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.
All Science Journal Classification (ASJC) codes
- Business and International Management
- Applied Psychology
- Management of Technology and Innovation
- Political Science and International Relations