Quantifying the Importance of Firms by Means of Reputation and Network Control
dc.contributor.author
Zhang, Yan
dc.contributor.author
Schweitzer, Frank
dc.date.accessioned
2021-07-12T06:39:10Z
dc.date.available
2021-07-12T04:58:54Z
dc.date.available
2021-07-12T06:39:10Z
dc.date.issued
2021-06
dc.identifier.issn
2624-909X
dc.identifier.other
10.3389/fdata.2021.652913
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/493916
dc.identifier.doi
10.3929/ethz-b-000493916
dc.description.abstract
As recently argued in the literature, the reputation of firms can be channeled through their ownership structure. We use this relation to model reputation spillovers between transnational companies and their participated companies in an ownership network core of 1,318 firms. We then apply concepts of network controllability to identify minimum sets of driver nodes (MDSs) of 314 firms in this network. The importance of these driver nodes is classified according to their control contribution, their operating revenue, and their reputation. The latter two are also taken as proxies for the access costs when utilizing firms as driver nodes. Using an enrichment analysis, we find that firms with high reputation maintain the controllability of the network but rarely become top drivers, whereas firms with medium reputation most likely become top driver nodes. We further show that MDSs with lower access costs can be used to control the reputation dynamics in the whole network.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Frontiers Media
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
network analysis
en_US
dc.subject
reputation
en_US
dc.subject
companies/firms
en_US
dc.subject
ownership
en_US
dc.subject
controllability
en_US
dc.title
Quantifying the Importance of Firms by Means of Reputation and Network Control
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2021-06-16
ethz.journal.title
Frontiers in Big Data
ethz.journal.volume
4
en_US
ethz.journal.abbreviated
Front. Big Data
ethz.pages.start
652913
en_US
ethz.size
9 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank (emeritus) / Schweitzer, Frank (emeritus)
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank (emeritus) / Schweitzer, Frank (emeritus)
ethz.date.deposited
2021-07-12T04:59:18Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-07-12T06:39:16Z
ethz.rosetta.lastUpdated
2025-02-13T23:44:35Z
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true
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true
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