Graphical abstract

Highlights•The research deals with the heterogeneous impacts of disused railways recovery.•The study develops a framework for the evaluation of competing requalification options according to multiple impacts.•A real decision analysis intervention is presented and discussed.•The results highlight the policy implications of alternative transportation systems.

AbstractFinding a new use for neglected infrastructures, such as disused railways, provides an opportunity for low carbon travel experiences as reconversion policies promote new uses, arrest decay processes and re-establish continuity in the environmental system, using existing linear infrastructures. Nevertheless, the decision of what to do in order to reuse abandoned railways represents a complex decision making problem, involving heterogeneous impacts and stakeholders. Within this context, Multi Criteria Analysis techniques can be used to synthesize stakeholders’ preferences by accommodating conflicting and incommensurable impacts. The present study thus uses Multi Criteria Analysis to answer a real demand for transportation systems’ planning coming from the Piedmont Region Authority in Italy, where 12 passenger railway lines have recently been abandoned and replaced by bus services.The main objective of the study is to develop a methodological framework able to support collaborative planning and decision-making processes related to the requalification of disused railways in mixed urban and rural contexts.The ultimate objective is to provide a robust recommendation to the Regional Authority with reference to the best requalification option for one of the abandoned railway lines in the Region. The contribution brought by the study is twofold and refers to: (i) improved operability of the proposed tools obtained by combining visualization analytics with consolidated preference elicitation protocols for assessing multiple impacts and (ii) the provision of a replicable working tool for policy makers. The study has thus an innovative value and may increase the use of Decision Analytics to support the evaluation of environmental impacts of different transportation systems.