Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 608-619 |
| Number of pages | 12 |
| Journal | Technological Forecasting and Social Change |
| Volume | 76 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2009 Jan 1 |
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Keywords
- Biotechnology cluster
- Evolution
- Origin
- Policy-driven
- Spontaneous
ASJC Scopus subject areas
- Business and International Management
- Applied Psychology
- Management of Technology and Innovation
Cite this
Spontaneous vs. policy-driven : The origin and evolution of the biotechnology cluster. / Su, You-Shan; Hung, Ling Chun.
In: Technological Forecasting and Social Change, Vol. 76, No. 5, 01.01.2009, p. 608-619.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Spontaneous vs. policy-driven
T2 - The origin and evolution of the biotechnology cluster
AU - Su, You-Shan
AU - Hung, Ling Chun
PY - 2009/1/1
Y1 - 2009/1/1
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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UR - http://www.scopus.com/inward/citedby.url?scp=67349280336&partnerID=8YFLogxK
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 -