Michela Le Pira

Simulating Opinion Dynamics on Stakeholders’ Networks through Agent-based Modeling for Collective Transport Decisions☆

In transport planning several actors with conflicting objectives are involved in the decision-making process. Though public participation is fundamental to legitimate a transport plan, some inconsistencies may arise when individual preferences are aggregated into a collective decision. In this work, we reproduce the process of collective preference ranking among plan alternatives using agent-based simulations of the opinion dynamics on groups of stakeholders linked in typical social networks. The results show the efficacy of interaction and the relevance of the network topology to find a transitive and shared collective preference ranking.

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

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.

Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas

Passengers and freight mobility in urban areas represents an increasingly relevant component of modern city life. On one side, it fosters economic growth, but, on the other, it also generates high social costs. Congestion and pollution are two problems policy-makers want to curb adopting appropriate measures. The pervasive use of information and communication technology will contribute to the fuller affirmation of the sharing economy paradigm. In this context, connected shared mobility can play a crucial role in relieving cities from transport-related negative externalities. This paper analyses the feasibility and behavioral levers that might facilitate the diffusion of crowdshipping in urban areas. Two are the main objectives the paper pursues. First: investigate under which conditions passengers would be willing to act as crowdshippers. Second: find out under which conditions people would be willing to receive their goods via a crowdshipping service. Crowdshipping can generate positive impacts such as the reduction of total and ad-hoc trips, by optimizing, through sharing, the use of resources and infrastructures. The study described in this paper represents a preliminary investigation, focusing on University students, to acquire the necessary knowledge base for developing a stated preference research endeavor. Preliminary results show that 87% of students would, in principle, be willing to act as crowdshippers (i.e. supply) with an adequate compensation, while 93% of them are willing to receive their goods through a crowdshipping system (i.e. demand) under certain conditions, especially characterized by delivery timing and punctuality.

Dealing with the Complexity of Stakeholder Interaction in Participatory Transport Planning

Including an active participation of citizens and stakeholders from the beginning of transport decision-making processes is widely recognized as a precondition to avoid the failure of projects/policies/plans as a consequence of a lack of consensus. Appropriate methods and tools are needed to support participation processes towards well-thought and shared solutions. In this paper quantitative methods, stakeholder interaction and simulation models are used to guide and reproduce a participatory experiment aimed at consensus building about mobility management strategies. Analytic Hierarchy Process (AHP) has been used to elicit stakeholder preferences, different voting methods have been used to aggregate the individual preferences, group interaction has been performed via a facilitated dialogue to reach a consensus among stakeholders and an agent-based model (ABM) has been used to simulate the same consensus building process. Besides the social network of stakeholders has been analyzed to gain insights on its influence on the consensus formation.