Paper detail

An Analysis of Transaction and Joint-patent Application Networks

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.

preprint2010arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.