“From Fast Follower to Global Knowledge Leader? Network Relationships in Biopolis, Multimedia Supercorridor, Zhongguancun and New Songdo City”

Dr. Thomas D. Lairson

Gelbman Professor of International Business

Professor of Political Science

Rollins College

Emerging economies in Asia face striking challenges as they attempt to upgrade their economic capabilities to keep pace with rapid global changes. Previous strategies for learning and application of knowledge and technology to low wages and effective infrastructure were often improved to achieve status as a fast follower. However, institutions and capabilities that support re-engineering and imitation for participation in global production networks are inadequate for the difficulties of operating at the knowledge and technology frontier.

Several Asian nations have created new institutional capabilities in an effort to raise their status to global knowledge leaders: Singapore with Biopolis, Malaysia with Multimedia Supercorridor, China with Zhongguancun and Korea with New Songdo City. Each has a distinct geographic location, though these efforts are based on different strategies in different industries and thus far have quite different outcomes. Existing research has focused on individual knowledge centers in Malaysia, Singapore and China, but comparative studies are rare and none has examined these centers from the perspective of links to global knowledge networks.

This research compares each knowledge center in terms of internal and external network relationships. Internal networks exist among various actors within the knowledge center, including firms, research centers, universities and government and non-government actors. External networks exist with global firms and non-local research centers,

universities, government agencies and non-government organizations. The networks are differentiated in terms of the number of nodes, the complexity of nodes (entrepreneurial autonomy), and the number and richness of links to internal and external nodes. This is a basic mapping exercise based on a hypothesis linking these network characteristics to the capacity for innovation.

Data will be gathered from samples of researchers from each knowledge center reporting on interactions with researchers in other groups in and out of the center. (Time in Singapore will be spent doing interviews at Biopolis and MMSC.) Evidence about the number and types of actors, the quantity and richness of interactions, and the entrepreneurial opportunities for these actors will be gathered. This will provide behavioral data that permits conclusions about clustering, relationship of knowledge creation and entrepreneurial activity, connections to global knowledge networks with global knowledge trading and participation in distributed co-creation.