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The Role Of Network Embeddedness On The Selection Of Collaboration Partners: An Agent-Based Model With Empirical Validation

Author

Listed:
  • 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)

  • LUCA VERGINER

    (Chair of Systems Design, Department of Management Technology and Economics, ETH Zürich, Weinbergstrasse 56/58, CH-8092 Zürich, Switzerland)

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.

Suggested Citation

  • Frank Schweitzer & Antonios Garas & Mario V. Tomasello & Giacomo Vaccario & Luca Verginer, 2022. "The Role Of Network Embeddedness On The Selection Of Collaboration Partners: An Agent-Based Model With Empirical Validation," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 25(02n03), pages 1-18, March.
    • Handle: RePEc:wsi:acsxxx:v:25:y:2022:i:02n03:n:s0219525922500035
    DOI: 10.1142/S0219525922500035
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    Cited by:

    1. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.

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