  Many firms these days are opting to specialize rather than generalize as a
way of maintaining their competitiveness. Consequently, they cannot rely solely
on themselves, but must cooperate by combining their advantages. To obtain the
actual condition for this cooperation, a multi-layered network based on two
different types of data was investigated. The first type was transaction data
from Japanese firms. The network created from the data included 961,363 firms
and 7,808,760 links. The second type of data were from joint-patent
applications in Japan. The joint-patent application network included 54,197
nodes and 154,205 links. These two networks were merged into one network.
  The first anaysis was based on input-output tables and three different tables
were compared. The correlation coefficients between tables revealed that
transactions were more strongly tied to joint-patent applications than the
total amount of money. The total amount of money and transactions have few
relationships and these are probably connected to joint-patent applications in
different mechanisms. The second analysis was conducted based on the p* model.
Choice, multiplicity, reciprocity, multi-reciprocity and transitivity
configurations were evaluated. Multiplicity and reciprocity configurations were
significant in all the analyzed industries. The results for multiplicity meant
that transactions and joint-patent application links were closely related.
Multi-reciprocity and transitivity configurations were significant in some of
the analyzed industries. It was difficult to find any common characteristics in
the industries. Bayesian networks were used in the third analysis. The learned
structure revealed that if a transaction link between two firms is known, the
categories of firms' industries do not affect to the existence of a patent
link.
