on the cluster's configuration.
KW - Biotechnology cluster
KW - Evolution
KW - Origin
KW - Policy-driven
KW - Spontaneous
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U2 - 10.1016/j.techfore.2008.08.008
DO - 10.1016/j.techfore.2008.08.008
M3 - Article
AN - SCOPUS:67349280336
VL - 76
SP - 608
EP - 619
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
SN - 0040-1625
IS - 5
ER -