Network Shapley-Shubik Power Index: Measuring Indirect Influence in Shareholding Networks

Takayuki Mizuno, Shohei Doi, Shuhei Kurizaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Extending the Shapley-Shubik power index to networks, we propose a new measure and numerical method to calculate the indirect influence of investors on companies: Network power index (NPI). While the original index, reflecting the characteristics of majority vote in a shareholders meeting, measures the direct voting power of a shareholder, NPI captures not only an investor’s direct influence over a company but also indirect influence over this company’s subsidiary. Since NPI is often incalculable in a large network, we present a new method to numerically compute NPI: label propagation. Applying this method to the global shareholding networks in 2016, we find NPIs and raw vote shares dramatically diverge for some investors and this discrepancy suggests the difference in investment strategies between governments and private financial institutions.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VIII - Volume 2 Proceedings of the 8th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019
EditorsHocine Cherifi, Sabrina Gaito, José Fernendo Mendes, Esteban Moro, Luis Mateus Rocha
PublisherSpringer
Pages611-619
Number of pages9
ISBN (Print)9783030366827
DOIs
Publication statusPublished - 2020
Event8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019 - Lisbon, Portugal
Duration: 2019 Dec 102019 Dec 12

Publication series

NameStudies in Computational Intelligence
Volume882 SCI
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

Conference8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019
CountryPortugal
CityLisbon
Period19/12/1019/12/12

Keywords

  • Complex networks analysis
  • Indirect control
  • Shareholding networks
  • The Shapley-Shubik power index

ASJC Scopus subject areas

  • Artificial Intelligence

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