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Finding shared decisions in stakeholder networks: An agent-based approach

Author

Listed:
  • Le Pira, Michela
  • Inturri, Giuseppe
  • Ignaccolo, Matteo
  • Pluchino, Alessandro
  • Rapisarda, Andrea

Abstract

We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations’ results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

Suggested Citation

  • Le Pira, Michela & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea, 2017. "Finding shared decisions in stakeholder networks: An agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 277-287.
  • Handle: RePEc:eee:phsmap:v:466:y:2017:i:c:p:277-287
    DOI: 10.1016/j.physa.2016.09.015
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    References listed on IDEAS

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    Cited by:

    1. Xueyan Li & Jing Li, 2021. "A freight transport price optimization model with multi bounded-rational customers," Transportation, Springer, vol. 48(1), pages 477-504, February.
    2. Marcucci, Edoardo & Le Pira, Michela & Gatta, Valerio & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro, 2017. "Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders’ preferences and interaction effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 69-86.
    3. Simpson, Jesse R. & Mishra, Sabyasachee, 2021. "Developing a methodology to predict the adoption rate of Connected Autonomous Trucks in transportation organizations using peer effects," Research in Transportation Economics, Elsevier, vol. 90(C).
    4. Nadia Giuffrida & Michela Le Pira & Giuseppe Inturri & Matteo Ignaccolo & Giovanni Calabrò & Blochin Cuius & Riccardo D’Angelo & Alessandro Pluchino, 2020. "On-Demand Flexible Transit in Fast-Growing Cities: The Case of Dubai," Sustainability, MDPI, vol. 12(11), pages 1-15, May.

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