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Resilient Agent-Based Networks in the Automotive Industry

In: Machine Learning Perspectives of Agent-Based Models

Author

Listed:
  • Ana Nogueira

    (University of Porto, FEP)

  • Conceição Rocha

    (CPES - INESC TEC)

  • Pedro Campos

    (University of Porto, FEP, LIAAD-INESC TEC)

Abstract

The present work is inspired by the aftermarket companies of the automotive industry. The goal is to investigate how companies react to market change, by understanding the effect of a perturbation (such as a business cessation) on the rest of the companies that are interconnected through peer-to-peer relationships. An agent-based model has been developed that simulates a multilayer network involving different types of companies: suppliers, aftermarket companies; retailers and consumers. The effect of the cessation is measured by the resilience of the multilayer network after suffering the perturbation. The multilayer network is inspired in a business model of the automobile industry’s aftermarket and each type of company has some defined characteristics. The agent-based model produces the network dynamics due to the changes in its configuration throughout time. No learning mechanism is introduced in this work. We demonstrate that the number of links, the volume of sales and the total profit of a node in the network has an impact on its survival throughout time.

Suggested Citation

  • Ana Nogueira & Conceição Rocha & Pedro Campos, 2025. "Resilient Agent-Based Networks in the Automotive Industry," Springer Books, in: Pedro Campos & Anand Rao & Joaquim Margarido (ed.), Machine Learning Perspectives of Agent-Based Models, chapter 0, pages 341-377, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-73354-3_14
    DOI: 10.1007/978-3-031-73354-3_14
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