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Article: Exploring communication networks to understand organizational crisis using exponential random graph models

TitleExploring communication networks to understand organizational crisis using exponential random graph models
Authors
Issue Date2013
Citation
Computational and Mathematical Organization Theory, 2013, v. 19 n. 1, p. 25-41 How to Cite?
AbstractIn recent social network studies, exponential random graph (ERG) models have been used comprehensively to model global social network structure as a function of their local features. In this study, we describe the ERG models and demonstrate its use in modelling the changing communication network structure at Enron Corporation during the period of its disintegration. We illustrate the modelling on communication networks, and provide a new way of classifying networks and their performance based on the occurrence of their local features. Among several micro-level structures of ERG models, we find significant variation in the appearance of A2P (Alternating k-two-paths) network structure in the communication network during crisis period and non-crisis period. We also notice that the attribute of hierarchical positions of actors (i. e., high rank versus low rank staff) have impact on the evolution process of networks during crisis. These findings could be used in analyzing communication networks of dynamic project groups and their adaptation process during crisis which could lead to an improved understanding how communications network evolve and adapt during crisis. © 2011 Springer Science+Business Media, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/194377
ISSN
2015 Impact Factor: 0.37
2015 SCImago Journal Rankings: 0.278
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorUddin, S-
dc.contributor.authorHamra, J-
dc.contributor.authorHossain, L-
dc.date.accessioned2014-01-30T03:32:31Z-
dc.date.available2014-01-30T03:32:31Z-
dc.date.issued2013-
dc.identifier.citationComputational and Mathematical Organization Theory, 2013, v. 19 n. 1, p. 25-41-
dc.identifier.issn1381-298X-
dc.identifier.urihttp://hdl.handle.net/10722/194377-
dc.description.abstractIn recent social network studies, exponential random graph (ERG) models have been used comprehensively to model global social network structure as a function of their local features. In this study, we describe the ERG models and demonstrate its use in modelling the changing communication network structure at Enron Corporation during the period of its disintegration. We illustrate the modelling on communication networks, and provide a new way of classifying networks and their performance based on the occurrence of their local features. Among several micro-level structures of ERG models, we find significant variation in the appearance of A2P (Alternating k-two-paths) network structure in the communication network during crisis period and non-crisis period. We also notice that the attribute of hierarchical positions of actors (i. e., high rank versus low rank staff) have impact on the evolution process of networks during crisis. These findings could be used in analyzing communication networks of dynamic project groups and their adaptation process during crisis which could lead to an improved understanding how communications network evolve and adapt during crisis. © 2011 Springer Science+Business Media, LLC.-
dc.languageeng-
dc.relation.ispartofComputational and Mathematical Organization Theory-
dc.titleExploring communication networks to understand organizational crisis using exponential random graph models-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10588-011-9104-8-
dc.identifier.scopuseid_2-s2.0-84874412148-
dc.identifier.hkuros239071-
dc.identifier.volume19-
dc.identifier.issue1-
dc.identifier.spage25-
dc.identifier.epage41-
dc.identifier.isiWOS:000315359700002-

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