A Sustainable Evaluation Processes for Investments in the Transport Sector: A Combined Multi-Criteria and Cost–Benefit Analysis for a New Highway in Italy

In the transport sector, a rational and shared planning process is commonly based on the comparison of different design alternatives through quantitative evaluations and stakeholders’ engagement. Among the most adopted evaluation methods, there are cost–benefit analysis (CBA) and multi-criteria analysis (MCA). Both these methods have strengths and weaknesses, which do not allow the conclusion that one technique is dominant over the other. Starting from these considerations, the aim of this paper is to propose a sustainable evaluation process for investments in the transport sector, based on the combined use of both CBA and MCA analysis and a stakeholders’ engagement. The proposed evaluation method was also applied to a real case study: the decision-making process for a new highway in a high naturalistic and touristic area in north of Italy. Furthermore, a “weighted criteria process definition” based on the Delphi method was also performed within a public engagement process. Research results show that the application of both the evaluation analyses (CBA and MCA) allows the selection of the most rational althernative from a sustainable, shared and technical point of view. Precisely, the estimations performed underline that the CBA analysis significantly underestimated the non-users’ benefits, while the opposite occurred for the MCA analysis. The incidence of the non-users’ benefits is only the 14% of the total for the CBA, while it reaches more than the 79% for the MCA. This result is very relevant underling how, for a decision-making processes aimed in comparing different design alternatives for which non-users impacts are expected as relevant against the users ones, the unique application of the most consolidated CBA analyses are not always adequate, while the joint use of the two evaluation methods ensures robust and rational choices for a sustainable development.