It consists of two main parts: a modelling process and a real participation process. The whole procedure can be divided into 7 steps:. The definition of the problem is the first and most important preliminary step. The problem under consideration could be of different nature, e. Context analysis is important in this phase to better outline the problem. The preliminary analysis aims at identifying relevant UFT stakeholders to be involved and define the policy package components.
In this respect, it is important to identify the most appropriate attributes and levels to be used in the experimental design. Social networks re-creation and social influence investigation can be performed using different techniques, such as those described in section 2 e. In the modelling phase, DCM are estimated and the ABM implemented accordingly by feeding it with all the data and the agent-specific utility functions. The interaction process is reproduced via opinion dynamics mechanisms, assuming that stakeholders decide to cooperate to find a shared decision with respect to alternative policies available.
Since agents are characterised with individual utility functions, they can be endowed with a certain willingness to change opinion, where the probability of changing opinion is linked to the utility alternative policies produce for the specific agent considered. In parallel, mathematical models could be used to simulate ex-ante the effects of the policies on the transport network.
In general, the opinion dynamics process leads to an increase in the degree of consensus as interactions take place, while the overall utility decreases, since agents, being willing to negotiate, can change opinion toward the non-preferred option. The results of the evaluations are presented to stakeholders and policy-makers with the intent of validating them and using them as a starting point of a participation process aimed at consensus building.
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The aim is to identify ex-ante which policies are most likely to be accepted and perform also well from a technical analysis perspective. The output of the consensus building process should be a subset of shared from the participatory process and effective from the technical evaluations policies, derived from the first set of policies which emerged from the modelling process. This section aims at illustrating, through a case study, how to apply the participatory decision-support procedure for UFT policy-making.
The case study refers to urban freight distribution in Rome, where the extensive work performed in [ 17 , 21 , 64 , 72 , 97 ] provides an in-depth knowledge of the decision-making context and of the preferences of heterogeneous stakeholders. Gatta and Marcucci [ 72 ] shows the potential policy distortions and bias if a stakeholder-generic approach is used instead of adopting a well-defined stakeholder-specific perspective in both data acquisition and modelling. The steps of the participatory decision-support procedure described in Fig.
While the modelling process steps 1—5 refers to a real world application of the framework even if data acquisition is temporally disjoint from the modelling phase , the participation process steps 6—7 is here presented with the intent of extending the case study for further research and prove the feasibility of the proposed approach. Problem definition. Data refer to LTZ legislation in , when access and parking of freight vehicles in the LTZ were subject to time windows restrictions between Preliminary analysis.
Stakeholders were identified and divided in three categories: a demand i. Phase 1 allowed to select the most preferred policy solutions, in view of the subjective problem perception and current regulation; phase 2 allowed to gain confirmation of the information gathered in phase 1, make stakeholders interact with each other and obtain relevant inputs to define the crucial elements for constructing the SP survey. Demand actors were further split into retailers and own-account operators who themselves organise transport services.
The following criteria were chosen for attribute selection: 1 attributes need to be credible and salient for the majority of respondents; 2 support for a policy attribute needs to be shared among respondents; 3 attributes need to reflect plausible future changes to the current policy scenario. The questionnaire was divided in five parts with the first part aimed at collecting socioeconomic data. In this respect, an additional section of the questionnaire could have elicited characteristics related to their social behaviour via qualitative questions, e.
The social network could also have been recreated by using the techniques described in section 2 e. Modelling phase. In the modelling phase, agent-specific DCM have been estimated and an ABM has been implemented and fed with all the data and the agent-specific utility functions. In particular, latent class models have been estimated for each agent category [ 92 ]. Transport providers can be split into three classes having different preference structures, while retailers and own-account operators are both characterized by two classes.
Starting from the three models presented, individual-specific posterior estimates of the coefficients have been obtained by averaging class parameter estimates weighted by person-specific conditional class probabilities [ 92 ]. The participation process for UFT policy-making is described in the ABM by means of a multilayer network, where each layer represents a different level of description and details of the process.
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The ABM links stakeholders in a social network, where the nodes represent the agents and the links are the relationships among them. The interaction process is simulated by means of an opinion dynamics model, reproducing the opinion flows through the network of relationships. Each simulation reproduces the decision between the status quo and a given policy change.
The modelling approach assumes that stakeholders initially choose the policy they prefer according to the associated utility function.
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Once the dynamic process starts, they can modify their opinion depending on the interactions with other actors. Their willingness to change is increased by repeated cycles of interactions. It expresses a cooperative attitude where a decrease in utility is accepted in front of the higher goal of a collective interest toward a shared solution. A complete description of the model can be found in [ 92 ]. In parallel, mathematical models should be used to simulate ex-ante the effects of the policies simulated on the transport network.
Scenario simulations. Scenario simulations have been performed by reproducing different policy changes to be compared with the status quo. The rationale behind the choices made is the following: different scenarios for improving LTZ accessibility and usability conditions were considered by varying the attribute levels used in the experimental design, within the range defined by two extreme scenarios, i. Different scenarios more in line with one of the three categories were also tested on the base of some a-priori knowledge about their preferences [ 21 ]. In general, due to the interaction and the opinion change, the degree of consensus usually shows an increasing trend, while the overall utility generally decreases.
As a consequence, the global satisfaction, being the product of these two quantities, initially increases in time, rapidly reaching a maximum, then slowly decreases. Policy ranking is based on 5 potentially accepted policy changes. The best policy in terms of global satisfaction is the one that maximizes at the same time the improvements for the three categories while slightly increasing the entrance fee, i. This ex-ante evaluation of policy acceptability should be combined with other evaluations e. Presentations of results to stakeholders and policy-maker.
The results of the evaluations should be presented to stakeholders and policy-makers with the intent of validating them and using them as a starting point of a participation process aimed at consensus building. It is important to explain all the steps that led to those results, so to make stakeholders and policy-makers aware of the transparency and reproducibility features characterising the entire procedure. Participation process aimed at consensus building.
A consensus building process should be set up with the aim of obtaining a convergence of opinions towards a subset of shared from the participatory process and effective from the technical evaluations policies, based on the first set of policies which resulted from the modelling process. Another way to foster a convergence of opinions could be to use a Delphi-like iterative procedure, where stakeholders participate by answering a questionnaire iteratively. The proposed modelling approach produces an added value for UFT policy-making and it can be appreciated in an UFT planning context.
Cascetta et al. As reported in section 1 , a decision-making process for UFT planning requires a deeper knowledge of the heterogeneous nature and preferences of the stakeholders involved, whose aims and behaviours can be hardly predicted by conventional transport models. For the sake of simplicity, only the first step is reported in this flow diagram. For more information, the reader can refer to [ 24 ]. Finally, assessment results are presented to decision-makers and stakeholders, so to support the final decision that should be consistent with the previously identified objectives see Fig.
The modelling framework proposed within a UFT context can realistically be applied to any decision-making process dealing with transport planning, especially when the complexity of the decision, the heterogeneity of the actors involved and the interaction of mixed competitive and cooperative behaviour are relevant for the implementation and the success of the plan, as in the case of UFT.
This paper presented a procedure based on an integrated modelling approach to support stakeholder involvement in the decision-making processes regarding urban freight transport solutions. In fact, together with technical and economic analyses, the stakeholder behavioural analysis proposed contributes to the ex-ante policy assessment needed to support decision-makers in taking well-thought-out decisions. In future development of this research, the authors will test the procedure in different decision-making contexts regarding urban freight transport solutions, trying to adapt it to the specific problem type.
In this sense, the behavioural analysis proposed can be considered as the general framework for a participatory decision-support tool. According to Cascetta et al. In: Proceedings of the 2nd state of Australian cities conference pp 1— Gatta V, Marcucci E, Le Pira M Smart urban freight planning process: integrating desk, living lab and modelling approaches in decision-making.
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