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The interdependence of corporate reputation and ownership: a network approach to quantify reputation

We propose a novel way to measure the reputation of firms by using information about their ownership structure. Supported by the signalling theory, we argue that ownership relations channel reputation spillovers between shareholders and their invested companies. We model such reputation spillovers b...

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Detalles Bibliográficos
Autores principales: Zhang, Yan, Schweitzer, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6837230/
https://www.ncbi.nlm.nih.gov/pubmed/31824691
http://dx.doi.org/10.1098/rsos.190570
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author Zhang, Yan
Schweitzer, Frank
author_facet Zhang, Yan
Schweitzer, Frank
author_sort Zhang, Yan
collection PubMed
description We propose a novel way to measure the reputation of firms by using information about their ownership structure. Supported by the signalling theory, we argue that ownership relations channel reputation spillovers between shareholders and their invested companies. We model such reputation spillovers by means of a simple dynamics that runs on the ownership network, constructed from available databases. We focus on the core of the global ownership network with 1300 firms and 12 100 ownership links. Our method assigns an ownership-based reputation value to each firm, used to provide a quantitative reputation ranking. We compare our ranking with alternative rankings, to confirm that the top-ranked firms are correctly identified. We also demonstrate that our reputation measure does not correlate substantially with operating revenue or control and thus provides additional information about firms.
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spelling pubmed-68372302019-12-10 The interdependence of corporate reputation and ownership: a network approach to quantify reputation Zhang, Yan Schweitzer, Frank R Soc Open Sci Mathematics We propose a novel way to measure the reputation of firms by using information about their ownership structure. Supported by the signalling theory, we argue that ownership relations channel reputation spillovers between shareholders and their invested companies. We model such reputation spillovers by means of a simple dynamics that runs on the ownership network, constructed from available databases. We focus on the core of the global ownership network with 1300 firms and 12 100 ownership links. Our method assigns an ownership-based reputation value to each firm, used to provide a quantitative reputation ranking. We compare our ranking with alternative rankings, to confirm that the top-ranked firms are correctly identified. We also demonstrate that our reputation measure does not correlate substantially with operating revenue or control and thus provides additional information about firms. The Royal Society 2019-10-30 /pmc/articles/PMC6837230/ /pubmed/31824691 http://dx.doi.org/10.1098/rsos.190570 Text en © 2019 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Mathematics
Zhang, Yan
Schweitzer, Frank
The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title_full The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title_fullStr The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title_full_unstemmed The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title_short The interdependence of corporate reputation and ownership: a network approach to quantify reputation
title_sort interdependence of corporate reputation and ownership: a network approach to quantify reputation
topic Mathematics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6837230/
https://www.ncbi.nlm.nih.gov/pubmed/31824691
http://dx.doi.org/10.1098/rsos.190570
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