Institutional cooperations in Austrian research: An analysis of shared researchers

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