Institutional cooperations in Austrian research: An analysis of shared researchers

Abstract Researchers increasingly hold multiple organisational affiliations, yet the effects of such arrangements on organisational performance remain poorly understood. We develop a scalable network-based framework that represents simultaneous affiliations as relational links and apply it to harmonised bibliometric data from Austria. Two co-affiliation networks are constructed: a network capturing all simultaneous affiliations and a temporally filtered network retaining recurring affiliation pairs. Analysing these networks in parallel allows us to distinguish transient from persistent co-affiliations and examine how short-lived and enduring ties shape organisational connectivity. Network regressions show that geographic proximity remains an important determinant, with greater distance reducing the likelihood of a co-affiliation link forming. Once transient affiliations are removed, most same-type organisational links lose statistical significance, indicating that many observed co-affiliations reflect temporary overlaps rather than durable structural ties. Persistent cross-type links are rare, with ties primarily observed between universities and research institutes. To evaluate the effects of co-affiliations on organisational citation impact, we use field- and year-normalised indicators. Sensitivity analyses show that citation impact depends on how affiliations of multi-affiliated authors are assigned, including whether the first or last listed affiliation is used. Research institutes and universities exhibit higher citation impact, and persistent co-affiliations are associated with greater visibility. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/QSS.a.486

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Publication Details

Journal
Quantitative Science Studies
Published
2026-05-21
DOI
https://doi.org/10.1162/qss.a.486
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
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article

Institutional cooperations in Austrian research: An analysis of shared researchers

Gerald Schweiger, Lutz Bornmann, Christoph Schlager
Quantitative Science Studies
scientometrics and bibliometrics research
article

Institutional cooperations in Austrian research: An analysis of shared researchers

Gerald Schweiger, Lutz Bornmann, Christoph Schlager
article en

Abstract

Abstract Researchers increasingly hold multiple organisational affiliations, yet the effects of such arrangements on organisational performance remain poorly understood. We develop a scalable network-based framework that represents simultaneous affiliations as relational links and apply it to harmonised bibliometric data from Austria. Two co-affiliation networks are constructed: a network capturing all simultaneous affiliations and a temporally filtered network retaining recurring affiliation pairs. Analysing these networks in parallel allows us to distinguish transient from persistent co-affiliations and examine how short-lived and enduring ties shape organisational connectivity. Network regressions show that geographic proximity remains an important determinant, with greater distance reducing the likelihood of a co-affiliation link forming. Once transient affiliations are removed, most same-type organisational links lose statistical significance, indicating that many observed co-affiliations reflect temporary overlaps rather than durable structural ties. Persistent cross-type links are rare, with ties primarily observed between universities and research institutes. To evaluate the effects of co-affiliations on organisational citation impact, we use field- and year-normalised indicators. Sensitivity analyses show that citation impact depends on how affiliations of multi-affiliated authors are assigned, including whether the first or last listed affiliation is used. Research institutes and universities exhibit higher citation impact, and persistent co-affiliations are associated with greater visibility. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/QSS.a.486

Quantitative Science Studies
TU Wien (AT), Max Planck Society (DE), Austrian Research Institute for Artificial Intelligence (AT), Max Planck Innovation (DE), Hochschule Campus Wien (AT)
Partnerships for the goals
Openalex Percentile: Top 6%
scientometrics and bibliometrics research
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