Overview
2009 - 2010
We investigate various kinds of interactions among firms in order to understand mechanisms creating innovations. Concretely, we will take the following approaches in this study:
- (1) We analyze networks that include one million Japanese firms as nodes and four relationships defined by joint-patent applications, stock-sharings, transactions and director-interlockings;
- (2) We calculate statistics based on topologies of the networks and discuss how the statistics are related to economical statistics; and
- (3) We re-define new nodes that are sets of firms and analyze the new networks. This enables us to understand what kinds of boundaries among firms are suitable for dividing firms from the view point of network topologies.
2008
The purpose of this project is to develop new indicators to be used in the formulation of economic policy. The approach taken is to investigate innovation, resulting from multiple and diverse inter-firm interactions, by using multi-tiered network analysis and patent value assessment methods to analyze data on corporate transactions and joint invention. Specifically, the project analyzes networks that connect about 1 million Japanese firms through joint patent applications, mutual share holding, business transactions and interlocking directorates. As the first step, the topological features of networks are identified by computing various network indicators for cases in which the strength of relations is not considered. These indicators are then examined to determine how they can contribute to economic policy formulation.In the next step, the strength of inter-firm relations is defined and multi-tiered networks are weighted accordingly and analyzed. In particular, a theoretical model will be developed to compute the value of a number of firms that are connected to form a cluster. Finally, properties of high value-added clusters will be analyzed and economic policies for promoting the generation of high value-added clusters will be examined.
April 1, 2008 - March 31, 2011
