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

Marchi H, Fuchs C (2023)
The Journal of Mathematical Sociology: 1-28.

Zeitschriftenaufsatz | E-Veröff. vor dem Druck | Englisch
 
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Abstract / Bemerkung
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.
Erscheinungsjahr
2023
Zeitschriftentitel
The Journal of Mathematical Sociology
Seite(n)
1-28
ISSN
0022-250X
eISSN
1545-5874
Page URI
https://pub.uni-bielefeld.de/record/2969305

Zitieren

Marchi H, Fuchs C. Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks. The Journal of Mathematical Sociology. 2023:1-28.
Marchi, H., & Fuchs, C. (2023). Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks. The Journal of Mathematical Sociology, 1-28. https://doi.org/10.1080/0022250X.2023.2180000
Marchi, Hannah, and Fuchs, Christiane. 2023. “Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks”. The Journal of Mathematical Sociology, 1-28.
Marchi, H., and Fuchs, C. (2023). Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks. The Journal of Mathematical Sociology, 1-28.
Marchi, H., & Fuchs, C., 2023. Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks. The Journal of Mathematical Sociology, , p 1-28.
H. Marchi and C. Fuchs, “Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks”, The Journal of Mathematical Sociology, 2023, pp. 1-28.
Marchi, H., Fuchs, C.: Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks. The Journal of Mathematical Sociology. 1-28 (2023).
Marchi, Hannah, and Fuchs, Christiane. “Hurdle-QAP models overcome dependency and sparsity in scientific collaboration count networks”. The Journal of Mathematical Sociology (2023): 1-28.

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