We used social network analysis to understand the jurisdiction relationship between companies, in addition to employing a geographic information system to determine whether the companies include geographical considerations during investment. Industry and Commerce Registration data provided by the Taiwanese government were used to model a new approach for overcoming business concerns, such as the problem of companies with cross-shareholdings being unable to quantify their individual jurisdictions through holding ratios. Using progeny networks, we explored whether geographical correlations exist between cross-shareholding companies. On the basis of our results, we made the following conclusions: 1. Without considering interlocking relationships, registered companies are distributed randomly. 2. Interlocking companies are associated with high levels of spatial clustering in the spatial context; furthermore, shareholding companies consider the geographic locations of other companies for investment. 3. Corporate power migration through a progeny network is effective. 4. The applied approach can determine the structure of a company that conceals its control power behind other companies through directly investing in such companies. 5. The methodologies adopted in this study can be applied to various fields to discover problems related to social networks and power migration within a geographical context.
The 6th International Conference on Complex Networks and Their Applications, Université de Lyon International Conference on Complex Networks and their Applications , COMPLEX NETWORKS 2017: Complex Networks & Their Applications VI pp 1076-1087 , Studies in Computational Intelligence, vol 689