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

Part of the Studies in Computational Intelligence book series (SCI,volume 882)

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.

Keywords

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

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Acknowledgements

This work was partially supported by JSPS KAKENHI Grant Numbers 18H03627 and 16H05904.

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Correspondence to Shohei Doi .

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Mizuno, T., Doi, S., Kurizaki, S. (2020). Network Shapley-Shubik Power Index: Measuring Indirect Influence in Shareholding Networks. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_49

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