THE ROLE OF NETWORK EMBEDDEDNESS ON THE SELECTION OF COLLABORATION PARTNERS: AN AGENT-BASED MODEL WITH EMPIRICAL VALIDATION
Frank Schweitzer,
Antonios Garas,
Mario V. Tomasello,
Giacomo Vaccario and
Luca Verginer
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Frank Schweitzer: Chair of Systems Design, Department of Management Technology and Economics, ETH Zürich, Weinbergstrasse 56/58, CH-8092 Zürich, Switzerland
Antonios Garas: Chair of Systems Design, Department of Management Technology and Economics, ETH Zürich, Weinbergstrasse 56/58, CH-8092 Zürich, Switzerland
Mario V. Tomasello: Chair of Systems Design, Department of Management Technology and Economics, ETH Zürich, Weinbergstrasse 56/58, CH-8092 Zürich, Switzerland
Giacomo Vaccario: Chair of Systems Design, Department of Management Technology and Economics, ETH Zürich, Weinbergstrasse 56/58, CH-8092 Zürich, Switzerland
Advances in Complex Systems (ACS), 2022, vol. 25, issue 02n03, 1-18
Abstract:
We use a data-driven agent-based model to study the core–periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value obtained from a weighted k-core decomposition. We study the change of these coreness values when collaborations with newcomers or established agents are formed. Our agent-based model is able to reproduce the empirical coreness differences of collaboration partners and to explain why we observe a change in partner selection for agents with high network embeddedness.
Keywords: R&D network; agent-based modeling; scientific collaborations; R&D alliances; firm alliances (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:25:y:2022:i:02n03:n:s0219525922500035
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DOI: 10.1142/S0219525922500035
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