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dc.contributor.authorMoges, H.
dc.contributor.authorDejaeger, Karel
dc.contributor.authorLemahieu, Wilfried
dc.contributor.authorBaesens, Bart
dc.date.accessioned2017-12-02T14:43:03Z
dc.date.available2017-12-02T14:43:03Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/20.500.12127/4599
dc.description.abstractInterest in group moods as an emergent phenomenon of group members’ interactions has significantly increased over the past two decades (Barsade & Gibson, 2007). Most studies focused particularly on understanding the effects of group moods on group processes (Barsade, 2001, Baartel & Saavedra, 2000, Barsade, Ward, Turner & Sonnenfled, 2000, Chiayu Tu, 2009) and group performance (Seung -Yoon Ree, 2006, Jordan, Lawrence & Troth, 2006). However, research investigating the antecedents of group moods is still scant. The current study fills this gap by focusing on the affective potential of group conflict. In this sense, group conflict focuses on how differences of opinion (task conflict) and person-related disagreements (relationship conflict) trigger group moods that differ in their valence (positive and negative) and level of activation (activated and unactivated) (Baartel & Saavedra, 2000). In this context, the group’s ability to define and understand its moods, their cause, evolution and relations between them - ability known as group emotional intelligence (Salovey & Mayer, 1990) - is expected to buffer the relation between conflict and group moods. By studying group moods in relation to group conflict, the current study extends previous research by considering group moods’ antecedents and not only their consequences. This contributes to a better understanding of group affect dynamics. In addition, the current study investigates different nuances of group moods given by different types of conflict. Whether an affect has a positive or negative valence, or whether it is activated or inactivated, has implications upon the further group dynamics.
dc.language.isoen
dc.subjectAccounting & Finance
dc.titleA multidimensional analysis of data quality for credit risk management: new insights and challenges
dc.identifier.journalInformation and Management
dc.source.volume50
dc.source.issue1
dc.source.beginpage43
dc.source.endpage58
vlerick.knowledgedomainAccounting & Finance
vlerick.supervisor
vlerick.typearticleArticle in academic journal
vlerick.vlerickdepartmentA&F
dc.identifier.vperid94350
dc.identifier.vperid140550
dc.identifier.vperid140860
dc.identifier.vperid162303
dc.identifier.vpubid5474


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