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Marchi, H. ; Fuchs, C.

Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks.

J. Math. Socio. 48, 100-127 (2024)
Verlagsversion DOI
Open Access Gold (Paid Option)
Spatial proximity may facilitate scientific collaboration. We regress its impact within two German research institutions, defining collaboration strength and proximity by the number of joint publications and spatial distance between work places. The methodological focus lies on accounting for (i) the dependency structure in network data and (ii) excess zeros in the sparse target matrix. The former can be addressed by a quadratic assignment procedure (QAP), the second by a hurdle model. To offer a joint solution, we combine the methods to novel parametric and non-parametric hurdle-QAP models. The analysis reveals that proximity can facilitate collaboration, but significant effects get lost within building structures. Outcomes of this study may inform about how to target the promotion of interdisciplinary research.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Collaboration Network ; Count Data ; Hurdle Model ; Network Regression ; Qap ; Sparse Networks ; Spatial Proximity
ISSN (print) / ISBN 0022-250X
e-ISSN 1545-5874
Zeitschrift Journal of Mathematical Sociology
Quellenangaben Band: 48, Heft: 1, Seiten: 100-127 Artikelnummer: , Supplement: ,
Verlag Taylor & Francis
Verlagsort 530 Walnut Street, Ste 850, Philadelphia, Pa 19106 Usa
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Förderungen Deutsche Forschungsgemeinschaft (DFG)
Bielefeld University