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dc.date.accessioned2024-08-09T08:50:25Z
dc.date.available2024-08-09T08:50:25Z
dc.date.issued2024-07-01
dc.identifierdoi:10.17170/kobra-2024080910654
dc.identifier.urihttp://hdl.handle.net/123456789/15962
dc.description.sponsorshipGefördert im Rahmen des Projekts DEALger
dc.language.isoeng
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMultiple goalseng
dc.subjectSocial capitaleng
dc.subjectResearch performanceeng
dc.subjectResearch commercializationeng
dc.subjectResearch ambidexterityeng
dc.subject.ddc300
dc.subject.ddc330
dc.titleUniversity scientists’ multiple goals achievement: Social capital and its impact on research performance and research commercializationeng
dc.typeAufsatz
dcterms.abstractThis study conceptualizes a quadrant model characterizing four profiles by contrasting university scientists’ multiple goals: research performance and commercialization. Since literature shows that these goals are conflicting but not mutually exclusive, social capital theory is drawn to test the influence of scientists’ bonding, bridging, and linking social capital on their profile affiliation. Survey data from 1057 German scientists is utilized to estimate a multinomial logistic regression model relating scientists’ profiles to the different forms of social capital. The results show that only 4.16% of the scientists achieve above-average research performance and also commercialize their research results, whereby all three forms of their social capital positively impact the achievement of these goals. Furthermore, bonding social capital positively relates to scientists with above-average research performance but no commercialized research results. Bridging social capital facilitates scientists to commercialize results, albeit with below-average research performance. In addition, an inverted U-shaped relationship between scientists’ bonding social capital and their research performance is identified, suggesting that an excess of this form of social capital may impede scientists’ ability to achieve multiple goals. The results are discussed and policy recommendations are derived.eng
dcterms.accessRightsopen access
dcterms.creatorHuegel, Matthias
dcterms.extent16 Seiten
dc.relation.doidoi:10.1016/j.technovation.2024.103065
dc.subject.swdSoziales Kapitalger
dc.subject.swdKommerzialisierungger
dc.subject.swdOrganisationale Ambidextrieger
dc.subject.swdForschungsleistungger
dc.subject.swdUniversitätger
dc.subject.swdRegressionsmodellger
dc.type.versionpublishedVersion
dcterms.source.identifiereissn:1879-2383
dcterms.source.issueIssue July
dcterms.source.journalTechnovationeng
dcterms.source.volumeVolume 135
kup.iskupfalse
dcterms.source.articlenumber103065


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Namensnennung 4.0 International
Except where otherwise noted, this item's license is described as Namensnennung 4.0 International