Abstract
This article deals with measuring indirect control in complex corporate shareholding networks using the concept of power indices from cooperative game theory. We focus on the approaches by Mercik-Łobos and Stach-Mercik which measure the control power of all firms involved in shareholding networks with algorithms based on the raw Johnston index. We point out how these approaches can be generalized replacing the raw Johnston index by various other power indices in a modular fashion. We further extend the algorithmic framework by investigating more than one regression and present requirements for software and modelling. Finally, we test the new framework of generalized implicit power indices for a network with 21 players and discuss how properties of the underlying power index like efficiency or null player removability influence the measurements of indirect control.
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Acknowledgements
The first author thanks the funding of the Bavarian State Ministry of Science and Arts. The third author’s contribution to the article was funded under subvention funds for the AGH University of Science and Technology in Krakow, Poland. Moreover, the authors thank two anonymous reviewers for their careful reading of the manuscript and their helpful comments and suggestions.
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Staudacher, J., Olsson, L., Stach, I. (2021). Implicit Power Indices for Measuring Indirect Control in Corporate Structures. In: Nguyen, N.T., Kowalczyk, R., Motylska-Kuźma, A., Mercik, J. (eds) Transactions on Computational Collective Intelligence XXXVI. Lecture Notes in Computer Science(), vol 13010. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-64563-5_4
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